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Algotrading

Entries do not matter (Course #3)Entries do not matter (Course #3) One thing that I have read many times but never believed is, entries do not matter. After trading a whole lot of different strategies in a repeatable fashion (algo trading), I found that indeed, entries don’t matter. Of course, if you get in at a bottom for a long or at the top for a short, it feels nice and the entry is absolutely great, because you get the maximum possible outcome in you think about the market played out. This being said, over time, what will make you successful is really a factor of when you exit AND your system overall (covered course #5). You should not look at the market and hope to get in here and exit there, because the market is not consistent. The market has no rules and no discipline. Instead, you should look at your system and hope to get out when it’s the right time. It is the same in life, look at what you can control - here this is your system, since you can't control the market. READ THIS AGAIN. In other words, let’s say I always enter at the wrong time, but the price always goes in my direction for at least 0.25% before going the other way. If I can exit on that 0.25%, I will make money! If my – consistent, disciplined - trading system can get out at 0.25% all the time, it doesn't matter I had a bad entry, because first of all I am not losing money and second, I am making some. So yes, entries don’t really matter, but exits do. Look at Crypto Face of Market Cipher. Very often he enters before a pump, because he is good and because his indicator is good as well. You can call this a “good entry”. But sometimes, he does enter and the trades goes against him. Many times I noticed he would not close his trade, and just wait overnight for it to come back. Let’s say the price does come back, and now goes into profit – he exits. What mattered? His exit. If he had exited when the trade was against him, he would have lost money. In his book “Trade your way to financial freedom”, Van Tharp talks about it and he explains how a random entry system can beat any other system with a specific entry technique. Whether you are trading algos or manually, you have to understand that it doesn’t matter when you enter. What matters is your system and when you exit. My #1 profitable algo is designed to never get in at a bottom or a top, for respectively a long or a short trade. Yet, this algo strategy is profitable.
Education
by Maddrix_club
9 things that do not come easy when implementing Algo TradingA collection of less obvious hurdles you may discover on the Algo trading implementation journey. #1 Data is king Some brokers provide basic data feed for algo trading, but more often you will be looking for: Decent amount of historical data of decent quality for backtesting. Real time market data. Not the end of the day, and not 15 minutes delayed. As close to real time as possible, with possibility to subscribe for data push notifications. Data aggregated from multiple exchanges. If you want to make decisions (you do) based on pre- or after- market hours data, this is a must have. No or reasonable limit on the number of tickers you can get data for concurrently. Data on market index constituents. And ideally historical data, as constituents change, and you want to backtest our algos without “cheating” (survival bias). Corporate and fundamentals data. Historical data is quite useful here as well. Even to satisfy this short list, you need a specialized data provider or a few. For personal use it comes to a couple of hundred dollars of fees a month. It might be under one hundred if you sacrifice some requirements and data quality. #2 Orders can be over-executed Ever encountered a situation when your limit order and stop-loss order were executed simultaneously? Well, it does happen. It’s much more rare when trading manually, but when a program is able to submit orders so much faster, and generate higher order flow, probability of it naturally increases. A trading engine must be able to recognize such situations and react accordingly. I.e. calmly close the resulting short position (or long position if you are exiting a short trade). #3 Not all brokers let you set order validity Quite typical for brokers is to allow an order validity of 1 day, but not shorter. A common situation is that you submit a buy limit order, the market goes up, our order remains pending, and never executes expiring at the end of the day. A good trading engine would be able to handle such cases and provide configurable validity. E.g. submit a limit order and if it does not execute after 5 minutes — cancel the order and try something else, adjust the price or try a different ticker altogether. #4 Circuit breakers is the new reality Remember when the SEC halted trading on meme stocks or the stocks would not trade during the covid news? Halts happen for various reasons, so a trading engine needs to react accordingly. I.e. not go frenzy during the pause, and continue trading as soon as trading reopens. #5 Stock splits, ticker renames, mergers and acquisitions are a lot more challenging for an algo Apple, Tesla, anyone who decides to do a stock split, you need to handle that properly as well: take it into account when exiting the trade, calculating profits and benchmarks. Same with reverse split, which is quite common for the stock trading under $1. As well as another subtle but similar in nature event of issuing stock dividends by a company. Facebook renames to Meta and changes the ticker. Hertz files for bankruptcy and emerges back on the market under a new ticker. Cloudera gets acquired and becomes private. All these and many more need to be smoothly handled by the engine, data needs sourced to be linked back to action. #6 Penny stocks need a special treatment Stocks under $1 are quite special indeed. Besides the risk being delisted if a stock trades for under $1 for a period of time, such stock has also a privilege, it can be traded for sub-penny amounts, i.e. for multiples of $.0001. You should carefully handle that in the trading engine, so you can benefit from more precise order placement and stop losses. #7 Index constituents are harder than it should be to For a good trading engine you need an ability to continuously screen a set of securities for desired market patterns. Probably you don’t want to manually enter a bunch of tickers, but use well recognized “buckets” such as market indexes, S&P 500, DJIA, and others. And of course you need to monitor how the constituents of these buckets change over time. Get the historical data and index updates in a reliable way is a project on it’s own. #8 Speed of execution matters a lot Working with the arrays of data, monitoring and trading multiple tickers soon starts taking quite a bit of time, minutes or even hours. Performance optimization, parallel execution and scaling are soon to come as a requirement. Even for a retail trader delays longer than a few seconds may noticeably impact the gains. #9 Unattended execution is costly You don’t want the algo to stop trading when you close a laptop, or don’t have internet connectivity. To achieve unattended execution, you need the right infrastructure, monitoring, backups, disaster recovery and many other fun things. It’s an extra buck but definitely worth the spend.
