The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the...

The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the...

The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons. We derive a universal approximation result for the...

This paper introduces a general class of combined neural network-GARCH models suitable to financial time series analysis. We put special emphasis on designing a full model-building cycle for this class of models that includes all stages of econometric modelling (specification, estimation and...

This paper is written with two complementary purposes in mind. The first is to provide estimates of systematic risk for Canadian commodities futures (western barley, canola, flaxseed, feed wheat) using a market portfolio based on a similar weighting scheme suggested by Marcus. The second is to...

We discuss efficiency of the quadratic bridge volatility estimator in comparison with Parkinson, Garman-Klass and Roger-Satchell estimators. It is shown in particular that point and interval estimations of volatility, resting on bridge estimator, are considerably more efficient than analogous...

The complexity of the world oil market has increased dramatically in recent years and new approaches are needed to understand, model, and forecast oil prices today. Many models have been explored and most of the papers and modeling projects referenced in this paper identify their own...

We present a simple rational approximation to the solution of the rough Heston Riccati equation valid in a region of its domain relevant to option valuation. Pricing under rough Heston using this approximation is both fast and very accurate

From an analysis of the time series of volatility using recent high frequency data, Gatheral, Jaisson and Rosenbaum previously showed that log-volatility behaves essentially as a fractional Brownian motion with Hurst exponent H of order 0.1, at any reasonable time scale. The resulting Rough...

We use the Itô Decomposition Formula (see Alòs (2012)) to express certain conditional expectations as exponentials of iterated integrals. As one application, we compute an exact formal expression for the leverage swap for any stochastic volatility model expressed in forward variance form. As...