scholarly journals OPEC news and predictability of energy futures returns and volatility: evidence from a conditional quantile regression

2020 ◽  
Vol 25 (50) ◽  
pp. 239-259
Author(s):  
Abdelkader Derbali ◽  
Shan Wu ◽  
Lamia Jamel
Keyword(s):  
Quantile Regression ◽  
Futures Market ◽  
Market Returns ◽  
Predictive Capacity ◽  
Causality Test ◽  
Content Type ◽  
Conditional Quantile ◽  
Energy Futures ◽  
The Impact ◽  
Quantile Causality

Purpose This paper aims to provide an important perspective to the predictive capacity of Organization of the Petroleum Exporting Countries (OPEC) meeting dates and production announcements for energy futures (crude oil West Texas Intermediate (WTI), gasoline reformulated gasoline blendstock for oxygen blending (RBOB), Brent oil, London gas oil, natural gas and heating oil) market returns and volatilities. Design/methodology/approach To examine the impact of OPEC news on energy futures market returns and volatilities, the authors use a conditional quantile regression methodology during the period from April 01, 2013 to June 30, 2017. Findings From the empirical findings, the authors show a conditional dependence between energy futures returns and OPEC-based predictors; hence, the authors can find clear the significance of relationship in the process of financialization of the OPEC announcements and energy futures in the case of this paper. From the quantile-causality test, the authors find that the effect of OPEC news is important to energy futures. Specifically, OPEC announcements dates predict the quantiles of the conditional distribution of energy futures market returns. Originality/value The authors confirm the presence of unidirectional nexus between OPEC news and energy commodities futures in the long term.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

scholarly journals Do average higher moments predict aggregate returns in emerging stock markets?

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sumaira Chamadia ◽  
Mobeen Ur Rehman ◽  
Muhammad Kashif
Keyword(s):  
Quantile Regression ◽  
Stock Markets ◽  
Higher Order ◽  
Higher Moments ◽  
Excess Returns ◽  
Market Returns ◽  
Content Type ◽  
Emerging Stock Markets ◽  
The Impact ◽  
Skewness And Kurtosis

PurposeIt has been demonstrated in the US market that expected market excess returns can be predicted using the average higher-order moments of all firms. This study aims to empirically test this theory in emerging markets.Design/methodology/approachTwo measures of average higher moments have been used (equal-weighted and value-weighted) along with the market moments to predict subsequent aggregate excess returns using the linear as well as the quantile regression model.FindingsThe authors report that both equal-weighted skewness and kurtosis significantly predict subsequent market returns in two countries, while value-weighted average skewness and kurtosis are significant in predicting returns in four out of nine sample markets. The results for quantile regression show that the relationship between the risk variable and aggregate returns varies along the spectrum of conditional quantiles.Originality/valueThis is the first study that investigates the impact of third and fourth higher-order average realized moments on the predictability of subsequent aggregate excess returns in the MSCI Asian emerging stock markets. This study is also the first to analyze the sensitivity of future market returns over various quantiles.

scholarly journals The drivers of economic growth in China and India: globalization or financial development?

2017 ◽  
Vol 16 (1) ◽  
pp. 54-84 ◽  
Author(s):  
Magda Kandil ◽  
Muhammad Shahbaz ◽  
Mantu Kumar Mahalik ◽  
Duc Khuong Nguyen
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Emerging Market ◽  
Annual Data ◽  
Test Results ◽  
Causality Test ◽  
Content Type ◽  
China And India ◽  
Integration Test ◽  
The Impact

Purpose Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing capital and inflation and drawing comparisons between the two fastest growing emerging market economies. Design/methodology/approach In the long run, co-integration test results indicate that financial development increases economic growth in China and India. Findings The results also reveal that globalization accelerates economic growth in India but, surprisingly, impairs economic growth in China, as it increases competition for exports. The results furthermore disclose that acceleration in capitalization and inflation, as a proxy for aggregate demand, are positively linked to economic growth in China and India. Originality/value Causality test results indicate that both financial development and economic growth are interdependent. In contrast, causality runs from higher economic growth to increased globalization in India, while the results do not support long-term causality between globalization and economic growth in China.