AMEX:SPYEducation
by BreakingEquity_official
Position Sizing (Course #0)My very first course was going to be the winning rate. As I wrote down the other ones, I realized that position sizing, understanding what it is and how it works, was actually the most important part of it all. Therefore, I have decided to create this course #0 as the one you MUST take first to understand the other stuff. Understanding position sizing is very tricky actually. The very first time I learned about it was with Crypto Cred. He’s got a lot of great courses on trading and Technical Analysis, I also recommend you checking him out. So here is what most people think about doing: I will buy 100% of my account balance into bitcoin ($1,000 account), my account size will then be $1,000. Or, I will buy with 15% of my account, so my position will be $150. Even better, I will go 10x and my position size will be $10,000. This is great and all, but this is NOT how you should look at it. Whenever you trade, you MUST – SHALL – HAVE TO HAVE – an plan on where and why do you enter, where you need to exit at profit AND where you need to exit at loss. If you don’t want to accept that, no good. If you want to invest into something, you MUST – SHALL – HAVE TO HAVE – an plan on where and why do you enter, where you need to exit at profit AND where you need to exit at loss. If you don’t want to accept that, no good. It’s like driving, you must know when to turn, accelerate and break. So, because you will have a plan, you will know OR you will decide where to put your Stop Loss. For example, you want to put your stop loss the 20 EMA. Or, you want to put your stop loss at the low of the previous candle. Or, you want to put your stop loss 0.5% below your entry. Or, you want to put your stop loss at the previous support level. Once you have decided where to put your Stop Loss, based on your strategy and on the structure of the market/chart, you will need to decide how much you will risk on that trade. Basically, trading is like betting. You will bet/risk an amount of money, hoping to make a profit. To give you an idea, 1% risk is cool, if you want fast results you can go to 2-3% (of your account balance). Some great traders like to do 5-20%, but this is super high risk. 5-20% on an intraday trading strategy (in and out during the same day), then this is degen to me. On an intraday 1-2% risk per trade is good. So now, you are starting to be good at position sizing: you know where your stop loss will be and you know how much you will risk. Let’s go back to our examples of stop losses. Example 1: you want to put your stop loss the 20 EMA Example 2: you want to put your stop loss at the low of the previous candle Example 3: you want to put your stop loss 0.5% below your entry Example 4: you want to put your stop loss at the previous support level On the above chart, here are the distance between your entry and the stop losses: Example 1, the 20 EMA is 0.28% below your entry. Example 2, the low of the previous candle is 2.30% below your entry. Example 3, the stop loss is exactly 0.50% below the entry, like you decided. Example 4, the previous support level is 4.60% below your entry. Now let’s calculate your position size: Magic Formula: Position size = Risk % / Distance to SL % Example 1: 1% / 0.28% = 3.57 This means your position size will be 3.57 times your account balance. Example 2: 1% / 2.30% = 0.437 This means your position size will be 0.437 times your account balance, so a little bit less than half of it. Example 3: 1%/0.5% = 0.50 Your position size is equal to half your account. Example 4: 1%/4.60% = 0.22 Your position size will be 0.22 times your account. So now, do you understand that leverage should only be necessary when your strategy calls for a Stop Loss that is positioned at a distance that is less than your risk %? This is example 1. You should NEVER think “I want to use 10x” just for fun. You should only apply leverage because your position size calculation told you so. Conclusion: Position Sizing is the calculation of how much should your position be, so that when you hit your SL, you only lose what you planned losing. Position size = RISK % / DISTANCE TO SL %
Education
by Maddrix_club
1
Mid term forecast of XAU/USD GOLDZEYAN here!!!! I'm looking at the market as a bearish pov i was bullish on gold before but now as far as i can see market is quite bearish so ill be looking to sell the retracements This is a general idea of how I view the market; I use various entry techniques; please do not take this information at face value; conduct your own research. Please let me know in the comments if you want me to analyse your charts. like for more!!!!!!!!! This is not financial advice; please conduct your own research and use this information as confirmation in addition to your own analysis.
