Portfolio optimization with non-constant volatility and partial information
Portfolio optimization with non-constant volatility and partial information
复制标题
具有非恒定波动性和部分信息的投资组合优化
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Jörn Sass
中科院分区：
文献类型：
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作者：
Markus Hahn;Jörn Sass
考虑一个股票市场模型，其中价格满足一个随机微分方程。瞬时收益率被建模为一个连续时间的马尔可夫链，具有多个状态。对于波动率，我们考虑Hobson-Rogers模型及其修正。一方面，这些允许在一个完整的市场中工作，另一方面，他们是很好的动机，因为他们可以解释现实的波动微笑。投资者的目标是在部分信息下最大化终端财富的期望效用，后者意味着投资决策仅基于对股票价格的了解。我们推导出一个明确的表示使用Malliavin演算的最优交易策略和估计模型参数使用马尔可夫链蒙特卡罗方法。我们将理论结果应用于模拟和市场数据。
We consider a stock market model where prices satisfy a stochastic differential equation. The instantaneous rates of return are modeled as a continuous time Markov chain with finitely many states. For the volatility we consider the Hobson-Rogers model and one of its modifications. On one hand these allow to work within a complete market, on the other hand they are well motivated since they can account for realistic volatility smiles. The investor's objective is to maximize the expected utility of the terminal wealth under partial information; the latter meaning that investment decisions are based on the knowledge of the stock prices only. We derive an explicit representation of the optimal trading strategy using Malliavin calculus and estimate the model parameters using Markov chain Monte Carlo methods. We apply the theoretical results to simulated and market data.
DOI：
10.1002/9781118231296.ch8
发表时间：
2018-11
期刊：
Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics
影响因子：
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作者：
Dr. Gergely Záruba
通讯作者：
Dr. Gergely Záruba