scholarly journals Futures trading and the underlying stock volatility: A case of the FTSE/JSE TOP 40

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Mr. Rabson Magweva ◽  
Mrs. Magret Munyimi ◽  
Mr. Justine Mbudaya
Keyword(s):  
Time Series Data ◽  
Financial Time Series ◽  
Garch Model ◽  
Stock Index ◽  
Futures Contracts ◽  
Series Data ◽  
Policy And Practice ◽  
Stock Volatility ◽  
Top 40 ◽  
The Impact

Purpose: This study analyzed the impact of listing and trading futures contracts on the underlying stock index volatility behavior. The FTSE/JSE TOP 40 index was the index of interest.Methodology: To capture the non-constant variance of the residuals, a modified Generalised Autoregressive Conditionally Heteroscedasticity (GARCH) model was adopted. This model was used was adopted given that financial time series data exhibited ARCH effects. The GARCH model was estimated after dividing the sample period into pre-and post-futures eras.Findings: The research findings point towards stabilization effects on underlying stock volatility and refute the suggestion that futures markets improve the dissemination of information to the corresponding spot markets. On the same note, the introduction of futures increased the volatility persistence of index returns.Unique contribution to theory, policy, and practice: This paper applied a modified-GARCH by incorporating a dummy variable to the traditional GARCH model. The study used an emerging economy as a case study which makes the results and conclusions more specific and applicable. On the same note, the study covered the pre-and post-global crisis of 2007/8 in a Sub-Saharan nation. In practice, stock markets are encouraged to introduce futures contracts on highly volatile spot market assets.

scholarly journals Modeling Conditional Dependence of Stock Returns Using a Copula-based GARCH Model

2017 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Eun-Joo Lee ◽  
Noah Klumpe ◽  
Jonathan Vlk ◽  
Seung-Hwan Lee
Keyword(s):  
Stock Returns ◽  
Time Series Data ◽  
Financial Time Series ◽  
Garch Model ◽  
Series Data ◽  
Future Price ◽  
Investment Strategies ◽  
Volatility Clustering ◽  
Technology Stocks ◽  
Stock Portfolio

Investigating dependence structures of stocks that are related to one another should be an important consideration in managing a stock portfolio, among other investment strategies. To capture various dependence features, we employ copula to overcome the limitations of traditional linear correlations. Financial time series data is typically characterized by volatility clustering of returns that influences an estimate of a stock’s future price. To deal with the volatility and dependence of stock returns, this paper provides procedures of combining a copula with a GARCH model which leads to the construction of a multivariate distribution. Using the copula-based GARCH approach that describes the tail dependences of stock returns, we carry out Monte Carlo simulations to predict a company’s movements in the stock market. The procedures are illustrated in two technology stocks, Apple and Samsung.

The impact of embedded location options on price discovery of agricultural futures contracts – the evidence from the Chana contract

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanjay Mansabdar ◽  
Hussain C. Yaganti ◽  
Sankarshan Basu
Keyword(s):  
Price Discovery ◽  
Time Series Data ◽  
Futures Contracts ◽  
Series Data ◽  
Futures Prices ◽  
Content Type ◽  
Futures Contract ◽  
Agricultural Futures ◽  
Embedded Options ◽  
The Impact

Purpose Embedded options can create asymmetries in information impounded by cash and futures markets, causing errors in price discovery estimation. This paper aims to investigate the impact of embedded location options on measures of price discovery. Design/methodology/approach Various price discovery metrics are computed using observed futures prices that contain embedded location options and cash prices for Chana. Prices of a futures contract that contains no options using observed futures prices and estimates of location option value are synthesized. The price discovery measures are recomputed using synthetic option-adjusted futures contract prices and cash prices, and changes in these measures are attributed to the impact of the embedded location option. Findings If the presence of the location option is ignored, futures appear to dominate price discovery. Once the location option is adjusted for, cash markets are found to dominate price discovery. Research limitations/implications The lack of complete time-series data from the exchange for multiple commodities allows only limited empirical evidence for generalizing conclusions. Practical implications This paper highlights that regulators, exchanges and policymakers in India need to revisit delivery specifications of agricultural commodity futures contracts to enhance their utility from a price discovery perspective. Originality/value This work shows that ignoring the presence of embedded options can cause significant errors in price discovery assessment of agricultural futures contracts, particularly in heterogenous cash markets.

