Better than Pre-Commitment Mean-Variance Portfolio Allocation Strategies: A Semi-Self-Financing Hamilton-Jacobi-Bellman Equation Approach

We generalize the idea of semi-self-financing strategies, originally discussed in Ehrbar (1990), and later formalized in Cui et al (2012), for the pre-commitment mean-variance (MV) optimal portfolio allocation problem. The proposed semi-self-financing strategies are built upon a numerical solution framework for Hamilton–Jacobi–Bellman equations, and can be readily employed in a very general setting, namely continuous or discrete re-balancing, jump-diffusions with finite activity, and realistic portfolio constraints. We show that if the portfolio wealth exceeds a threshold, an MV optimal strategy is to withdraw cash. These semi-self-financing strategies are generally non-unique. Numerical results confirming the superiority of the efficient frontiers produced by the strategies with positive cash withdrawals are presented. Tests based on estimation of parameters from historical time series show that the semi-self-financing strategy is robust to estimation ambiguities.

[1]  Nicole Bäuerle,et al.  Complete markets do not allow free cash flow streams , 2015, Math. Methods Oper. Res..

[2]  Ricardo Josa-Fombellida,et al.  Mean-variance portfolio and contribution selection in stochastic pension funding , 2008, Eur. J. Oper. Res..

[3]  J. Jacod,et al.  Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data , 2009 .

[4]  P. Yu Cone convexity, cone extreme points, and nondominated solutions in decision problems with multiobjectives , 1974 .

[5]  Elena Vigna On efficiency of mean–variance based portfolio selection in defined contribution pension schemes , 2014 .

[6]  Steven Haberman,et al.  Mean-variance optimization problems for an accumulation phase in a defined benefit plan , 2008 .

[7]  X. Zhou,et al.  Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework , 2000 .

[8]  Huyen Pham,et al.  Continuous-time stochastic control and optimization with financial applications / Huyen Pham , 2009 .

[9]  Peter Forsyth,et al.  Continuous Time Mean-Variance Optimal Portfolio Allocation Under Jump Diffusion: An Numerical Impulse Control Approach , 2013 .

[10]  Robert Almgren,et al.  Optimal Trading with Stochastic Liquidity and Volatility , 2012, SIAM J. Financial Math..

[11]  R. C. Merton,et al.  Option pricing when underlying stock returns are discontinuous , 1976 .

[12]  P. Forsyth,et al.  COMPARISON OF MEAN VARIANCE LIKE STRATEGIES FOR OPTIMAL ASSET ALLOCATION PROBLEMS , 2012 .

[13]  Markus Leippold,et al.  A Geometric Approach To Multiperiod Mean Variance Optimization of Assets and Liabilities , 2004 .

[14]  Andrew E. B. Lim,et al.  Dynamic Mean-Variance Portfolio Selection with No-Shorting Constraints , 2001, SIAM J. Control. Optim..

[15]  George Tauchen,et al.  Realized Jumps on Financial Markets and Predicting Credit Spreads , 2006 .

[16]  P. Forsyth,et al.  Numerical solution of the Hamilton-Jacobi-Bellman formulation for continuous time mean variance asset allocation , 2010 .

[17]  Peter Forsyth,et al.  Numerical Solution of the Hamilton – Jacobi – Bellman Formulation for Continuous-Time Mean – Variance Asset Allocation Under Stochastic Volatility , 2016 .

[18]  L. Clewlow,et al.  Energy Derivatives: Pricing and Risk Management , 2000 .

[19]  Duan Li,et al.  BETTER THAN DYNAMIC MEAN‐VARIANCE: TIME INCONSISTENCY AND FREE CASH FLOW STREAM , 2012 .

[20]  Michael S. Gibson,et al.  Dynamic Estimation of Volatility Risk Premia and Investor Risk Aversion from Option-Implied and Realized Volatilities , 2007 .

[21]  Yuying Li,et al.  Preservation of Scalarization Optimal Points in the Embedding Technique for Continuous Time Mean Variance Optimization , 2014, SIAM J. Control. Optim..

[22]  Suleyman Basak,et al.  Dynamic Mean-Variance Asset Allocation , 2009 .

[23]  P. Honoré Pitfalls in Estimating Jump-Diffusion Models , 1998 .

[24]  Duan Li,et al.  Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation , 2000 .

[26]  J. Wang,et al.  Continuous time mean variance asset allocation: A time-consistent strategy , 2011, Eur. J. Oper. Res..

[27]  Nicole Bäuerle,et al.  Benchmark and mean-variance problems for insurers , 2005, Math. Methods Oper. Res..

[28]  Rama Cont,et al.  Nonparametric tests for pathwise properties of semimartingales , 2011, 1104.4429.

[29]  M. Schweizer Mean–Variance Hedging , 2010 .

[30]  Cecilia Mancini,et al.  Non‐parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps , 2006, math/0607378.

[31]  Lukasz Delong,et al.  Mean-variance portfolio selection for a non-life insurance company , 2007, Math. Methods Oper. Res..

[32]  Peter A. Forsyth,et al.  Continuous time mean-variance optimal portfolio allocation under jump diffusion: An numerical impulse control approach: Numerical Impulse Control Approach , 2014 .

[33]  Yuying Li,et al.  Convergence of the embedded mean-variance optimal points with discrete sampling , 2016, Numerische Mathematik.

[34]  Hans G. Ehrbar Mean-variance efficiency when investors are not required to invest all their money , 1990 .

[35]  X. Zhou,et al.  CONTINUOUS‐TIME MEAN‐VARIANCE PORTFOLIO SELECTION WITH BANKRUPTCY PROHIBITION , 2005 .

[36]  Tomas Bjork,et al.  A General Theory of Markovian Time Inconsistent Stochastic Control Problems , 2010 .