Quantitative Finance:
One of the projects that I have been wanting to do for a long time is to have an automated trading system that does trades on my behalf based on programmed algorithms. I’ve been learning a lot about the financial markets over the course of the past few weeks. Some important lessons I’ve found along the way as I am tracking the Indian Equities Market in 2024:

1. Keep things simple, don’t use the latest tech just for the sake of it: Trying to write your own APIs in Rust/C++ to analyse market data can be cumbersome. Python seems to be the easiest and quickest. When you are short on time and want to prototype ideas quickly, it does not make sense to reinvent the wheel in another programming language, unless you are interested in learning it.
2. Statistical tools can be powerful: Simple statistical tools can generate great insight into the market behaviour. Be wary, sometimes statistics can also be misleading when not used correctly.
3. News / Sentiment is more powerful than you think: Seemingly simple events like news can trigger great volatility in the market. News can sometimes also be misleading about an asset class.
4. Simple APIs: Try a bunch of APIs from different vendors. I found the Yahoo Finance and AlphaVantage APIs the simplest one to use, Yahoo Finance APIs worked out of the box in my first attempt.
5. Importance of Backtesting: You can come with all kinds of strategies that are based on the current data, but it’s important to validate them against historical information. Strategies that work in the current moment might not stand the test of time. It’s important to test your strategy based on data that you have not seen before (like a simulated market environment or historical data). Think of all cases your strategy might not work.
6. Importance of logging: Log all information from the asset class you are analyzing.
7. Visualize the data: It’s important to visualize the data you are analyzing. Combining statistics with visual information can lead to new insights.
8. Success with the market does not mean you can predict the market: Your strategy might have worked at one moment, but that does not mean it can consistently work in the long term. It’s easy to fall into the trap that you can understand market trends and predict them when you see success a few times. You might be riding on trends/effects that you have not taken into account and not a result of your own strategy.
9. Automate generously: Automatic analysis of portfolio and getting market insights via the use of automation can help gain some valuable insights into market behaviour.
10. Learning: You can learn a lot about technology, markets, algorithms, human psychology trying to learn about markets. I think that is a great reward in itself.