We propose a novel method to estimate risk-neutral quantiles that uses sorting to minimize an objective function given by a convex combination of call and put option prices over the range of available strike prices. We demonstrate that this new method significantly improves the accuracy of...

This paper analyzes the stability and distribution of ambiguity attitudes using a broad population sample. Using high-powered incentives, we collected six waves of data on ambiguity attitudes about financial markets – our main application – and climate change. Estimating a structural...

The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called...

This paper focuses on the successive partition method applied to a binomial coefficient in combinatorial geometric series. The coefficient for each term in combinatorial geometric series refers to a binomial coefficient. These ideas can enable the scientific researchers to solve the real life...

We propose a new 3-step resampling approach to forecast portfolio tail risk conditional on the economic state. The approach first predicts economic states using a set of macroeconomic and financial variables. We then forecast the joint distribution of multiple assets in the portfolio according...

This paper proposes a new and robust methodology to obtain conditional density forecasts, based on information not contained in an initial econometric model. The methodology allows to condition on expected marginal densities for a selection of variables in the model, rather than just on future...

This study proposes a novel expectile regression complete subset averaging (ECSA) method to forecast the downside risk for asset returns. Given a high-dimensional set of covariates, we combine the forecasts from a complete subset of expectile regression models that use a fixed number of...

We propose a multi-asset pricing model which allows both the calibration to single-asset vanilla options, and the specification of any joint terminal distribution at each step of a discrete time grid. We also propose a way to calibrate that joint terminal distributions via normal mean-variance...

This thesis deals with the mathematical models used to forecast future asset prices. Estimating asset prices is arguably one of the most relevant problems for risk managers, central bankers, and investors. Traditional statistical methods rely on point estimates or confidence intervals to...

This thesis deals with the mathematical models used to forecast future asset prices. Estimating asset prices is arguably one of the most relevant problems for risk managers, central bankers, and investors. Traditional statistical methods rely on point estimates or confidence intervals to...