Disintermediation of banks in a developing economy

2019 ◽  
Vol 45 (2) ◽  
pp. 222-243 ◽  
Author(s):  
Tahseen Mohsan Khan ◽  
Syed Kumail Abbas Rizvi ◽  
Ramla Sadiq
Keyword(s):  
Design Methodology ◽  
Structural Changes ◽  
Banking System ◽  
Causality Test ◽  
Correction Model ◽  
Content Type ◽  
Balance Sheets ◽  
Panel Regressions ◽  
The Impact ◽  
Major Hypothesis

Purpose The purpose of this paper is to investigate how Pakistani banks manage their portfolios (lending vs investment) when the economic indicators are not supportive. This study investigates three aspects of the banking system in Pakistan – prevalence of disintermediation, post-crisis profitability orientation and depositor protection by financial system in unfavorable conditions. Design/methodology/approach This study is limited to identifying the key economic and financial drivers behind disintermediation and its subsequent impact on banks’ profitability and depositors’ protection. GLS panel regressions and Engle–Granger causality test as specified by the error correction model have been used to test the major hypothesis of this study. Findings This study shows that small banks have been shifting major part of their portfolios toward risk-free investments to be able to maintain their profitability more efficiently and effectively, like large banks. The study also observes that significant pairing causality exists between gross credit loans and investments confirming disintermediation hypothesis for all types of banks except Islamic or Sharia compliant banks, whereas for significant pairing causality, the results are mixed for remaining variables among gross credit loans as a proportion of assets and economic variables that include GDP growth, unemployment, KSE-100 and SBP policy rate. It is also confirmed by the results that disintermediation improves banks profitability and depositor protection, thus providing a good rationale and justification to banks for opting it. Originality/value The study focuses on the impact of structural changes in portfolios only of commercial banks’ revenue-generating assets not including other financial institutions as a part of banking system. Furthermore, data are extracted from balance sheets and is the sole property of corresponding author.

COVID-19 news in USA and in China: Which is suitable in explaining the nexus among Bitcoin and Gold?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdelkader Derbali ◽  
Kamel Naoui ◽  
Lamia Jamel
Keyword(s):  
Design Methodology ◽  
Conditional Heteroskedasticity ◽  
Conditional Correlation ◽  
Predictive Capacity ◽  
Content Type ◽  
Dynamic Conditional Correlation ◽  
The Hours ◽  
Important Correlation ◽  
The Impact ◽  
First Time

Purpose The purpose of this paper is to examine empirically the impact of COVID-19 pandemic news in USA and in China on the dynamic conditional correlation between Bitcoin and Gold. Design/methodology/approach This paper offers a crucial viewpoint to the predictive capacity of COVID-19 surprises and production pronouncements for the dynamic conditional correlation (DCC) among Bitcoin and Gold returns and volatilities using generalized autoregressive conditional heteroskedasticity-DCC-(1,1) through the period of study since July 1, 2019 to June 30, 2020. To assess the unexpected impact of COVID-19, this study pursues the Kuttner’s (2001) methodology. Findings The empirical findings indicate strong important correlation among Bitcoin and Gold if COVID-19 surprises are integrated in variance. This study validates the financialization hypothesis of Bitcoin and Gold. The correlation between Bitcoin and Gold begin to react significantly further in the case of COVID-19 surprises in USA than those in China. Originality/value This paper contributes to the literature on assessing the impact of COVID-19 confirmed cases surprises on the correlation between Bitcoin and Gold. This paper gives for the first time an approach to capture the COVID-19 surprise component. Also, this study helps to improve financial backers and policymakers' comprehension of the digital currencies' market elements, particularly in the hours of amazingly unpleasant and inconspicuous occasions.

