There are different types of investors based on risk aversiveness and this significantly impacts their investment decisions. A common goal of any type of investor is to maximize the returns by minimizing the risk. This study tries to solve this problem as a nonlinear programming problem and aims to optimize the portfolio weights. A diversified portfolio is built for aggressive and defensive investors and a modified version of the Markowitz model with different strategies is used to analyze the returns. A peculiar observation on the analysis reveals that the aggressive investor maximizes the reward to risk ratio but due to the presence of higher risk-bearing assets in his portfolio the investor needs a higher CVaR to be prepared for the downfall. The regression model helps to understand the relation between absolute portfolio returns and absolute market returns. It identifies the higher certainty and predictability of the defensive investor which becomes crucial since this becomes an important trade-off against returns. We also find that this fact holds since the aggressive investor holds a higher margin as compared to a defensive investor due to the high exposure to uncertainty in the investment. This study fulfills the objectives for the two investors in the Indian market where the asset classes are allocated and defined as per qualitative security and fundamental analysis

Keywords : Expected Return, Risk, Standard Deviation, Beta, Risk-free rate, Market Risk Premium, Portfolio Optimisation, Tail Risk