We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor mimicking portfolios to build climate risk hedge portfolios. The new mimicking...

Insurance companies can be exposed to climate-related physical risk through their operations and to transition risk through their $12 trillion of financial asset holdings. We assess the climate risk exposure of property and casualty (P&C) and life insurance companies in the U.S. We construct a...

We explore the design of climate stress tests to assess and manage macro-prudential risks from climate change in the financial sector. We review the climate stress scenarios currently employed by regulators, highlighting the need to (i) consider many transition risks as dynamic policy choices;...

We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor mimicking portfolios to build climate risk hedge portfolios. The new mimicking...

The systemic risk measure (SRISK) by V-Lab provides a market view of the vulnerability of financial institutions to a sudden downturn in the economy. To overcome the shortcoming that it cannot be applied to non-listed banks, SRISK characteristics of listed banks are mapped on balance sheet...

This paper investigates the significance of dynamic conditional beta in predicting the cross-sectional variation in expected stock returns. The results indicate that the time-varying conditional beta is alive and well in the cross-section of daily stock returns. Portfolio-level analyses and...

We introduce SRISK to measure the systemic risk contribution of a financial firm. SRISK measures the capital shortfall of a firm conditional on a severe market decline, and is a function of its size, leverage and risk. We use the measure to study top US financial institutions in the recent...

Second moments of asset returns are important for risk management and portfolio selection. The problem of estimating second moments can be approached from two angles: time series and the cross-section. In time series, the key is to account for conditional heteroskedasticity; a favored model is...

We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past...

Modeling and forecasting dynamic (or time-varying) covariance matrices has many important applications in finance, such as Markowitz portfolio selection. A popular tool to this end are multivariate GARCH models. Historically, such models did not perform well in large dimensions due to the...