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Designing dynamic portfolio insurance strategies under market conditionsswitching between two or more regimes is a challenging task in financialeconomics. Recently, a promising approach employing the value-at-risk (VaR)measure to assign weights to risky and riskless assets has been proposed in[Jiang C., Ma Y. and An Y. "The effectiveness of the VaR-based portfolioinsurance strategy: An empirical analysis" , International Review of FinancialAnalysis 18(4) (2009): 185-197]. In their study, the risky asset follows ageometric Brownian motion with constant drift and diffusion coefficients. Inthis paper, we first extend their idea to a regime-switching framework in whichthe expected return of the risky asset and its volatility depend on anunobservable Markovian term which describes the cyclical nature of assetreturns in modern financial markets. We then analyze and compare the resultingVaR-based portfolio insurance (VBPI) strategy with the well-known constantproportion portfolio insurance (CPPI) strategy. In this respect, we employ avariety of performance evaluation criteria such as Sharpe, Omega and Kapparatios to compare the two methods. Our results indicate that the CPPI strategyhas a better risk-return tradeoff in most of the scenarios analyzed andmaintains a relatively stable return profile for the resulting portfolio at thematurity.

Value-at-Risk-Based Portfolio Insurance: Performance Evaluation and Benchmarking Against CPPI in a Markov-Modulated Regime-Switching Market