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1
Tilakaratne, Chandima University of Ballarat. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12798.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
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Tilakaratne, Chandima. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15394.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
3
Tilakaratne, Chandima University of Ballarat. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12804.
Full textAbstract:
This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
4
Tilakaratne, Chandima. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15397.
Full textAbstract:
This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
5
Wan, Hon-kuen Francis. "The Hong Kong stock index futures market /." [Hong Kong] : University of Hong Kong, 1987. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12334868.
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Wan, Hon-kuen Francis, and 溫漢權. "The Hong Kong stock index futures market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1987. http://hub.hku.hk/bib/B31263926.
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Kalogeropoulou, Joanna. "Arbitrage in the FTSE 100 index futures." Thesis, Brunel University, 1998. http://bura.brunel.ac.uk/handle/2438/5396.
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This thesis presents five empirical papers investigating the issue of arbitrage trading of the FTSE 100 stock index futures. The first paper explores the effects of nonsynchronous trading on the spot index and develops a new technique as well as improving current methodologies for removing them. Studies in U. S. have shown that if the problem of non-synchronous trading is severe, the reported spot index is not reliable affecting the correct pricing of futures contracts. The second paper investigates the elasticity of supply of arbitrage in the futures market and the ability of the spot and the futures markets to respond to new information. It shows that arbitrage trading is initiated when spot prices largely drift apart from the futures prices. In addition, the futures prices tend to uncover new information before the spot prices, although this relationship is not stable over time. The analysis incorporates all possible channels of information to the -markets, which previous research fails to consider. The third paper analyses the behaviour of the deviation of the actual futures price from its theoretical value. Although this deviation is seen to have decreased its size over the years, it is still significant and persistent. Furthermore, it cannot be explained by the tax-timing option on pricing the futures or the effects of nonsynchronous trading. The fourth paper examines the presence, size and frequency of the profitability of the observed arbitrage opportunities by applying different transactions costs bounds to account for different classes of traders. After applying trading simulations arbitrage profitability is found to be frequent and significant, despite the fact that its size has decreased over the years. Finally, the thesis concludes with the fifth empirical paper which investigates the impact of futures trading on the spot and futures market volatility. It finds that arbitrage increases spot and futures price volatility but a volatile market brings the two markets closer on the whole, the thesis shows that although profitable arbitrage opportunities are not present in the long-run, they are not quickly removed in the short-run, allowing the spot and futures prices to drift apart.
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Holmes, Richard Roland. "The economics of stock index futures : theory and evidence." Thesis, Brunel University, 1993. http://bura.brunel.ac.uk/handle/2438/5391.
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This thesis aims to provide detailed investigation into the role and functioning of the FTSE-100 stock index futures contract, by examining four interrelated issues. Chapter 1 reviews the literature, demonstrating that stock index futures can increase investor utility by offering hedging and investment opportunities. Further, the price discovery role of futures is discussed. Chapter 2 investigates the risk return relationship for the FTSE-100 contract within a CAPM framework. While CAPM adequately explains returns prior to October 1987, post-crash the contract is riskier and excess returns and a day of the week effect are evident. Chapter 3 examines the impact of futures on the underlying spot market using GARCH, which allows examination of the link between information and volatility. While spot prices are more volatile post-futures, this is due to more rapid impounding of information. The view that futures destabilise spot markets and should be subject to further regulation is questioned. Chapter 4 examines futures market efficiency using the Johansen cointegration procedure and variance bounds tests which are developed here. Results suggest futures prices provide unbiased predictions of future spot prices for 1, 2 and 4 months prior to maturity of the contract. For 3, 5 and 6 months prior to maturity the unbiasedness hypothesis does not hold. Chapter 5 discusses the major role of futures; hedging. Hedge ratios and hedging effectiveness are examined in relation to duration and expiration effects. Hedge ratio stability is also examined. Finally, hedging strategies based on historical information are examined. Results show there are duration and expiration effect, hedge ratios are stationary and using historical information does not greatly reduce hedging effectiveness. The FTSE-100 contract is shown to be a highly effective means by which to hedge risk. Chapter 6 provides a summary and concluding remarks concerning the relevance of the research carried out here.
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Luo, Wu-chang. "The predictability of stock index futures markets in Taiwan." Thesis, University of Southampton, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423215.