scholarly journals Analysis of Integration of the Indonesian Sharia Stock Index with Developing Countries

2021 ◽  
Vol 9 (2) ◽  
pp. 347
Author(s):  
Budiandru Budiandru ◽  
Deni Nuryadin ◽  
Muhammad Dika Pratama
Keyword(s):  
Developing Countries ◽  
Time Series Data ◽  
Stock Index ◽  
Series Data ◽  
Policy Reforms ◽  
Vector Error Correction ◽  
Trade Relations ◽  
Vector Error ◽  
The Impact

<p><em>Globalization is rapidly causing an integration of economic and financial systems worldwide, resulting in shocks to the Islamic stock index and reducing the benefits of diversification for investors. Therefore, this study analyzes the integration, influence, response, and contribution of shocks to each developing country’s Islamic stock index. Specifically, analyzing the effect of developing country sharia stock index shocks on Indonesia's sharia stock index. The study uses monthly time series data for 2011-2021 with samples from Indonesia, Turkey, Malaysia, Pakistan, Kuwait, and India using the Vector Error Correction Model (VECM) method. The results showed cointegration or a long-term relationship in the developing countries’ sharia stock index. The Malaysian Islamic Stock Index and the Indian Islamic Stock Index influence the Indonesian Islamic Stock Index. Furthermore, the Indonesian Islamic Stock Index stabilized the fastest in response to the Turkish Islamic Stock Index shocks. However, the Malaysian Islamic Stock Index shock contributes the most to the Indonesian Islamic Stock Index. Developing countries could improve the infrastructure of the Islamic stock index and policy reforms. This would minimize the impact of international stock index shocks and accelerate integration. Investors should consider the dominant economic strength, geographical factors, and trade relations in determining portfolio diversification in global economic conditions.</em></p><div class="notranslate" style="all: initial;"> </div>

scholarly journals Impact of Global Oil Shocks on the Russian Stock Market

2021 ◽  
Vol 92 ◽  
pp. 07037
Author(s):  
Igor Lukasevich ◽  
Ludmila Chikileva
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Value Added ◽  
Stock Index ◽  
Series Data ◽  
Var Model ◽  
Oil Shocks ◽  
Russian Market ◽  
Russian Stock Market ◽  
The Impact

Research background: The study focuses on modeling assessment of oil shocks impact on the Russian stock market. Purpose of the article: The purpose of the study is to determine the impact of oil prices abrupt changes on the Russian stock market, its quantitative and temporal specifications. The study consists of two interrelated sections. The first section includes the results of statistical processing of initial data, calculation of their key characteristics and preliminary analysis. The second section of the study is devoted to modeling the assessment of the impact of oil shocks on the behavior of the Russian market RTS stock index. Methods: Based on an extensive sample of daily price values for Brent North sea oil and the Russian stock index RTS for the period from 1997 to May 2020, the study was conducted using models vector auto regression (VAR-model). Findings &Value added: The VAR model was developed and tested to assess the impact of oil shocks on the Russian stock market. Unlike the results of other studies, it is shown that the Brent oil price variance explains only about 10% of the RTS index yield variance in long-term time intervals. The low correlation of time series data and time limit of the impact of oil shocks on the Russian market have been revealed. According to the results of the study, the market recovery takes about 2 months, then the stock index returns to the ‘historical’ range of average ± standard deviation.

SPLINE ESTIMATION OF A SEMIPARAMETRIC GARCH MODEL

2015 ◽  
Vol 32 (4) ◽  
pp. 1023-1054 ◽  
Author(s):  
Rong Liu ◽  
Lijian Yang
Keyword(s):  
Time Series Data ◽  
Kernel Method ◽  
Financial Time Series ◽  
Garch Model ◽  
Real Data ◽  
Series Data ◽  
Link Function ◽  
Numerical Performance ◽  
Spline Estimation ◽  
Better Than

The semiparametric GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) model of Yang (2006, Journal of Econometrics 130, 365–384) has combined the flexibility of a nonparametric link function with the dependence on infinitely many past observations of the classic GARCH model. We propose a cubic spline procedure to estimate the unknown quantities in the semiparametric GARCH model that is intuitively appealing due to its simplicity. The theoretical properties of the procedure are the same as the kernel procedure, while simulated and real data examples show that the numerical performance is either better than or comparable to the kernel method. The new method is computationally much more efficient than the kernel method and very useful for analyzing large financial time series data.

