In this thesis, we focus on the goal-reaching model, in which an investor seeks to achieve a predetermined terminal wealth at the end of the investment period. We follow the quantile formulation approach from He and Zhou (2011), where the quantile function of the terminal cash flow, instead of the cash flow itself, is used as the decision variable.
We find that in accordance with He and Zhou (2011) the optimal payoff in the goal-reaching model is binary and that the investor must choose their risk preference by weighing the probability to reach the benchmark. We further prove, that the payoff of the goal-reaching model equals a digital call option and derive explicit solutions for the replicating portfolio in a Black-Scholes market.
An extensive empirical study is conducted to test the goal-reaching investment strategy using 25 years of DAX index data. The results confirm the theoretical findings of the inverse relationship between the chosen benchmark, time horizon and the probability of success. However, in our study we find that the applicability of the model is limited due to model limitations, such as the assumption of constant volatility and log-returns, and practical constraints like parameter estimation errors.
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In this thesis, we focus on the goal-reaching model, in which an investor seeks to achieve a predetermined terminal wealth at the end of the investment period. We follow the quantile formulation approach from He and Zhou (2011), where the quantile function of the terminal cash flow, instead of the cash flow itself, is used as the decision variable.
We find that in accordance with He and Zhou (2011) the optimal payoff in the goal-reaching model is binary and that the investor must choose their...
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