If you want to learn algorithmic trading, check out this free course that I created here on RU-vid: ru-vid.com/group/PLtqRgJ_TIq8Y6YG8G-ETIFW_36mvxMLad
It's so refreshing to see high-quality content on this topic from someone who clearly means well. And there are no scammers pushing bitcoin scams in your comments, again so refreshing. Thanks for this wonderful video.
SIR, Which support is more likely to hold-- A) one with fractal support Or B) one without fractal support? Which support is more likely to hold A) fresh recent support--not tested before Or B) Support which has proved successful being tested many times before? Which support is more likely to hold A) where price spent little time before being repelled away successfully Or where price spent a lot of time before moving away?And I Seek your wisdom on these life & death questions.
Yes, check out my free algorithmic trading course playlist. There you will learn how to code your own algorithms using Python and QuantConnect. I’ll release a video demonstrating how to trade crypto like that soon.
@@MrSimonw58 That depends on your trading volume. But IB was just one example. Like I said, most brokers that have an open API and options, allow you to trade options algorithmically...
Thank you very much for your videos. They are all very helpful. I have advanced degrees in Finance and Economics and I use python on daily basis. You inspired me dozens of projects that I can work on in the future. Thanks again. Your explanation is very simple but informative.
Firstly, you need to make sure that you actually have a complete strategy. Try to write it down in an “if this then do that” manner. You only have a strategy if you actually cover every possible case. As for coding, you could check out some of the best algorithmic trading platforms here: tradeoptionswithme.com/best-algo-trading-platforms/ For examples of how to code a trading bot using Python, you could check out my algorithmic trading video playlist.
In statistical arbitrage strategies, you usually don’t only look at the correlation between 2 securities. Instead, you often look at and analyze the correlations between hundreds of different securities and look for small inefficiencies. Even though this is still based on the pairs trading idea, I wouldn’t directly call it a mean reversion strategy. I hope this answers your question.
Or you can keep it simple... Price moves in waves and you are trying to catch one of these 3 stages: - Momentum switch: your algo is trying to catch the start of a new wave. - Countertrend: the algo is trying to anticipate the peak or bottom of an existing wave. - Zero cross: The algo is entering in the mid-point of an existing wave, and assumes there is room left before reaching a turning point. Each market is a different animal, and one of those 3 stages could be their weakness (i.e Countertrend for EURUSD or Zero-cross for most GBP pairs on the Daily TF).
@@animeshsahu2803 If you want to see a "zero-cross" in action, take a look into a MACD histogram or normalized oscillator. You could build an algo by using a middle-cross as signal. For example, when histogram goes below the middle point (zero) you sell and when it goes above you buy. You are assuming that there is still movement left for such wave and are trying to reach a price over-extension (also known as overbought/oversold). You will notice that these signals are usually a lot slower than slope switching or countertrends, but eliminates a lot of false signals. You can speed up the algo by switching the averaging method and lookback periods (ie: Instead of using simple or exponential try KAMA or FRAMA averaging in your oscillators; google them up). You can build a well balanced portfolio by mixing these 3 types.
can you please tell me what if i want to trade through trading bot on exchange platform that i use and i did not want my limit order to show up in order book on the basic exchange platform what i meant here is hidden order on the basic exchange platform So can you please tell me what is the name of this strategy
QuantConnect since they allow you to create, backtest, and host your algos in one place: www.quantconnect.com/?ref=towm I have a course in which you also learn how to create algorithms using Python and their platform.
Hi! As always very awesome content! I have a question for you. What's your opinion about mean reversion strategies? I mean, markets are a random sequence of time series data, where given prices are not pure random but the behaviour and "patterns" like mean reversion can change from one day to one... Don't you think is a kind of gambling use a mean reversión strategy? Thanks in advance.
Good discussion of some basic strategies that have been around for many years. The straegies are good strategies and often lead to profits.But why do you need to call the strategies "algorithms". The "following a trend strategy" has been around since Jesse Livermore! What is the signifiacnce of calling the strategy an "algo"?
I'm Forex trader and cryptos the most, for some years and starting to learn to code for my own strategies i love algos, it's other kind of different subject than Mql4 for metatrader, this videos it's having a full understand of all market as well as i know in different strategies i'm using manual, but since this is a more complex it´s worth great video my friend thank you i'm sticking to your videos and advices how to also learn algorith trading and what is it, so for me in the years to come i will be more confident to automatize strategies to be more relax.