Analysis of risk spillover effect of copper option in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wuyi Ye ◽  
Yiqi Wang ◽  
Jinhai Zhao
Keyword(s):  
Value At Risk ◽  
Risk Model ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Futures Market ◽  
Content Type ◽  
Conditional Autoregressive ◽  
Derivative Markets ◽  
The Impact ◽  
Risk Spillover Effects

Purpose The purpose of this paper is to compare the changes in the risk spillover effects between the copper spot and futures markets before and after the issuance of copper options, analyze the risk spillover effects between the three markets after the issuance of the options and can provide effective suggestions for regulators and investors who hedge risks. Design/methodology/approach The MV-CAViaR model is an extended form of the vector autoregressive model (VAR) to the quantile model, and it is also a special form of the MVMQ-CAViaR model. Based on the VAR quantile model, this model has undergone continuous promotion of the Conditional Autoregressive Value-at-Risk Model (CAViaR) and the Multi-quantile Conditional Autoregressive Value-at-Risk Model (MQ-CAViaR), and finally got the current form of the model. Findings The issuance of options has led to certain changes in the risk spillover effect between the copper spot and its derivative markets, and the risk aggregation effect in the futures market has always been significant. Therefore, when supervising the copper product market and investors using copper derivatives to avoid market risks, they need to pay attention to the impact of futures on the spot market, the impact of options on the futures market and the risk spillover effects of spot and futures on the options market. Practical implications The empirical results of this paper can be used to hedge market risk investment strategies, and the changes in market relationships also provide an effective basis for the supervision of the copper product market by the supervisory authority. Originality/value It is the first literature research to discuss the risk and the impact of spillover effects of copper options on China copper market and its derivative markets. The MV-CAViaR model can capture the mutual risk influence between markets by modeling multiple markets simultaneously.

Does Ban on Futures trading (de)stabilise spot volatility?

2019 ◽  
Vol 9 (2) ◽  
pp. 145-166 ◽  
Author(s):  
Neharika Sobti
Keyword(s):  
Granger Causality ◽  
Price Discovery ◽  
Futures Trading ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
The Impact ◽  
Spot Volatility ◽  
Non Parametric

Purpose The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility. Design/methodology/approach The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis. Findings The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility. Originality/value This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.

scholarly journals Determinants of household income of micro-finance women participants: a quantile regression approach

2020 ◽  
Vol 1 (1) ◽  
pp. 63-74
Author(s):  
Jarita Duasa ◽  
Nur Hidayah Zainal
Keyword(s):  
Quantile Regression ◽  
Capita Income ◽  
Per Capita Income ◽  
Content Type ◽  
Income Distributions ◽  
Asset Value ◽  
Regression Approach ◽  
Convenience Sampling ◽  
Per Capita ◽  
The Impact

Purpose The purpose of this study is to adopt quantile regression to investigate the impact of several factors on per capita income of participants of micro-financing scheme (Amanah Ikhtiar Malaysia [AIM]), who are mostly women at different point on the income distributions. Design/methodology/approach This study uses data collected from a survey on respondents who are the participants of AIM program using convenience sampling in Perak and Kelantan. Findings The empirical results show that the value of asset, value of loan, household size, ratio of spending to income and dummy state are consistently giving similar impacts on per capita income of participants at different quantiles. Originality/value However, age negatively and significantly affects per capita income only at middle and lower quantiles but not at higher quantile of per capita income.

