Introduction

In the field of finance and investment, the Capital Asset Pricing Model (CAPM) is a widely used tool for calculating the expected return on an investment based on its risk and the overall market return. This model helps investors make informed decisions about their investment portfolio by understanding the relationship between risk and return. In this academic project, we will study the application of CAPM in the context of selected banking stocks traded at the Bombay Stock Exchange (BSE).

Problem Statement

While CAPM is a valuable tool for investors, there are limitations to its accuracy and applicability in real-world scenarios. The traditional CAPM formula assumes that all investors have the same information and expectations, which may not always be the case in practice. Additionally, the model relies on historical data for estimating risk and return, which may not always reflect current market conditions accurately. Therefore, there is a need to assess the limitations of the existing system and propose improvements to enhance the effectiveness of CAPM in predicting stock returns for banking stocks traded at BSE.

Existing System

The existing system of using CAPM for calculating expected returns on investments involves estimating the risk-free rate, the beta of the stock, and the expected market return. The formula for calculating the expected return on a stock using CAPM is as follows:

Expected Return = Risk-Free Rate + Beta*(Market Return – Risk-Free Rate)

While this formula provides a theoretical framework for understanding the relationship between risk and return, it has several limitations. One of the main drawbacks of the traditional CAPM model is its assumption of a linear relationship between risk and return, which may not always hold true in volatile markets such as those of banking stocks.

Disadvantages

Some of the disadvantages of the traditional CAPM model include its sensitivity to changes in the market and the assumptions it makes about investor behavior. Additionally, the reliance on historical data for estimating risk and return may not accurately reflect current market conditions, leading to potential inaccuracies in predicting stock returns. These limitations call for a reevaluation of the existing system and the potential for developing a more robust model for calculating expected returns on banking stocks traded at BSE.

Proposed System

To address the limitations of the existing CAPM model, we propose incorporating more up-to-date market data and accounting for factors such as market volatility and investor sentiment in our calculations. By analyzing a wider range of variables and considering the dynamic nature of stock markets, we aim to develop a more accurate and reliable model for predicting stock returns for banking stocks traded at BSE. This proposed system will provide investors with more nuanced insights into the risk-return profile of their investments, ultimately leading to more informed decision-making.

Conclusion

In conclusion, the study on the application of CAPM in the context of selected banking stocks traded at BSE highlights the limitations of the traditional model and the need for a more sophisticated approach to estimating expected returns. By proposing improvements to the existing system and considering factors such as market volatility and investor sentiment, we aim to develop a more robust model for calculating expected returns on banking stocks. This research will contribute to the field of finance and investment by enhancing the accuracy and reliability of CAPM in predicting stock returns in dynamic market conditions.