scholarly journals Are soft commodities markets affected by the Halloween effect?

2021 ◽  
Author(s):  
Monika Krawiec ◽  
Anna Górska
Keyword(s):  
Commodity Markets ◽  
Wilcoxon Test ◽  
January Effect ◽  
Conditional Heteroskedasticity ◽  
Arch Effect ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Long Time ◽  
The Impact ◽  
Halloween Effect ◽  
Commodities Markets

Within the last three decades commodity markets, including soft commodities markets, have become more and more like financial markets. As a result, prices of commodities may exhibit similar patterns or anomalies as those observed in the behaviour of different financial assets. Their existence may cast doubts on the competitiveness and efficiency of commodity markets. It motivates us to conduct the research presented in this paper, aimed at examining the Halloween effect in the markets of basic soft commodities (cocoa, coffee, cotton, frozen concentrated orange juice, rubber and sugar) from 1999 to 2020. This long-time span ensures the credibility of results. Apart from performing the two-sample t-test and the rank-sum Wilcoxon test, we additionally investigate the autoregressive conditional heteroskedasticity (ARCH) effect. Its presence in our data allows us to estimate generalised autoregressive conditional heteroskedasticity [GARCH (1, 1)] models with dummies representing the Halloween effect. We also investigate the impact of the January effect on the Halloween effect. Results reveal the significant Halloween effect for cotton (driven by the January effect) and the significant reverse Halloween effect for sugar. It brings implications useful to the main actors in the market. They may apply trading strategies generating satisfactory profits or providing hedging against unfavourable changes in soft commodities prices.

Impact of the COVID-19 Outbreak on the Currency Exchanges of Selected Countries

2022 ◽  
Vol 14 (2) ◽  
pp. 73-91
Author(s):  
Sudhi Sharma ◽  
Miklesh Prasad Yadav ◽  
Babita Jha
Keyword(s):  
Growth Rate ◽  
Negative Impact ◽  
Annual Growth ◽  
Conditional Heteroskedasticity ◽  
Annual Growth Rate ◽  
Dummy Variable ◽  
Currency Market ◽  
Autoregressive Conditional Heteroskedasticity ◽  
The Impact

The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies—USD/JPY, AUD/USD, and USD/CHF—and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers.

scholarly journals Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes

2005 ◽  
Vol 12 (1) ◽  
pp. 55-66 ◽  
Author(s):  
W. Wang ◽  
P. H. A. J. M Van Gelder ◽  
J. K. Vrijling ◽  
J. Ma
Keyword(s):  
Seasonal Variation ◽  
Moving Average ◽  
Arma Model ◽  
Autoregressive Moving Average ◽  
Conditional Heteroskedasticity ◽  
Daily Streamflow ◽  
Arch Effect ◽  
Monthly Streamflow ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Residual Series

Abstract. Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity) effect), a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community.

Estimation of Persistence and Predictability of Volatility in The Indian Banking Sector

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Dr. Vandana Dangi
Keyword(s):  
Serial Correlation ◽  
Banking Sector ◽  
Stock Exchange ◽  
Conditional Heteroskedasticity ◽  
Arch Model ◽  
Stock Market Returns ◽  
Volatility Clustering ◽  
Arch Effect ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Augmented Dickey Fuller

The impulsiveness in investment’s price is volatility and its meticulous estimation and forecasting is valuable to investors in the risk management of their portfolio. Earlier volatility of an asset was assumed to be constant. However, the pioneering studies of Mandelbrot, Engle and Bollerslev on the property of stock market returns did not support this assumption. The family of autoregressive conditional heteroskedasticity models were developed to capture time-varying characteristics of volatility. The present treatise attempts to study the presence of autoregressive conditional heteroskedasticity in four Indian banking sector indices viz. BSE Bankex, BSE PSU, CNX bank and CNX PSU. The daily banking sector indices for the period of January 2004 to December 2013 were taken from the online database maintained by the Bombay Stock Exchange and the National Stock Exchange. The data of four indices was studied for stationarity, serial correlation in the returns and serial correlation in the squares of returns with the help of Augmented Dickey–Fuller test, Box-Jenkins methodology and autoregressive conditional heteroscedasticity models respectively. The results of ACF, PACF and Ljung–Box Q test indicates that there is a tendency of the periods of high and low volatility to cluster in the Indian banking sector. All the four banking sector indices display the presence of ARCH effect indicating the presence of volatility clustering. Engle's ARCH test (i.e Lagrange multiplier test) and Breush-Godfrey-Pagan test and ARCH model confirmed the high persistence and predictability of volatility in the Indian banking sector.