Herding behavior in Islamic GCC stock market: a daily analysis

2018 ◽  
Vol 11 (2) ◽  
pp. 182-193 ◽  
Author(s):  
Mustapha Chaffai ◽  
Imed Medhioub
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Financial Markets ◽  
Stock Returns ◽  
Stock Markets ◽  
Content Type ◽  
Quantile Regression Analysis ◽  
Herd Behaviour ◽  
The Impact ◽  
Quantile Regression Method

Purpose This paper aims to examine the presence of herd behaviour in the Islamic Gulf Cooperation Council (GCC) stock markets following the methodology given by Chiang and Zheng (2010). Generalized auto regressive conditional heteroskedasticity (GARCH)-type models and quantile regression analysis are used and applied to daily data ranging from 3 January 2010 to 28 July 2016. Results show evidence of herd behaviour in the GCC stock markets. When the data are divided into down and up market periods, herd information is found to be statistically significant and negative during upward market periods only. These results are similar to those reported in some emerging markets such as China, Japan and Hong Kong, where stock returns perform more similarly during down market periods and differently during rising markets. Design/methodology/approach The authors present a brief literature on herd behaviour. Second, the authors provide some specificity of the GCC Islamic stock market, followed by the presentation of the methodology and the data, results and their interpretation. Findings The authors take into account the difference existing in market conditions and find evidence of herding behaviour during rising markets only for GCC markets. This result was confirmed after using the quantile regression method, as evidence of herding was observed only in highly extreme periods. Stock returns perform more similarly when market is down in Islamic GCC stock market. Research limitations/implications The research limitation consists in the fact that this work can be extended to compare the GCC stock markets with other markets in Asia such as Malaysia and Indonesia. Practical implications The principal implication consists in the fact that herding behaviour is limited in the GCC markets and Islamic finance can have an important contribution to moderate the behaviour in the financial markets. Social implications The work focusses on the role of ethics in the financial markets and their ability to reduce the impact of behavioural biases. Originality/value The paper studies the behaviour of investors in the Islamic financial markets and gives an idea about the importance of the behaviour in this particular market regarding its characteristics.

The asymmetric impact of rational and irrational components of fear index on S&P 500 index returns

2017 ◽  
Vol 9 (3) ◽  
pp. 278-291 ◽  
Author(s):  
Gökçe Soydemir ◽  
Rahul Verma ◽  
Andrew Wagner
Keyword(s):  
Risk Factors ◽  
Risk Premium ◽  
Var Model ◽  
Impulse Responses ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
Market Risk Premium ◽  
Economic Fundamentals ◽  
The Impact

Purpose Investors’ fear can be rational, emanating from the natural dynamics of economic fundamentals, or it can be quasi rational and not attributable to any known risk factors. Using VIX from Chicago Board Options Exchange as a proxy for investors’ fear, the purpose of this paper is to consider the following research questions: to what extent does noise play a role in the formation of investors’ fear? To what extent is the impact of fear on S&P 500 index returns driven by rational reactions to new information vs fear induced by noise in stock market returns? To what extent do S&P 500 index returns display asymmetric behavior in response to investor’s rational and quasi rational fear? Design/methodology/approach In a two-step process, the authors first decompose investors’ fear into its rational and irrational components by generating two additional variables representing fear induced by rational expectations and fear due to noise. The authors then estimate a three-vector autoregression (VAR) model to examine their relative impact on S&P 500 returns. Findings Impulse responses generated from a 13-variable VAR model show that investors’ fear is driven by risk factors to some extent, and this extent is well captured by the Fama and French three-factor and the Carhart four-factor models. Specifically, investors’ fear is negatively related to the market risk premium, negatively related to the premium between value and growth stocks, and positively related to momentum. The magnitude and duration of the impact of the market risk premium is almost twice that of the impact of the premium on value stocks and the momentum of investors’ fear. However, almost 90 percent of the movement in investors’ fear is not attributable to the 12 risk factors chosen in this study and thus may be largely irrational in nature. The impulse responses suggest that both rational and irrational fear have significant negative effects on market returns. Moreover, the effects are asymmetric on S&P 500 index returns wherein irrational upturns in fear have a greater impact than downturns. In addition, the component of investors’ fear driven by irrationality or noise has more than twice the impact on market returns in terms of magnitude and duration than the impact of the rational component of investors’ fear. Originality/value The results are consistent with the view that one of the most important drivers of stock market returns is irrational fear that is not rooted in economic fundamentals.

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