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Yadav, Pradeep Kumar. "Studies on stock index futures pricing : a UK perspective." Thesis, University of Strathclyde, 1992. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21498.
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There has been considerable interest among market participants, market regulators and academics in the pricing of stock index futures contracts. Academic research in this area has been motivated by several considerations. First, the utility of these contracts for risk allocation and price discovery depends on the efficiency with which they are priced relative to the underlying index. Second, it has been widely believed that they have adverse impact on price dynamics in the stock market. Third, and most important, stock index futures offer the possibility of directly studying the economics of arbitrage in the context of market microstructure. This dissertation extends the theoretical framework on stock index futures pricing in two directions. First, within the static cost of carry framework, it generalises the forward pricing formula by allowing for cash market settlement procedures. Second, it shows that in the presence of arbitrage related transaction costs, the time series of stock index futures "mispricing" can be modelled as a threshold autoregressive (TAR) process, a piecewise linear autoregressive process in which the process parameters are path dependent. The TAR model is potentially attractive for many financial applications and this dissertation appears to be the first use of the TAR model in finance. This dissertation also provides substantial and significant new empirical evidence relevant to the theoretical issues involved. Inter-alia, it analyses several important aspects not adequately examined in past research, and it utilises the unique microstructural features of the London stock market to explore several major theoretical issues. The empirical analysis is based mainly on about four years of "time and sales" transactions data from the London International Financial Futures Exchange together with synchronous hourly cash index data.
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Wu, Pai-hao, and 吳百浩. "A Study of Price Discovery on Stock Index Futures─Taiwan Stock Index Futures and Mini Taiwan Stock Index Futures." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/24620139264200993095.
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碩士東吳大學
企業管理學系
94
Taiwan's stock index futures has launched for almost eight years since July 21,1998. The price discovery role of stock index futures was concerned by investors gradually. This paper examined the relationship between each two of Taiwan Stock Index , Taiwan Stock Index Futures and Mini Taiwan Stock Index Futures using Unit Root Test, Cointegration Test, Vector Error Correction Model and Granger Causality Test. The data were every-five-minute price measured from October 3,2005 to February 27,2006. The empirical results are as follows: 1.All the three series are stable series after first difference; therefore, they are I(1) series. 2.There was a long term cointegration vector existing between each two of three series; therefore, there were a long term balance relationship between each two of three series. 3.In the long term, the three series are all adjusted toward the equilibrium. Comparing the adjusted speed of three series, Taiwan Stock Index was the first, Mini Taiwan Stock Index Futures rated after Taiwan Stock Index, and Taiwan Stock Index Futures rated as the last. 4.Taiwan Stock Index Futures and Taiwan Stock Index affected each other. Mini Taiwan Stock Index Futures and Taiwan Stock Index affected each other. Both Taiwan Stock Index Futures and Mini Taiwan Stock Index Futures performed stronger function of price discovery than Taiwan Stock Index did. The power of price discovery function of Taiwan Stock Index Futures is similar to that of Mini Taiwan Stock Index Futures.
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Li, Te-Cheng, and 李德成. "Revisiting the Dynamic Linkage in Taiwan Stock Index, Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/34990848973540803341.
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碩士樹德科技大學
金融與風險管理系碩士班
100
This research uses the statistical methods proposed by Rahbek and Mosconi(1998), Granger(1969), and Pesaran and Shin(1998) to investigate the dynamic linkage between Taiwan Stock Index, Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures under the influence of exogenous variables such as NASDAQ Composite Index. The sample period is from July, 2004 to June, 2008. The conclusions are as follows: First, there is a long-term equilibrium relationship between these three endogenous variables. Second, from Granger Causality test we find that these three endogenous variables Granger cause each other. Finally, from the generalized impulse response analysis we show that all the impacts of these three endogenous variables on each other are all permanent, and the half lives are all about two months.
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Lin, Chia-yi, and 林家伊. "Price clustering in index futures: Evidence from Taiwan stock index futures contracts and MSCI Taiwan stock index futures contracts." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/00232105884011956496.
