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I am working on a program to backtest it. Honestly, I still have much to learn. I do things visually. So I take the little fib retracement chart tool in trading view and make the anchor at the beginning of a price movement and align the lines to the closing prices of significant support/resistance (defined mathematically as any 5 bars such that the the middle bar has the lowest low or highest high in like pyramid form.) If I see at least 3 lines of the fib retracement align, I consider the market to be demonstrating that pattern and I make a bet the market will reverse when it hits the highest fib line. This is much easier to see btw and I have a website where I’m going to write this out if you’re interested: https://seanneilan.com/ I have corresponding Python code that automates this strategy too that I intend to post once it’s ready.


No hate. But just remember that when you think that something is a good BUY, the other side (the seller) think that it is a good SELL. Hence, before trading in the stock market (or in any other market which is a zero sum game, e.g. used cars, NFT), you must be sure that you have more information than the seller.


>Hence, before trading in the stock market (or in any other market which is a zero sum game, e.g. used cars, NFT)

None of these are zero sum games. Especially stock market. Stock market is not a zero sum game at all. https://money.stackexchange.com/questions/72945/is-the-stock...


It is if you are trading.

Ofcourse, if you are not trading, or buy a company stock and hope to get dividends than there is no transaction and hence it is not zero sum. But if you are trading it is zero sum.


Of course. Part of the fun is also considering why a trade will go the wrong way too. There are infinite scenarios and part of trading is sketching why scenario X's probabililty is more likely than scenario Y's probability. And this can all be a wash when the completely unexpected happens too.


I'm sorry to say you're seeing the future in tea leaves, but I guess you're learning some stuff along the way.


I lost about $3k doing algo crypto trading (all of that to fees - without fees I made money! aha) but learned a ton about different programming concepts and had a lot of fun.


That's awesome! :) That sounds like an amazing experience. I bet you learned a lot! And 3k is enough to make it memorable but not enough to go into massive debt or anything like that. And sure it's a loss but nobody goes into this trying to lose money. (AFAIK)


I think that trading is ultimately a creative endeavor and no matter how one trades whether it's based on phases of the moon or insider information, one needs to know when they are entering and exiting the market. Trading is an incredibly fun and creative endeavor and as long as one takes the time to precisely define what they are doing, it is great <3


Strange, I would have thought the stock-market would be the opposite to a creative endeavor. Can you expand on how that works for you?


There's so much to study and learn.

Trading algorithms are often implemented in Python/Pandas so learning hackerrank problems about stacks/queues can make one better at implementing trading algorithms. Some hackerrank problems involve hashes which are verified empirically which calculus. Studying calculus can lead to better understanding of the black-scholes theorem and brownian motion.

There's even an aesthetic nature to really good trades which can lead down an interesting path on gestalt theory and composition. Drawing charts is an art form too. Check out https://www.tradingview.com/u/tntsunrise/ for examples of minimalism in the stock market.

A previous commentor on this topic wrote that I'm studying tea leaves but what if for fun I wrote an image processing algorithm that processed the position of tea leaves in a cup and traded small amounts based on that?

Even something like moving averages has applications in programming language theory. It's easier to implement a moving average in a stateful rather than functional way. It's fun to figure out faster ways of cranking out new algorithms to trade markets which leads to better productivity. Markets move really fast. Old algorithms quickly become outdated.

As long as one does not make huge risks (that aren't well thought out), one can trade based on whatever their imagination leads them to. Anything can be tried and systematically backtested. Most traders won't think outside the box but it's so much more fun when you do.

There's so much synergy between math, computer science, betting strategies, art, drawing, data science and visual theory. Everything one studies in trading can lead to 10 insights in other areas. It's just a genuinely fun topic that can lead to a lifetime of happiness.




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