1. Dynamic Responses of Major Asian Emerging Equity Markets to the U.S. Crude
Oil Fear Index
Bahram Adrangi
W.E. Nelson Professor of Financial Economics
University of Portland
5000 N. Willamette Blvd. Portland, Oregon 97203
adrangi@up.edu
Arjun Chatrath
Schulte Professor of Finance
University of Portland
5000 N. Willamette Blvd.
Portland, Oregon 97203 chatrath@up.edu
Kambiz Raffiee
Foundation Professor of Economics
College of Business University of Nevada, Reno
Reno, Nevada 89557
raffiee@unr.edu
January 2020
2. I. Introduction
This paper examines the response of four major emerging market equity markets to
Chicago board of Exchange (CBOE) Crude Oil ETF Volatility Index ("Oil VIX" or
OVX). OVX , or Oil VIX, functions similar to the stock version, VIX. OVX measures
the market's expectation of 30-day implied volatility of crude oil prices by applying
the VIX methodology to United States Oil Fund, LP (Ticker: USO) options covering a
wide range of strike prices.
3. II. Motivation
The higher values of OVX is usually associated with rising crude oil
prices. For instance, upward movements of OVX may be positive for
bond markets, currency values in exporting economies and negative for
the equity prices in most economies. Thus, tracking the movements of
OVX may offer hedging strategies for investors as well as corporations.
4. III. Objective of the Research
This study examines the reactions of four major emerging equity
indices of Hong Kong, Korea, Shanghai, and Taiwan to OVX. The
objective is to determine whether investors in these markets are
sensitive to movements in OVX. While China is the fourth largest
crude oil producer in the world, the remaining three indices represent
equity indies of economies that are dependent of imported crude oil.
5. IV. Data
The daily data for the study for the period covers 9/18/2014 through
9/27/2019. The daily index values of Hang Seng Index for Hong Kong
(HK), Korea Composite Index (KO), Shanghai Stock Exchange Index
(SH), and Taiwan Stock Exchange Index (TW) and OVX are taken from
the Bloomberg data base. These indices represent the main national
stock exchanges of the markets under study.
6. V. Methodology
Structural Vector Autoregressive Formulation
(1)
Where A is a n x n square matrix, in our case 5X5 because we have
five endogenous variables.
ut = ( ut
OVX, ut
HS ,ut
KO ,ut
SH, ut
TW)’,
,
7.
8. Subperiod 2, 1-1-2016 through 12/28/2017 is marked by several
significant events.
1. Trans-Pacific Partnership (TPP) unravels
2. North Korea Missile tests
3. Brexit Vote in Britain
Subperiod 3, covers from January through November 2018.
The most significant economic event: Trump,s trade war
Switch to Word Tables
9. Summary And Conclusions
Equity markets of Asia respond to OVX shocks
Subperiod 2 and 3 show that perhaps the state of global geopolitics
influences market responses to OVX in the markets of Asia
Subperiods 2 and 3 show that the news of events that directly affected
the region, increased the sensitivity of markets in the region to OVX
shocks.
