How long did you take to make money

Studying entries with MAE and MFE values and time segments can be fruitful visually. I think the point the contributors are making you must learn how to trade FIRST. No one can post a paragraph to teach you that. Put in screen time on charts...test your ideas...rinse and repeat..

You have a one up on many traders already as you can code.

Good trading to you.

ES

Thank you for the responses.

There appears to be consensus to get the basics of understanding the market dynamics first, and quite a few people rely on charts.

To clarify I don't code strategies straight away. I get hold of data and visualise the data using various tools; often overlaying instruments with their derivatives. Then I identify a strategy that may appear to work with some regularity and finally backtest with hard data to measure the performance. But yes, in the early stages I did attempt to build a general model using machine learning and let's just say I won't be doing it again.

One of the things I picked up from the market wizards book is that you have to find your own trading style based on your strengths and emotional comfort. I don't mind coding hence I picked the algo route and I'm exploring trades within a day since I'm not comfortable with all the moving parts affecting prices for longer time frames.

I must admit I'm a bit surprised with the number of people that use charts as the primary source for developing the positions. Chart patterns always seemed subjective to me so haven't pursued it.

How do you get understanding of market dynamics manifested in the charts? Other than market announcements, isn't this a bit of guesswork?
 
Hi all,

Just joined the forum today after someone recommended it.

I've been working on algorithmic trading for the last 3 years. I have a full time job, so I do this just about every night and every weekend. The first 1.5 years was just on data sourcing and cleansing. Then generating signals and testing various strategies.

So far my result has been zilch. I haven't found not one strategy that is worth taking live. Now feeling defeated and dejected after the last idea turned out to be a dud as well.

Just wondering what other people's experiences are. How long did it take you to become profitable. Are there any pitfalls or secret sauce to become successful?

Thanks.
What is your coding background?
 
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This is basically my hurricane strategy (I live in Florida, that helps I guess).
 
First, don't take any advice from Padutrader, he is a notorious liar.

Second, trading can be very simple or it can be very complex, as a retail trader it is best to keep things as simple as possible, there is no way we can compete with the machines and resources large firms have. Since i have started trading i started to notice that some areas of the day where more important than others, i now trade a system in which i look at 2 price levels from throughout the day for each instrument i trade and i just wait until one of those levels is reached, only then depending on the price action around these levels i might take a trade. This is the easiest strategy i ever traded, i set some alerts around those price levels so i can do some other stuff while keeping an eye on the fundamentals every now and then, with Trump these days markets sentiment can change in seconds if he posts some stupid tweets. The easiest strategy i ever traded but also the most profitable one and maybe even more important, reasonably scalable.

I have also decided to set a fixed target and stop, this is a personal preference since i never was that good with letting trades run. So after i logged every trade i made in a journal i noticed that when i thought i should close a trade i was much better of to let it run to my original target instead of closing it early. The loses i avoided every now and then didn't compensate for the profit i was missing out on. So now i open a trade, calculate my stop price and based on that information i decide my target price with a fixed 1:1,5 risk-reward ratio. I am still working on some other exit strategies but for now i will keep using this one until i find one that has proven statistics of beating my current exit strategy.

There is also a stock swing trading strategy in development (positions from at least 1 day up to several months), based somewhat on the same "rules" once i complete the strategy and again i have statistics that prove the system is profitable i will stop day trading since this strategy only requires 1 or 2 hours of my time each day and is extremely scalable.

How long it will take for you is unpredictable, some guys are profitable after a few months or so and some will never be profitable. Be honest with yourself, that is the most important thing, don't hold on to false hopes and be realistic.
 
How do you get understanding of market dynamics manifested in the charts? Other than market announcements, isn't this a bit of guesswork?

Most math around economics is basically guess work. There's an assumption of normality of log returns that is mostly false in the tails. The tails of the return distribution tend to be significantly different than the tails of a normal distribution - however majority of "data driven" approaches are underpinned by this assumption. As a result most applications of hard math to predicting stocks have failed. This is also, funny enough, why put call parity falls apart in practice and often times there are significant opportunities for arbitrage in stocks and futures. The major greats in financial math, for example Ed Thrope, took advantage of a flaw in the pricing of contracts - and not the predicting of stock prices themselves.

The application of machine learning to finance is more or less useless in the retail space. I have book called Advances in Financial Machine Learning which is the seminal work on this. Not only does the author go into mathematically complex ideas that are only really implementable at hedge fund scale, he also makes it clear there's virtually no room for this work in the retail space. There just isnt enough good quality data for a retail to do any meaningful work. You need millions of ticks of cleaned and processed data to have any hope of getting something like a neural net to be useful. Even then, you need to decide how you bin your ticks, what works and what doesn't, etc. It's a daunting task that needs a team of quants and data monkeys. You are one guy.

For me, charts aren't useful for MACDs and such. There are a handful of indicators I consider useful - namely indicators that tell me supply and demand characteristics of the market. I trade based on these, news, and probabilities. Since I trade options I can more-or-less define my risk characteristic for each trade. If the odds are good and the price is right, I'm in. Period. I just use charts to confirm there's something of substance (a major pivot off of a point the market is telling me is a demand limit, for example). Recently I've been profitable just watching Trump's twitter, so it goes to show you that you really need to be creative.
 
Most math around economics is basically guess work. There's an assumption of normality of log returns that is mostly false in the tails. The tails of the return distribution tend to be significantly different than the tails of a normal distribution - however majority of "data driven" approaches are underpinned by this assumption. As a result most applications of hard math to predicting stocks have failed. This is also, funny enough, why put call parity falls apart in practice and often times there are significant opportunities for arbitrage in stocks and futures. The major greats in financial math, for example Ed Thrope, took advantage of a flaw in the pricing of contracts - and not the predicting of stock prices themselves.

The application of machine learning to finance is more or less useless in the retail space. I have book called Advances in Financial Machine Learning which is the seminal work on this. Not only does the author go into mathematically complex ideas that are only really implementable at hedge fund scale, he also makes it clear there's virtually no room for this work in the retail space. There just isnt enough good quality data for a retail to do any meaningful work. You need millions of ticks of cleaned and processed data to have any hope of getting something like a neural net to be useful. Even then, you need to decide how you bin your ticks, what works and what doesn't, etc. It's a daunting task that needs a team of quants and data monkeys. You are one guy.

For me, charts aren't useful for MACDs and such. There are a handful of indicators I consider useful - namely indicators that tell me supply and demand characteristics of the market. I trade based on these, news, and probabilities. Since I trade options I can more-or-less define my risk characteristic for each trade. If the odds are good and the price is right, I'm in. Period. I just use charts to confirm there's something of substance (a major pivot off of a point the market is telling me is a demand limit, for example). Recently I've been profitable just watching Trump's twitter, so it goes to show you that you really need to be creative.

I have the same book but haven't finished. Found out I have been using some of the techniques he is describing around cross validation. Machine learning in finance is a totally different beast. Given the author has changed employers I'm not overly convinced he's cracked it either.
 
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