We introduce a novel method to identify information networks in stock markets, which explicitly accounts for the impact of public information on investor trading decisions. We show that public information has a clear effect on the empirical investor networks' topology. Most importantly, our...

According to information theory, central agents are better informed. Thus to gain higher returns, investors are motivated to seek connections. At the same time, previous studies provide evidence on homophily in social networks: individuals tend to establish relationships with the alike to...

The bias between the expected realised variance under the historical measure and the risk neutral probability introduces the concept of the risk premium. How does the market variance risk premium vary over time or look like in the future? Our work introduced a probabilistic modeling of the...

This paper proposes a new method for predicting jump arrivals in stock markets with high-frequency limit order book data. We introduce a new model architecture, based on Convolutional Long Short-Term Memory with attention, to apply time series representation learning with memory and to focus the...

The geometric Brownian motion is routinely used as a dynamic model of underlying project value in real option analysis, perhaps for reasons of analytic tractability. By characterizing a stochastic state variable of future cash flows, this paper considers how transformations between a state...