scholarly journals The long memory HEAVY process: modeling and forecasting financial volatility

2020 ◽  
Author(s):  
M. Karanasos ◽  
S. Yfanti ◽  
A. Christopoulos
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Fractional Integration ◽  
Capital Budgeting ◽  
Regression Equations ◽  
Forecasting Accuracy ◽  
Modeling And Forecasting ◽  
The Global Financial Crisis ◽  
Heavy System

AbstractThis paper studies the bivariate HEAVY system of volatility regression equations and its various extensions that are directly applicable to the day-to-day business treasury operations of trading in foreign exchange and commodities, investing in bond and stock markets, hedging out market risk, and capital budgeting. We enrich the HEAVY framework with powers, asymmetries, and long memory that improve its forecasting accuracy significantly. Other findings are as follows. First, hyperbolic memory fits the realized measure better, whereas fractional integration is more suitable for the powered returns. Second, the structural breaks applied to the bivariate system capture the time-varying behavior of the parameters, in particular during and after the global financial crisis of 2007/2008.

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.

Structural breaks in unbiased volatility estimator: Modeling and forecasting

2017 ◽  
Vol 11 (1) ◽  
pp. 27-50 ◽  
Author(s):  
Dilip Kumar
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Realized Volatility ◽  
Extreme Value ◽  
Trading Strategy ◽  
Risk Averse ◽  
Memory Property ◽  
Economic Significance ◽  
Forecasting Performance ◽  
Modeling And Forecasting

The study provides a framework to model the unbiased extreme value volatility estimator (The AddRS estimator) in presence of structural breaks. We observe that the structural breaks in the volatility based on the AddRS estimator can partly explain its long memory property. We evaluate the forecasting performance of the proposed framework and compare the results with the corresponding results of the models from the GARCH family. The forecasts evaluation exercises consider the cases when future breaks are known as well as unknown. Our findings indicate that the proposed framework outperform the sophisticated GARCH class of models in forecasting realized volatility. Moreover, we devise a trading strategy based on the forecasts of the variance to highlight the economic significance of the proposed framework. We find that a risk averse investor can make substantial gain using the volatility forecasts based on the proposed frameworks in comparison to the GARCH family of models.

The Impact of Structural Breaks on Volatility Linkages between Asian Stock and Oil Futures Markets

2016 ◽  
Vol 24 (1) ◽  
pp. 31-64
Author(s):  
Sang Hoon Kang ◽  
Seong-Min Yoon
Keyword(s):  
Futures Markets ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Garch Model ◽  
Time Varying ◽  
Oil Futures ◽  
Volatility Spillovers ◽  
Icss Algorithm ◽  
The Global Financial Crisis ◽  
The Impact

This paper investigates the impact of structural breaks on volatility spillovers between Asian stock markets (China, Hong Kong, India, Indonesia, Japan, Korea, Singapore, and Taiwan) and the oil futures market. To this end, we apply the bivariate DCC-GARCH model to weekly spot indices during the period 1998-2015. The results reveal significant volatility transmission for the pairs between the Asian stock and oil futures markets. Moreover, we find a significant variability in the time-varying conditional correlations between the considered markets during both bullish and bearish markets, particularly from early 2007 to the summer of 2008. Using the modified ICSS algorithm, we find several sudden changes in these markets with a common break date centred on September 15, 2008. This date corresponds to the collapse of Lehman Brothers which is considered as our breakpoint to define the global financial crisis. Also, we analyse the optimal portfolio weights and time-varying hedge ratios based on the estimates of the multivariate DCC-GARCH model. The results emphasize the importance of overweighting optimal portfolios between Asian stock and the oil futures markets.

scholarly journals The Impact of the Global Financial Crisis on the Co-Integration Relationship between Reit and Stock Markets: A Dynamic Co-Integration Approach

2017 ◽  
Vol 9 (7) ◽  
pp. 86
Author(s):  
S. Aydin Yüksel ◽  
Asli Yüksel ◽  
Ümit Erol ◽  
Hakki Öztürk
Keyword(s):  
Financial Crisis ◽  
Stock Markets ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Main Tool ◽  
Developed Countries ◽  
Integration Approach ◽  
Variable Nature ◽  
The Global Financial Crisis ◽  
The Impact

