Quant Trading & Research
Table of Contents
Data Analysis
Usually no trading company will hire new QRs directly to the front-office buy side unless they have pedigree meaning they come from a famous school. You can however move internally from the back office where you are doing shit work in tech to the front office and perform more shit work (at first) to get into QR if you know the basics of data analysis.
What does a QR do?
A good breakdown of quantitative trading is here and the same author's PDF floating around from 2011 on algorithmic trading that he was forced to abandon upon signing NDAs. Note that he doesn't agree anymore with his old notes they should just be a curious read and none of the recommendations for mental math or anything else followed.
I have witnessed most of their time is spent in meetings presenting to senior risk committees and the longer the strategy the more planning and meetings. During this time there's a ton of other work to do that's where you come in as the lackey assistant or trainee researcher.
What does an 'assistant' QR do?
You can easily spot the shit work from the above blog post that a professional researcher making 7 figures would love to dump on some eager trainee. Even if there is a small army of teams set up for the QR department there is always something tedious they would rather someone else to do for them like maintenance of the research infrastructure, writing documentation, analysis of the production system to optimize trading fees or reconciliation tasks end of day if you can be trusted with that work.
Why would you offer to do this? Because then they have time to show you the magic of predicting the future.
If you sell yourself as a reliable portal where increasingly complex shitwork can be dropped that is always returned with high attention to detail they will want you around. Depending where you work some more non-disclosures are signed and you are moved into their office.
What are the basics?
I assume you can program so all you need is the basics of data analysis on noisy but semi-structured data meaning S-expressions, JSON, Apache Parquet column-oriented files, etc.
- Probability
- this is a workbook really not a textbook
- look who sponsors the course for this book
- Modern Regression and Data Analysis
- uses R but Julia/Matlab/Python exists too use whatever you want
- Intro to Game Theory (optional)
- helps to understand QR lingo and strategies
- or try The Mathematics of Poker by Chen/Ankenman
That's it. You can learn more statistical learning when you get there.
Transformers (LLMs) are used for things you wouldn't expect like predicting 40 septillion floating point operations so trades or researchers don't have to use computational resources to calculate them. Anything to speed up data analysis or lower the fees tweaking the trading is being constantly worked on by machine learning teams usually seperate from QR.
Game Theoretic Probability
I'm personally interested in Game-Theoretic Probability where essentially all concepts of randomness are thrown out. Probabilities are now forecasts and statistical models are tested with betting and non-stochastic. If you've ever been highly skeptical of stock markets being supposedly stochastic instead of a game played by multiple participants then you'll probably want to take this too.
One of the authors Glenn Shafer designed a simple betting test for statistics tossing out p-values.
Martingaling
The craziest example of casino martingaling can be seen in the videos floating around of Dana White filling up a blackjack table with markers going deep into debt and then paying them all off. Strategies where you bet more when you are losing and less (or quit) when you are winning obscures the risk of large losses and are called martingales.
This is not limited to sports betting or casinos. Corporate executives and professional financial traders deceive themselves with martingales all the time. A good paper to read is The Martingale Index by Shafer/Dimitrov to ensure that's never your strategy as it's an easy trap to fall into and also easy to read when someone else is martingaling like day traders and you can bet against them.
Probability
What we should do is work through Real Analysis by Bruckner/Thomson while reading Mathematical Methods of Statistics by Cramer. If you want to do that then try the Tripos.
I will start going through the Mor Harchol-Balter book until we can understand modern regression which means we can understand advanced data analysis and you're done, everything else is optional. I will do what Cramer does and look up prereqs as needed as you will always be doing data analysis using a programming language.
TODO