M. Avellaneda, T. Li, A. Papanicolaou, Gaozhan Wang
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引用次数: 3
Abstract
ABSTRACT We propose a new approach for trading VIX futures. We assume that the term structure of VIX futures follows a Markov model. Our trading strategy selects a position in VIX futures by maximizing the expected utility for a day-ahead horizon given the current shape and level of the term structure. Computationally, we model the functional dependence between the VIX futures curve, the VIX futures positions, and the expected utility as a deep neural network with five hidden layers. Out-of-sample backtests of the VIX futures trading strategy suggest that this approach gives rise to reasonable portfolio performance, and to positions in which the investor will be either long or short VIX futures contracts depending on the market environment.
期刊介绍:
The journal encourages the confident use of applied mathematics and mathematical modelling in finance. The journal publishes papers on the following: •modelling of financial and economic primitives (interest rates, asset prices etc); •modelling market behaviour; •modelling market imperfections; •pricing of financial derivative securities; •hedging strategies; •numerical methods; •financial engineering.