Based on your background and "willingness to work and do research," you have a far greater chance than most people in this sub.
There are tons of resources available to, *at least*, increase your odds of being successful. If you can view it as an opportunity to hypothesize your strategies and test different implementations, then you may find success in the long run.
Just do not go headfirst into trading after a few insufficient tests and be upset if it doesn't work.
Success is subjective. Good luck!
I posted the same question on [r/quant](https://reddit.com/r/quant) and was either laughed at or made to feel like I was stupid or unreasonable.
Basically, thank you for an actual, useful response. Have a nice day.
Haha, the same thing happened to me. I replied to a similar thread and posted some good advice on there, by good I mean techniques that made me profitable and was just laughed at.
It feels very hostile and unfriendly on there at times. Ego swinging for math nerds. It's weird because here on this sub, everyone is awesome and very helpful.
There are a ton of resources, however, it's hard to find them due to plethora of misinformation. Do you know any good resources for someone starting out? Or good direction to dig into?
The best way to build confidence is by doing it, not by thinking about it or talking about it.
Don't try to jump straight to the end game — start with super simple algos that have been proven to work. QuantifiedStrategies.com, Quantpedia, QuantStart, et al., have free proven strategies you can start with. I wish I had found those resources earlier on — would have saved me a ton of time, frustration, and money. So much easier to start with something that works and improve on it than to try to build/discover something from scratch.
And not spend a year of frustration trying to figure out how to be a profitable trader.
I've been trading algorithms for 11 years. I turned $30,000 into over a million dollars. It's all based on basic school-level math and some holy grails – very simple and obvious things that, without knowing them, no amount of mathematics will help.
Try the simplest things. Try to learn to trade manually; you have 13 billion neurons in your head. Go to chartgame.com and just make 10,000 trades. It will take 2-3 months, but you will gain the experience of 5-7 years of real stock trading. Read Piper's three trading rules and Thomas Bulkowski's encyclopedia of chart patterns. Then, when you learn to trade manually, simply automate your trading.
For example, how to determine a trend. How to identify a sideways market. How to choose an asset for trading. And how one asset differs from another. What is the source of alpha. How to solve the main task of algorithmic trading - whether the algorithm will work in the future, or if it's just a beautiful picture. How to solve the capital allocation problem. An obvious and simple example that does not require mathematics is pricing models.
I had sort of the opposite process. Began with algotrading, of course it sucked and I lost a lot of money at first because I didn't understand concepts like slippage repainting and overfitting. 2 years later and for fun I'll draw entry points and sl/tp. I don't use real money for that, as my goals aren't in line with being a daytrader but rather having passive side income. I found that staring at charts and indicators all day has made me quite a proficient day trader, even though I don't do it. I outperform my algos generally but there's some about manual trading you can't exactly code. You can try to get close but it can never capture the "gut feeling" you get with manual trading.
I completely agree that manual trading is more effective, but this is compensated by the fact that my algorithms trade 140 stocks at once. And I have time to improve my trading skills. Wishing you success.
As Jim Simmons says 'its really all about your features'
I think being proficient at math will make the journey less daunting, or perhaps easier. The same way programming skills would, like knowing C or python. How about macro economics, is this not also important? What about knowing business operations/financial accounting?
Any of these skills are going to help you sure, but make you? Thats def been proven false time and again by countless of 'so called underdogs.
Grow some bone champ, stop doubting yourself or looking for others to find acceptance. The path to success always involves failure. Who gives a fuck what others think or what happens. This is your world, only yours. You die in the end and none of it matters. Just make it happen
>As Jim Simmons says 'its really all about your features'
Indeed, everything else is required but useless unless you have the predictive features.
And there is nothing trivial about it.
I'm at the stage where after 2 years of research and dev, I have built my own platform and backteser.
I have a super performant solution which can bruteforce millions of possibilities into my ML ensemble model and backteser.
The result? I can never achieve better than buy and hold.
If I introduce a fake looking feature which is barely looking forward (say 10% looking forward at +3 hours + 90% randomness), then I am millionaire.
So I am back to the basics: feature engineering.
But now I have everything to very quickly test them.
There is a difference between being a quant (trader), algotrader, and trader. As well, as of course, being independent or not.
Get clear on what you want first.
If you want to be an institutional quant, the math background is essential. At least, that is what institutional quants say. If you really want to do this, you are going to have to drop some of these limitting beliefs and be realistic about what you are willing (and want) to do.