Modeling volatility on the Karachi Stock Exchange, Pakistan

2016 ◽  
Vol 10 (3) ◽  
pp. 253-275 ◽  
Author(s):  
Shahan Akhtar ◽  
Naimat U. Khan
Keyword(s):  
Financial Crises ◽  
Stock Exchange ◽  
Small Sample ◽  
Leverage Effect ◽  
Data Series ◽  
Conditional Heteroskedasticity ◽  
Content Type ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Modeling Volatility ◽  
The Impact

Purpose The current paper aims to fill a gap in the literature by analyzing the nature of volatility on the Karachi Stock Exchange (KSE) 100 index of the KSE, and develop an understanding as to which model is most suitable for measuring volatility among those used. The study contributes significantly to the literature as, compared with the limited previous studies of Pakistan undertaken in the past, it covers three types of data (i.e. daily, weekly and monthly) for the whole period from the introduction of the KSE 100 index on November 2, 1991 to December 31, 2013. In addition, to analyze the impact of global financial crises upon volatility, the data have been divided into pre-crisis (1991-2007) and post-crisis (2008-2013) periods. Design/methodology/approach This study has used an advanced set of volatility models such as autoregressive conditional heteroskedasticity [ARCH (1)], generalized autoregressive conditional heteroskedasticity [GARCH (1, 1)], GARCH in mean [GARCH-M (1, 1)], exponential GARCH [E-GARCH (1, 1)], threshold GARCH [T-GARCH (1, 1)], power GARCH [P-GARCH (1, 1)] and also a simple exponentially weighted moving average (EWMA) model. Findings The results reveal that daily, weekly and monthly return series show non-normal distribution, stationarity and volatility clustering. However, the heteroskedasticity is absent only in the monthly returns making only the EWMA model usable to measure the volatility level in the monthly series. The P-GARCH (1, 1) model proved to be a better model for modeling volatility in the case of daily returns, while the GARCH (1, 1) model proved to be the most appropriate for weekly data based on the Schwarz information criterion (SIC) and log likelihood (LL) functionality. The study shows high persistence of volatility, a mean reverting process and an absence of a risk premium in the KSE market with an insignificant leverage effect only in the case of weekly returns. However, a significant leverage effect is reported regarding the daily series of the KSE 100 index. In addition, to analyze the impact of global financial crises upon volatility, the findings show that the subperiods demonstrated a slightly low volatility and the global economic crisis did not cause a rise in volatility levels. Originality/value Previously, the literature about volatility modeling in Pakistan’s markets has been limited to a few models of relatively small sample size. The current thesis has attempted to overcome these limitations and used diverse models for three types of data series (daily, weekly and monthly). In addition, the Pakistani economy has been beset by turmoil throughout its history, experiencing a range of shocks from the mild to the extreme. This paper has measured the impact of those shocks upon the volatility levels of the KSE.

scholarly journals Impact Of Financial Crisis On Hedging Effectiveness Of Futures Contracts: Evidence From The National Stock Exchange Of India

2015 ◽  
Vol 10 (2) ◽  
pp. 69-88 ◽  
Author(s):  
Kapil Gupta ◽  
Mandeep Kaur
Keyword(s):  
Financial Crisis ◽  
Stock Exchange ◽  
Moving Average ◽  
Futures Contracts ◽  
Conditional Heteroskedasticity ◽  
Vector Autoregressive ◽  
Hedging Effectiveness ◽  
Autoregressive Conditional Heteroskedasticity ◽  
The 2008 Financial Crisis ◽  
The Impact

