Real-world financial data can be multimodal distributed, and generating multimodal distributed real-world data has become a challenge to existing generative adversarial networks (GANs). For example, neural stochastic differential equations (Neural SDEs), treated as infinite-dimensional GANs, are only capable of generating unimodal time series data. In this talk, we present a novel time series generator, named...
Tuesday, February 6th @ 11:00-12:30 PM, 648 Evans Hall and Zoom
The Inflation Reduction Act of 2022 (IRA) represents the largest climate policy action ever undertaken in the United States. Its legislative path was marked by two abrupt shifts as the likelihood of climate policy action fell to near zero and then rose to near certainty. We investigate equity price reactions to these two events, which represent major realizations of climate policy transition risk. Our results...
Automated Market Makers (AMMs) are a decentralized approach for creating financial markets by allowing investors to invest in liquidity pools of assets against which traders can transact. Liquidity providers are compensated for making the market with fees on transactions. The collected fees, along with the final value of the pooled portfolio, act as a derivative of the underlying assets with price given by the pooled assets....
Tuesday, January 23rd @ 11:00-12:30 PM, 648 Evans Hall and Zoom
Factor risk models are used for three primary purposes: (1) predicting portfolio volatility, (2) portfolio optimization, and (3) decomposing risk and return into factor and idiosyncratic components. In this paper, we propose explicit tests or “horse races” to evaluate and compare the performance of competing risk models along these three basic dimensions. For evaluating the accuracy of volatility forecasts, we apply bias statistics and Q-statistics and stress the central importance of identifying the predicting horizon...