Long story short: I created an option backtester (MesoSim) and started analyzing public domain trades.
I have a couple of listed in this blog: https://blog.deltaray.io/tags/strategies/
If you are interested I'd suggest taking a look at the Weekend Effect, it's relatively easy to understand.
Best luck to you getting back to trading!
"Automated" trading, even if there is an edge (and unless you are a crook, there is not) will sink you with transaction costs
You should know this.
Anyone who worked in quantitative trading knows you can consistently outperform the S&P500/VTI/SPY over 20+ year horizons.
Buy and hold passive US equity index funds gives a Sharpe ratio of ~0.7 with annual return of 8-10%. Meanwhile, high frequency trading does upward of Sharpe 10+ with 40-60% annual return, with 10+ year track records, of course.
Hell, even Citadel hedge fund, after their ridiculous 50% performance fee, returned 19% _after fees_ annually to outside passive investors over 20 years. And this is billions of AUM, so the ”quant don’t scale” argument goes out the window.
Why is nobody talking about this? Because the elite politicians and businessmen invest in these very quant funds, and thus suppress any news or regulation. Sucks for middle class professionals with <$5M net worth.
But before you unleash your automated proprietary model, you should be able to explain why you think you have any edge whatsoever over your far better funded, far more experienced counterparties.
And, no, getting great results from backtesting your model is not evidence of edge in the future against adversaries with access to better data than you have.
RenTech famously tried to understand exact mechanics of their successful models after they (models) proved to be successful. Sometimes they succeeded.
The average index fund fails to outperform the S&P.
How many passive index funds are there worldwide? Thousands? How many beat VTI or S&P500? Answer: QQQ and small cap.
> Of those how much can be attributed statistically to skill rather than luck?
If you are picking S&P as your champion, then I am allowed to pick a hedge fund as my champion.
And Citadel outperforms S&P over 20+ year horizon. Citadel 19% vs S&P 10%.
This is a straw man as most people understand investing in indexes as buying a an index that tracks the s&p.
>If you are picking S&P as your champion, then I am allowed to pick a hedge fund as my champion.
You are making a false equivalence. The s&p is a proxy for the us market and therefore is a benchmark. It captures the captures the bets placed by all market participants including citadel.
Citadel does something beyond buying and selling equities to generate that alpha. And it’s likely not just restricted to equities. Nonetheless they are an outlier. Which is the point I was making. Most people won’t do better than the us market in aggregate over a similar stretch of time.
1. SPY shares long/short on margin/leverage
1. SPY options
1. SPX options
1. /ES e-mini futures
1. a blend of all
Does one trump another in popularity?
a lot of technical analysis is done on psychological levels related to (in my opinion) SPY strike prices/SPX strike prices/SPX levels.
Yet, /ES is typically 20 points ahead of SPX. For example, there can be a battle zone of support/resistance at 4900 on SPX, but /ES blew past it a day ago. I wasn't sure if one had more power/prominence than the other.
There is no such thing as support/resistance in reality.
Where would you say 80% of the daily trade volume comes from on average?
The powers to be that I can think of:
institutional investors / fund managers slowly reallocating (selling stuff off, buying stuff) daily
high frequency trading algorithms trading shares back and forth to each other in an artificial way to generate synthetic volume/movement
market makers reacting to option chain volume to remain neutral
"hedge funds" / "quant funds" running their algorithm
what do those algorithms look for at the "minute by minute" scale if not things like support/resistance/patterns/volume?
That speaks volumes about your integrity. Good on you!
But it is not true.
Do you have a source?
What sort of shenanigans do you think profitable automated traders are engaged in?
Market rigging
Survivor bias (not shenanigans that one)
Market rigging: the market can be affected by your behaviour without you rigging anything
Survivorship bias: this can be argued for any competitive industry. Don't engage in it unless you're good at it.