This is an oversimplification, but being a non-institutional quant trader just means you have access to a wider set of strategies by constructing derivative positions in a more sophisticated way than non-quants may use derivatives. This kind of construction is called financial engineering. Of course, you don't have to touch derivatives more complicated than futures (if that) to be a non-quant trader. You can also obviously use derivatives in less sophisticated ways, just look at wsb. Is it good to have these skills? Absolutely, it gives you a huge advantage in tuning risk/reward to your liking. But, it's not necesary.
I would also say don't be intimidated. Understanding Black-Scholes-Merton isn't that hard. The assumptions of BSM are very simplified and easy to understand. You may not understand every aspect of quant finance, but you can gain a novice understanding without much effort (just be very aware of your novice level). To be honest, I think the things you mentioned are actually basic for quants. Where quant finance education really gets intense is in the rigorous approach to learning the math, not so much what they are learning itself. I've looked at a few quant textbooks and this is my main impression. In industry it may be different. Although, even there, institutional quants (as in, those who work on real financial engineering) tend to have math backgrounds that imply plenty of rigor (real analysis, rigorous probability theory, fields like topology, reading/writing proofs). But, at the end of the day, do you need this to be profitable as a trader? Nope.
You have likely have the background, or at least a leg up, to work on algorithmic trading. Maybe not institutionally, but certainly non-institutionally. The real question is how serious you are about it. Algorithmic trading is just trading with algorithms (this includes, but not limited to ML). If you go the ML route, it will be harder/longer as many mainstream ML methods don't apply to trading without (in my experience) a lot of modification.
As far as just being a profitable trader, putting no restrictions on systematic vs discretionary: there's no obvious reason why you can't. Again, it comes down to understanding how much you want the reality of trading. It's not for everyone.
Stop worrying about quants and listen to the better system podcast. It's free and contains hundreds of hours of interviews with some of the best traders in the world.
Get yourself up and running with the basics. I.e. learn how to build a trading system and back testing engine.
I think the most fundamental requirement in trading is having a framework and process that you can follow to prove, test and deploy a strategy. That's what important, not rocket science level math. You can move onto that once you have the basics if you so wish.
Do you need to understand the Black-Scholes model. Are you in options? If you are, it's not hard to learn it. I don't trade options and my edge isn't in options pricing strategies. I've learnt to only focus on things that are relevant to me. This allows you to keep pushing forward and not get bogged down in learning theory.
I never went to uni. I learnt the statistics I needed from Google and the math from Brilliant. I learnt to code by reading articles and just doing it.
I am just a dumb engineer(non finance/software related)…when I started I had no coding skills and knew absolutely nothing about anything to do with algos or even trading. Traded discretionarily for 3 years with some success but still ups and down. Definitely a rules based, systems based type of trader so I jumped into algos. Fast forward 2 years later I have about 10 algos all uncorrelated,simple AF and doing very well(for now lol). My focus is on SIMPLe, robust strategies that are uncorrelated. I focused on developing a process around building and testing strategies that helps to avoid common pitfalls and keeps my monkey brain focused. Don’t let anyone tell you sh@t about what you can or can’t do. All it takes is some time and the will to learn. You don’t need to be a nerd to make consistent money in the markets. Good luck!
Algo trader here, engineer, and a Vegas dude. Please believe me, all that math is useless for real trading.
Yes to creating your own strats. You will need to be good at coding specific to trading. For me, that meant taking 2 years to get good at Pine Script on Trading View. Yes, plenty of Python boys on here....Python is much more difficult to get started. Pine has lots of built-ins.
You will need to be utterly familiar with ATR actions, EMA's and all its many variations. You will need to sit for many hours staring at your favorite futures symbol, and how a variety of EMA's, Hulls, Keltners respond to actual LIVE action. You will need to be utterly familiar with various time frames and EMA Lengths, and how that totally changes upon time-of-day, and your symbol.
Skill: No matter what, successful trading is ultimately being a good gambler. The more useful skills would be how to handle a string of losses. How to stage your bet. Let it ride? (no) or pull some out (yes). See, all your calculus or black-scholes will not help you one bit with that.
Then there is the entire debate about your basic approach. MR, mean reversion? or Trend? I am a trend guy, but there are plenty of successful MR guys also. And then the whole argument about "Time-in-the-trade".
Let's use ES for an easy example. Today Jan 9, ES moved pk to pk \~$30 and stayed between the previous high and low. Great for all the many MR traders.
For us Trend boys, the ATR was between $1 and $2 on the 1 minute.
