This paper provides a review of some recent theoretical results for time series models with
GARCH errors, and is directed towards practitioners. Starting with the simple ARCH model …

Amongmanyexcitingdevelopmentsinstatistic…, nonlineartimeseriesanddata-
analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths. In …

The success of the Multi-Layer Perceptron Neural Network (MLP) relies on carefully
configuring its weights and biases to promising values. The gradient descent technique is …

Ksi ka czy og ln wiedz o rynkach papier w warto ciowych z nowoczesnym wyk adem
matematyki finansowej, kt ry obejmuje modele i metody dotycz ce wyceny instrument w …

Tong's threshold models have been found useful in modelling nonlinearities in the
conditional mean of a time series. The threshold model is extended to the so‐called double …

This paper proposes a threshold heteroscedastic model which integrates threshold
nonlinearity and GARCH-type conditional variance for modeling mean and volatility …

The usefulness of the investor sentiment measure in the stock market has received
increasing attention in recent years. Various measures of investor sentiment have been …

This article introduces a new model to capture simultaneously the mean and variance
asymmetries in time series. Threshold non‐linearity is incorporated into the mean and …

In this paper we introduce the STAR-STGARCH model that can characterize nonlinear
behaviour both in the conditional mean and the conditional variance. A modelling cycle for …

This study investigates the behavior of international capital flows by considering northbound
capital flows into China's A-share market—a market where northbound capital is widely …