Index Portfolio Analysis

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Introduction This assignment aims to employ a dynamic CPPI strategy and discuss its effectiveness in managing an Index Portfolio. After defining strategic criteria, we construct an optimal portfolio based on the Mean-Variance theory. We then manage it for the defined one-year period and apply classical (e.g. Sharpe Ratio, Treynor Ratio) as well as CPPI-specific (e.g. Omega Ratio, T2, M2) performance measures to create a consolidated portfolio view. Finally, using data form the Wharton Database we employ a multifactor analysis and discuss the performance of the managed Index Portfolio and its risk characteristics. 2. Investment Policy and Strategic Criteria The investment objective is to achieve a combination of capital growth and income through index investment. The portfolio will be initially optimised using data focusing on the period 31/12/2002-31/12/2012 and it will be managed based on the quantitative principles of a dynamic Constant Proportion Portfolio Insurance (CPPI) strategy for the fiscal year 2013. We consider that a Medium Risk portfolio is suitable to achieve capital growth and income and for this reason we have chosen a risk aversion parameter of 6 and a CPPI floor of 90.000 to mitigate the potential for capital loss. The personal constraints include: the Budget constraint, the Short-Sale constraint and the investment horizon. We will be investing £100,000.00 into eight UK FTSE stock industry indexes and the Risk-Free asset. Typically, the defined investment horizon based on the purposes of this project will be 12 months. However, the flexibility, effectiveness and protection from downward risk of the selected strategy can allow us to set an 18-24 months investment period. 3. Statistical Analysis A... ... middle of paper ... portfolio based on risk preferences, personal constraints and investment objectives following the Mean-Variance Theory. We have applied a CPPI strategy to allocate assets dynamically over-time and highlighted its superiority compared to the Market and Benchmark Portfolios. We have used both classical (e.g. Sharpe Ratio) and advanced performance measures (e.g. T2, Omega Ratio). We have identified that much of the portfolio’s performance can be attributed to the Selection Effect. The significant MoM indicates the presence of Momentum Effect in the portfolio’s returns. We have highlighted the contribution of Omega Ratio in modern portfolio management because of its ability to capture Higher Moments. Overall, we conclude that insurance strategies, such as CPPI, can be quite useful when investors seek insurance against rapid falls in the market and crash in equities.

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