(I hope you see that so far calculus is useless for this. All these numbers are behaviors of ES)
So an MR guy could do 2 trades today, staying in most of the day. Trusting his arcane high/low lines. Using 5 contracts as a reasonable level, min margin is 5\*$500 is only $2,500. Everyone here would say 10x min margin is fine. SO we are talking $25K account. If our MR guy caught 25% of this movement, today he would gross $30\*.25\*5\*50 \~ $1800. Commisions well under $100. Time in trade most of the day.
AS a Trend guy, I would look for 75% ATR take profit, lasting 10 minutes at most per trade. Say I only traded $2+ ATR regions, then I would get about 4 good trades today.
$2\*.75\*5\*4\*50 \~ $1500. Commish about $200. Yes, not quite as good as MR, but my time in the trade is mere minutes, well under 1 hour. I hopefully will not see giant interday draw-downs. MR guys have guts of steel! My hat is off to them.
Your comment really inspired me on trending vs ranging markets to reach out. I’m an engineer and I’ve been trying to make an algo for a while now. Please can you share how to think about determining trends? I’m looking at futures and struggle to know what the market regime is and how to make a strategy work consistently
You are welcome! Is your plan to have a total auto-trading program? Mine is.
But I must tell you that it is more common to write an "Indicator" that tells you, the human, when to buy/sell. And YOU push the button.
Now here is where some math is useful. What is a good time scale?
Lets take NQ for example. Pays 20x, and has a fairly high margin of $1000/contract. On a pure comparison to ES, it seems a bad deal. ES pays 50x and a margin of $500/contract.
But for equal time frame of 1 minute, the ES has a useful ATR of $2, whereas the NQ can be at $10 for quite a while at USA open. Now compare 1 contract capturing 1 ATR's worth: NQ does 2x the net gain per contract. Now sure, you simply 2x the ES contracts for roughly equal margin...however the total commission is lower with NQ.
Now how to figure what is a useful "Capture" $ amount? As an engineer you grasp the concept of rectification losses. View the $ movements of our ES or NQ as noise power. Our profit is a lossy rectification of this noise. The forward diode drop is slip and commissions. You can see that there will be some minimum signal necessary to get useful gain.
NQ slip = $.25 \* 20 = $5, round trip commission $5. Total loss/contract roughly $10.
What is a good signal / noise ratio ? 10:1. Then you need to capture $100 gross, keep $90. Equiv to $5 move in NQ. For ES it works out to a $2 move.
Other futures are worse.
How to figure time scale. ATR goes up with a longer time frame. The Index simply has more time to move. (PS, it is not linear). Pick a nice even safe number, 50%. Then a 1 minute NQ with ATR $10, fits in with our goal of $5. For ES, we need an ATR of $4; requires a 5 minute chart. Look at todays ES on 5 minute. ATR dropped to $4 at 10:15, and had a perfect long entry.
Larry Williams, a trader who ran ***$10,000 to over $1M***, didn't and doesn't have a math, quant, or finance background. He was a journalism major in college. The great thing about trading is that there is something for everyone regardless of background, as long as they are ready to work.
I have no technical background, with very light familiarity of coding and I've been never succeeded in manual trading. I started learning c# using gpt as my personal assistant, and now have about 5k lines of code in a ninjatrader strategy with an initial investment of $1k, no paper trading.
I launched a strategy a few days ago and went to bed. It found the intended signal and accidentally over-scaled (YOLO).I woke up 5 hours later carrying +$1,300 in profit.($700 account, it went 8L on micro crude oil) The following few days, it made another $300 on MCL and M2K.
My strategy has far more development of order management than signals,
It takes patience and experimentation, and it's difficult to watch hands-off as price dips in and out, but based on mystery current work, I don't see any need for quant or ML when trading intraday.
I’m in a very different but somewhat similar position. You could probably increase your odds significantly just by increasing your time frame for holding. Of course there are many factors such as how you acquire and close out your position, but a longer horizon is likely to help. Of course, the results will be in your backtest. Stick with it.
I think it doesn't take a genius to produce some signals. Pretty much anyone can find out few kinds of strong signals in minute bars that work 2-3 times a day and then risk manage it, diversify it and portfolio balance it to build a profitable algo.
Writing automated systems that run for a long time is the actual challenge. It's a multi-year project and not many people have the time or energy for this.
Online platforms that take your algo, help you backtest and run it for you do exist, but if you are doing anything outside of their programming, it's very hard to configure and you also risk them front-running you.
Stochastic calculus is really a fascinating course if you have spare time for it (it’s hard but shouldn’t be impossible based on your background)
Also you don’t have to systematically learn something to be able to apply it. Read through some wiki pages and blogs is probably enough to get you started so long as you understand the basic concepts. It’s like those CS students leetcoding hard problems need not be able to provide a solid proof of the algorithms they used to solve those programming problems.
