Forex Trading 2020 - Trade FX For Profit. Strategy, Tips ...

List of 110+ Free Udemy & Popular Discounted : ETL & Data Integration Masterclass, HTML, JavaScript, & Bootstrap, Marketing Analytics, Microsoft Excel, Machine Learning, Android App Developer, React JS - A Complete Guide for Frontend Web Development, Python, Tableau, Instructional Design & Many More

ETL & Data Integration Masterclass, HTML, JavaScript, & Bootstrap, Marketing Analytics, Microsoft Excel, Machine Learning, Android App Developer, React JS - A Complete Guide for Frontend Web Development, Python, Tableau, Instructional Design & Many More
Source: Freebies Global - https://freebiesglobal.com/
  1. [English] 6h 24m HTML, JavaScript, & Bootstrap - Certification Course https://www.udemy.com/course/html-javascript-bootstrap-certification-course/?couponCode=YOUACCELOCT26 2 Days left at this price!
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  7. [English] 2h 23m Learn XML-AJAX - For Beginners https://www.udemy.com/course/learn-xml-ajax-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  8. [English] 2h 45m Learn Bootstrap - For Beginners https://www.udemy.com/course/learn-bootstrap-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
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  10. [English] 3h 9m CSS & JavaScript - Certification Course for Beginners https://www.udemy.com/course/css-javascript-certification-course-for-beginners/?couponCode=YOUACCELOCT26 2 Days left at this price!
  11. [English] 6h 2m Ultimate AWS Certified Alexa Skill Builder Specialty 2020 https://www.udemy.com/course/ultimate-aws-certified-alexa-skill-builder-specialty/?couponCode=20F2F1085B9FE981B09C 2 Days left at this price!
  12. [English] 9h 13m Pentaho for ETL & Data Integration Masterclass 2020- PDI 9.0 https://www.udemy.com/course/pentaho-for-etl-data-integration-masterclass/?couponCode=OCTXXVI20 1 Day left at this price!
  13. [English] 34h 56m Machine Learning & Deep Learning in Python & R https://www.udemy.com/course/data_science_a_to_z/?couponCode=OCTXXVI20 1 Day left at this price!
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  18. [Spanish] 11h 40m Curso Excel y Power BI – Análisis y Visualización de Datos https://www.udemy.com/course/curso-tutorial-aprender-como-usar-power-bi-excel-ejercicios-practicos/?couponCode=OCT20-1 2 Days left at this price!
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  41. [English] 1h 14m Sell Photo Online: Beginners Guide Stock Photography https://www.udemy.com/course/mastering-stock-photography-step-by-step-guideline/?couponCode=STOCKOCT2020F3 2 Days left at this price!
  42. [English] 6h 5m Tableau 2020 Training for Data Science & Business Analytics https://www.udemy.com/course/tableau-for-data-science-and-business-analytics/?couponCode=FB27OCT2020 2 Days left at this price!
  43. [English] 11h 46m Futures Trading Ninja: DIY 12Hour TOP-NOTCH Trading Strategy https://www.udemy.com/course/futures-trading/?couponCode=1OCT20 2 Days left at this price!
  44. [Spanish] 5h 35m Google Adsense. 99 Secretos que Internet No te Enseña. 2020. https://www.udemy.com/course/google-adsense-gana-dinero-achirou-alvaro-chirou-pablo-munoz/?couponCode=TWITCH 2 Days left at this price!
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  60. [Spanish] 1h 18m Comienza con R ¡Añade valor a tu CV en 2 horas! https://www.udemy.com/course/el-arte-de-programar-en-r-anade-valor-a-tu-cv/?couponCode=B90E90DE425C8BAC6D10 2 Days left at this price!
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  63. [Spanish] 1h 4m Microsoft Excel - Análisis de datos con tablas dinámicas https://www.udemy.com/course/microsoft-excel-analisis-de-datos-con-tablas-dinamicas/?couponCode=E132A1381313060EADBA 2 Days left at this price!
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  76. [English] 0h 49m Color Theory Basics: Learning Color Theory With Adobe Color https://www.udemy.com/course/color-theory-basics-learning-color-theory-with-adobe-colo?couponCode=6950A9D3ED98C8948A02 2 Days left at this price!
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submitted by ViralMedia007 to FREECoursesEveryday [link] [comments]

THROW YOUR FD's in FDS

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down:
https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a

https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp
https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7
So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%
https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.
https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd

P/E has declined in the past 2 years, making it a great time to buy.

https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d
Increasing ROE despite lowering of leverage post 2016
https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.
https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares
I’d say it’s a great long term investment, and it should at least be on your watchlist.
submitted by WannabeStonks69 to wallstreetbets [link] [comments]

Some trading wisdom, tools and information I picked up along the way that helped me be a better trader. Maybe it can help you too.

