This paper presents a quantifying measure for heteroskedasticity of a time series. In this research, heteroskedasticity levels are measured by decomposing the examined time series recursively into ...

Discover how heteroskedasticity affects regression analysis and why it matters for accurate data interpretation in analytics.

In statistics, heteroskedasticity happens when the standard deviations of a variable, monitored over a specific amount of time, are nonconstant.

Since the advent of heteroskedasticity-robust standard errors, several papers have proposed adjustments to the original White formulation. We replicate earlier findings that each of these adjusted ...

While most financial models assume constant volatility over time, anyone who has ever traded the markets knows that volatility is dynamic from one moment to the next - a phenomenon known as ...

Clearly in the financial markets, there are many different ways to trade and build your portfolio. Some traders like to play direction, some like to trade time, some like stocks and some like ...

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We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the ...