2025/11/29 by Hiroki Yamamichi, Yamamichi, Hiroki · 1 voice
Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #Financial Markets and Investment Strategies #Portfolio Management (q-fin.PM) #Stochastic processes and financial applications #q-fin.PM
paper · pdf · doi:10.48550/arxiv.2512.00346
openalex publication_date 2025/11/29 · arxiv published 2025/11/29 · arxiv updated 2025/11/29 · openalex created_date 2025/12/03 · openalex updated_date 2026/07/28
Turnpike theorems state that if an investor's utility is asymptotically equivalent to a power utility, then the optimal investment strategy converges to the CRRA strategy as the investment horizon tends to infinity. This paper aims to derive the convergence rates of the turnpike theorem for optimal feedback functions in stochastic factor models. In these models, optimal feedback functions can be decomposed into two terms: myopic portfolios and excess hedging demands. We obtain convergence rates for myopic portfolios in nonlinear stochastic factor models and for excess hedging demands in quadratic term structure models, where the interest rate is a quadratic function of a multivariate Ornstein-Uhlenbeck process. We show that the convergence rates are determined by (i) the decay speed of the price of a zero-coupon bond and (ii) how quickly the investor's utility becomes power-like at high levels of wealth. As an application, we consider optimal collective investment problems and show that sharing rules for terminal wealth affect convergence rates.