This study examines the role of volatility mean reversion in option pricing and evaluates the performance of commonly used volatility estimators within a broad market context. Using a comprehensive dataset of end-of-day option chains for the 100 most actively traded U.S. equities from 2018 to...

Extreme movements in financial time series pose challenges for risk management and forecasting, particularly when their timing is irregular and difficult to anticipate. This study aims to develop a probabilistic framework for detecting and predicting such events using daily Bitcoin returns as a...

This paper examines long-run linkages and possible instabilities in the gold–silver price relationship using daily futures prices over the period from 4 January 2010 to 28 November 2025. The empirical analysis includes unit-root and cointegration tests as well as endogenous structural break...

We use small-area estimation methods that combine information from a household budget survey, a much larger survey of local demographics and employment, and area-level information on bank account outflows and energy consumption to estimate average equivalised consumption measures across 367...

Total factor productivity (TFP) is crucial for evaluating technological innovation, yet its accurate measurement remains challenging due to diverse methodologies. Notably, the selection of proxy variables in control function approach (CFA) significantly influences TFP estimation, yet existing...

This paper presents a novel method for estimating treatment effects in cases where prior knowledge of the exogeneity of the treatment variable is limited. We employ a machine learning technique, double selection via Lasso, to identify a robust set of control variables without requiring prior...