2015/02/10 by Michele Longo, Longo, Michele, Alessandra Mainini +1
Decision Sciences · Economics, Econometrics and Finance · #93E20 #FOS: Economics and business #Financial Markets and Investment Strategies #Portfolio Management (q-fin.PM) #Risk and Portfolio Optimization #Stochastic processes and financial applications #msc:93E20 #q-fin.PM
paper · pdf · doi:10.48550/arxiv.1502.02968
arxiv created 2015/02/10 · openalex publication_date 2015/02/10 · arxiv updated 2015/02/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We maximize the expected utility from terminal wealth for an HARA investor when the market price of risk is an unobservable random variable. We compute the optimal portfolio explicitly and explore the effects of learning by comparing it with the corresponding myopic policy. In particular, we show that, for a market price of risk constant in sign, the ratio between the portfolio under partial observation and its myopic counterpart increases with respect to risk tolerance. As a consequence, the absolute value of the partial observation case is larger (smaller) than the myopic one if the investor is more (less) risk tolerant than the logarithmic investor. Moreover, our explicit computations enable to study in details the so called hedging demand induced by learning about market price of risk.