Whilst you have made this accessible, you talk about algorithmic trading - do you teach how to code in your course? What is your own background that means you can teach us?
You can check out my free course here: ru-vid.com/group/PLtqRgJ_TIq8Y6YG8G-ETIFW_36mvxMLad I also go over coding in it, but I expect you to already be familiar with basic Python
@@TradeOptionsWithMe what's your experience with python? Are you a hobbyist or professional coder? How many years experience do you have? I can't find it on your Web page.
You can certainly use moving averages as tools inside of a given strategy. For instance, they are great to measure an average for a mean reversion strategy. Note that how you implement your strategy is entirely up to you. You can make it as simple or complex as you want to. So it is definitely possible to create a strategy that solely relies on moving averages for its trade signals. The performance of such a simple strategy, however might not be very outstanding.
Ich finde "Inside the black box" ist ein sehr gutes Buch in diesem Themenbereich: amzn.to/3vGJngN Ansonsten wird "Quantitative Trading" von Ernest Chan oft empfohlen: amzn.to/3c2dnfi (das habe ich jedoch noch nicht gelesen)
I made my own trading robot and tested it on old data and found that it was 80% effective, but when I tried it on real data, I noticed that it was not working, I don’t know why, even though I use a good server with a fast speed
Thanks for the comment. Note that there is a huge difference between historical results and actual real-life results. These differences can be due to biases, errors, market changes and much more. I have two videos going over some of the potential problems when it comes to analyzing backtest results that you can check out here: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-VmD2fUt8KYY.html ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-oFvYbfDOJ5c.html (this one is part of my free algo trading course) I recommend using QuantConnect since they allow you to create, backtest, and host your algos in one place: www.quantconnect.com/?ref=towm In my course, you also learn how to create algorithms using Python and their platform.
trades still not happen instantly like in your simulation. Real time trading is a very copetitive field. A "good" server is simply not good enough here. We are talking reactions to price movents in nanoseconds
Thanks for the question. I recommend checking out my post for an overview of some of the best algorithmic trading platforms: tradeoptionswithme.com/best-algo-trading-platforms/ If you choose QuantConnect, you can check out my algorithmic trading playlist for some tutorial videos on sample trading algorithms. I hope this helps.
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1:23 This is known as the gambler's fallacy and is false for human heights. It may be true for stocks, but that's because movement of stock prices are not time independent.
Hi Mike, Thanks for your comment. I think you misunderstood me. Since human height is a normally distributed variable, you are much more likely to meet a person with a height near the mean than a person that is particularly short or tall. I am not saying that this probability changes just because you met a tall person like the gambler's fallacy would imply. But if you meet a person that is taller than 90% of the population, chances are high that the next person you see is part of this 90% and thus shorter than the tall person. I am sorry if I didn't make this clear enough. If you are interested in a detailed breakdown of the gambler's fallacy, and 9 other trading-related biases, you could check out this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-oDJBscAgDFk.html
@@TradeOptionsWithMe Yes, that is correct. Seeing a taller than average person doesn't change the probability distribution of heights you will see in the future, but you would still expect them to be shorter than that initial person on average because that person was taller than the mean. Thanks for the quick response!
You said that if you meet a tall person, that there's higher chance that the next person will be shorter. That's not true, and is an example of gambler paradox, gamblers often think that if they lost many times on a bandit machine, their probability of winning increases so they can bet more. In fact the probability is constantly the same (unless the bandit machine cheats). As for people, even the opposite may be true, eg when a group of basketball players is coming, all of them are very tall.
Hi Mike, Thanks for your comment. I think you misunderstood me. Since human height is a normally distributed variable, you are much more likely to meet a person with a height near the mean than a person that is particularly short or tall. I am not saying that this probability changes just because you met a tall person like the gambler's fallacy would imply. The probability distribution stays constant. But if you meet a person that is taller than 90% of the population, chances are high that the next person you see is part of this 90% and thus shorter than the tall person. I am sorry if I didn't make this clear enough. If you are interested in a detailed breakdown of the gambler's fallacy, and 9 other trading-related biases, you could check out this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-oDJBscAgDFk.html
I am sorry that the video didn’t meet your expectations. The purpose of this video was to give a conceptual overview of different (algorithmic) trading approaches. What exactly did you expect?
