In contrast to decision models which use in-sample scenarios we use out-of-sample scenarios to conduct simulation and decision evaluation including backtesting. We propose two simulation methodologies and describe six decision evaluation techniques that can be applied to test the performance of...

Robust optimization is a tractable alternative to stochastic programming particularly suited for problems in which parameter values are unknown, variable, and their distributions are uncertain. We evaluate the cost of robustness of the robust counterpart to the maximum return portfolio...

This paper considers long-short portfolio optimization in the presence of two risk measures: variance and Conditional Value at Risk (CVaR) and asset choice constraints of (i) buy, sell and holding thresholds (ii) cardinality restrictions on the number of stocks to be held in the portfolio. The...

The paper considers kernel estimation of conditional quantiles for both short-range and long-range-dependent processes. Under mild regularity conditions, we obtain Bahadur representations and central limit theorems for kernel quantile estimates of those processes. Our theory is applicable to...

We apply a regime switching Markov chain model to determine bond prices. Our work builds upon the work of Thomas, Allen amp; Morkel-Kingsbury (2002) and Jarrow, Lando amp; Turnbull (1997). The interest rate process and credit rating migration process are considered. Our aim is to study the price...

Recently considerable attention has been given to downside risk control in the context of portfolio choice; see Sortino and Satchell (2005). We propose an integrated model for portfolio choice in which downside risk is considered explicitly at the stage of the scenario generation which describes...