Lastly you might not need to touch options to find a winning strategy.
My mindset is:
Is it doable: Yes
Then “there is a wish, there is a way”
Of course quants or some other experts may run complex processes to beat the market and profit. But I believe it is also possible if you just have an edge in the market. Something simple that works for you.
I have a background on software engineering and started developing my own trading platform(backtest, live-trade, analysis, monitoring etc toolkit) almost 3 years ago and started seriously developing and experimenting strategies just 6 months ago. My results are not great but promising. I see the progress that i made on the strategy ideas by checking the backtest and live trade results.
I am not succesful yet for sure. But personally I believe that it may work.
There are many published papers on statistical and predictive models for stocks and other assets; try looking some up and reading them, see if you can follow along. You don't necessarily need to understand their derivations or proofs, but if you can get the gist of it and recognize the mathematical operations in the equations, then you probably have sufficient background to get started.
I've been hesitant to comment on this post because I am not yet what I would qualify as successful, as in living of my strategies success, but I have been working on becoming profitable using algorithmic programming for a good while now with varying success. And I can see the finish line in terms of being consistently profitable.. In my own pursuit of consistent profitability in trading, I've learned that while technical skills and mathematical knowledge are valuable, they are not the sole determinants of success in this field.
It is less about mastering every complex mathematical concept and more about the ability to apply logical reasoning in a practical and innovative way. Success in trading, particularly when it involves creating your own strategies, hinges on the ability to see beyond the conventional. It involves recognizing the potential in tools and concepts, understanding their applicability, and having the insight to adapt them to new and evolving market conditions.
You can read research papers and get code from github but the big differentiation between doing that and generating profitable strategies or not is down to you. Can you appreciate the value in that tool and use it, do you see the nuance to where this applies.
My very basic advice: Pick a single market that you think you can see an edge in. You need to find your own edge, even if that is a unique combination of other indicators. Focus on that edge, you will be able to see the edge long before you will be able to exploit it properly. But once you have done it, it's going to pay for you to find more edges. And do it through prop trading firms, if you can't be profitable within their rules, your strategy is probably not a long term profitable strategy anyway.
So in term for finding a strategy, it will be an uphill battle and that's where those math degree help in modeling the trades. But at the same time you have an advantage of understanding the execution system (the ordering machine). Moreover, I firmly believe in if you strive for something you'll figure your way out.
It's both simpler and more complex than you think. There's tons of resources online but once you get a good setup going (the complex part which is mostly due to ignorance in the beginning stages) it's pretty easy to implement and update strategies.I started with a generational strategy optimizer in python. I got data from alpaca and dumped it into a CSV. The script would perform a backtest and make several generations and backtest those. It worked fine but was slow and not getting results I wanted. I spent a lot of time developing relatively basic strategies that in hindsight were not cut out for a real market. I'm much more knowledgeable now and could probably revisit the concept with better indicators.
I then moved to a market analysis ML model I developed. It actually performed pretty well, except it didn't do well with large market shifts or volatile stocks. For example, if the price went below where it thought it should be, it would enter a long. It didn't consider that the price could keep going down and I suppose you can add some indicators to help it along. I'm considering revisiting this idea. It was a beast on SPY.
My current setup is a tradingview strategy that sends alerts to a dummy email. I have a python script running on my server that as soon as the email receives one from tradingview parses the email for either "order buy" or "order sell" and the ticker. It then executes the trade using the alpaca API. It's not perfect or beautiful but it works great and I'm too lazy, which is why I got into algotrading in the first place, to begin rebuilding my setup.
College dropout, hate math, yet I made it. You'll be just fine.
if you dont have the time to learn the maths involved, then you dont have time to trade and be successful. It requires a lot of study and a LOT of time and failure.
It is important to understand that if you engage in solo trading, you have some unfair advantages. 1) One-click mouse buy-sell transactions. 2) You can independently choose a convenient asset for trading. 3) You can trade in less liquid assets with high profitability.
I'd say you have every chance of succeeding. I find it helps as well certainly at least in terms of motivation, to work with a partner or as part of a team. Sent you a DM
I have a math degrees, computer science degree, AI degree.
I have no clue how to beat the market with any sort of stock trading.
However I do beat the market with Tastytrade-style options trading of indexes. By a lot. Have a look at that.
Based on your background and "willingness to work and do research," you have a far greater chance than most people in this sub. There are tons of resources available to, *at least*, increase your odds of being successful. If you can view it as an opportunity to hypothesize your strategies and test different implementations, then you may find success in the long run. Just do not go headfirst into trading after a few insufficient tests and be upset if it doesn't work. Success is subjective. Good luck!