Its a bit lengthy and I tried to condense it as much as I can. So take everything at a high level as each subject is has a lot more depth but fundamentally if you distill it down its just taking simple things and applying your experience using them to add nuance and better deploy them.
There are exceptions to everything that you will learn with experience or have already learned. If you know something extra or something to add to it to implement it better or more accurately. Then great! However, my intention of this post is just a high level overview. Trading can be far too nuanced to go into in this post and would take forever to type up every exception (not to mention the traders individual personality). If you take the general information as a starting point, hopefully you will learn the edge cases long the way and learn how to use the more effectively if you end up using them. I apologize in advice for any errors or typos.
Introduction After reflecting on my fun (cough) trading journey that was more akin to rolling around on broken glass and wondering if brown glass will help me predict market direction better than green glass. Buying a $100 indicator at 2 am when I was acting a fool, looking at it and going at and going "This is a piece of lagging crap, I miss out on a large part of the fundamental move and never using it for even one trade". All while struggling with massive over trading and bad habits because I would get bored watching a single well placed trade on fold for the day. Also, I wanted to get rich quick.
On top all of that I had a terminal Stage 4 case of FOMO on every time the price would move up and then down then back up. Just think about all those extra pips I could have trading both directions as it moves across the chart! I can just sell right when it goes down, then buy right before it goes up again. Its so easy right? Well, turns out it was not as easy as I thought and I lost a fair chunk of change and hit my head against the wall a lot until it clicked. Which is how I came up with a mixed bag of things that I now call "Trade the Trade" which helped support how I wanted to trade so I can still trade intra day price action like a rabid money without throwing away all my bananas.
Why Make This Post? - Core Topic of Discussion I wish to share a concept I came up with that helped me become a reliable trader. Support the weakness of how I like to trade. Also, explaining what I do helps reinforce my understanding of the information I share as I have to put words to it and not just use internalized processes. I came up with a method that helped me get my head straight when trading intra day.
I call it "Trade the Trade" as I am making mini trades inside of a trade setup I make from analysis on a higher timeframe that would take multiple days to unfold or longer. I will share information, principles, techniques I used and learned from others I talked to on the internet (mixed bag of folks from armatures to professionals, and random internet people) that helped me form a trading style that worked for me. Even people who are not good at trading can say something that might make it click in your head so I would absorbed all the information I could get.I will share the details of how I approach the methodology and the tools in my trading belt that I picked up by filtering through many tools, indicators strategies and witchcraft. Hopefully you read something that ends up helping you be a better trader. I learned a lot from people who make community posts so I wanted to give back now that I got my ducks in a row.
General Trading Advice If your struggling finding your own trading style, fixing weakness's in it, getting started, being reliably profitable or have no framework to build yourself higher with, hopefully you can use the below advice to help provide some direction or clarity to moving forward to be a better trader.
  1. KEEP IT SIMPLE. Do not throw a million things on your chart from the get go or over analyzing what the market is doing while trying to learn the basics. Tons of stuff on your chart can actually slow your learning by distracting your focus on all your bells and whistles and not the price action.
  2. PRICE ACTION. Learn how to read price action. Not just the common formations, but larger groups of bars that form the market structure. Those formations carry more weight the higher the time frame they form on. If struggle to understand what is going on or what your looking at, move to a higher time frame.
  3. INDICATORS. If you do use them you should try to understand how every indicator you use calculates its values. Many indicators are lagging indicators, understanding how it calculates the values can help you learn how to identify the market structure before the indicator would trigger a signal . This will help you understand why the signal is a lagged signal. If you understand that you can easily learn to look at the price action right before the signal and learn to watch for that price action on top of it almost trigging a signal so you can get in at a better position and assume less downside risk. I recommend using no more than 1-2 indicators for simplicity, but your free to use as many as you think you think you need or works for your strategy/trading style.
  4. PSYCOLOGY. First, FOMO is real, don't feed the beast. When you trade you should always have an entry and exit. If you miss your entry do not chase it, wait for a new entry. At its core trading is gambling and your looking for an edge against the house (the other market participants). With that in mind, treat as such. Do not risk more than you can afford to lose. If you are afraid to lose it will negatively effect your trade decisions. Finally, be honest with your self and bad trading happens. No one is going to play trade cop and keep you in line, that's your job.
  5. TRADE DECISION MARKING: Before you enter any trade you should have an entry and exit area. As you learn price action you will get better entries and better exits. Use a larger zone and stop loss at the start while learning. Then you can tighten it up as you gain experience. If you do not have a area you wish to exit, or you are entering because "the markets looking like its gonna go up". Do not enter the trade. Have a reason for everything you do, if you cannot logically explain why then you probably should not be doing it.
  6. ROBOTS/ALGOS: Loved by some, hated by many who lost it all to one, and surrounded by scams on the internet. If you make your own, find a legit one that works and paid for it or lost it all on a crappy one, more power to ya. I do not use robots because I do not like having a robot in control of my money. There is too many edge cases for me to be ok with it.However, the best piece of advice about algos was that the guy had a algo/robot for each market condition (trending/ranging) and would make personalized versions of each for currency pairs as each one has its own personality and can make the same type of movement along side another currency pair but the price action can look way different or the move can be lagged or leading. So whenever he does his own analysis and he sees a trend, he turns the trend trading robot on. If the trend stops, and it starts to range he turns the range trading robot on. He uses robots to trade the market types that he is bad at trading. For example, I suck at trend trading because I just suck at sitting on my hands and letting my trade do its thing.

