We investigate long-run stock-bond correlation using a model that combines the dynamic conditional correlation model with the mixed-data sampling approach and allows long-run correlation to be affected by macro-finance factors (historical and forecasts). We use macro-finance factors related to...

We propose a new approach to the definition of stress scenarios for volatilities and correlations. Correlations and volatilities depend on a common market factor, which is the key to stressing them in a consistent and intuitive way. Our approach is based on a new asset price model where...

We propose a new approach to the definition of stress scenarios for volatilities and correlations. Correlations and volatilities depend on a common market factor, which is the key to stressing them in a consistent and intuitive way. Our approach is based on a new asset price model where...

The influence of past stock price movements on volatilities and correlations is essential for understanding diversification and contagion in financial markets. We develop a model that makes the influence of past returns on volatilities and correlations explicit. Employing information about...

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with exogenous predictors. Unlike existing Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms, our approach is not based on a structural form representation of the...

Using filtering techniques, spectral analysis, and Markov chain models, I document trends and cycles of factors have significantly changed over the period to December 2000 compared to the period post-January 2001. The recent weaker performance of value in the 21st century, including the value...

This paper examines the trading performances of several technical oscillators created using crypto assets pricing methods for short-term bitcoin trading. Seven pricing models proposed in the professional and academic literature were transformed into oscillators, and two thresholds were...

This study investigated how stock market volatility responded dynamically to unexpected changes during the COVID-19 pandemic and the resulting uncertainty in Thailand. Using a multivariate GARCH-BEKK model, the conditional volatility dynamics, the interlinkages, and the conditional correlations...

This study proposes a wavelets approach to estimating time-frequency-varying betas in the capital asset pricing model (CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk-profile robustness. Furthermore, we emphasize the effect of an...