In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to monetary policy shocks. Although the increase in the...

In a production economy with trade in financial markets motivated by the desire to share labor-income risk and to speculate, we show that speculation increases volatility of asset returns and investment growth, increases the equity risk premium, and reduces welfare. Regulatory measures, such as...

We present a simple model that quantitatively replicates the behavior of stock prices and business cycles in the United States. The business cycle model is standard, except that it features extrapolative belief formation in the stock market, in line with the available survey evidence....

COVID-19 has quickly emerged as a novel risk, generating feverish behavior among investors, and posing unprecedented challenges for policymakers. The empirical analysis provides evidence for a significant negative effect on stock markets of COVID-19-related measures announced in the Euro Area...

The objective of this paper is to analyze what are the main determinants of the exchange rate risk premium (ERP). The empirical case is conducted for the daily Mexican peso-USD exchange rate for a sample period from 2007 until 2015. According to the results the ERP is influenced by several...

This paper shows that changes in market participants' fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and...

There are competing arguments about the likely effects of Sovereign Bond-Backed Securitisation on the liquidity of sovereign bond markets. By analysing hedging and diversification opportunities, this paper shows that positive liquidity spillovers would dominate or at least constrain the extent...

This paper analyzes the performance of temporal fusion transformers in forecasting realized volatilities of stocks listed in the S&P 500 in volatile periods by comparing the predictions with those of state-of-the-art machine learning methods as well as GARCH models. The models are trained on...

Information on the allocation and pricing of over-the-counter (OTC) markets is scarce. Furfine (1999) pioneered an algorithm that provides transaction-level data on the OTC interbank lending market. The veracity of the data identified, however, is not well established. Using permutation methods,...