> Insider trading: there's a lot of information freely available that can be used to make predictions
The efficient market hypothesis deals with that. The freely available information is priced in (nothing is free, and it takes time)
> Market rigging: the market can be affected by your behaviour without you rigging anything
I am talking of things like: https://en.wikipedia.org/wiki/Libor_scandal and https://en.wikipedia.org/wiki/Forex_scandal. These are incidences where the traders got caught. Given the millions at stake, do you think many are caught?
To win at active trading you need an edge nobody else has. There have been cases of traders having insights not known to others. Pairs trading is the only example I know of. In that case the people who kept it secret made out like bandits for a few years, then the secret leaked and it is no longer profitable
The most common legal edge players have is scale: They are huge and nimble and can take advantage of opportunities at scale. It goes really well, until it does not, and another trading house collapses.
The most common edge I believe, after studying it for a decade, is crime. Big trading house, big crime
it can be done...no one say it is easy, but it's doable
Their other funds can't just do what Medallion does, otherwise you are just increasing the cap of Medallion and thus hurting it, which is why they aren't as successful.
fixed it
How come they figured it out for one single fund, but aren't able to make any alternative strong strategies except the secret and closed one?
My questions are valid, and there might be valid answers. We don't know, because nobody knows how Medallion works. All we know is that nobody else can replicate it, not even RenTech itself. Which makes asking questions very important.
Several firms have done similar things.
That being said, RenTech is indeed very interesting. For all we know, it could be a money laundering operation or something similar to Madoff's structure. Or they are just very very good, or lucky. Time will tell !
Medallion does not act on its own or any human sentiment. It is a black box trading strategy that looks for signals. It's not aurprise that during downturns, the overall market is incredibly inefficient. Medallion makes money off of the market's inefficiencies. I don't know what that has to donwith internal vs external investors though.
> How come they figured it out for one single fund, but aren't able to make any alternative strong strategies except the secret and closed one?
I dislike responding to a question with a question, but why would that work? Medallion has made several people billionaires and has done so incredibly quickly. Trying to replicate it with the same strategy will just step on its toes.
It helps to understand Medallion. It is a massive statistical trading system that places a huge amount of bets across all markets, like all of them, and hopes to win say 51% of the bets. When it reaches a certain size, they cap it by taking off all money above the cap and returning it to investors. You can't add more money to Medallion and keep its performance up. It moves the market too much and degrades its positions.
[0] FinGPT: Open-Source Financial Large Language Models https://github.com/AI4Finance-Foundation/FinGPT
[1] Zipline is a Pythonic algorithmic trading library https://github.com/quantopian/zipline
If you want equities, I think you can get that from Databento for low cost (won't need the CME cert for their stuff to get historical from here).
Then just write the code. The basic structure is not that much in a modern language (use Java, Rust). To trade, you can use Sequencer architecture as basic https://sissoftwarefactory.com/blog/an-introduction-to-the-s... (article describes so maybe jog your memory, but has only old code link so useless if not new to you, just sequence your messages) ChatGPT will help build this quick.
IMHO if you want to do this, crypto markets are ideal. Fees are high, but low upfront costs. Can eke out small wins with low capacity strategy.
Should be advised, though. Everyone who wants to get into this does this stuff and then finds that if you want to do big, you need to apply large force on long lever. So everyone and their uncle had "a few profitable strategies as a side bet". Means nothing at small scale. Only for fun.
Affordable data, especially tick level L3 data at scale is difficult to get. Having enough capital to make trading worth well (pricing in losses etc.) is also difficult. Direct market access etc. all cost money. Use interactive brokers if you need a compromise between fully professional and amateur. Spend more time on your financial models, and less time building beautiful frameworks. The engineering of quant finance is the least interesting part. Focus on the market microstructure and financial models. If your model is bad, you lose money regardless of how great your infra is.
It's difficult to find a good off the shelf backtester. This ties into your model too. At its core, a backtester is just a for loop. Computation of variables like slippage and integration of monte Carlo Sims is where the secret sauce lies. Those are all proprietary.