Trade the Trade - The Methodology

Base Principles These are the base principles I use behind "Trade the Trade". Its called that because you are technically trading inside your larger high time frame trade as it hopefully goes as you have analyzed with the trade setup. It allows you to scratch that intraday trading itch, while not being blind to the bigger market at play. It can help make sense of why the price respects, rejects or flat out ignores support/resistance/pivots.
  1. Trade Setup: Find a trade setup using high level time frames (daily, 4hr, or 1hr time frames). The trade setup will be used as a base for starting to figure out a bias for the markets direction for that day.
  2. Indicator Data: Check any indicators you use (I use Stochastic RSI and Relative Vigor Index) for any useful information on higher timeframes.
  3. Support Resistance: See if any support/resistance/pivot points are in currently being tested/resisted by the price. Also check for any that are within reach so they might become in play through out the day throughout the day (which can influence your bias at least until the price reaches it if it was already moving that direction from previous days/weeks price action).
  4. Currency Strength/Weakness: I use the TradeVision currency strength/weakness dashboard to see if the strength/weakness supports the narrative of my trade and as an early indicator when to keep a closer eye for signs of the price reversing.Without the tool, the same concept can be someone accomplished with fundamentals and checking for higher level trends and checking cross currency pairs for trends as well to indicate strength/weakness, ranging (and where it is in that range) or try to get some general bias from a higher level chart that may help you out. However, it wont help you intra day unless your monitoring the currency's index or a bunch of charts related to the currency.
  5. Watch For Trading Opportunities: Personally I make a mental short list and alerts on TradingView of currency pairs that are close to key levels and so I get a notification if it reaches there so I can check it out. I am not against trading both directions, I just try to trade my bias before the market tries to commit to a direction. Then if I get out of that trade I will scalp against the trend of the day and hold trades longer that are with it.Then when you see a opportunity assume the directional bias you made up earlier (unless the market solidly confirms with price action the direction while waiting for an entry) by trying to look for additional confirmation via indicators, price action on support/resistances etc on the low level time frame or higher level ones like hourly/4hr as the day goes on when the price reaches key areas or makes new market structures to get a good spot to enter a trade in the direction of your bias.Then enter your trade and use the market structures to determine how much of a stop you need. Once your in the trade just monitor it and watch the price action/indicators/tools you use to see if its at risk of going against you. If you really believe the market wont reach your TP and looks like its going to turn against you, then close the trade. Don't just hold on to it for principle and let it draw down on principle or the hope it does not hit your stop loss.
  6. Trade Duration Hold your trades as long or little as you want that fits your personality and trading style/trade analysis. Personally I do not hold trades past the end of the day (I do in some cases when a strong trend folds) and I do not hold trades over the weekends. My TP targets are always places I think it can reach within the day. Typically I try to be flat before I sleep and trade intra day price movements only. Just depends on the higher level outlook, I have to get in at really good prices for me to want to hold a trade and it has to be going strong. Then I will set a slightly aggressive stop on it before I leave. I do know several people that swing trade and hold trades for a long period of time. That is just not a trading style that works for me.
Enhance Your Success Rate Below is information I picked up over the years that helped me enhance my success rate with not only guessing intra day market bias (even if it has not broken into the trend for the day yet (aka pre London open when the end of Asia likes to act funny sometimes), but also with trading price action intra day.
People always say "When you enter a trade have an entry and exits. I am of the belief that most people do not have problem with the entry, its the exit. They either hold too long, or don't hold long enough. With the below tools, drawings, or instruments, hopefully you can increase your individual probability of a successful trade.
**P.S.*\* Your mileage will vary depending on your ability to correctly draw, implement and interpret the below items. They take time and practice to implement with a high degree of proficiency. If you have any questions about how to do that with anything listed, comment below and I will reply as I can. I don't want to answer the same question a million times in a pm.
Tools and Methods Used This is just a high level overview of what I use. Each one of the actions I could go way more in-depth on but I would be here for a week typing something up of I did that. So take the information as a base level understanding of how I use the method or tool. There is always nuance and edge cases that you learn from experience.
Conclusion
I use the above tools/indicators/resources/philosophy's to trade intra day price action that sometimes ends up as noise in the grand scheme of the markets movement.use that method until the price action for the day proves the bias assumption wrong. Also you can couple that with things like Stoch RSI + Relative Vigor Index to find divergences which can increase the probability of your targeted guesses.

