Derivative instruments have been gaining importance in finance area over the last 30 years as all developed economies have established regulated derivative exchanges. Although the need for derivative markets criticized by many researchers, developing countries offer their own derivative markets...

This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection of...

Recent episodes of financial crises have revived the interest in developing models that are able to timely signal their occurrence. The literature has developed both parametric and non parametric models to predict these crises, the so called Early Warning Systems. Using data related to sovereign...

Market risk can be described as potential losses in portfolio value caused by price changes in the investor's portfolio. Value-at-Risk (VaR) quantifies a loss bound that cannot be exceeded with a specified probability at a given time horizon, i.e., a quantile of the portfolio's loss...

Attraction models are very popular in marketing research for studying the effects of marketing instruments on market shares. However so far the marketing literature only considers attraction models with certain functional forms that exclude threshold or saturation effects on attraction values....

The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical...

We propose an analytically tractable class of models for the dynamics of a limit order book, described as the solution of a stochastic partial differential equation (SPDE) with multiplicative noise. We provide conditions under which the model admits a finite dimensional realization driven by a...

Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all the trades with each counterparty under both market and credit risk. We present a multi-Gaussian process regression approach, which is well suited for OTC derivative portfolio...

The yield curve is one of the fundamental input parameters of pricing theories in capital markets. Information about yields can be observed in a discrete form either directly through traded yield instruments (e.g. Interest Rate SWAP's) or indirectly through prices of bonds (e.g. Government...

The interdependence, dynamics and riskiness of financial institutions are the key features frequently tackled in financial econometrics. We propose a Tail Event driven Network Quantile Regression (TENQR) model which addresses these three aspects. More precisely, our framework captures the risk...