Here, I document my learning, everything that I learned from books, videos, courses etc regarding the stock market.
Some topics that you will find on this blog include:
- Options strategies (e.g. selling Cash Secured Puts, Buying Covered Calls etc)
- Python Tutorial
- Machine Learning Code
- Amibroker and AFL Tutorials and Code Snippets
- Quantitative Finance
My focus at the moment is on mechanical trading, specifically algorithmic trading. This includes learning how to code the strategy, backtest it and test for statistical significance.
Why am I into algorithmic trading?
- I do not believe I have an edge in fundamental analysis. Firstly, I do not have an accounting background and thus do not have an analytical edge. I can only understand about 50% of the information presented in a financial report. Next, I do not have an information edge. While big fund managers have a lot of manpower to gather relevant information about a company and read through the financial reports and expert analysis, I do not have the time nor resources to do the same.
- I also do not have the temperament to do discretionary day trading. Firstly, I do not want to sit in front of the computer all day waiting for trades. In addition, since I live in Asia with a time difference of 12 hours, the US trading hours correspond to midnight to dawn for me. Hence, it is not practical for me to do discretionary day trading. I also do not like the inconsistency of discretionary trading. Based on my practice results, I know I am too inconsistent and it is thus very stressful.
- Considering my skills and temperament, I believe a mechanical system works best for me. It does not have to be automated, but it has to be mechanical. The only way for me to trust a mechanical system is to fully backtest it.