Trade Example from Yesterday This is an example of a trade I took today and why I took it. I used the following core areas to make my trade decision.
It may seem like a lot of stuff to process on the fly while trying to figure out live price action but, for the fundamental bias for a pair should already baked in your mindset for any currency pair you trade. For the currency strength/weakness I stare at the dashboard 12-15 hours a day so I am always trying to keep a pulse on what's going or shifts so that's not really a factor when I want to enter as I would not look to enter if I felt the market was shifting against me. Then the higher timeframe analysis had already happened when I woke up, so it was a game of "Stare at the 5 min chart until the price does something interesting"
Trade Example: Today , I went long EUUSD long bias when I first looked at the chart after waking up around 9-10pm Eastern. Fortunately, the first large drop had already happened so I had a easy baseline price movement to work with. I then used tool for currency strength/weakness monitoring, Pivot Points, and bearish divergence detected using Stochastic RSI and Relative Vigor Index.
I first noticed Bearish Divergence on the 1hr time frame using the Stochastic RSI and got confirmation intra day on the 5 min time frame with the Relative Vigor Index. I ended up buying the second mini dip around midnight Eastern because it was already dancing along the pivot point that the price had been dancing along since the big drop below the pivot point and dipped below it and then shortly closed back above it. I put a stop loss below the first large dip. With a TP goal of the middle point pivot line
Then I waited for confirmation or invalidation of my trade. I ended up getting confirmation with Bearish Divergence from the second large dip so I tightened up my stop to below that smaller drip and waited for the London open. Not only was it not a lower low, I could see the divergence with the Relative Vigor Index.
It then ran into London and kept going with tons of momentum. Blew past my TP target so I let it run to see where the momentum stopped. Ended up TP'ing at the Pivot Point support/resistance above the middle pivot line.
Random Note: The Asian session has its own unique price action characteristics that happen regularly enough that you can easily trade them when they happen with high degrees of success. It takes time to learn them all and confidently trade them as its happening. If you trade Asia you should learn to recognize them as they can fake you out if you do not understand what's going on.

TL;DR At the end of the day there is no magic solution that just works. You have to find out what works for you and then what people say works for them. Test it out and see if it works for you or if you can adapt it to work for you. If it does not work or your just not interested then ignore it.
At the end of the day, you have to use your brain to make correct trading decisions. Blindly following indicators may work sometimes in certain market conditions, but trading with information you don't understand can burn you just as easily as help you. Its like playing with fire. So, get out there and grind it out. It will either click or it wont. Not everyone has the mindset or is capable of changing to be a successful trader. Trading is gambling, you do all this work to get a edge on the house. Trading without the edge or an edge you understand how to use will only leave your broker happy in the end.
submitted by marcusrider to Forex [link] [comments]

Profitable Forex Strategy Reddit | 3 Easy Forex Strategies Easy For MT4

Profitable Forex Strategy Reddit | 3 Easy Forex Strategies Easy For MT4

The need for a trading strategy in Forex market

https://preview.redd.it/r6u8stdmeaw51.jpg?width=1320&format=pjpg&auto=webp&s=1b0292502d6e68f5c220af5a5851aeb8061b395b
Almost all trading manuals talk about the need to have your own trading strategy. First of all, the process of creating your trading scheme allows you to perfectly understand trading and exclude from it any eventuality that hides additional risk.
Profitable forex strategy: it is a type of instruction for the trader, which helps to follow a clearly verified algorithm and safeguard his deposit from emotional errors and consequences of the unpredictability of the Forex currency market.
Thanks to her, you will always know the answer to the question: how to act in certain market conditions. You have the conditions of opening a transaction, the conditions of its closing, likewise, you do not guess if it is time or not. You do what the trading strategy tells you. This does not mean that it cannot be changed. A healthy trading scheme in the forex market must be constantly adjusted, it must comply with the realities of current market trends, but there must be no unfounded arguments in it.
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Profitable Forex Strategy Reddit

Types of trading strategies
The forms of a trading strategy can combine a variety of methods. However, several of the most commonly used options can be highlighted.
  • Trading strategy based on various complementary technical indicators
  • Trading strategy using Bollinger Bands
  • Moving Average Strategy
  • Technical figures and patterns
  • Trading with Fibonacci levels
  • Candlestick trading strategy
  • Trend trading strategy
  • Flat trading strategy
  • Scalping
  • Fundamental analysis as the basis of the strategy

Three most profitable Forex strategies

Important! These strategies are the basis for building your own trading system. Indicator settings and recommended pending order levels are for consultation only. If you do not get a satisfactory outcome in the test result or in a live account, that does not mean that the problem is the strategy. It is enough to choose individual parameters of indicators under a separate asset and under the current market situation.

