Purpose: This paper examines the associative and causal relationship between changes in the implied volatility index (VIX) and stock market returns, with data from 15 countries representing both developed and emerging economies.1 We also examine the dynamic variation, if any in the nature of the...

Recent literature show that leverage has a negative effect on stock returns, which is contradicting with influential finance theories and models. Based on the time-period 1966-2015, the five-factor model and an international dataset, this thesis sets the focus on the question what kind of effect...

Traditional machine learning methods have been widely studied in financial innovation. My study focuses on the application of deep learning methods on asset pricing.I investigate various deep learning methods for asset pricing, especially for risk premia measurement. All models take the same set...

We present a statistic to generally represent extremes in the distribution of temperature anomalies and demonstrate its consequences on financial markets. The diverse shocks that our measure portrays are established to be primary drivers of electricity consumption and the weather futures market....

We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...

We establish the financial materiality of temperature variability by demonstrating its impact on US firms and investors. A long-short strategy that sorts firms based on exposure earns a market-adjusted alpha of 39 basis points per month. This variability metric is related to aggregate decreases...

We demonstrate that a stochastic model consistent with the scaling properties of financial assets is able to replicate the empirical statistical properties of the S&P 500 high frequency data within a window of three hours in each trading day. This result extends previous findings obtained for...