We investigate the role of speculation in the European natural gas market over the period 2020- 2024, a period marked by extreme price volatility driven by the energy crisis following Russia's invasion of Ukraine. Replicating the framework of Knittel and Pindyck (2016), we disentangle the...

This paper examines the pricing effect of cross-sectional patterns in the cryptocurrency market, aiming to enhance the composition of asset pricing factors for a better explanation of cross-sectional variability in cryptocurrency returns.The study utilizes data from 1,160 cryptocurrencies...

This paper aims to deliver a comprehensive analysis of the theories and concepts that have formed the foundational link between two separate academic fields: finance and economics, resulting in the emergent field of financial economics. The main schools of thought can be divided, with a...

Machine learning applications in finance commonly employ feature decorrelation techniques developed for generic statistical problems. We investigate whether this practice appropriately addresses the unique characteristics of financial data, where correlations often encode fundamental economic...

Comparing the Efficient Market Hypothesis and Behavioral Finance, the Adaptive Markets Hypothesis (AMH), which identifies the extremes of these two hypotheses and adapts them to each other, argues that calendar anomalies can coexist, but also focuses on how investor behavior reacts to changing...

Can environmentally-minded investors impact the cost of capital of green firms even when they invest through financial intermediaries? To answer this and related questions, I build an equilibrium intermediary asset pricing model with three investors, two risky assets, and a riskless bond....

Financial bubbles and crashes have repeatedly caused economic turmoil notably but not only during the 2008 financial crisis. However, both in the popular press as well as scientific publications, the meaning of bubble is sometimes unspecified. Due to the multitude of bubble definitions, we...

Can rising asset prices reduce wealth inequality? This paper builds a continuous-time heterogeneous-agent general equilibrium in which entrepreneurs hold risky private capital and traditional savers hold safe assets. Safe-asset expansions-via financial innovation, public debt, or a stable equity...

The Korean equity market is characterized by extreme concentration, with the top five stocks accounting for approximately 25-45 percent of total market capitalization. This study examines whether such concentration structurally distorts the Fama and French (1993) three-factor model (FF3) and...

The Korean equity market is characterized by extreme concentration, with the top five stocks accounting for approximately 25-45 percent of total market capitalization. This study examines whether such concentration structurally distorts the Fama and French (1993) three-factor model (FF3) and...

The objective of this study was to examine the level and behaviour of the weak-form efficiency of the 16 most capitalised cryptocurrencies using intraday data. The study employed martingale difference hypothesis tests utilising the rolling window method. The predictability of high frequency...

This paper identifies active addresses-to-network value as an additional common risk factor in the returns on cryptoassets. Investigating 652 cryptoassets, I find anomalous returns that increase with active addresses-to-network value ratio, a proxy for the value anomaly. Cryptoassets with a high...

This novel work is the first study in India to incorporate the Human capital (HC) factor as a six-factor asset-pricing model and presents a robust methodology. The aim of this work is to examine the ability of the six-factor model to capture excess returns using a GMM framework with time periods...

Cross-predictability denotes the fact that some assets can predict other assets' returns. I propose a novel performance-based measure that disentangles the economic value of cross-predictability into two components: the predictive power of one asset's signal for other assets' returns...

We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory...