(Luận văn) the impact of index futures trading on underlying stock index volatility empirical evidence from vietnam on vn30

STATE BANK OF VIETNAM MINISTRY OF EDUCATION AND TRAINING BANKING UNIVERSITY OF HO CHI MINH CITY _ lu an n va p ie gh tn to LE CHI TRUNG oa nl w THE IMPACT OF INDEX FUTURES TRADING d ON UNDERLYING STOCK INDEX lu nf va an VOLATILITY: EMPIRICAL EVIDENCE FROM VIETNAM ON VN30 z at nh oi lm ul GRADUATION THESIS z MAJOR: FINANCE – BANKING @ an Lu HO CHI MINH CITY, 2018 m co l gm CODE: 7340201 n va ac th si STATE BANK OF VIETNAM MINISTRY OF EDUCATION AND TRAINING BANKING UNIVERSITY OF HO CHI MINH CITY _ _ lu an n va p ie gh tn to LÊ CHÍ TRUNG oa nl w THE IMPACT OF INDEX FUTURES TRADING ON d UNDERLYING STOCK INDEX VOLATILITY: lu va an EMPIRICAL EVIDENCE FROM VIETNAM ON ll u nf VN30 oi m MAJOR: FINANCE – BANKING z at nh CODE: 7340201 z @ m co l gm SUPERVISOR: MsC NGUYỄN MINH NHẬT an Lu HO CHI MINH CITY, MAY 2018 n va ac th si ACKNOWLEDGEMENT A completed study would not be done without any assistance Therefore, the authors who conducted this research would like to express our deepest gratitude my supervisors Nguyen Minh Nhat for his supports, encouragement, invaluable academic advice Since this is a relatively new field at the Banking University of Ho Chi Minh City in particular and of Vietnam in general, so this study required a lot of expertise and knowledge of social psychology in finance Finally, I would like to dedicate my concluding words to all friends and fellows of mine Without their support, the work could not be done successfully lu an The author would like to undertake research projects with the topic name “The va Impact of Futures Trading on Underlying Spot Market Volatility: Empirical n tn to Evidence from Vietnam on VN30” The figures and references are cited from clear gh source and unity in the references The contents and results of this study have not p ie been published in any public works until the present time The author would like to oa nl w be responsible for my commitment d Ho Chi Minh City, May 2018 lu nf va an Student in charge z at nh oi lm ul Le Chi Trung z m co l gm @ an Lu n va ac th si lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si i ABSTRACT The onset of derivatives in Viet Nam and futures trading in specific may cause the concerns in the participants in market Over the world investors have started using derivatives to manage their risks and futures is one of the most effective one Since derivatives markets interact continuously with spot markets, the effect of derivatives markets on spot market volatility has become an important research topic The present study tries to estimate the effect of introduction of futures index on the underlying stock volatility in Vietnamese stock market To estimate the effect lu of introduction of derivatives on stock market, GARCH family models which are an known for their ability to model volatility Using these models, the asymmetric nature va n of stock returns and the volatility of stock returns on the introduction of derivatives tn to are checked Most of the previous studies break the sample period into two sub- ie gh periods, one period before the introduction of futures trading and one after that p introduction In this paper, we are going to use the same approach In order to capture nl w the volatility, we apply at the same time the EGARCH (1,1), GARCH (1,1) models oa for the pre-futures period and the post-futures period as well The results of this study d indicate that the introduction of futures leads to a change in the spot market volatility lu nf va an of the VN30 index but not significant and there is also the existence of leverage effect and huge difference of ARCH and GARCH effect impact on spot price volatility in z at nh oi lm ul each sub-period z m co l gm @ an Lu n va ac th si ii ABBREVIATION WORDS GARCH MEANINGS Generalized Autoregressive Conditional Heteroskedasticity Exponential Generalized Autoregressive Conditional Heteroskedasticity Integrated Generalized Autoregressive Conditional Heteroskedasticity Autoregressive Conditional Heteroskedasticity Ordinary Least Squares London Stock Exchange State Securities Commission Hanoi Stock Exchange Borsa Instanbul Exchange Ho Chi Minh Stock Exchange National Stock Exchange of India Stocks traded in the Shanghai and Shenzhen stock exchanges Hang Seng China Enterprises Index Top 50 companies in the Shanghai Stock Exchange EGARCH IGARCH lu an n va gh tn to ARCH OLS FTSE SSC HNX BIST HOSE NSE CSI p ie HSCEI A50 d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si iii LIST OF TABLE Table 2.1 Some typical previous research with GARCH Family models 27 Table 4.1 Descriptive and statistics of VN30 closing price in 10/2/2012 – 17/4/2018 43 Figure 4.2 VN30 Daily Closing Price Chart 43 Figure 4.3 VN30 Daily Logarithm Return Chart 44 Table 4.4 Descriptive and statistics of VN30’s return in 10/2/2012 – 17/4/2018 lu 45 an