1. “Bali” scalping strategy

This strategy is one of the most popular, at least its description can be found on many websites. However, the recommendations will be different. According to the author's idea, "Bali" refers to scalping tactics, as it facilitates a fairly short stop loss (SL) and take profit (TP). However, the recommended time frame is high, because the signals appear not very often. The authors recommend using the H1 interval and the EUR / USD currency pair.
Indicators used:
  • Linear Weighted Moving Average. Period 48 (red line).
https://preview.redd.it/9mhs67mxeaw51.jpg?width=461&format=pjpg&auto=webp&s=913d428edd4cab0a3237e7039829a76dd587f1f5
The weighted linear moving average here acts as an additional filter. Due to the fact that LWMA gives more weight to the values ​​of the last periods, the indicator in the long periods practically excludes delays. In some cases, LWMA can give a signal beforehand, but in this strategy only the moving position relative to price is important. Bearish LWMA is a buy signal, sell bullish.
  • Trend Envelopes_v2. Period 2 (orange and blue lines).
https://preview.redd.it/8bap0s41faw51.jpg?width=627&format=pjpg&auto=webp&s=a6236ad06765280bbfd655fa1fb4153b28aaaf56
The indicator is also based on the moving average, but the formula is slightly different for the calculation. Its marking is more precise (the impact of price noise has been eliminated). It allows you to identify the twists of the trend compared to the usual mobile with a slight anticipation. Trend Envelopes has an interesting property: the color of the line and its new location changes when the price penetrates its old trend line, a kind of signal.
  • DSS of momentum. The configuration in the screenshot below.
https://preview.redd.it/9ch27cj4faw51.jpg?width=630&format=pjpg&auto=webp&s=00558bbd90378009bef33b7c96c77f884b912667
The indicator is placed in a separate window below the chart. This is an oscillator whose task is to determine the pivot points of the trend. And it does so much faster than standard oscillators. It has two lines: the signal is dotted, the additional line is solid, but the receiver has 2 kinds of colors (orange and green).
  • Important! Note that the indicators for the “Bali” strategy are chosen in such a way as to ultimately give an early signal. This gives the trader time to confirm the signal and check the fundamentals.
MA is one of the basics on MT4, the other two indicators can be found in the archive for free here. To add them to the platform, click on MT4: "File / Open data directory". In the folder that opens, follow the following path: MQL4 / Indicators. Copy the flags to the folder and restart the platform.
Also Read: Make Money With Trading
Conditions to open a long position:
  • Price penetrates the orange Trend Envelopes line from the bottom up. At the same time in the same candle there is a change of the orange line that falls to a growing celestial.
  • The candle is above LWMA. Once the above condition has been met, we wait for the candle to appear above the moving one. It is important that it closes above the LWMA red line. It is mandatory to have a Skyline Trend Envelopes on a signal candle.
  • The additional DSS of momentum line on the signal candle is green and is above the dotted line of the signal (that is, it crosses or crosses it).
We open a trade at the close of the signal candle. The recommended stop level is 20-25 points in 4-digit quotes, take profit at 40-50 points.
https://preview.redd.it/t48d55s8faw51.jpg?width=1000&format=pjpg&auto=webp&s=1e93863745e74dec536178539817225767cbeb1c
The arrow indicates a signal candle where a Trend Envelopes color change occurred. Note (purple ovals) that the blue line is below the orange line and goes upwards (in other cases the signal should be ignored). In the signal candle, the green DSS of momentum line is above the dotted line.
Conditions to open a short position:
  • Price penetrates the Trend Envelopes sky line from top to bottom. At the same time in the same candle there is a change from the increasing celestial line to the falling orange.
  • The candle is below LWMA. Once the above condition has been met, we wait for the candle to appear below the mobile. It is important that it closes below the LWMA red line. It is mandatory to have an orange Trend Envelopes line on a signal candle.
  • The additional DSS of momentum line on the signal candle is orange and is below the dotted line of the signal (i.e. crosses or crosses it).
https://preview.redd.it/6uixkl1dfaw51.jpg?width=1000&format=pjpg&auto=webp&s=dd53442c633e80c1e55da72cd5ffe9cda2e85b8a
Some examples where a transaction cannot be opened:
  1. In the screenshot below the signal candle closed at the moving level (red line), it was practically below it.
https://preview.redd.it/2o1wpocgfaw51.jpg?width=1000&format=pjpg&auto=webp&s=58d3286bf2884b5f0dfdaa0a62b68d2d50cdabf8
  1. In the screenshot below the signal candle is DSS below its signal line. Also, the celestial line is horizontal and not ascending.
https://preview.redd.it/1nfi1etjfaw51.jpg?width=801&format=pjpg&auto=webp&s=ff9fcbc10a485c5102ef7a135de47332827caf54
The signals are relatively rare, a signal can be expected for several days. In half the cases, it is better to control the transaction and close in advance, without waiting for profit taking. We do not operate at the time of flat. Try this strategy directly in the browser and see the result.
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2. “Va-Bank” candle strategy

