We introduce an ensemble learning method for dynamic portfolio valuation and risk management building on regression trees. We learn the dynamic value process of a derivative portfolio from a finite sample of its cumulative cash flow. The estimator is given in closed form. The method is fast and...

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and nonellipticity. It introduces a so-called...

We introduce a simulation method for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the dynamic value process of a portfolio from a finite sample of its cumulative cash flow. The learned value process is given in closed form thanks to a...

Monetary risk measures classify a financial position by the minimal amount of external capital that must be added to the position to make it acceptable.We propose a new concept: intrinsic risk measures. The definition via external capital is avoided and only internal resources appear. An...

The present article deals with intra-horizon risk in models with jumps. Our general understanding of intra-horizon risk is along the lines of the approach taken in [BRSW04], [Ro08], [BMK09], [BP10], and [LV19]. In particular, we believe that quantifying market risk by strictly relying on...

We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. The model learns the features necessary for an effective low-dimensional representation, overcoming the curse...

In this paper we gauge the degree of interconnectedness and quantify the linkages between global and other systemically important institutions, and the global financial system. We document that the two groups and the financial system become more interconnected during the global financial crisis...

Wealth management constitutes an important aspect of today's banking world, but very little is known about what explains the differences among banks in their ability to attract new assets under management. Using a unique panel database of Swiss private banks, we test the hypothesis that the...

We address the problem of risk sharing among agents using a two-parameter class of quantile-based risk measures, the so-called Range-Value-at-Risk (RVaR), as their preferences. The family of RVaR includes the Value-at-Risk (VaR) and the Expected Shortfall (ES), the two popular and competing...

The forward-looking nature of option market data allows one to derive economically-based and model-free risk measures. This article proposes an extensive analysis of the performances of option-implied VaR and CVaR, and compare them with classical risk measures for the S&P500 Index. Delivering...