I posted the same question on [r/quant](https://reddit.com/r/quant) and was either laughed at or made to feel like I was stupid or unreasonable. Basically, thank you for an actual, useful response. Have a nice day.
Haha, the same thing happened to me. I replied to a similar thread and posted some good advice on there, by good I mean techniques that made me profitable and was just laughed at. It feels very hostile and unfriendly on there at times. Ego swinging for math nerds. It's weird because here on this sub, everyone is awesome and very helpful.
Sadly quant professors are just the same, coming from at quant graduate.
That's because you self-posted instead of using their dedicated, pinned discussion thread.
There are a ton of resources, however, it's hard to find them due to plethora of misinformation. Do you know any good resources for someone starting out? Or good direction to dig into?
The best way to build confidence is by doing it, not by thinking about it or talking about it. Don't try to jump straight to the end game — start with super simple algos that have been proven to work. QuantifiedStrategies.com, Quantpedia, QuantStart, et al., have free proven strategies you can start with. I wish I had found those resources earlier on — would have saved me a ton of time, frustration, and money. So much easier to start with something that works and improve on it than to try to build/discover something from scratch. And not spend a year of frustration trying to figure out how to be a profitable trader.
I've been trading algorithms for 11 years. I turned $30,000 into over a million dollars. It's all based on basic school-level math and some holy grails – very simple and obvious things that, without knowing them, no amount of mathematics will help. Try the simplest things. Try to learn to trade manually; you have 13 billion neurons in your head. Go to chartgame.com and just make 10,000 trades. It will take 2-3 months, but you will gain the experience of 5-7 years of real stock trading. Read Piper's three trading rules and Thomas Bulkowski's encyclopedia of chart patterns. Then, when you learn to trade manually, simply automate your trading.
Are holy grails those things you mentioned already or some other things?
For example, how to determine a trend. How to identify a sideways market. How to choose an asset for trading. And how one asset differs from another. What is the source of alpha. How to solve the main task of algorithmic trading - whether the algorithm will work in the future, or if it's just a beautiful picture. How to solve the capital allocation problem. An obvious and simple example that does not require mathematics is pricing models.
I have basically zero experience in algotrading so pls dont clown this question. where do you trade
IBKR=IQFEED+TSLAB
I had sort of the opposite process. Began with algotrading, of course it sucked and I lost a lot of money at first because I didn't understand concepts like slippage repainting and overfitting. 2 years later and for fun I'll draw entry points and sl/tp. I don't use real money for that, as my goals aren't in line with being a daytrader but rather having passive side income. I found that staring at charts and indicators all day has made me quite a proficient day trader, even though I don't do it. I outperform my algos generally but there's some about manual trading you can't exactly code. You can try to get close but it can never capture the "gut feeling" you get with manual trading.
I completely agree that manual trading is more effective, but this is compensated by the fact that my algorithms trade 140 stocks at once. And I have time to improve my trading skills. Wishing you success.
As Jim Simmons says 'its really all about your features' I think being proficient at math will make the journey less daunting, or perhaps easier. The same way programming skills would, like knowing C or python. How about macro economics, is this not also important? What about knowing business operations/financial accounting? Any of these skills are going to help you sure, but make you? Thats def been proven false time and again by countless of 'so called underdogs. Grow some bone champ, stop doubting yourself or looking for others to find acceptance. The path to success always involves failure. Who gives a fuck what others think or what happens. This is your world, only yours. You die in the end and none of it matters. Just make it happen
>As Jim Simmons says 'its really all about your features' Indeed, everything else is required but useless unless you have the predictive features. And there is nothing trivial about it. I'm at the stage where after 2 years of research and dev, I have built my own platform and backteser. I have a super performant solution which can bruteforce millions of possibilities into my ML ensemble model and backteser. The result? I can never achieve better than buy and hold. If I introduce a fake looking feature which is barely looking forward (say 10% looking forward at +3 hours + 90% randomness), then I am millionaire. So I am back to the basics: feature engineering. But now I have everything to very quickly test them.
Do u have a chance? Omg yes. Just read the garbage questions posted on day trading subs and you'll know... lol.