Multi-Factor Fuzzy Time Series Model Based on Stock Volatility for Forecasting Taiwan Stock Index

2011 ◽  
Vol 211-212 ◽  
pp. 1119-1123 ◽  
Author(s):  
Ching Hsue Cheng ◽  
Jing Wei Liu ◽  
Tzu Hsuan Lin
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Stock Exchange ◽  
Time Series Model ◽  
Fuzzy Time Series ◽  
Stock Index ◽  
Series Data ◽  
Stock Volatility ◽  
Taiwan Stock Exchange ◽  
Proposed Model

Fuzzy time series have in recent years drawn many scholars' attention due to their ability can handle the time series data with incomplete, imprecise and ambiguous pattern. However, most traditional time series models employed only single variable (stock index) in forecasting, yet ignored some factors that would also affect the stock volatility. Therefore, this paper proposes a novel forecasting model using multi-factor fuzzy time series model to forecast TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock index). Multi-factor fuzzy time series model is composed of three main components: stock index, trading volume and interactions between two stock markets. In order to evaluate the performance of the proposed model, the transaction records of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock index) and NASDAQ(National Association of Securities Dealers Automated Quotations) from 2000/01/04 to 2003/12/31 are used as experimental dataset and the root mean square error (RMSE) as evaluation criterion. The results show that the proposed model outperforms the listing models in accuracy for forecasting Taiwan stock market.

scholarly journals Estimation of causal relationship between world gold prices and KSE 100 index: Evidence from Johansen cointegration technique

2018 ◽  
Vol 68 (1) ◽  
pp. 51-77
Author(s):  
Rizwan Raheem Ahmed ◽  
Jolita Vveinhardt
Keyword(s):  
Stock Prices ◽  
Time Series Data ◽  
Equity Returns ◽  
Stock Index ◽  
Series Data ◽  
Sample Period ◽  
Full Sample ◽  
The Third ◽  
Johansen Cointegration ◽  
The Impact

The aspiration of this research paper is to investigate the impact of international gold prices on the equity returns of Karachi Stock Index (KSE100 index) of Pakistan Stock Exchange. The daily observations from January 1, 2000 – June 30, 2016 have been divided into three sub-periods along with the full sample period on the basis of structural breaks. Descriptive analysis used to calculate the average returns, which showed significant returns of KSE100 for the full sample, the first and the third sample periods as compared to gold returns. Standard deviation depicted the higher volatility in all the sample periods. Correlation analysis has shown an inverse relationship amid equity returns and gold returns, whereas, Philips-Perron and Augmented Dickey-Fuller tests have been employed, and time series data became stationary after taking the first difference. Johansen cointegration results have shown that the series are cointegrated in the full-sample and the first sample periods. Thus, this has demonstrated the long run association amid equity returns and gold returns in the first sub-sample and the full-sample periods. However, the second and the third sub-sample periods do not exhibit long-term association amid equity returns of KSE100 and gold returns. The outcomes of Granger causality approach identified bidirectional causation amid equity returns and gold returns in the full sample period in lag 2, and unidirectional causality has been observed from gold prices to stock prices in the full sample and the first sub-sample periods in lag 1 and lag 2 respectively.

