Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever

Financial word of the day: Heteroscedasticity describes a situation where risk (variance) changes with the level of a ...
JSTOR Daily

Hybrid quantile regression estimation for time series models with conditional heteroscedasticity

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 80, No. 5 (2018), pp. 975-993 (19 pages) Estimating conditional quantiles of financial time series is essential for ...
JSTOR Daily

A Nonparametric Test of Conditional Autoregressive Heteroscedasticity for Threshold Autoregressive Models

The Canadian Journal of Statistics / La Revue Canadienne de Statistique Threshold autoregressive models are widely used in time-series applications. When building or using such a model, it is ...
Investopedia

Autoregressive Conditional Heteroskedasticity (ARCH) Explained

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...
Risk

Modeling conditional correlations for risk diversification in crude oil markets

This paper estimates univariate and multivariate conditional volatility and conditional correlation models of spot, forward and futures returns from three major benchmarks of the international crude ...
Risk.net

Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...
Simon Fraser University

Testing for Heteroscedasticity

One of the key assumptions of the ordinary regression model is that the errors have the same variance throughout the sample. This is also called the homoscedasticity ...