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碩士國立中正大學
財務金融所
96
This paper provides the evidence of price clustering for the Taiwan stock index futures contract（TX）traded on the Taiwan Futures Exchange（TAIFEX）, and the MSCI Taiwan stock index futures contract（STW）on the Singapore Exchange Derivatives Trading Limited（SGX-DT）by using intraday traded prices. The result documents the existence of price clustering in TX and STW for last digits of prices. About 47% and 25% trades cluster on 0 or 5 points in spite of the minimum tick size for TX and STW. Among the result, price clustering in TX is significant more than that in STW. In investigating the factors that influence price clustering, we find that the degree of price clustering is a negative function of trading volume or trade size, and a positive function of price level or volatility by using daily data. The results indicate that TX and STW support the negotiation hypothesis proposed by Harris（1991）as well as economic-cost hypothesis proposed by Grossman et al.（1997）, Kleidon & Willig（1995）. In addition, only STW agrees with attraction hypothesis proposed by Goodhart & Curcio（1991）. The intraday pattern of price clustering is also found in TX and STW eventually. An extremely high percentage of price clustering appears at the opening interval, with a moderately low percentage in the middle and closing intervals for a trading day.
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HSU, SHU-MING, and 徐菽銘. "THE IMPACY OF STOCK INDEX FUTURES ON CASH STOCK PRICES VOLATILITY:THE CASE OF SIMEX TAIWAN STOCK INDEX FUTURES." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/29069589943988906987.
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碩士國立臺灣大學
國際企業學系
86
SIMEX台股指數期貨於民國86年1月9日在新加坡上市，上市迄今不過一年 多的時間，雖然成交量已較初期增加，不過和其他成熟的國際性期 交所相比，仍有一段差距。環顧國外期貨市場之發展，猶如雨後春 筍般朝氣蓬勃，尤其是金融期貨近年來之進展更是一日千里，產官 學界及投資大眾均期盼即將開放的台灣股價指數期貨交易，能為證 券市場提供一個有效的避險管道。從國外期貨交易經驗發現，股價 指數期貨與現貨之間的互動關係及股價指數期貨上市對現貨波動性 的影響，均是期貨學術研究的重點。本研究擬以SIMEX台股指數期 貨資料進行實證，探討國外率先推出股價指數期貨對台股現貨市場 波動性之影響，以供國內建立指數期貨交易制度之參考。 本研究以SIMEX台股指數期貨為樣本，以日報酬率之變異數代表股 價之波動。研究目的如下：(1)檢視摩根台股指數之股性特徵及遲 滯性之檢定；(2)探討摩根台股指數在SIMEX上市是否會對現貨市場 的波動性造成影響。研究方法分別採用(1)李又剛(民國78年)所發 展出對於股性特徵之四項指標以及以Kleidon and Whaley(1992)所 提出以交叉相關係數來檢定遲滯性；(2)分別以F統計量及Levene統 計量來檢定股價指數期貨之上市效果。研究期間為SIMEX台股指數期 貨在新加坡上市前、後各50天(短期)、100天(中期)及200天(長期)。 經實證後得到以下的結果： 1. SIMEX台股指數期貨除了報酬率外，在風險、投機色彩及暴漲暴跌 上均表現得比現貨強烈。在遲滯性檢定方面，期貨有領先現貨波動的 趨勢，即現貨指數在反映市場訊息上要比期貨指數來的遲滯。 2. SIMEX台股指數期貨上市後， 波動性只有在中期有顯著上升的情形 ，但是顯著性在臨界邊緣，而短期及長期波動性則並無明顯的改變， 所以股價指數期貨上對於現貨市場的波動性並沒有很顯著的影響。 SIMEX started trading Taiwan stock index futures in January 1997. Its impact on spot market is of interest to policymakers as well as practitioners. This research studies the relationship between the volatility of futures prices at SIMEX and the cash index of Taiwan stock . The volatility is computed as the variances of daily returns. The empirical results show that during the sample period: (1) SIMEX Taiwan stock index futures behave stronger than cash stock prices in the four indicators of market characteristics ,(2) SIMEX Taiwan stock index futures trading has no significant
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LIN, SHIH-CHAO, and 林世釗. "The Research of Expiration Effect among TSE Stock Index, TAIFEX Taiwan Stock Index Futures, and SIMEX MSCI Taiwan Stock Index Futures." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/92273085997488969511.