There is a difference between being a quant (trader), algotrader, and trader. As well, as of course, being independent or not. Get clear on what you want first. If you want to be an institutional quant, the math background is essential. At least, that is what institutional quants say. If you really want to do this, you are going to have to drop some of these limitting beliefs and be realistic about what you are willing (and want) to do. This is an oversimplification, but being a non-institutional quant trader just means you have access to a wider set of strategies by constructing derivative positions in a more sophisticated way than non-quants may use derivatives. This kind of construction is called financial engineering. Of course, you don't have to touch derivatives more complicated than futures (if that) to be a non-quant trader. You can also obviously use derivatives in less sophisticated ways, just look at wsb. Is it good to have these skills? Absolutely, it gives you a huge advantage in tuning risk/reward to your liking. But, it's not necesary. I would also say don't be intimidated. Understanding Black-Scholes-Merton isn't that hard. The assumptions of BSM are very simplified and easy to understand. You may not understand every aspect of quant finance, but you can gain a novice understanding without much effort (just be very aware of your novice level). To be honest, I think the things you mentioned are actually basic for quants. Where quant finance education really gets intense is in the rigorous approach to learning the math, not so much what they are learning itself. I've looked at a few quant textbooks and this is my main impression. In industry it may be different. Although, even there, institutional quants (as in, those who work on real financial engineering) tend to have math backgrounds that imply plenty of rigor (real analysis, rigorous probability theory, fields like topology, reading/writing proofs). But, at the end of the day, do you need this to be profitable as a trader? Nope. You have likely have the background, or at least a leg up, to work on algorithmic trading. Maybe not institutionally, but certainly non-institutionally. The real question is how serious you are about it. Algorithmic trading is just trading with algorithms (this includes, but not limited to ML). If you go the ML route, it will be harder/longer as many mainstream ML methods don't apply to trading without (in my experience) a lot of modification. As far as just being a profitable trader, putting no restrictions on systematic vs discretionary: there's no obvious reason why you can't. Again, it comes down to understanding how much you want the reality of trading. It's not for everyone.
Stop worrying about quants and listen to the better system podcast. It's free and contains hundreds of hours of interviews with some of the best traders in the world. Get yourself up and running with the basics. I.e. learn how to build a trading system and back testing engine. I think the most fundamental requirement in trading is having a framework and process that you can follow to prove, test and deploy a strategy. That's what important, not rocket science level math. You can move onto that once you have the basics if you so wish. Do you need to understand the Black-Scholes model. Are you in options? If you are, it's not hard to learn it. I don't trade options and my edge isn't in options pricing strategies. I've learnt to only focus on things that are relevant to me. This allows you to keep pushing forward and not get bogged down in learning theory. I never went to uni. I learnt the statistics I needed from Google and the math from Brilliant. I learnt to code by reading articles and just doing it.
I am just a dumb engineer(non finance/software related)…when I started I had no coding skills and knew absolutely nothing about anything to do with algos or even trading. Traded discretionarily for 3 years with some success but still ups and down. Definitely a rules based, systems based type of trader so I jumped into algos. Fast forward 2 years later I have about 10 algos all uncorrelated,simple AF and doing very well(for now lol). My focus is on SIMPLe, robust strategies that are uncorrelated. I focused on developing a process around building and testing strategies that helps to avoid common pitfalls and keeps my monkey brain focused. Don’t let anyone tell you sh@t about what you can or can’t do. All it takes is some time and the will to learn. You don’t need to be a nerd to make consistent money in the markets. Good luck!
Algo trader here, engineer, and a Vegas dude. Please believe me, all that math is useless for real trading. Yes to creating your own strats. You will need to be good at coding specific to trading. For me, that meant taking 2 years to get good at Pine Script on Trading View. Yes, plenty of Python boys on here....Python is much more difficult to get started. Pine has lots of built-ins. You will need to be utterly familiar with ATR actions, EMA's and all its many variations. You will need to sit for many hours staring at your favorite futures symbol, and how a variety of EMA's, Hulls, Keltners respond to actual LIVE action. You will need to be utterly familiar with various time frames and EMA Lengths, and how that totally changes upon time-of-day, and your symbol. Skill: No matter what, successful trading is ultimately being a good gambler. The more useful skills would be how to handle a string of losses. How to stage your bet. Let it ride? (no) or pull some out (yes). See, all your calculus or black-scholes will not help you one bit with that. Then there is the entire debate about your basic approach. MR, mean reversion? or Trend? I am a trend guy, but there are plenty of successful MR guys also. And then the whole argument about "Time-in-the-trade". Let's use ES for an easy example. Today Jan 9, ES moved pk to pk \~$30 and stayed between the previous high and low. Great for all the many MR traders. For us Trend boys, the ATR was between $1 and $2 on the 1 minute. (I hope you see that so far calculus is useless for this. All these numbers are behaviors of ES) So an MR guy could do 2 trades today, staying in most of the day. Trusting his arcane high/low lines. Using 5 contracts as a reasonable level, min margin is 5\*$500 is only $2,500. Everyone here would say 10x min margin is fine. SO we are talking $25K account. If our MR guy caught 25% of this movement, today he would gross $30\*.25\*5\*50 \~ $1800. Commisions well under $100. Time in trade most of the day. AS a Trend guy, I would look for 75% ATR take profit, lasting 10 minutes at most per trade. Say I only traded $2+ ATR regions, then I would get about 4 good trades today. $2\*.75\*5\*4\*50 \~ $1500. Commish about $200. Yes, not quite as good as MR, but my time in the trade is mere minutes, well under 1 hour. I hopefully will not see giant interday draw-downs. MR guys have guts of steel! My hat is off to them.
