scholarly journals The Forecasting Power of the Volatility Index in Emerging Markets: Evidence from the Taiwan Stock Market

2012 ◽  
Vol 4 (2) ◽  
Author(s):  
Ming Jing Yang ◽  
Meng-Yi Liu
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Volatility Index

Response of stock market volatility to COVID-19 announcements and stringency measures: A comparison of developed and emerging markets

2021 ◽  
pp. 102350
Author(s):  
Walid Bakry ◽  
Peter John Kavalmthara ◽  
Vivienne Saverimuttu ◽  
Yiyang Liu ◽  
Sajan Cyril
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Market Volatility ◽  
Stock Market Volatility

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

Agriculture ◽  
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.

Revisiting Macroeconomy–Stock Market Relationship During Times of Economic Crisis: A Study of Emerging Markets

2017 ◽  
Vol 13 (1-2) ◽  
pp. 52-69
Author(s):  
Gagan Deep Sharma ◽  
Mrinalini Srivastava ◽  
Mansi Jain
Keyword(s):  
Latin America ◽  
Financial Crisis ◽  
Stock Market ◽  
Emerging Markets ◽  
Economic Crisis ◽  
Global Financial Crisis ◽  
Market Returns ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
The Relationship

This article examines the relationship between six macroeconomic variables and stock market returns of 13 emerging markets from Latin America, Europe, Africa and Asia in the context of global financial crisis of 2008. The findings reveal some commonality in determination and variation of returns with macroeconomic variables from pre-crisis (1st January 2005–31st March 2009) to post-crisis period (1st April 2009–31st March 2016). Further, results show co-integration among most of the macroeconomic variables depicting significant implications for investors and policymakers.

International Portfolio Diversification Benefits among Developed and Emerging Markets within the Context of the Recent Global Financial Crisis

2014 ◽  
pp. 162-185
Author(s):  
Gülin Vardar ◽  
Berna Aydoğan ◽  
Ece Erdener Acar
Keyword(s):  
Stock Market ◽  
Emerging Markets ◽  
Global Financial Crisis ◽  
Vector Error Correction ◽  
Emerging Stock Markets ◽  
Long Run ◽  
International Investors ◽  
The Uk ◽  
Market Interdependence ◽  
The Impact

This chapter aims to examine the existence of dynamic linkages among the major emerging stock markets, namely Brazil, Hungary, China, Taiwan, Poland, and Turkey, as well as developed markets, particularly the US, the UK, and Germany during the period 2004-2013. Potential dynamic long-run interdependencies are investigated using Johansen and Juselius (1990) multivariate cointegration test and causal relationship through the Vector Error Correction Model (VECM). Moreover, to capture the impact of the recent global crisis on the cointegrating relationship among the developed and emerging markets, the sample period is divided into pre- and post-crisis sub periods. The empirical findings show that, after the crisis period, the direction of the long-run relationship varies, and furthermore, the stock market interdependence increases, supporting herding behavior of investors during the stock market crash period. Therefore, the increasing dynamic co-movements in the period after the crisis provide direct implications for the international investors due to potential limitation in the international risk diversification and the achievement of greater portfolio returns through global investment.

scholarly journals Predicting Stock Price Trend Using MACD Optimized by Historical Volatility

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Jian Wang ◽  
Junseok Kim
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Moving Average ◽  
Rapid Development ◽  
Price Trend ◽  
Technical Indicators ◽  
Volatility Index ◽  
Fixed Weight ◽  
The Stability

With the rapid development of the financial market, many professional traders use technical indicators to analyze the stock market. As one of these technical indicators, moving average convergence divergence (MACD) is widely applied by many investors. MACD is a momentum indicator derived from the exponential moving average (EMA) or exponentially weighted moving average (EWMA), which reacts more significantly to recent price changes than the simple moving average (SMA). Traders find the analysis of 12- and 26-day EMA very useful and insightful for determining buy-and-sell points. The purpose of this study is to develop an effective method for predicting the stock price trend. Typically, the traditional EMA is calculated using a fixed weight; however, in this study, we use a changing weight based on the historical volatility. We denote the historical volatility index as HVIX and the new MACD as MACD-HVIX. We test the stability of MACD-HVIX and compare it with that of MACD. Furthermore, the validity of the MACD-HVIX index is tested by using the trend recognition accuracy. We compare the accuracy between a MACD histogram and a MACD-HVIX histogram and find that the accuracy of using MACD-HVIX histogram is 55.55% higher than that of the MACD histogram when we use the buy-and-sell strategy. When we use the buy-and-hold strategy for 5 and 10 days, the prediction accuracy of MACD-HVIX is 33.33% and 12% higher than that of the traditional MACD strategy, respectively. We found that the new indicator is more stable. Therefore, the improved stock price forecasting model can predict the trend of stock prices and help investors augment their return in the stock market.

Sign in / Sign up

Export Citation Format

Share Document