Testing and Dating Structural Breaks in Generalized Linear Multivariate Models for Stock Market Contagion

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

Download Full-text

Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Agriculture ◽

10.3390/agriculture11020093 ◽

2021 ◽

Vol 11 (2) ◽

pp. 93

Author(s):

Pavel Kotyza ◽

Katarzyna Czech ◽

Michał Wielechowski ◽

Luboš Smutka ◽

Petr Procházka

Keyword(s):

Financial Crisis ◽

Stock Market ◽

Financial Market ◽

Structural Breaks ◽

Structural Changes ◽

Global Financial Crisis ◽

Market Uncertainty ◽

Volatility Index ◽

The Global Financial Crisis ◽

The Relationship

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

Download Full-text

Testing for Stock Market Contagion: A Quantile Regression Approach

SSRN Electronic Journal ◽

10.2139/ssrn.2585468 ◽

2015 ◽

Cited By ~ 1

Author(s):

Sungyong Park ◽

Wendun Wang ◽

Naijing Huang

Keyword(s):

Stock Market ◽

Quantile Regression ◽

Regression Approach ◽

Market Contagion

Download Full-text

The 2008 financial crisis: Stock market contagion and its determinants

Research in International Business and Finance ◽

10.1016/j.ribaf.2014.09.007 ◽

2015 ◽

Vol 33 ◽

pp. 178-203 ◽

Cited By ~ 54

Author(s):

Kimberly F. Luchtenberg ◽

Quang Viet Vu

Keyword(s):

Financial Crisis ◽

Stock Market ◽

2008 Financial Crisis ◽

Market Contagion ◽

The 2008 Financial Crisis

Download Full-text

The Finance Growth Link: Comparative Analysis Of Two Eastern African Countries

Comparative Economic Research ◽

10.1515/cer-2016-0025 ◽

2016 ◽

Vol 19 (3) ◽

pp. 147-167 ◽

Cited By ~ 1

Author(s):

Ashenafi Beyene Fanta ◽

Daniel Makina

Keyword(s):

Economic Growth ◽

Stock Market ◽

Financial Development ◽

Low Income ◽

Structural Breaks ◽

Response Analysis ◽

African Countries ◽

Vector Autoregressive ◽

Stock Market Development ◽

Sub Saharan

This paper examines the finance growth link of two low-income Sub-Saharan African economies – Ethiopia and Kenya – which have different financial systems but are located in the same region. Unlike previous studies, we account for the role of non-bank financial intermediaries and formally model the effect of structural breaks caused by policy and market-induced economic events. We used the Vector Autoregressive model (VAR), conducted impulse response analysis and examined variance decomposition. We find that neither the level of financial intermediary development nor the level of stock market development explains economic growth in Kenya. For Ethiopia, which has no stock market, intermediary development is found to be driven by economic growth. Three important inferences can be made from these findings. First, the often reported positive link between finance and growth might be caused by the aggregation of countries at different stages of economic growth and financial development. Second, country-specific economic situations and episodes are important in studying the relationship between financial development and economic growth. Third, there is the possibility that the econometric model employed to test the finance growth link plays a role in the empirical result, as we note that prior studies did not introduce control variables.

Download Full-text

International stock market contagion: A CEEMDAN wavelet analysis

Economic Modelling ◽

10.1016/j.econmod.2018.02.010 ◽

2018 ◽

Vol 72 ◽

pp. 333-352 ◽

Cited By ~ 8

Author(s):

Zhongbao Zhou ◽

Ling Lin ◽

Shuxian Li

Keyword(s):

Stock Market ◽

Wavelet Analysis ◽

Market Contagion

Download Full-text

Stock market liberalization, structural breaks and dynamic changes in emerging market volatility

Review of Accounting and Finance ◽

10.1108/14757700810920784 ◽

2008 ◽

Vol 7 (4) ◽

pp. 396-411 ◽

Cited By ~ 9

Author(s):

Duc Khuong Nguyen ◽

Mondher Bellalah

Keyword(s):

Stock Market ◽

Structural Breaks ◽

Emerging Market ◽

Market Volatility ◽

Market Liberalization ◽

Dynamic Changes ◽

Stock Market Liberalization

Download Full-text

Stock prices' long memory in China and the United States

International Journal of Emerging Markets ◽

10.1108/ijoem-11-2019-0921 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Zhengxun Tan ◽

Yao Fu ◽

Hong Cheng ◽

Juan Liu

Keyword(s):

Stock Market ◽

Stock Prices ◽

Long Memory ◽

Stock Markets ◽

Information Disclosure ◽

Structural Breaks ◽

Efficient Market Hypothesis ◽

The United States ◽

Chinese Stock Market ◽

Content Type

PurposeThis study aims to examine the long memory as well as the effect of structural breaks in the US and the Chinese stock markets. More importantly, it further explores possible causes of the differences in long memory between these two stock markets.Design/methodology/approachThe authors employ various methods to estimate the memory parameters, including the modified R/S, averaged periodogram, Lagrange multiplier, local Whittle and exact local Whittle estimations.FindingsChina's two stock markets exhibit long memory, whereas the two US markets do not. Furthermore, long memory is robust in Chinese markets even when we test break-adjusted data. The Chinese stock market does not meet the efficient market hypothesis (EMHs), including the efficiency of information disclosure, regulations and supervision, investors' behavior, and trading mechanisms. Therefore, its stock prices' sluggish response to information leads to momentum effects and long memory.Originality/valueThe authors elaborately illustrate how long memory develops by analyzing not only stock market indices but also typical individual stocks in both the emerging China and the developed US, which diversifies the EMH with wider international stylized facts and findings when compared with previous literature. A couple of tests conducted to analyze structural break effects and spurious long memory demonstrate the reliability of the results. The authors’ findings have significant implications for investors and policymakers worldwide.

Download Full-text