Stocks Risks Analysis with Python
By: Roberto Salazar
Tags: Python, Finance, Data Science, Programming, Stock Market

Python for Financial Analysis

Stocks Risks Analysis with Python

Understanding Stocks Volatilities

Image by Nicholas Capello available at Unsplash

Stock Market and Investments

There is one main fundamental principle to make a profit out of investments in the stock market: sell stocks at a higher price than what you paid for. In other words: buy low, sell high. As simple as it sounds, but not as simple as it is.

However, there is always a time lapse between the stock price at its acquisition and its price at its selling; either its price increases or drops. For some stocks, the time required to increase (or decrease) their price is shorter or longer than for others. This is due to a company’s recent activity and the market opinion/sentiment on it based on its results, growth, goals, change in management or strategic plans.

Risk, Volatility and Return

A stock’s risk is measured (along with other metrics) by its volatility; in other words: by its growth’s degree of steadiness.

The higher the stock risk (i.e. high volatility), the greater the probability of a higher return (or loss). On the other hand, the lower the stock risk (i.e. low volatility), the greater the probability of a smaller return (or loss). This is commonly known as the Risk Return Trade Off, which is encountered by every investor while considering investment decisions.

In these decisions, it all comes to two factors when determining which stocks to buy: the time an investor is willing to hold it and the desired return/profit (in term of percentage gains).

Consider the following scenarios:

If an investor would like to make a huge profit in a short period of time , he/she would have to invest in high volatile stocks and hope to catch positive streaks. Even though this represents the best scenario, it is also the one with the highest investment risk. Example: an increase of 20% in your portfolio value in 1 day.

in a , he/she would have to invest in high volatile stocks and hope to catch positive streaks. Even though this represents the best scenario, it is also the one with the highest investment risk. Example: an increase of 20% in your portfolio value in 1 day. If an investor would like to make a moderate profit in a short period of time , he/she would have to look for low volatile stocks and hope to catch a positive streak. This represents a short-term investment scenario with moderate investment risk. Example: an increase of 3% in your portfolio value in 1 day.

in a , he/she would have to look for low volatile stocks and hope to catch a positive streak. This represents a short-term investment scenario with moderate investment risk. Example: an increase of 3% in your portfolio value in 1 day. If an investor would like to make a moderate profit in a long period of time , he/she would have to look for low volatile stocks with positive trends. This represents the most conservative scenario with the lowest investment risk. Example: an increase of 3% in your portfolio value in 1 year.

in a , he/she would have to look for low volatile stocks with positive trends. This represents the most conservative scenario with the lowest investment risk. Example: an increase of 3% in your portfolio value in 1 year. If an investor would like to make a huge profit in a long period of time, he/she would have to look for low volatile stocks with positive trends and hold them for a more extended period of time. This represents a long-term investment scenario with low investment risk. Example: an increase of 20% in your portfolio value in 5 years.

Nowadays, investors are encouraged to leverage the applications and benefits of multiple programming languages and software to analyze stocks’ risks, trends and volatilities to build effective decision support systems and make optimum and trustworthy decisions.