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Spillover Effect on the Stock Market and Bond Prices in Relation with GARCH
Abstract
This study examines the spillover effect between bond and stock markets in the U.S. using GARCH. The finding of a unidirectional spillover flow from bonds to stocks in the U.S. is discussed in the light of new marketplace variables that have been introduced into the markets in the previous decade. These variables include the rise of HFT, algorithm-driven trading, and central banking interventionism via unconventional monetary policy. The effect on forecasting volatility, price and return of asset classes, studied through the lens of other commodity price movement and volatility—such as oil and gold markets—creates a compelling picture for why GARCH models may need to be reworked to incorporate new data regarding the new ways in which the 21st century marketplace is using technology and central bank interventionism to shape market movements and market outcomes.
Table of Contents
1 Introduction 4
1.1 Why this research is important 4
1.2 What this paper examines 6
1.3 The most important findings and contributions this study makes to existing literature 7
2 Literature Review 11
3 Hypothesis Development 19
3.1 Spillover as a Result of Unconventional Monetary Policy 19
3.2 Low-Vol Complacency 20
3.3 Spillover is Unidirectional 21
3.4 Algorithm-Driven Trading and Market Movement 22
4 Data and Methodology 23
5 Findings 27
6 Analysis 37
7 Conclusion 47
References 49
1 Introduction
Globalization has substantially altered the working dynamics of markets of both developed and emerging nations. Sakthivel, Bodke and Kamaiah (2012) note that as a result of globalization, the spillover effect has become far more commonplace than what once used to be the case, for “world financial markets and economics are increasingly integrated due to free flow capital and international trade” (p. 253). This phenomenon has been seen most recently in the spillover effect of the 2008 housing bubble crisis in the U.S., which was quickly felt across sectors both domestically and internationally and served as an indication of the interconnectedness of modern markets and economies in the 21st century. Understanding spillover among equities and bonds along with other commodities, such as oil and gold, can play a significant role in how to forecast volatility and better manage funds, such as those responsible for guaranteeing pensions for workers in the not-too-distant future.
1.1 Why this research is important
Research in the spillover effect between the stock and bond markets is important because each represents one of the major asset classes for investors. According to Dean et al. (2010), there a number of theories which may explain the relationship between equities and bonds—the asset substitution hypothesis, the financial contagion hypothesis, the news specificity hypothesis, the news decomposition hypothesis, and the asymmetric price adjustment hypothesis. In short, the two asset classes are more or less seen as two sides of a negatively correlating coin. However, with the introduction of QE (quantitative easing) in the U.S., the relationship has seemingly altered, especially with respect to volatility, as a rebalancing towards both US and non-US assets was triggered with QE1 through 3 (Fratzscher, Lo Duca, Straub, 2016). The CBOE Volatility Index US:VIX on a two-year chart shows an ever-dwindling sense of volatility or risk in the market.
Figure 1. Two-year chart for VIX.
Source: CBOE Volatility Index (2017)
Park and Um (2016) likewise highlight the spillover effect of unconventional monetary policy in the US on bond markets and note that a mere mention of “news” of unconventional monetary policy in the US is enough to trigger a short-term spillover in the bond market in Korea. Short-term hedges in gold during such swings have been found by Baur and Lucey (2010) to be effective in protecting a portfolio from headline-driven spillover between equities and bond markets. But for forecasting the spillover effects, today’s GARCH models may need to take into consideration a rapidly changing market culture—namely, one that is driven by algorithms which have been blamed both for flash crashes and for melt-ups in recent years, along with the “existence of pure contagion” (Jayech, 2016, p. 631; Kirilenko, Kyle, Samadi and Tuzun, 2017). The velocity of volatility, the absence of liquidity (save for that provided by central banks), counter party risk, sovereign debt, risk parity, and overall fundamentals (AMZN is trading currently at...
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