We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model …

network without compromising prediction accuracy. We evaluate its performance by predicting the daily volatility and closing …

use of counterparty risk mitigation techniques including the use of market compression. In this process groups of market … compression is a serious alternative counterparty risk mitigation technique to the use of CCPs that should be encouraged by …

as decreasing absolute risk aversion (DARA) stochastic dominance (DSD). For comparison with DSD we also consider …

shifts and stochastic volatility. The filter adapts to regime shifts extremely rapidly and delivers a clear heuristic for … distinguishing between regime shifts and stochastic volatility, even though the model dynamics assumed by the filter exhibit neither …

rate and risk premiums using recursive utility in a continuous-time model. We use the stochastic maximum principle to …

We propose a simple risk-adjusted linear approximation to solve a large class of dynamic models with time-varying and … non-Gaussian risk. Our approach generalizes lognormal affine approximations commonly used in the macro-finance literature … risk-adjusted linearizations. We provide a formal foundation for approximation methods that remained so far heuristic, and …