Price discovery in equity markets: A state-dependent analysis of spot and futures markets
提出一种状态依赖的组件份额和信息份额方法，使用马尔可夫转换VECM模型分析现货和期货市场在价格发现中的时变作用，发现交易日内状态概率模式与波动率微笑相似。
This paper investigates the potentially time-varying importance of spot and futures markets in the price discovery process of financial assets. For this purpose, we generalize the concept of component shares and information shares to allow for state-dependent relevance of different markets over time. Instead of using a linear vector error correction model (VECM) to construct the component shares and information shares as it is common in the literature, we employ a Markov-switching VECM with time-varying adjustment behaviour and state-dependent covariance matrices. Simulation results confirm that state-dependent component shares and information shares can be estimated consistently within this framework. We apply our approach to spot and futures prices for different stock indices such as EuroStoxx50, FTSE100, Nikkei225, and SP500. We find a clear state probability pattern over the trading day that closely resembles the well-studied volatility smile and might be related to the presence of heterogeneous agents in those markets.