n va Table 4.5 Heteroskedasticity Test: ARCH Effect at latency 46 gh tn to Table 4.6 Heteroskedasticity Test: ARCH Effect at latency 46 p ie Table 4.7 Standard GARCH (1,1) model with dummy variable 47 nl w Table 4.8 Standard GARCH (1,1) model in two sub-period 47 d oa Table 4.9 Standard EGARCH (1,1) model with dummy variable 48 nf va an lu Table 4.10 Standard EGARCH (1,1) model in two sub-period 50 z at nh oi lm ul z m co l gm @ an Lu n va ac th si iv TABLE OF CONTENT ABSTRACT i ABBREVIATION ii LIST OF TABLE iii CHAPTER 1: INTRODUCTION 1.1 Necessity of the topic 1.2 Objectives and research questions lu an 1.2.1 Objectives va n 1.2.2 Research questions Research methodology 1.4 Subject of the research 1.5 Scope of research p ie gh tn to 1.3 nl w Significance of study 1.7 Thesis structure d oa 1.6 an lu nf va CHAPTER 2: THEORETICAL FRAMEWORK AND LITERATURE REVIEW lm ul 2.1 An overview of futures contract z at nh oi 2.1.1 Futures contract definition 2.1.2 Development of futures trading over the world 10 2.2 Stock Index Futures Trading .12 z @ gm 2.2.1 Index futures trading definition 12 co l 2.2.2 The onset of futures trading in Vietnam 14 m 2.3 Stock index volatility 16 an Lu 2.3.1 Stock index in Vietnam 16 n va ac th si v 2.3.2 Spot price volatility 17 2.4 Theoretical research basis 19 2.4.1 Review previous researches on impact of futures trading on spot market 19 2.4.1.1 Impact of futures trading on spot price volatility in emerging market countries 19 2.4.1.2 Impact of futures trading on spot price volatility in developed market countries 22 lu an 2.4.4 General approaches in previous studies .25 va 2.4.4.1 Determination the impact of futures trading on spot price n 2.4.4.2 Determination how spot price volatility has been impacted in two ie gh tn to volatility 25 p sub-period 27 nl w 2.4.5 Gaps of previous studies 30 d oa CHAPTER 3: DATA AND METHODOLOGY 32 an lu 3.1 Generalized Autoregressive Conditional Heteroskedasticity (GRACH) nf va model .32 lm ul 3.2 Exponential GARCH model - EGARCH(1,1) 34 z at nh oi 3.3 Testing for ARCH effect 35 3.4 Data processing .36 z 3.5 Research model .37 @ gm 3.6 Hypothesis 41 co l CHAPTER 4: RESULTS AND DISCUSSION OF RESULTS 43 m 4.1 Descriptive statistics .43 an Lu 4.2 Testing of ARCH effect on the set of data 45 n va ac th si vi 4.3 Empirical findings and results of estimation of GARCH model 47 4.3.1 Results on existence of the impact of futures trading introduction on spot price volatility – GARCH (1,1) with dummy variable 47 4.3.2 Results of GARCH estimation in two sub-period .48 4.4 Empirical findings and results of estimation of EGARCH model 49 4.4.1 Results on existence of the impact of futures trading introduction on spot price volatility – EGARCH (1,1) with dummy variable .49 4.4.2 Results of EGARCH estimation in two sub-period .50 lu an 4.4.3 Comparing with other emerging market countries 52 n va CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS 54 gh tn to 5.1 Conclusion .54 p ie 5.2 Policy implications 55 w 5.3 Limitation and suggestion for further research .57 oa nl REFERENCE i d APPENDIXES .vi nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si 54 CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS 5.1 Conclusion The operation of futures markets and the introduction of futures contracts trading in stock markets have produced many important changes in the volatility of the markets and more particularly, in the volatility of the underlying asset Many studies have shown that the introduction of futures markets leads to a decrease in the volatility of the underlying index lu This paper examines the impact of futures trading in the VN30 contract on the an va volatility of the underlying market using both symmetric and asymmetric GARCH n techniques Tests undertaken to determine whether there exist asymmetries in the gh tn to response of volatility to news suggest that for the VN30 index the response of p ie volatility to news was symmetric The results reported for the VN30 index indicate that while the existence of futures trading has made little impact on the underlying oa nl w level of volatility, as measured by the standard deviation d The results indicate that there is a great impact in the spot market volatility of an lu the VN30 index after the introduction of futures contracts because of the significance nf va of the coefficient of the dummy with all GARCH family models In addition, this lm ul impact is negative because the coefficient of the dummy is negative Thus, there is a z at nh oi decrease on the volatility of the VN30 after the introduction of futures The crucial idea in this research eventually could be determined with the EGARCH analysis result which can satisfy the objectives and questions in this research z gm @ According to both GARCH (1,1) and EGARCH (1,1) analysis result, we can see obviously in the post-futures period the information flowing into the market l co perform less rapidly