TVC:GOLDShort
by zeyankhan1318
Can Just One Trade a Day Be Any Good?Everyone wants a trading strategy that allows you to make one trade per day, yet you can still beat the market. Here we explore how you could make one. The Strategy: Gap & Go for Biotech Stocks We decided not to reinvent the wheel and just took the highly popularized "Gap & Go" strategy. The “Gap & Go” is looking for a stock gap up from the previous day's close price with the goal to follow an uptrend. We use biotech stocks as they tend to have higher volatility compared to other industries. You can easily find way more information about the idea and the thesis behind it. We also have a detailed explanation of the enter and exit conditions below. Screening Criteria Biotech Equities (we're using iShares Biotechnology ETF $IBB as a list) Up in the morning 3% or more Are above pre-market high and yesterday’s high Enter Criteria (when to open the position) Stock price is above EMA 9 Stock is going up and EMA 9 is going Exit Criteria(when to close the position) Price crosses below EMA 9 and stays there for 3 bars End of the same day Trailing stop loss of 1.0% Conditions $10,000 trading capital Do not trade early close days Only one trade per day If no equities meet the screening or entry criteria, do not trade The Results: +58% gain over one year Profit $5,801.4 | Wins 48 | Losses 49 Looks pretty decent, but we think that’s just the beginning as we’re going to improve it even further by looking at overall market conditions like $SPY behavior or news. Disclaimer: Not financial / investment advice
NASDAQ:IBBEducation
by BreakingEquity_official
BUY NOW and set your year RETURN. Hi traders, USD loosing strength due to the increase of interest rates. that will not only affect the currency short term but long term, consequences of Inflation. currently many central governments are raising interest rates and according to their monetary policy, we can expect the price to behave emphatically. -------------------------------------------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------------------------------------- Prices do change constantly and following PRIMEALGO channel will keep you updated with a highly experienced traders around the globe.
Long
by BlaiseThewinner
2
Most gains for $SPY happen overnight: a quantitative studyAccording to the New York Times 2018: most gains for $SPY happen overnight. "If you had bought the SPY at the last second of trading on each business day since 1993 and sold at the market open the next day — capturing all of the net after-hour gains — your cumulative price gain would be 571 percent." We thought why not to review this thesis in a bit more detailed way. We set a simple backtest that is not going back to 1993 but to Jan 1, 2010: hold overnight and sell in the morning. The Setup $10,000 to trade daily (nightly actually) Trading only $SPY Buy at 3:59 using a market order Sell at 9:30, 9:31, 9:32, 9:33, 9:34, 9:35 (let's see which one does better) using a market order Do not trade on early close days Algo Parameters Enter Criteria: 1.#No condition - just enter a position 2.True Exit Criteria: 1.#Exit next day, when there is a position 2.$Position.size>0 The Results Strategy: Hold overnight, exit 9:30 Total wins: 1651 Total loses: 1359 Total gain: 79.54% Total gain 2022: -2.59% Strategy: Hold overnight, exit 9:31 Total wins: 1629 Total loses: 1341 Total gain: 80.04% Total gain 2022: -2.88% Strategy: Hold overnight, exit 9:32 Total wins: 1628 Total loses: 1342 Total gain: 88.80% Total gain 2022: -3.31% Strategy: Hold overnight, exit 9:33 Total wins: 1618 Total loses: 1352 Total gain: 94.28% Total gain 2022: -3.96% Strategy: Hold overnight, exit 9:34 Total wins: 1617 Total loses: 1353 Total gain: 94.11% Total gain 2022: -3.63% Strategy: Hold overnight, exit 9:35 Total wins: 1633 Total loses: 1337 Total gain: 90.48% Total gain 2022: -4.36% Disclaimer: This post is for fun and educational purposes only with no attempt to beat buy and hold. Do not use this as trading/investment advice.
