A stochastic programming model for dynamic portfolio management with financial derivatives

Stochastic optimization models have been extensively applied to financial portfolios and proven their effectiveness in asset asset-liability management. Occasionally, however, they dynamic portfolio problems including not only assets traded secondary markets but also derivative contracts such as options or futures with dedicated payoff functions. Such extension allows the construction of asymmetric payoffs for hedging speculative purposes leads several mathematical issues. Derivatives-based nonlinear a discrete multistage stochastic programming (MSP) framework can be potentially very beneficial shape dynamically return distribution attain superior performance. In this article we present model equity options, which extends significantly previous efforts area, analyse potential from modeling methodological viewpoints. We consider an universe set-up equity, bonds, money market, volatility-based exchange-traded-fund (ETF) over-the-counter (OTC) option on equity. Relying market structure formulate analyse, best our knowledge, first time, comprehensive set optimal strategies framework, canonical protective puts, covered calls straddles, well more advanced combined based volatility index. The problem formulation relies data-driven scenario generation method returns prices consistent arbitrage-free conditions incomplete assumptions. joint inclusion VIX class domain volatility-driven policies. By introducing trade-off expected wealth Conditional Value-at-Risk (CVaR), linear program extended numerical results across different phases, discuss interplay among classes relevant engineers fund managers. find that options’ trading strengthen effective tail risk control, help shaping returns’ distributions, consistently investor’s attitude. Furthermore introduction index universe, jointly risk-adjusted returns, both in- out-of-sample, shown final case-study.