Abstract The present study examines the impact of the 2008 financial crisis on the hedging effectiveness of three index futures contracts traded on the National Stock Exchange of India for near, next and far month contracts over the sample period of January 2000 – June 2014. The hedge ratios were calculated using eight methods; Naive hedging, Ederington’s Model, Autoregressive Integrated Moving Average, Vector Autoregressive, Vector Error Correction Methodology, Generalized Autoregressive Conditional Heteroskedasticity, Exponential Generalized Autoregressive Conditional Heteroscedasticity and Threshold Generalized Autoregressive Conditional Heteroskedasticity. The study finds an improvement in hedging effectiveness during the post-crisis period, which implies that during the high-volatility period hedging effectiveness also improves. It was also found that near month futures contracts are a more effective tool for hedging as compared to next and far month contracts, which imply that liquidity is a more important determinant of hedging effectiveness than hedge horizons. The study also finds that a time-invariant hedge ratio is more efficient than time-variant hedging. Therefore, knowledge of sophisticated econometrical tools does not help to improve hedge effectiveness.

GARCH AND VOLUME EFFECTS IN THE AUSTRALIAN STOCK MARKETS

2009 ◽  
Vol 05 (01) ◽  
pp. 0950005 ◽  
Author(s):  
JINGLIANG XIAO ◽  
ROBERT D BROOKS ◽  
WING-KEUNG WONG
Keyword(s):  
Stock Returns ◽  
Firm Size ◽  
Trading Volume ◽  
Explanatory Power ◽  
Garch Model ◽  
Conditional Heteroskedasticity ◽  
Autoregressive Conditional Heteroskedasticity ◽  
The Impact ◽  
Daily Returns ◽  
Volume Effects

This paper explores the relationship between volume and volatility in the Australian Stock Market in the context of a generalized autoregressive conditional heteroskedasticity (GARCH) model. In contrast to other studies who only examine the interaction of GARCH and volume effects on a small number of stocks, we examine these effects on the entire available data for the Australian All Ordinaries Index. We also emphasize on the impact of firm size and trading volume. Our results indicate that GARCH model testing and estimation is impacted by firm size and trading volume. Specifically, our analysis produces the following major findings. First, generally, daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns. Second, the actively traded stocks which may have a larger number of information arrivals per day have a larger impact of volume on the variance of daily returns. Third, we find that low trading volume and small firm lead to a higher persistence of GARCH effects in the estimated models. Fourth, unlike the elimination effect for the top most active stocks, in general, the elimination of both autoregressive conditional heteroskedasticity (ARCH) and GARCH effects by introducing the volume variable on all other stocks on average is not as much as that for the top most active stocks. Fifth, the elimination of both ARCH and GARCH effects by introducing the volume variable is higher for stocks in the largest volume and/or the largest market capitalization quartile group. Our findings imply that the earlier findings in the literature were not a statistical fluke and that, unlike most anomalies, the volume effect on volatility is not likely to be eliminated after its discovery. In addition, our findings reject the pure random walk hypothesis for stock returns.

STUDI SPILLOVER EFEK EXCHANGE-TRADED FUNDS (ETFs) DI ASEAN

2019 ◽  
Vol 4 (2) ◽  
pp. 245-256
Author(s):  
Ahmad Juliana ◽  
Apriliani Mutoharo
Keyword(s):  
Unit Root ◽  
Unit Root Test ◽  
Spillover Effect ◽  
Garch Model ◽  
Conditional Heteroskedasticity ◽  
Financial Asset ◽  
Financial Security ◽  
Exchange Traded Funds ◽  
Arch Effect ◽  
Autoregressive Conditional Heteroskedasticity