This profitable Forex strategy is weekly and can be used on different currency pairs. It is based on the spring principle of price movement, what went up quickly, sooner or later must fall. To trade you will only need a schedule on any platform and W1 time frame (although the daily interval can be used).
You should estimate the size of the candle bodies of different currency pairs ( AUDCAD , AUDJPY , AUDUSD , EURGBP , EURJPY , GBPUSD , CHFJPY , NZDCHF , EURAUD , AUDCHF , CADCHF , EURUSD , EURCAD , GBPCHF ) and choose the largest distance from the opening to the close of the candle in the framework of the week. In this to open a transaction at the beginning of the following week.
Conditions to open a long position:
  • The bearish candle, which signifies last week's movement, has a relatively large body.
Open a long position early next week. Make sure to place a stop loss at 100-140 points and a take profit at 50-70 points. When it is midweek, close the order if it has not yet been closed at take profit or stop loss. After that, wait again for the beginning of the week and repeat the procedure, in any case do not open operations at the end of the current week.
https://preview.redd.it/vuihnqspfaw51.jpg?width=1000&format=pjpg&auto=webp&s=7641e9d7701911cc255c4f0c8a53e1660c35c9fe
On this chart it is clearly seen that after each large bearish candle there is necessarily a bullish candle (although smaller). The only question is what period to take where it makes sense to compare the relative length of the candles. Here everything is individual for each currency pair. Note that a rising candle was observed followed by a few small bearish candles. But when it comes to minimizing risks, it is best not to open a long response position, as the relatively small decline from the previous week may continue.
Conditions to open a short position:
  • The bullish candle, which signifies last week's movement, has a relatively large body.
We open a short position early next week.
https://preview.redd.it/tv4zmf5ufaw51.jpg?width=1000&format=pjpg&auto=webp&s=61cd1dcfc4aebfa6f80343b6c51f7a6e46358602
The red arrows point to the candles that had a large body around the previous bullish candles. Almost all signals turned out to be profitable, except for the transactions indicated by a blue arrow. The shortcomings of the strategy are rare signs, albeit with a high probability of profit. The best thing is that it can be used in several pairs at the same time.
This strategy has an interesting modification based on similar logic. Investors with little capital opt for intraday strategies, as their money is insufficient to exert radical pressure on the market. Therefore, if there is a strong move on the weekly chart, this may indicate a cluster of large strong traders. In other words, if there are three weekly candles in one direction, it is most likely the fourth. Here you also have to take into account the psychological factor, 4 candles is equal to one month, and those who "push" the market in one direction, within a month will begin to set profits.
Strategy principle:
  • A "three candles" pattern (ascending and descending) formed on the weekly chart.
  • It is preferable that each subsequent candle was larger than the previous one. Doji is not taken into account (disembodied candles).
  • Stop is placed at the closing level of the first candle of the constructed formation. Take profit at 50-100% of the last candle, but it is often better to manually close the trade.
An example of this type of formation in the screenshot below.
https://preview.redd.it/iu7cwa7xfaw51.jpg?width=1000&format=pjpg&auto=webp&s=9195d24b72d2bda5394614380e9e5bc167f108a5
Of the 5 patterns, 4 were effective. Lack of strategy, the pattern can be expected 2-3 months. But when launching a multi-currency strategy this expectation is justified. Consider swaps!
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3. Parabolic Profit Based on Moving Average