than the pre-futures period In contrast with Hypothesis 1, we m realize the introduction of futures would not improve the speed of information an Lu flowing to the market The reason accounting for this phenomenon can be that the n va ac th si 55 listed enterprises want to control and prevent their stock price on the market from the frequent significant fluctuation so that only small percentage of volatility in the spot price could be explained by the information in the previous period In addition, with EGARCH (1,1) analysis we also determine the presence of asymmetry regarding the response of volatility to news The study also found asymmetric fluctuations during market downturns This shows that the sudden increase or decrease in stock indexes has affected the volatility of the stock index at time t + 1, however, this effect is small, only 3.12 % which is in line with the Hypothesis However, we have to note that in the post-futures the leverage effect does not exist in our set of data because the time lu an after the post-futures may not be long enough to capture the asymmetry, but it would va be fine if we try to capture the asymmetry whole the period from 2012 to now n tn to Consequently, we also have other further action and behavior without leverage effect ie gh in the pre-futures p 5.2 Policy implications nl w At this time, it is not possible to say that the stock market is successful or not, d oa but according to experience from the stock market development as well as the attitude an lu of the market, I believe in the success of the derivatives market since the document process, the law is fully adequate, suitable and meet the requirements of the market nf va In order to obtain such legal regulations, the world stock market has experienced great lm ul ups and downs and draws on lessons learned from market management We have z at nh oi opportunity for learning, inheriting those experiences and reflecting the new management of the world As a result, the legal basis has responded well to market z management @ gm On the other hand, members of the market, stock exchanges and securities m international standards and prepare them carefully co l depository centers have been well aware that the system construction must meet an Lu n va ac th si 56 The SSC can fully trust the initial achievements that derivatives has achieved after nearly a year of implementation while market participants also expressed their strong interest, active coordination with the SSC so high depth Investors who have some experience in joining the market, but with the stock market is still new so they are interested Along with the objectives set out, futures trading has partly helped the market to stabilize volatility, creating the next momentum along with good support from the macro economy Based on the results, the SSC has more facilities to launch new derivative products Particularly, the index on the HNX was also a noticeable tool Based on the results of the research, the reflection of information is significant lu an to the volatility of stock prices, especially after the launch of derivative product, the va rate of information reflected in the market will react quickly Therefore, the launch n tn to of the next derivative product for the HNX will also contribute to reflect the ie gh information of the market for stock prices because the companies listed on the HNX p are similar and also receive interested in comparison with HOSE nl w As a result, the advent of DERIVATIVES has influenced the volatility of the d oa spot market, the hedge funds and securities companies will be able to obtain more an lu reasonable tactics in each stage Derivative derivatives are such a good hedging tool that investment funds are fully capable to help their investors achieve the highest nf va return When the fund can use the results of this study to increase confidence in the lm ul spot market Investors are aware that when the quality of information flows into the z at nh oi market and reflected in the price, derivatives is a tool that will help a lot while buying stock, after days to sell (T+3) Buying derivatives, the next day is allowed to sell to z profit or cut losses The market is up or down, investors can make profits, interest or l gm @ losses reflected on the account every day Although the spot market after the introduction of the futures contract has been co m downward fluctuations, however, the drop is not so much a good opportunity for the an Lu fund to restructure its portfolio Especially the VN30 analysts in the fund should have n va ac th si 57 a short-term analysis and forecast the impact of information to the basket of stocks rather than focus technical analysis in the medium term For individual investors, the advent of derivatives during this period will become a very effective hedge Especially when the amount of information flowing into the market tends to reflect the price is not as fast