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碩士國立臺北大學
企業管理學系
91
Since the listing of the futures, researches of the relationship between futures and spots were constantly announced; most of the discussions focus on the effect of the trading of the derivative financial goods to the spot market. The expiration effect is broadly studied and considerably important. However, those researches lay too much weight on foreign market with a partial view. Compared with foreign countries, Taiwan stock market still is relatively a small-scaled market, and the major influential market movers are foreign capital, investment trust and self-employment business three greatest artificial persons. Add to the factor of few turnovers, the market is easily operated. Reasonably, we figure that it is supposed to have significant expiration effect. In light of the reasoning, this research intends to study whether the maturity of TAIFEX Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures has the prominent expiration effect relation to the three markets which have the same target, with TSE Stock Index as the object. Owing to the fact that TAIFEX Taiwan Stock Index Futures starts on 21st, July, 1998, the research is based on the data from the first day of trading, to 31st, March, 2003, 1210 daily-record in total as data, applying Tri-variate GARCH (1,1) Model. The empirical results are briefly described as follows: I. In return: TAIFEX Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures show significant negative expiration effect. The possible reasons are─ a.Risk averters consider that the more close to the expiration day of index futures, the greater volatility it become, the more risky it is. So they tend to sell their holdings to avoid the intense volatility of expiration day. b.The arbitrageurs incline to sell out their spot, which result in the heavier pressure of selling holdings in the market. The negative return is because of selling their holdings from investors; the less volatility and volume is because of the retreat of investors. II. In the volatility: There is a significant expiration effect in TAIFEX Taiwan Stock Index Futures on and before the expiration day, and most of them are negative. The result shows that investors expect there will be expiration effect, which means higher uncertainty. Therefore most investors hesitate the attitude and keep their holdings before expiration day, which leads to less volatility. In the conclusion of the study, it provides, based on the analyses, investors the adoptable strategy of speculators and risk averters in bull and bear markets.
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Huang, Jing-Lin, and 黃景琳. "The Study on the Price-Volume Relationship of Taiwan Stock Index, Taiwan Stock Index Futures, and MSCI Taiwan Stock Index Futures." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/63799429779965671067.
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碩士長榮大學
經營管理研究所
93
This study chooses the daily data of Taiwan Stock Index(TS), Taiwan Stock Index Futures(TF), and MSCI Taiwan Stock Index Futures(MF) from July 21, 1998 to August 31, 2004. This study investigates price-volume relationship between spot and future markets by using bivariate GJR-GARCH(1,1)-M model. Furthermore, Each market volume is separated into expected and unexpected components by moving-average method and VAR model. The empirical results are as follows: First, asymmetric effects are existed in spot and future markets return series, and the negative impact level is greater than positive impact level. Second, all of three markets have risk premium effects. Investors required more premiun, when market risk increased. Third, after adding market volume in the asymmetric GARCH model, the volumes of spot and future markets influence the volatilities of themselves and others. Forth, after adding expected and unexpected volumes in the asymmetric GARCH model, unexpected trading on the volatility has more influence than expected trading. Finally, based on the MLE, comparing both TS v.s TF and TS v.s MF, we find which explanation of first group is better than second one.
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WAN, LU-CHIEN, and 萬露茜. "The Study of Relationships among Taiwan Stock Index，Taiwan Stock Index Futures，MSCI Taiwan Index and MSCI Taiwan Index Futures." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/39748739589942336693.
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碩士國立高雄應用科技大學
金融系金融資訊碩士在職專班
105
This study explores the correlation between Taiwan Stock Index，Taiwan Stock Index Futures，MSCI Taiwan Index and MSCI Taiwan Index Futures. Among them, the non-constant measurement method, using Cointegration test as evidence, view the variable between the short, medium and long-term equilibrium relationship between the results found that there is a long-term equilibrium between the variables. In addition, the Granger Causibility Test shows that the MSCI Taiwan Index Futures has a two-way feedback on the Taiwan Stock Index and the MSCI Taiwan Index, and its changes will affect the Taiwan Stock Index and the MSCI Taiwan Index. Observe the changes in the MSCI Taiwan Index Futures . In the empirical study of the impact response function, the variables are affected by the impact of their own, but the fluctuation caused by other variables decreases rapidly with the increase of the time delay. At the same time, the MSCI Taiwan Index is the same as the other variables. The number of more impact of the longer time. Forecasting error variance decomposition empirical results, Taiwan Stock Index and the MSCI Taiwan Index of the highest degree of self-interpretation, the strongest exogenous, Taiwan Stock Index Futures and MSCI Taiwan Index Futures is the most endogenous.
