Using AI too much, we start thinking of AI for everything – often, learning new developments is more reliable with search engines plus official project documentation.

Hong Kong stocks entered on the dip, encountered a pullback, and then just randomly traded, resulting in basic losses.

Strategy Trading

Not necessarily to actually practice and make money, but rather to improve my own abilities through learning. I don’t believe in these trading indicators; I mostly trust the national fortune (luck) and investing in broad market indices via a buy-and-hold strategy.

Algorithmic Trading

The inspiration from last month’s “AI-less project” didn’t prove useful, so I started trying to implement it with AI – and that’s where the problems began. The correct approach should have been to first gather information and see what existing projects were doing. Previously, I hadn’t done any algorithmic trading; I wasn’t familiar with indicators, market data handling, etc.

The initial plan was unreliable, entirely based on my own speculation (“YY”) through communication with AI. I learned about the backtesting framework this way, and looked at GitHub – the project was quite active.

Over-reliance on AI led to wanting to use it for everything, even requesting an AI-generated learning resource, a vibrant project, and official documentation that’s well-maintained. Prioritizing official documentation or searching for high-quality blogs is better; the learning plans provided by AI were too weak and didn’t keep up with current code versions.

Project Structure Adjustments:

1. Data Download: I chose Yahoo Finance – this provides daily candlestick data for price changes (price fluctuations).
2. Backtesting Official Guide: Learning the basics of using the official backtesting guide.
3. TA-Lib Installation and Usage: Installing and using TA-Lib, calculating common indicators, and displaying the data through backtesting.
4. Implementing Alipay’s Fixed Investment Logic: This strategy is better suited for long-term ETF investments.

Hong Kong Stock Trading

Entering Hong Kong stock trading was roughly two months ago, a simple recap.

The timing and motivation for buying Meituan were straightforward – I saw the net inflow of domestic funds and didn’t delve deeply into Meituan’s recent situation; coincidentally, I caught the food delivery war and became a shareholder in Meituan. Buying Xiaomi was also at a high price point, and it was appropriate to reduce my position and exit some shares when an opportunity arose. The four factories were implemented, presenting an opportunity, but one that required persistence – about three years have passed.

The timing of entry was when Hong Kong’s new consumer and technology stocks were already expensive, coupled with the concept of virtual currencies; when technology stocks retraced, it was a recurring issue – the frequency of adding to positions is not suitable for long-term investment. Today, I thought about betting on a rebound, buying a hand full, but the next day it fell and I couldn’t bear to sell it. When encountering sustained declines, one easily gets trapped.

As a long-term investor, my trading frequency was too high – roughly twice a week would be sufficient. The Shanghai Composite Index is 3600; domestic large-cap stocks haven’t been much invested in through fixed deposits; this missed an opportunity as well.