AMEX:SPYEducation
by BreakingEquity_official
2
Can pre-market tell you anything: a quantitative studyPre-market is an exciting time when you start looking at your screens to check what's going on. There is a lot of information to consume: news, reports, charts... you can continue the list. In this study, we explore if price movement in pre-market can provide any indications of what the day is going to look like. There are 3 setups we tested from 2015 to 2022 Up 1%+ in pre-market Down 1%+ in pre-market Flat in pre-market (open and close are within 0.1%) Trading Conditions $10,000 to trade daily Trading only $SPY Buy at 9:30 if the condition is met Do not trade on early close days The Results: Most of the time when it's down in pre-market it tends to rebound. It's well known that bulls run by night and seem like tend to buy the lows if the early hours didn't work out. 2015: Down 1%: Gain 3.42%, Win/Loss 2/3 Up 1%: Gain -2.56%, Win/Loss 1/1 Flat: Gain -5.9%, Win/Loss 37/42 2016: Down 1%: Gain 1.26%, Win/Loss 2/1 Up 1%: Gain 2.66%, Win/Loss 2/1 Flat: Gain -2.11%, Win/Loss 37/39 2017: Down 1%: Gain 0%, Win/Loss 0/0 Up 1%: Gain 0%, Win/Loss 0/0 Flat: Gain 6.22%, Win/Loss 71/45 2018: Down 1%: Gain 3.61%, Win/Loss 2/1 Up 1%: Gain -2.73%, Win/Loss 0/2 Flat: Gain -1.44%, Win/Loss 48/35 2019: Down 1%: Gain 0.37%, Win/Loss 2/1 Up 1%: Gain 0.33%, Win/Loss 1/0 Flat: Gain 3.14%, Win/Loss 55/46 2020: Down 1%: Gain 3.85%, Win/Loss 8/9 Up 1%: Gain -2.85%, Win/Loss 5/7 Flat: Gain -3.02%, Win/Loss 39/27 2021: Down 1%: Gain 0%, Win/Loss 0/0 Up 1%: Gain 1.4%, Win/Loss 2/0 Flat: Gain 1.13%, Win/Loss 35/34 2022: Down 1%: Gain 1.25%, Win/Loss 1/1 Up 1%: Gain -3.26%, Win/Loss 0/2 Flat:Gain -2.61%, Win/Loss 2/2 Disclaimer: This post is for fun and educational purposes only with no attempt to beat buy and hold. Do not use this as trading/investment advice.
AMEX:SPYEducation
by BreakingEquity_official
Most traders underperform to a coin flip day trading botFirst-time day traders are most likely going to lose money. CNBC quotes at least four studies with a similar conclusion: 90% of traders fail to make money. The primary reason that most traders fail is not because of their strategy, it is because of their psychology. As Benjamin Graham liked to say, “The worst enemy of the investor is most likely himself.” To quantify how bad the fact of 90% losing money is, we compared it to a coin flip trading bot which makes a trading decision based on a virtual coin flip random(0,1) Below are the results for Trading $QQQ Random enter and exit at 10min intervals No stop loss Always exit EOD (no hold overnight) 100 simulations per year to smooth it out Algo parameters: Enter Criteria: $Random.random >=0.5 Exit Criteria: $Random.random >=0.5 Year over year performance: 2016: Average Performance 1.92% Best Performance 20.38% Worst Performance -10.21% Average MDD -6.65% 2017: Average Performance 3.08% Best Performance 10.92% Worst Performance -4.10% Average MDD -3.99% 2018: Average Performance -3.56% Best Performance 21.65% Worst Performance -21.08% Average MDD -12.05% 2019: Average Performance 4.80% Best Performance 15.61% Worst Performance -6.75% Average MDD -6.03% 2020: Average Performance 6.66% Best Performance 33.63% Worst Performance -17.12% Average MDD -10.69% 2021: Average Performance 2.41% Best Performance 26.31% Worst Performance -17.97% Average MDD -7.25% 2022: Average Performance -4.21% Best Performance 3.91% Worst Performance -10.00% Average MDD -5.40% We expected it to perform worse than that ;) Disclaimer: NOT financial/investment advice
NASDAQ:QQQEducation
by BreakingEquity_official