Investment Analysis: Evaluating Stocks with Sharpe Ratios Using Machine Learning

by Shivam Kashyap

This paper analyzes investment opportunities by evaluating the Sharpe coefficients of each of the stocks of the chosen corporations against the S&P 500. Its main aim is to provide useful data to be used in the investment decision process by estimating the returns with the risk factor included.

Our methodology includes:

  1. Data Collection: Gathering price data of stocks and the S&P 500 index.
  2. Data Pre-processing: Calculating the daily percentage difference and then annualizing the results for each stock and the S&P 500 index.
  3. Sharpe Ratio Calculation: Using the Sharpe ratio in order to determine the risk on the basis of the obtained returns.
  4. Comparative Analysis: Sharpe ratios of the individual stocks and S&P 500 to evaluate the attractiveness of the stocks
  5. Visualization: Creating graphics to explain one of the key aspects of stock analysis, namely risk-return profile of the investigated securities.

The results show that the particular shares have higher Sharpe ratios than the S&P 500, meaning upper outcomes with regards to risk-return pair. These findings are beneficial to the investors whereby through analysis of the data they can enhance their investment portfolios. It is also an important observation in the study that the consideration of investment prospects cannot do without risk assessment.

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