as before, investors will have more time to analyze and choose the most suitable investment tactics Plus, when the market there is the existence of leverage effect This shows that the sudden increase in or decrease in stock indexes affects the volatility of the stock index at time t + 1, lu but this effect is small in the study period This Investors need to be cautious about an shocks from the market n va tn to 5.3 Limitation and suggestion for further research The selected data sample from 2012 (the onset of VN30 index) to 2018 We p ie gh Limitation of research w can realize that there is a huge gap between the pre-futures period and the post-futures oa nl period regarding the trading days leading to the bias sample However, we just d consider the this limitation when comparing the difference in volatility of two-sub an lu period whether it increase or decrease, destabilize or not while this data sample still nf va relevant and applicable for this approach to inspect the impact of futures introduction two sub-period as well z at nh oi lm ul on spot price volatility and the effect of recent news or old news on the volatility in It seem to be difficult to determine and select the data sample for the prefutures period or really hard to set the appropriate tome The main reason here is that z @ our sample in the pre-futures is not sufficient due to the short period of futures trading of VN30 introduction co l gm Thus, it would be reasonable and acceptable if we select the data from the beginning m We just utilize the typical GARCH model to detect the impact of futures an Lu trading on the market volatility While there are many GARCH family models to n va ac th si 58 overcome these drawbacks of regression or homoscedasticity models Due to the lack of time the author cannot have understanding on the application of other GARCH family models Moreover there are also some better models in improving the forecast results such as I-GARCH, T-GARCH ANN-APGARCH, so that using GARCH and EGARCH could be considered as not fully cover the volatility of the market Suggestion for further researches Apparently, the appropriate data sample is really important especially in case of comparing and analyze the impact between two-sub period Thus, the further lu research should put more attention on selecting the reasonable period for both pre and an post-futures In the further research we may have sample in the post-futures which is va n more sufficient than the current one but for the pre-futures we have to decide the The other GARCH family models should be taken into account and continue p ie gh tn to suitable period in order not to incidentally make our data sample bias to make use of their function to capture the volatility of the spot market for variety of nl w aspect Moreover, we can continue to use the model in this research and upgrade them d oa with more variable such as industry variable or….In addition, further research should an lu consider to use the criterion as SIC, AIC to decide the optimal model With the nf va extended model we can recognize the impact of futures trading by the other factors not only the recent news 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Farlex Financial Dictionary (2009) Retrieved May 27 2018 p ie gh tn to 223056.aspx https://financial dictionary.thefreedictionary.com/Stock+Index+Future d oa nl w Serge Berger (2016) How to trade volatile market Education – Glossary and trading terms https://www.ig.com/za/glossary-trading-terms/volatilitydefinition lu an https://www.investopedia.com/articles/stocks/04/122204.aspx nf va Hai Ho (2017) “Thi truong chung khoan, dong luc tang truong nen kinh te” Tap chi tai chinh – Kinh te vi mo - Chung Khoan Ngan hang lm ul z at nh oi http://tapchitaichinh.vn/kinh-te-vi-mo/thi-truong-chung-khoan-dong-luctang-truong-nen-kinh-te-125509.html Huy Phuong (2017), “Mot thang, gia tri giao dich phai sinh đat 6.450 ty dong”, Nhan Dan Trang Chung Khoan – Phai Sinh z m co l gm @ http://www.nhandan.com.vn/chungkhoan/phai-sinh/item/34037002-motthang-gia-tri-giao-dich-phai-sinh-dat-6-450-ty-dong.html an Lu n va ac th si vi APPENDIXES Testing for ARCH effect at latency lu an n va p ie gh tn to nl w d oa Testing for ARCH effect at latency nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si vii GARCH analysis model with dummy variable lu an n va gh tn to p ie Result of GARCH (1,1) in pre-futures period d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si viii Result of GARCH (1,1) in post-futures period lu an n va p ie gh tn to d oa nl w Result of EGARCH (1,1) with dummy variable nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si ix Result of EGARCH (1,1) in pre-futures period lu an n va p ie gh tn to d oa nl w Result of EGARCH (1,1) in post-futures period nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si x lu an n va p ie gh tn to d oa nl w nf va an lu z at nh oi lm ul z m co l gm @ an Lu n va ac th si