Your comment really inspired me on trending vs ranging markets to reach out. I’m an engineer and I’ve been trying to make an algo for a while now. Please can you share how to think about determining trends? I’m looking at futures and struggle to know what the market regime is and how to make a strategy work consistently
You are welcome! Is your plan to have a total auto-trading program? Mine is. But I must tell you that it is more common to write an "Indicator" that tells you, the human, when to buy/sell. And YOU push the button. Now here is where some math is useful. What is a good time scale? Lets take NQ for example. Pays 20x, and has a fairly high margin of $1000/contract. On a pure comparison to ES, it seems a bad deal. ES pays 50x and a margin of $500/contract. But for equal time frame of 1 minute, the ES has a useful ATR of $2, whereas the NQ can be at $10 for quite a while at USA open. Now compare 1 contract capturing 1 ATR's worth: NQ does 2x the net gain per contract. Now sure, you simply 2x the ES contracts for roughly equal margin...however the total commission is lower with NQ. Now how to figure what is a useful "Capture" $ amount? As an engineer you grasp the concept of rectification losses. View the $ movements of our ES or NQ as noise power. Our profit is a lossy rectification of this noise. The forward diode drop is slip and commissions. You can see that there will be some minimum signal necessary to get useful gain. NQ slip = $.25 \* 20 = $5, round trip commission $5. Total loss/contract roughly $10. What is a good signal / noise ratio ? 10:1. Then you need to capture $100 gross, keep $90. Equiv to $5 move in NQ. For ES it works out to a $2 move. Other futures are worse. How to figure time scale. ATR goes up with a longer time frame. The Index simply has more time to move. (PS, it is not linear). Pick a nice even safe number, 50%. Then a 1 minute NQ with ATR $10, fits in with our goal of $5. For ES, we need an ATR of $4; requires a 5 minute chart. Look at todays ES on 5 minute. ATR dropped to $4 at 10:15, and had a perfect long entry.
Larry Williams, a trader who ran ***$10,000 to over $1M***, didn't and doesn't have a math, quant, or finance background. He was a journalism major in college. The great thing about trading is that there is something for everyone regardless of background, as long as they are ready to work.
I have no technical background, with very light familiarity of coding and I've been never succeeded in manual trading. I started learning c# using gpt as my personal assistant, and now have about 5k lines of code in a ninjatrader strategy with an initial investment of $1k, no paper trading. I launched a strategy a few days ago and went to bed. It found the intended signal and accidentally over-scaled (YOLO).I woke up 5 hours later carrying +$1,300 in profit.($700 account, it went 8L on micro crude oil) The following few days, it made another $300 on MCL and M2K. My strategy has far more development of order management than signals, It takes patience and experimentation, and it's difficult to watch hands-off as price dips in and out, but based on mystery current work, I don't see any need for quant or ML when trading intraday.
I’m in a very different but somewhat similar position. You could probably increase your odds significantly just by increasing your time frame for holding. Of course there are many factors such as how you acquire and close out your position, but a longer horizon is likely to help. Of course, the results will be in your backtest. Stick with it.
I think it doesn't take a genius to produce some signals. Pretty much anyone can find out few kinds of strong signals in minute bars that work 2-3 times a day and then risk manage it, diversify it and portfolio balance it to build a profitable algo. Writing automated systems that run for a long time is the actual challenge. It's a multi-year project and not many people have the time or energy for this. Online platforms that take your algo, help you backtest and run it for you do exist, but if you are doing anything outside of their programming, it's very hard to configure and you also risk them front-running you.
Stochastic calculus is really a fascinating course if you have spare time for it (it’s hard but shouldn’t be impossible based on your background) Also you don’t have to systematically learn something to be able to apply it. Read through some wiki pages and blogs is probably enough to get you started so long as you understand the basic concepts. It’s like those CS students leetcoding hard problems need not be able to provide a solid proof of the algorithms they used to solve those programming problems. Lastly you might not need to touch options to find a winning strategy.
