Ding, Liyuan 1988- (2012-12). Empirical Analysis of Value at Risk and Expected Shortfall in Portfolio Selection Problem. Master's Thesis. Thesis uri icon

abstract

  • Safety first criterion and mean-shortfall criterion both explore cases of assets allocation with downside risk. In this paper, I compare safety first portfolio selection problem and mean-shortfall portfolio optimization problem, considering risk averse investors in practice. Safety first portfolio selection uses Value at Risk (VaR) as a risk measure, and mean-shortfall portfolio optimization uses expected shortfall as a risk measure, respectively. VaR is estimated by implementing extreme theory using a semi-parametric method. Expected shortfall is estimated by two nonparametric methods: a natural estimation and a kernel-weighted estimation. I use daily data on three international stock indices, ranging from January 1986 to February 2012, to provide empirical evidence in asset allocations and illustrate the performances of safety first and mean-shortfall with their risk measures. Also, the historical data has been divided in two ways. One is truncated at year 1998 and explored the performance during tech boom and financial crisis. the mean-shortfall portfolio optimization with the kernel-weighted method performed better than the safety first criterion, while the safety first criterion was better than the mean-shortfall portfolio optimization with the natural estimation method.
  • Safety first criterion and mean-shortfall criterion both explore cases of assets allocation with downside risk. In this paper, I compare safety first portfolio selection problem and mean-shortfall portfolio optimization problem, considering risk averse investors in practice. Safety first portfolio selection uses Value at Risk (VaR) as a risk measure, and mean-shortfall portfolio optimization uses expected shortfall as a risk measure, respectively. VaR is estimated by implementing extreme theory using a semi-parametric method. Expected shortfall is estimated by two nonparametric methods: a natural estimation and a kernel-weighted estimation.



    I use daily data on three international stock indices, ranging from January 1986 to February 2012, to provide empirical evidence in asset allocations and illustrate the performances of safety first and mean-shortfall with their risk measures. Also, the historical data has been divided in two ways. One is truncated at year 1998 and explored the performance during tech boom and financial crisis. the mean-shortfall portfolio optimization with the kernel-weighted method performed better than the safety first criterion, while the safety first criterion was better than the mean-shortfall portfolio optimization with the natural estimation method.

publication date

  • December 2012