The aim of this paper is to analyze the impact of the Global Financial Crisis (GFC) on the co-integration relationship between the REIT and stock market indices using a sample of 10 developed countries. The main tool employed for this purpose is the dynamic co-integration approach. The empirical results strongly suggest that the stock and REIT markets were deeply affected by two successive crises. The first crisis was related to the U.S. subprime problems while the second shock emanated from the European insolvency problems. The shocks led to serious structural breaks in the financial data during the 2007-2012 period. As a result of this and the highly variable nature of the co-integration structure during this period, the conventional and static Johansen tests cannot detect the strong co-integration between the REIT and stock markets which were the result of common negative response of both markets to the successive shocks. Dynamic co-integration approach seems to be a more valid tool to capture the dynamics of the co-integration structure after the GFC. The dynamic approach implies that the destruction of diversification benefits between the REIT and stock markets was essentially a shock related outcome which also implies that the diversification potential between these two markets may still be valid in the absence of shocks.

The changing relationships between government bond yields and capitalisation rates

2015 ◽  
Vol 8 (2) ◽  
pp. 153-171 ◽  
Author(s):  
Colin Jones ◽  
Neil Dunse ◽  
Kevin Cutsforth
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Bond Yields ◽  
Government Bonds ◽  
Content Type ◽  
Yield Gaps ◽  
The Global Financial Crisis ◽  
Over Time

Purpose – The purpose of this paper is to analyse the gap between government bonds (index-linked and long-dated) and real estate yields/capitalization rates over time for the UK, Australia and the USA. The global financial crisis was a sharp shock to real estate markets, and while interest rates and government bond yields fell in response around the world, real estate yields (cap rates) have risen. Design/methodology/approach – The absolute yield gap levels and their variation over time in the different countries are compared and linked to the theoretical reasons for the yield gap and, in particular, a changing real estate risk premium. Within this context, it assesses whether there have been structural breaks in long-term relationships during booms and busts based on autoregressive conditionally heteroscedastic (ARCH) models. Finally, the paper provides further insights by constructing statistical models of index-linked and long-dated yield gaps. Findings – The relationships between bond and property yields go through a traumatic time around the period of the global financial crisis. These changes are sufficiently strong to be statistically defined as “structural breaks” in the time series. The sudden switch in the yield gaps may have stimulated a greater appreciation of structural change in the property market. Research limitations/implications – The research focuses on the most transparent real estate markets in the world, but other countries with less developed markets may respond differently. Practical implications – The practical implications relate to how to value real estate yields relative to interest rates. Originality/value – This is the first paper that has compared international yield gaps over time and examined the role of the gap between index-linked government bonds and real estate yields.

Oil Price Shocks and Sectoral Stocks Behaviour in Nigeria: How Relevant is Asymmetry and Structural Breaks?

2020 ◽  
Author(s):  
Ismail Fasanya ◽  
Oluwasegun B. Adekoya ◽  
Temitope F. Odudu
Keyword(s):  
Stock Returns ◽  
Structural Breaks ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Oil Price ◽  
Jel Codes ◽  
Monthly Data ◽  
The Global Financial Crisis ◽  
The Arab Spring ◽  
The Relationship

Abstract In this paper, we model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016. We employ both the Linear (Symmetric) ARDL by Pesaran et al. (2001) and Nonlinear (Asymmetric) ARDL by Shin et al. (2014) and we also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models. Our results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. We identify two structural breaks that occur in 2008 and 2010/2011 which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shut-downs), respectively.Moreover, we observe strong supportfor asymmetry and structural breaks for some sectorsin the reaction of sector returns to movement in oil prices.These findings are robust and insensitive when considering different oil proxy.While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.JEL codes: C22; C51; G12; Q43

scholarly journals Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

2019 ◽  
Vol 12 (2) ◽  
pp. 94 ◽  
Author(s):  
A. M. M. Shahiduzzaman Quoreshi ◽  
Reaz Uddin ◽  
Viroj Jienwatcharamongkhol
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Stock Index ◽  
Stock Market Volatility ◽  
Euro Zone ◽  
The Us ◽  
Market Contagion ◽  
The Global Financial Crisis

The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia, India, China and South Africa) countries, as a proxy for the measurement of volatility. Results from the conditional heteroskedasticity long memory model show the evidence of long memory in the squared stock returns of all 35 stock indices studied. Empirical findings show the evidence of contagion during the global financial crisis (GFC) and Euro Zone crisis (EZC). The intensity of contagion varies depending on its sources. This implies that the effects of shocks are not symmetric and may have led to some structural changes. The effect of contagion is also studied by decomposing the level series into explained and unexplained behaviors.

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