This strategy is universal and is usually given as an example for novice traders. It uses classic EMA (Exponential Moving Average) indicators for MT4 and Parabolic SAR, which acts as a confirmatory indicator.
The strategy is trend. Most sources suggest using it in "minutes", but price noise reduces its efficiency. It is better to use M15-M30 intervals. Currency pairs - Any, but you may need to adjust the indicator settings.
Indicators used:
  • EMA with periods 5, 25 and 50. EMA (5) in red, EMA (25) and EMA (50) in yellow. Apply to Close (closing price).
https://preview.redd.it/ly7ju8o3gaw51.jpg?width=1000&format=pjpg&auto=webp&s=61dee5b0d994d09a375e01e2b9afe188dd2ee0ed
  • Parabolic SAR, parameters remain unchanged (color correct at your discretion).
https://preview.redd.it/sonpv1m8gaw51.jpg?width=1000&format=pjpg&auto=webp&s=823e9ce5d279d3a98ef072694766a112a3ece775
Conditions to open a long position:
  • Red EMA (5) crosses the yellows from bottom to top.
  • Parabolic SAR is located under the sails.
Conditions to open a short position:
  • Red EMA (5) crosses the yellows from top to bottom.
  • Parabolic SAR is located above the candles.
The transaction can be opened on the same candle where the mobile crossover occurred. Stop loss at the local minimum, take profit at 20-25 points. But with the manual management of transactions you can extract great benefits. For example, close at the time of the transition from EMA (5) to a horizontal position (change of the angle of inclination of the growth to flat).
https://preview.redd.it/4un92jlegaw51.jpg?width=1000&format=pjpg&auto=webp&s=406a700c00722349622d031e20d0858e4196d18b
This screen shows that all three signals (two long and one short) were effective. It would be possible to enter the market on the candle by following the signal (in order to accurately verify the direction of the trend), but you would then miss the right time to enter. It is up to you to decide whether it is worth the risk. For one-hour intervals, these parameters hardly work, so be sure to check the performance of the indicators for each period of time in a minimum span of three years.
And now that you know the theory, a few words about how to put these strategies into practice.
Ready? Then let's get started!

From the theory to the practice

Step 1. Open demo account It's free, requires no deposit, takes up to 15 minutes, and no verification required. On the main page of your broker there is for sures a button "Register", click and follow the instructions. An account can also be opened from other menus (for example, from the top menu, from the commercial conditions of the account, etc.).
Step 2. Familiarize yourself with the functionality of the Personal Area. It won't take long. It is at the most user friendly and intuitive. You just need to understand the instruments of the platform and understand how the trades are opened.
Step 3. Launch the trading platform. The Personal Area has the platform incorporated, but it is impossible to add templates. Hence, the "Bali" and "Parabolic Profit" strategies can only be executed on MT4.

Characteristics of an effective Forex strategy Reddit

And finally, let's see what makes a profitable Forex strategy effective. What properties should it have? Perhaps three of the most important characteristics can be pointed out.
  • The minimum number of lag indicators. The smaller they are, the greater the forecast accuracy.
  • Easy. Understanding your strategy is more important than your saturation with complex elements, formulas, and schematics.
  • Uniqueness. Any trading strategy must be "tailored" to your trading style, your character, your circumstances, and so on.
It is very important to develop your own trading strategy, but it is necessary to test a large number of already available and proven strategies. On the Forex blog you will find trading strategies available for download. Before using a live account, test your chosen strategy on the demo account on the MetaTrader trading platform.
Conclusion. To successfully trade the Forex currency market, create your own trading strategy. Learn what's new, learn out-of-the-box trading schemes, and improve your individual action plan in the market. Only in this case, the trading results will satisfy you to the fullest. Success, dear readers!
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Join the community for more articles on trading and making money on the Forex and Stock market.
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submitted by kayakero to makemoneyforexreddit [link] [comments]

H1 Backtest of ParallaxFX's BBStoch system

Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are.
TL;DR at the bottom for those not interested in the details.
This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.

Background

For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX!
I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose.
This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem.
I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.

System Details

I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:

And now for the fun. Results!

As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker.
EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.

A Note on Spread

As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits.
Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way).
However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades.
You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term.
Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.

Time of Day

Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either.
On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate.
That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.

Moving stops up to breakeven

This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers.
Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability.
One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)?
Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right?
Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert.
I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall.
The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.

2-Candle vs Confirmation Candle Stops

Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it.
Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL.
Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.

Correlated Trades

As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular.
Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system.
This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here).
Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses.
Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels).
Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant.
One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak.
EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much.
I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system.
This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions.
There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated.
I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful.
Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.

What I will trade

Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.)
I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:

Demo Trading Results

Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc).
A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade.
I'm heading out of town next week, then after that it'll be time to take this sucker live!

Live Trading Results

I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
submitted by ForexBorex to Forex [link] [comments]

eToro: impressions, doubts and (ignored) lessons from copy trading

(no promotional content, no affiliate links)
Hi,
exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account:
https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing
In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot.
What I did after that?
Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading.
Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
My observations and thoughts are as follows:
  1. Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
  2. I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now?
I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are.
rubymza (Heloise Greeff)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market.
Wish me good luck!
Michael

P.S.
You might find those copy-trading related readings interesting:

Disclosures:
submitted by investing-scientist2 to StockMarket [link] [comments]

Factset DD

Factset: How You can Invest in Hedge Funds’ Biggest Investment
Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists
If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now:
Their latest 8k filing reported the following:
Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions.
Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region
Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic.
Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019.
Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results.
The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020.
FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders.
As you can see, there’s not much of a negative sign in sight here.
It makes sense considering how FactSet’s FCF has never slowed down
FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with.
Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis:
https://www.investopedia.com/terms/f/factset.asp

FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015:

So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33%

EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded.