Impact of exchange rate and oil price on the yield of sovereign bond and sukuk: Evidence from Malaysian capital market

2017 ◽  
Vol 5 (4) ◽  
pp. 27
Author(s):  
Huda Arshad ◽  
Ruhaini Muda ◽  
Ismah Osman
Keyword(s):  
Exchange Rate ◽  
Capital Market ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Sovereign Bond ◽  
Long Run ◽  
Short Run ◽  
The Impact

This study analyses the impact of exchange rate and oil prices on the yield of sovereign bond and sukuk for Malaysian capital market. This study aims to ascertain the effect of weakening Malaysian Ringgit and declining of crude oil price on the fixed income investors in the emerging capital market. This study utilises daily time series data of Malaysian exchange rate, oil price and the yield of Malaysian sovereign bond and sukuk from year 2006 until 2015. The findings show that the weakening of exchange rate and oil prices contribute different impacts in the short and long run. In the short run, the exchange rate and oil prices does not have a direct relation with the yield of sovereign bond and sukuk. However, in the long run, the result reveals that there is a significant relationship between exchange rate and oil prices on the yield of sovereign bond and sukuk. It is evident that only a unidirectional causality relation is present between exchange rate and oil price towards selected yield of Malaysian sovereign bond and sukuk. This study provides numerical and empirical insights on issues relating to capital market that supports public authorities and private institutions on their decision and policymaking process.

Transport infrastructure of the Rostov Oblast: Problems and prospects for development in the context of national projects implementation

2020 ◽  
Vol 19 (6) ◽  
pp. 1015-1034
Author(s):  
O.Yu. Patrakeeva
Keyword(s):  
Time Series Data ◽  
Mutual Influence ◽  
Rostov Oblast ◽  
Transport Infrastructure ◽  
Series Data ◽  
Cointegration Tests ◽  
Level Of Economic Development ◽  
Short Run ◽  
The Government ◽  
The Impact

Subject. The paper considers national projects in the field of transport infrastructure, i.e. Safe and High-quality Roads and Comprehensive Plan for Modernization and Expansion of Trunk Infrastructure, and the specifics of their implementation in the Rostov Oblast. Objectives. The aim is to conduct a statistical assessment of the impact of transport infrastructure on the region’s economic performance and define prospects for and risks of the implementation of national infrastructure projects in conditions of a shrinking economy. Methods. I use available statistics and apply methods and approaches with time-series data, namely stationarity and cointegration tests, vector autoregression models. Results. The level of economic development has an impact on transport infrastructure in the short run. However, the mutual influence has not been statistically confirmed. The paper revealed that investments in the sphere of transport reduce risk of accidents on the roads of the Rostov Oblast. Improving the quality of roads with high traffic flow by reducing investments in the maintenance of subsidiary roads enables to decrease accident rate on the whole. Conclusions. In conditions of economy shrinking caused by the complex epidemiological situation and measures aimed at minimizing the spread of coronavirus, it is crucial to create a solid foundation for further economic recovery. At the government level, it is decided to continue implementing national projects as significant tools for recovery growth.

A Macroeconomic Analysis of Agricultural Sector in Nigeria

2019 ◽  
Vol 5 (1) ◽  
pp. 18-25
Author(s):  
Isah Funtua Abubakar ◽  
Umar Bambale Ibrahim
Keyword(s):  
Value Chain ◽  
Crop Production ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Tourism Industry ◽  
Series Data ◽  
Size Analysis ◽  
The Real ◽  
Real Gdp ◽  
The Impact

This paper attempts to study the Nigerian agriculture industry as a panacea to growth as well as an anchor to the diversification agenda of the present government. To do this, the time series data of the four agriculture subsectors of crop production, livestock, forestry and fishery were analysed as stimulus to the Real GDP from 1981-2016 in order to explicate the individual contributions of the subsectors to the RGDP in order to guide the policy thrust on diversification. Using the Johansen approach to cointegration, all the variables were found to be cointegrated. With the exception of the forestry subsector, all the three subsectors were seen to have impacted on the real GDP at varying degrees during the time under review. The crop production subsector has the highest impact, however, taking size-by-size analysis, the livestock subsector could be of much importance due to its ability to retain its value chain and high investment returns particularly in poultry. Therefore, it is recommended that, the government should intensify efforts to retain the value chain in the crop production subsector, in order to harness its potentials optimally through the encouragement of the establishment of agriculture cottage industries. Secondly, the livestock subsector is found to be the most rapidly growing and commercialized subsector. Therefore, it should be the prime subsector to hinge the diversification agenda naturally. Lastly, the tourism industry which is a source through which the impact of the subsector is channeled to the GDP should be developed, in order to improve the impact of such channel to GDP with the sole objective to resuscitate the forestry subsector.

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