论文标题
最佳消费二元性 - 替代数据的投资问题
Duality in optimal consumption--investment problems with alternative data
论文作者
论文摘要
这项研究调查了一种最佳消费 - 投资问题，其中未观察到的股票趋势受到代表不同经济制度的隐藏的马尔可夫链的调节。在经典方法中，隐藏的状态是从历史资产价格中估算出来的，但是技术的最新进步使投资者能够在决策中考虑替代数据。其中包括社交媒体评论，专家意见，COVID-19-19大流行数据和GPS数据，这些数据源于市场数据的标准来源，但被认为可用于预测股票趋势。我们为这个问题开发了一种新颖的二元理论，并考虑了替代数据系列的跳跃扩散过程。该理论可以通过向滤波器方程提供条件，以允许根据动态编程原理使用控制方法来确定“有用”''有用的'''''''''替代数据，以进行动态决策。一旦从替代数据产生的信号分布满足有界的似然比条件后，我们证明了用于证明恒定相对风险避免风险剂的唯一平滑解决方案的应用。在这样做的过程中，我们获得了一种明确的消费 - 投资策略，该策略利用文献中未解决的不同类型的替代数据。
This study investigates an optimal consumption--investment problem in which the unobserved stock trend is modulated by a hidden Markov chain that represents different economic regimes. In the classical approach, the hidden state is estimated from historical asset prices, but recent advancements in technology enable investors to consider alternative data in their decision-making. These include social media commentary, expert opinions, COVID-19 pandemic data, and GPS data, which originate outside of the standard sources of market data but are considered useful for predicting stock trends. We develop a novel duality theory for this problem and consider a jump-diffusion process for the alternative data series. This theory helps investors in identifying ``useful'' alternative data for dynamic decision-making by offering conditions to the filter equation that permit the use of a control approach based on the dynamic programming principle. We demonstrate an application for proving a unique smooth solution for a constant relative risk-averse agent once the distributions of the signals generated from alternative data satisfy a bounded likelihood ratio condition. In doing so, we obtain an explicit consumption--investment strategy that takes advantage of different types of alternative data that have not been addressed in the literature.
