Investment

In the turbulent and unpredictable stock market, we often use faith and expectations as our compass, attempting to navigate through the fog and reach the shores of wealth. However, when our voyage deviates from the guidance of the compass, it’s easy to lose direction, even to run aground. This essay is about one such journey, beginning with an unwavering obsession with Xiaomi, which rose and fell repeatedly amidst the waves of capital.

Everyone has their own life trajectory, so the concept of “being a good teacher” often seems superfluous in adult circles. Worldview Our life’s journey begins with vastly different formative experiences, these experiences converging and flowing like rivers to ultimately shape our unique life paths. Each story, each choice, weaves together and merges within our minds, solidifying into our perception of the world – our worldview. What you’ve witnessed as tragedy may be merely a story in a book to another person.

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.

It’s difficult for ordinary people to understand a policy document, and traditional financial planning is based on understanding annualized returns. However, the calculation method of an increasing term life insurance policy is Internal Rate of Return (IRR), and there’s a difference between these two – what’s the difference and why does it exist? When funds are invested in one go, Internal Rate of Return (IRR) and Annualized Return (Annualized Return) produce the same results.

Backtesting requires: proportionate method (price-weighted return method), a simple explanation, and examples. Also, why cannot use add-subtract method for adjustment, and recommendations for Python historical data sources using the proportionate method. Okay, let’s explain the “proportionate method (price-weighted return method)” in an easy-to-understand way, along with why the “add-subtract method”

Reflecting on years of stock trading experiences, although I didn’t make a fortune, I also didn’t lose too much. The biggest issue was an unreasonable allocation of funds and an unstable mindset. Currently, my primary source of income is work, earning a fixed salary each day through part-time jobs, and my ability to withstand financial fluctuations remains at the level of bonds and bank deposits. However, people are inherently greedy; if you buy too little, even when prices rise, you won’t make money; and if you buy too much, you will lose money.

Those of us born in the 90s, we didn’t really feel the impact of the 2008 financial crisis – after all, we were young and hadn’t yet started to focus on finance. The roaring bull market of 2015 came with a lot of fanfare, and when it ended, it made quite a stir, ultimately requiring government intervention to stabilize the markets. Simultaneously, this brought the concept of “funds” into the view of ordinary people.