Regime Switching in High-Tech ETFs: Idiosyncratic Volatility and Return

Laura Arenas,Ana Maria Gil-Lafuente

doi:10.3390/math9070742

Abstract

The volatility of asset returns can be classified into market and firm-specific volatility, otherwise known as idiosyncratic volatility. Idiosyncratic volatility is increasing over time with some literature attributing this to the IT revolution. An understanding of the relationship between idiosyncratic risk and return is indeed relevant for idiosyncratic risk pricing and asset allocation, in a context of emerging technologies. The case of high-tech exchange traded funds (ETFs) is especially interesting, since ETFs introduce new noise to the market due to arbitrage activities and high frequency trading. This article examines the relevance of idiosyncratic risk in explaining the return of nine high-tech ETFs. The Markov regime-switching (MRS) methodology for heteroscedastic regimes has been applied. We found that high-tech ETF returns are negatively related to idiosyncratic risk during the high volatility regime and positively related to idiosyncratic risk during the low volatility regime. These results suggest that idiosyncratic volatility matters in high-tech ETF pricing, and that the effects are driven by volatility regimes, leading to changes across them.

Highlights

The results indicate that the heteroscedastic Markov regime-switching (MRS) models for the nine highRegarding the expected duration of regimes, the average for the high volatility regime tech exchange traded funds (ETFs) identify and distinguish between several sources of volatility clustering, where is four days and for the low volatility regime is five days, which is aligned with the behavior regime persistence implies that if the unconditional variance is high in one regime, of the high-tech sector subject to short-term noise across stock markets
We investigate the relationship between idiosyncratic risk and return among nine high-tech
We investigate the relationship between idiosyncratic risk and return among nine high-tech ETFs using daily return data for the 12/01/2017–1/31/2020 period using idiosyncratic volatility as a proxy for idiosyncratic risk

Summary

Introduction

The role of idiosyncratic volatility in asset pricing has not received much attention since, under the Capital Asset Pricing Model (CAPM), it is only the non-diversifiable systematic risk that matters [1,2,3]. According to modern portfolio theory, idiosyncratic risk can be completely diversified away. Several studies [4,5,6] have observed that portfolios of common stocks with higher idiosyncratic volatility record higher average returns. There is a positive relationship between idiosyncratic risk and their returns, providing empirical support for Merton’s [7] argument that in a world of incomplete information, under-diversified investors are compensated for not holding diversified portfolios. The existing literature is not clear about the relationship between idiosyncratic risk and return

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