Applying Machine Learning, Asset Allocation, and Risk Management in Selecting Stocks and Building Profitable Portfolio

Many years ago, the stock market became one of the considerable investment channels for

many individuals. When the Covid-19 pandemic occurred in the world, many people are

placed under full or partial lockdown, and the “stock” keyword became trendy on Google

Search. People started discussing investing or trading in the stock market. Approximately,

95% traders lose money due to many factors such as lack of experience, financial knowledge,

or fortune. The comparison between investors and traders, which includes all types of

traders such as day traders and swing traders, gradually became popular. There are many

strategies to invest or trade in the stock market. One of the efficient methods is to select

good stocks to build a profitable portfolio. It sounds easy, but it requires many steps and

effort including collecting and cleaning data, filtering stocks, gathering potential stocks,

predicting stock returns, creating portfolios, filtering portfolios by using risk management,

finding weights of each stock by asset allocation, and testing with a custom environment.