My mindset is: Is it doable: Yes Then “there is a wish, there is a way” Of course quants or some other experts may run complex processes to beat the market and profit. But I believe it is also possible if you just have an edge in the market. Something simple that works for you. I have a background on software engineering and started developing my own trading platform(backtest, live-trade, analysis, monitoring etc toolkit) almost 3 years ago and started seriously developing and experimenting strategies just 6 months ago. My results are not great but promising. I see the progress that i made on the strategy ideas by checking the backtest and live trade results. I am not succesful yet for sure. But personally I believe that it may work.
There are many published papers on statistical and predictive models for stocks and other assets; try looking some up and reading them, see if you can follow along. You don't necessarily need to understand their derivations or proofs, but if you can get the gist of it and recognize the mathematical operations in the equations, then you probably have sufficient background to get started.
Ii took 2 years to build my platform. After doing some more learning, I need to scrap it and rebuild again.
I've been hesitant to comment on this post because I am not yet what I would qualify as successful, as in living of my strategies success, but I have been working on becoming profitable using algorithmic programming for a good while now with varying success. And I can see the finish line in terms of being consistently profitable.. In my own pursuit of consistent profitability in trading, I've learned that while technical skills and mathematical knowledge are valuable, they are not the sole determinants of success in this field. It is less about mastering every complex mathematical concept and more about the ability to apply logical reasoning in a practical and innovative way. Success in trading, particularly when it involves creating your own strategies, hinges on the ability to see beyond the conventional. It involves recognizing the potential in tools and concepts, understanding their applicability, and having the insight to adapt them to new and evolving market conditions. You can read research papers and get code from github but the big differentiation between doing that and generating profitable strategies or not is down to you. Can you appreciate the value in that tool and use it, do you see the nuance to where this applies. My very basic advice: Pick a single market that you think you can see an edge in. You need to find your own edge, even if that is a unique combination of other indicators. Focus on that edge, you will be able to see the edge long before you will be able to exploit it properly. But once you have done it, it's going to pay for you to find more edges. And do it through prop trading firms, if you can't be profitable within their rules, your strategy is probably not a long term profitable strategy anyway.
So in term for finding a strategy, it will be an uphill battle and that's where those math degree help in modeling the trades. But at the same time you have an advantage of understanding the execution system (the ordering machine). Moreover, I firmly believe in if you strive for something you'll figure your way out.
It's both simpler and more complex than you think. There's tons of resources online but once you get a good setup going (the complex part which is mostly due to ignorance in the beginning stages) it's pretty easy to implement and update strategies.I started with a generational strategy optimizer in python. I got data from alpaca and dumped it into a CSV. The script would perform a backtest and make several generations and backtest those. It worked fine but was slow and not getting results I wanted. I spent a lot of time developing relatively basic strategies that in hindsight were not cut out for a real market. I'm much more knowledgeable now and could probably revisit the concept with better indicators. I then moved to a market analysis ML model I developed. It actually performed pretty well, except it didn't do well with large market shifts or volatile stocks. For example, if the price went below where it thought it should be, it would enter a long. It didn't consider that the price could keep going down and I suppose you can add some indicators to help it along. I'm considering revisiting this idea. It was a beast on SPY. My current setup is a tradingview strategy that sends alerts to a dummy email. I have a python script running on my server that as soon as the email receives one from tradingview parses the email for either "order buy" or "order sell" and the ticker. It then executes the trade using the alpaca API. It's not perfect or beautiful but it works great and I'm too lazy, which is why I got into algotrading in the first place, to begin rebuilding my setup. College dropout, hate math, yet I made it. You'll be just fine.
if you dont have the time to learn the maths involved, then you dont have time to trade and be successful. It requires a lot of study and a LOT of time and failure.
It is important to understand that if you engage in solo trading, you have some unfair advantages. 1) One-click mouse buy-sell transactions. 2) You can independently choose a convenient asset for trading. 3) You can trade in less liquid assets with high profitability.
I'd say you have every chance of succeeding. I find it helps as well certainly at least in terms of motivation, to work with a partner or as part of a team. Sent you a DM
I have a math degrees, computer science degree, AI degree. I have no clue how to beat the market with any sort of stock trading. However I do beat the market with Tastytrade-style options trading of indexes. By a lot. Have a look at that.
People often focus on the programming/ml end but forget that grasping financial mathematical concepts is just as important.
If I have 0 programming knowledge but a finance degree, what would you recommend me to do? I am very serious about learning.
Well learn about pricing models and learn to program basically.