In this paper, we forecast Bitcoin's returns and return jumps using a self-exciting process embedded in a stochastic volatility model. We show the existence of the jump clustering feature, which varies depending on the frequency of the data. In an out-of-sample setting, we use a particle filter...

This paper proposes an aggregate index of macro tail risk and examines its role in asset pricing. We observe that a positive market risk premium compensated for the downside risk of macro fundamentals; a high tail risk predicts subsequent high returns. This predictability exists both in- and...

Using a novel data set based on individual resumes of public firm employees, we propose a monthly index of aggregate labor flow that measures the dynamics of firm employment. We find that the index can predict the economic outputs significantly: an increase in the index leads to greater...

We examine the clustering behaviour of price and variance jumps using high-frequency data, modelled as a marked Hawkes process embedded in a bivariate jump-diffusion model. After de-periodisation of the intraday data, we find that the jumps of both individual stocks and a broad index exhibit...

This study develops a theoretical framework that differentiates the shares of electricity generation between two types of renewables, solar and wind, and evaluates the impacts of technology-neutral and technology-specific renewable energy policies on state-level solar and wind deployments. Our...

Capacity adjustment and dynamic pricing are long-term and short-term decisions respectively to match supply with demand. In an environment where the demand is unknown to the firm, it is worth investigating how to integrate the two decisions such that the firm can learn about the demand on the...