P/E has declined in the past 2 years, making it a great time to buy.

Increasing ROE despite lowering of leverage post 2016

Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself.

SGA expense/Gross profit has been declining despite expansion of offices
I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful.
Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
submitted by WannabeStonks69 to investing [link] [comments]

Copy trading with eToro: impressions, doubts and (ignored) lessons

(no promotional content, no affiliate links)
Hi,
exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account:
https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing
In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot.
What I did after that?
Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading.
Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
My observations and thoughts are as follows:
  1. Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
  2. I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now?
I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are.
rubymza (Heloise Greeff)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market.
Wish me good luck!
Michael

P.S.
You might find those copy-trading related readings interesting:

Disclosures:
submitted by investing-scientist2 to InvestmentClub [link] [comments]

Where is Bitcoin Going and When?

Where is Bitcoin Going and When?

The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.

Stock Market Crash

The Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.

Economic Analysis of Bitcoin

The reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.

Trading or Investing?

The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.

Technical Indicator Analysis of Bitcoin

Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
  • Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume for stocks is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. This does not occur with BTC, as it is open twenty-four-seven. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes (peaks and troughs) because of levels of fear. Volume allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Volume is steadily decreasing. Lows and highs are reached when volume is lower.
Therefore, due to the relatively high volume on the 12th of March, we can safely determine that a low for BTC was not reached.
  • VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. VIX is essentially useless for BTC as BTC-based options do not exist. It allows us to predict the market low for $SPY, which will have an indirect impact on BTC in the short term, likely leading to the yearly low. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend for the S&P 500 is imminent.
  • RSI (Relative Strength Index): The most important technical indicator, useful for determining highs and lows when time symmetry is not availing itself. Sometimes analysis of RSI can conflict in different time frames, easiest way to use it is when it is at extremes – either under 30 or over 70. Extremes can be used for filtering highs or lows based on time-and-price window calculations. Highly instructive as to major corrective clues and indicative of continued directional movement. Must determine if longer-term RSI values find support at same values as before. It is currently at 73.56.
  • Secondly, RSI may be used as a high or low filter, to observe the level that short-term RSI reaches in counter-trend corrections. Repetitions based on market movements based on RSI determine how long a trade should be held onto. Once a short term RSI reaches an extreme and stay there, the other RSI’s should gradually reach the same extremes. Once all RSI’s are at extreme highs, a trend confirmation should occur and RSI’s should drop to their midpoint.

Trend Definition Analysis of Bitcoin

Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.

Time Symmetry Analysis of Bitcoin

Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
  • Yearly Lows (last seven years): 1/1/13, 4/10/14, 1/15/15, 1/17/16, 1/1/17, 12/15/18, 2/6/19
  • Monthly Mode: 1, 1, 1, 1, 2, 4, 12
  • Daily Mode: 1, 1, 6, 10, 15, 15, 17
  • Monthly Lows (for the last year): 3/12/20 (10:00pm), 2/28/20 (7:09am), 1/2/20 (8:09pm), 12/18/19 (8:00am), 11/25/19 (1:00am), 10/24/19 (2:59am), 9/30/19 (2:59am), 8/29,19 (4:00am), 7/17/19 (7:59am), 6/4/19 (5:59pm), 5/1/19 (12:00am), 4/1/19 (12:00am)
  • Daily Lows Mode for those Months: 1, 1, 2, 4, 12, 17, 18, 24, 25, 28, 29, 30
  • Hourly Lows Mode for those Months (Military time): 0100, 0200, 0200, 0400, 0700, 0700, 0800, 1200, 1200, 1700, 2000, 2200
  • Minute Lows Mode for those Months: 00, 00, 00, 00, 00, 00, 09, 09, 59, 59, 59, 59
  • Day of the Week Lows (last twenty-six weeks):
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
  • 2/14/20 – yearly high ($10372 USD)
  • 3/12/20 – yearly low thus far ($3858 USD)
  • 5/9/20 – T-Theory true yearly low (BTC between 4863 and 3569)
  • 5/26/20 – hashrate difficulty halvening
  • 11/14/20 – stock market low
  • 1/15/21 – yearly low for BTC, around $8528
  • 8/19/21 – end of stock bear market
  • 11/26/21 – eighteen months from halvening, average peak from halvenings (BTC begins rising from $3000 area to above $23,312)
  • 4/23/22 – all-time high
Taken from my blog: http://aliamin.info/2020/
submitted by aibnsamin1 to Bitcoin [link] [comments]

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