MEAN–VARIANCE PORTFOLIO CHOICE: QUADRATIC PARTIAL HEDGING

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Continuous-time mean-variance efficiency: the 80% rule (2006, background): “) The dynamic extension of the Markowitz model, especially in continuous time, has been studied extensively in recent years; see, for example, [2, 6, 7, 8, 11, 12].”
ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY (2009, methodology): “Jorion (1985), Best and Grauer (1991) and Britten-Jones (1999) suggest the main difficulty concerns the extreme weights that often arise when constructing sample efficient portfolios that are extremely sensitive to changes in asset means. Another school suggests that the estimation of the correlatio”
MEAN–VARIANCE PORTFOLIO OPTIMIZATION WITH STATE‐DEPENDENT RISK AVERSION (2014, background): “Further extensions and improvements are carried out in, among many others, [13], [12], [3], and [20].”
A Hamilton-Jacobi-Bellman approach to optimal trade execution (2011, methodology): “The mean variance objective 54 function can be converted to linear-quadratic (LQ) objective function using a Lagrange multiplier method 55 [24, 10, 34, 4, 20].”