Best of luck in seeking alpha
There's a guy here explaining how to make trading bots in Python https://youtu.be/sUQmuL95_oY He has free code available on github to try out. He also explains how to backtest. There are a couple of popular packages like backtesting.py out there.
ccxt is a handy python package if you want to trade crypto. There are various free tutorials for it.
I also recommend playing around with Tradingview. It draws graphs and you can make your own indicators with their language Pinescript and even trade off that although Python probably gives you more flexibility.
Udemy courses https://www.udemy.com/course/algorithmic-trading-strategies-... and https://www.udemy.com/course/complete-algorthmic-forex-tradi... I paid about £14 each - they keep chopping and changing with the discounts
The details vary a bit depending what you want to trade - crypto, stocks fx or whatever.
One tip - chatgpt4 is surprisingly helpful and can almost code a whole bot for you if you know what you want. One slight pain for me has been finding brokers with the what I want. I'm the wrong nationality or they don't have futures or there isn't enough liquidity or they are sketchy or such like.
Hop on FinTwit or CryptoTwit.
Derivatives (options/futures) are your best bang:buck. But crypto is where the real speculation is.
Read up on a practical trading book (hypothesis building, backtesting without bias, and risk management via Kelly etc.) and then start testing strategies.
Backtesting you can build yourself with any broker that has an API, but not all are made equal. It’s dead simple.
Look into [redacted]
I ended up in twitter/reddit rabbit holes until I found a somewhat dodgy guy on twitter (@TerribleQuant - account is now deleted).
The person compiled a guide with study resources, courses, YT videos, podcasts, textbooks and everything else you can think of in 21 pages.
If you look for: BBM PUBLISHING INC “Roadmap” Resource Guide 3rd Edition you might be able to find a copy.
Only trade when you have an edge, i.e your model suggests that there is a higher probability of an outcome in your favor rather than a pure coin toss - either in entry or in exit.
Even coin toss entries can make money if you have an edge in exits and vice versa.
All in all, you can be right less than 50% of the time per trade, and still have alpha if your winning trade is 2 times your losing trade. Standard expected value stuff. Heck, I know traders who bat 30 or 35% and make colossal amounts of dollars.
1. SPY options
1. SPX options
1. /ES e-mini futures
1. a blend of all
Does one trump another in popularity?
Its a platform where you just focus on implementing strategy. Was fun but I realised it would be more work than just getting a better job.
I'm sure there are others as well.
for quant: https://community.quantopian.com/home https://pyquantnews.com https://www.quantscience.io
for backtesting - zipline reloaded - is event based. It is very slow for optimization.
vectorbt - vector optimization - optimize the parameters. optimize - entry and exit parameters, number of ticks. useful for single-asset or spread strategies (i.e. refiner crack spread).
I’d say this: It is very hard to beat the market consistently. It is even harder to statistically prove and convince yourself that our new strategy actually now beats the market. There are a lot of gotchas and caveats to watch out for when backtesting.
I spent most of my time with time series techniques as this was most fun to me. My current stack is ccxt, binance, polygon.io and self made backtesting in python.
I think it can be a fun project to make an engine, and try to make models, together with some form of ingestion pipeline and finally solve and calibrate the models. Try some simple products, and see how close you can get to real world prices.
Making pricing/risk engines are in my opinion somewhat close to game engines even through that the domain is so different.
I had a friend who was a forex trader at large banks and a lot of it is reading the psychology of the other people in the market. I think humans probably still have an edge there. He made a lot of money then did a lot of drugs then went a bit mad. One of the drawbacks of humans there.
Sell-side bank like JPMorgan, HSBC, then yes you are correct.
Buy-side hedge fund or prop shop, no you are wrong. The SEC/CFTC does not care what you trade in your personal account.
Sure you can still trade of course. but you might need things like preauthorization for every trade, and have to hold them for a given time before selling, which kinda makes algorithmic trading more difficult.
But hey ya'll just pile on. o/