The volatility of financial security make an investor difficult and inaccurate to predict the value of targeted investation. The failure for predicting the value of financial asset will mitigate for either succeed or not an investation. That condition will not happen if an investor has knowledge for predicting the volatility financial asset. There for, we need study for forecasting the spillover effect of financial asset using ARCH-GARCH model. The novelty of this study is, we compare the three of ASEAN ETFs that still rarely investigate, are:  Indonesia, Malaysia and Singapore using 5 samples of ETFs. We applied Autoregressive Conditional Heteroskedasticity (ARCH) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) for predicting the spillover efect. The result of unit root test shown that the data not stationer at level, however stationer at first difference. The result of GARCH for JK-LQ45, EWS and EIDO are not significant and it mean there is not ARCH effect. In contract the result are significant for ETF EWM and FXSG. We also found the best AIC are from ETF EWS and ETF FXSG.

scholarly journals The Impact of the Introduction of Index Futures on the Daily Returns Anomaly in the Ho Chi Minh Stock Exchange

2021 ◽  
Vol 9 (3) ◽  
pp. 43
Author(s):  
Loc Dong Truong ◽  
H. Swint Friday
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Least Square ◽  
Conditional Heteroskedasticity ◽  
Index Futures ◽  
Futures Contract ◽  
Autoregressive Conditional Heteroskedasticity ◽  
Day Of The Week ◽  
The Impact ◽  
Daily Returns

This study investigated the impact of the introduction of the VN30-Index futures contract on the daily returns anomaly for the Ho Chi Minh Stock Exchange (HOSE). Daily returns of the VN30-Index for the period 6 February 2012 through 31 December 2019 are used in this study to ascertain the new VN30-Index futures contract influence on the day-of-the-week anomaly observed in the HOSE. To test this effect, ordinary least square (OLS), generalized autoregressive conditional heteroskedasticity [GARCH (1,1)] and exponential generalized autoregressive conditional heteroskedasticity [EGARCH (1,1)] regression models were employed. The empirical results obtained from the models support the presence of the day-of-the-week effect for the HOSE during the study period. Specifically, a negative effect was observed for Monday. However, the analysis revealed that the day-of-the-week effect was only present in stock returns for the pre-index futures period, not for the post-index futures period. These findings suggest that the introduction of the VN30-Index futures contract had a significant impact on the daily returns anomaly in Vietnam’s HOSE, providing evidence that the introduction of the index futures contract facilitated market efficiency.

Euratom and Brexit: Could the United Kingdom Maintain One Foot in the European Union? Current Scenarios and Future Prospects of British withdrawal from the EAEC

2018 ◽  
Vol 18 (2) ◽  
pp. 134-151
Author(s):  
Andrea Circolo ◽  
Ondrej Hamuľák
Keyword(s):  
European Union ◽  
United Kingdom ◽  
Independent Solution ◽  
Legal Regulation ◽  
The European Union ◽  
The United Kingdom ◽  
The Status ◽  
Long Time ◽  
Energy Community ◽  
The Impact

Abstract The paper focuses on the very topical issue of conclusion of the membership of the State, namely the United Kingdom, in European integration structures. The ques­tion of termination of membership in European Communities and European Union has not been tackled for a long time in the sources of European law. With the adop­tion of the Treaty of Lisbon (2009), the institute of 'unilateral' withdrawal was intro­duced. It´s worth to say that exit clause was intended as symbolic in its nature, in fact underlining the status of Member States as sovereign entities. That is why this institute is very general and the legal regulation of the exercise of withdrawal contains many gaps. One of them is a question of absolute or relative nature of exiting from integration structures. Today’s “exit clause” (Art. 50 of Treaty on European Union) regulates only the termination of membership in the European Union and is silent on the impact of such a step on membership in the European Atomic Energy Community. The presented paper offers an analysis of different variations of the interpretation and solution of the problem. It´s based on the independent solution thesis and therefore rejects an automa­tism approach. The paper and topic is important and original especially because in the multitude of scholarly writings devoted to Brexit questions, vast majority of them deals with institutional questions, the interpretation of Art. 50 of Treaty on European Union; the constitutional matters at national UK level; future relation between EU and UK and political bargaining behind such as all that. The question of impact on withdrawal on Euratom membership is somehow underrepresented. Present paper attempts to fill this gap and accelerate the scholarly debate on this matter globally, because all consequences of Brexit already have and will definitely give rise to more world-wide effects.

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