We propose a novel time-changed L évy LIBOR market model for the joint pricing of caps and swaptions. The time changes are split into three components. The first component allows us to match the volatility term structure, the second generates stochastic volatility, and the third one...

We identify frictions in the market for liquidity as well as bank-specific and market-wide factors that affect the prices that banks pay for liquidity, captured here by borrowing rates in repos with the central bank and benchmarked by the overnight index swap. We have price data at the...

We identify local and global factors across international bond markets that are poorly spanned by the traditional level, slope and curvature factors but have strong forecasting power for future bond excess returns. Local and global factors are jointly significant predictors of bond returns,...

The search for a market design that ensures stable bank funding is at the top of regulators' policy agenda. This paper empirically shows that the central counterparty (CCP)-based euro interbank repo market features this stability. Using a unique and comprehensive data set, we show that the...

We document an inverse relation between stock-bond correlations and correlations of growth and inflation. We find that rising inflation uncertainty lowers stock prices but can either lower or raise nominal bond prices depending on whether inflation is counter- or procyclical. We show that the...

We incorporate a latent stochastic volatility factor and macroeconomic expectations in an affine model for the term structure of nominal and real rates. We estimate the model over 1999-2016 on U.S. data for nominal and TIPS yields, the realized and implied volatility of T-bonds and survey...

We show that the difference between the natural rate of interest and the current level of monetary policy stance, which we label Convergence Gap (CG), contains information that is valuable for bond predictability. Adding CG in forecasting regressions of bond excess returns significantly raises...

We provide a new method to derive the state price density per unit probability based on option prices and GARCH model. We derive the risk neutral distribution using the result in Breeden and Litzenberger (1978) and the historical density adapting the GARCH model of Barone-Adesi, Engle, and...

We develop a discrete-time stochastic volatility option pricing model, which exploits the information contained in high-frequency data. The Realized Volatility (RV) is used as a proxy of the unobservable log-returns volatility. We model its dynamics by a simple but effective (pseudo) long memory...

We model the dynamics of asset prices and associated derivatives by consideration of the dynamics of the conditional probability density process for the value of an asset at some specified time in the future. In the case where the asset is driven by Brownian motion, an associated "master...