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Chien, Ming-Hua, and 錢明華. "An Alternative Approach of Taiwan Stock Index Futures Arbitrage: Using Sector Stock Index Futures and ETF." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/45539524026056629705.
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碩士國立臺灣科技大學
財務金融研究所
93
The sector stock index futures is unique in Taiwan futures market. This article proposes using sector stock index futures or sector stock index futures combination or the ETF as proxies to substitute spot stock index to carry on stock index futures arbitrage transaction. Not only avoiding inconvenient and limit due to trading on stock portfolio, but also lowering transaction cost, moreover, the stock index futures trading in Taiwan is active, liquidity risk shall not be a issue. In the long run, proxies for spot stock index selected by cointegration method have the nature of mean reversion. Excessive mispricing will eventually turn to arbitrage opportunities. This article demonstrates that stock index futures arbitrage using sector stock index futures or sector stock index futures combination or the ETF as proxies to substitute spot stock index can be transformed to a spread arbitrage transaction. The empirical results showed that the spread arbitrage profit after transaction cost was remarkable. However, being a kind of rist arbitrage, spread arbitrage might not be profitable in every transaction, but in the long run, positive average return per trade was statistically significant. Out-of-Sample analysis result showed there was no evidence that the profitability of spread arbitrage was predictable.
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TSOU, YI-YU, and 鄒宜祐. "High Frequency Trading Price Discovery between Taiwan Stock Index Futures and Mini Taiwan Stock Index Futures." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/44374003050583175692.
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碩士輔仁大學
金融與國際企業學系金融碩士在職專班
104
This paper investigates the lead-lag relationship between Taiwan stock index futures and mini Taiwan stock index futures. The contribution of the study is to segment the high frequency trading data as three parts of periods and six time range (including 10 milliseconds, one minute, five minutes, ten minutes, thirty minutes, sixty minutes.) ,then analyze whether the price discovery function and arbitrage opportunity be in the two index futures or not. The empirical results reveal that different market trends and different time range will cause different lead-lag relationships between Taiwan stock index futures and mini Taiwan stock index futures. To obviate the sixty-minute time range of the correction market trend, co-integration test manifests there is long-term balanced relationship between Taiwan stock index futures and mini Taiwan stock index futures. Vector error correction model and vector autoregression model manifest that between the two index futures exist arbitrage opportunities under one-minute time range of the bull trend and ten-minute time range of the correction trend. Besides, feedback causality and arbitrage opportunities exist in the millisecond time range of the three trends.
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Qiu, An-Di, and 邱安迪. "Price Discovery function among Taiwan Stock Index, ETF, Index Futures and Mini Index Futures." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/qqh2t8.
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碩士國立交通大學
財務金融研究所
105
Hasbrouck (1995) proposed Information Share Model as the main research method, during the period from January 4, 2010 to December 28, 2012 between five minutes of the closing price of the data, the Unit Root Test, cointegration test and vector error correction model (VECM) to the final use of information share model to explore the Taiwan weighted index spot, futures, mini futures and Taiwan 50ETF price discovery between the degree of contribution relationship, and finally the use of regression analysis to explore the impact of various market price factors, the empirical results show that Taiwan weighted index spot, futures, mini futures and Taiwan 50ETF exist a cointegration relationship. From the vector error correction model, it is found that under the long-term equilibrium relationship, Taiwan 50ETF price discovery is stronger and the spot price discovery is weaker. Information Share Model shows that futures have a better price discovery ability. Regression analysis results find that the proportion of foreign transactions factors that affect the ability of price discovery.
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Su, Chung-Wei, and 蘇仲徽. "The Analysis of Stock Index Futures inTaiwan Futures Exchange." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/73122044882982256876.
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Chen, Chris W., and 陳其緯. "Stock Index Futures Arbitrage In Taiwan." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/39774531092678482984.
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碩士國立臺灣大學
商學研究所
85
This study uses intraday transaction data of SIMEX MSCI Taiwan Index futures to examine the relation between the cash and futures market. Under several arbitrage strategies, we investigate the frequency, persistence, and profits of index arbitrage. Trading restrictions and transaction costs will be considered in developing the arbitrage window. In addition to textbook-style index arbitrage, we also examine the performance of surrogate stock baskets.
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MENG-CHUN, CHO, and 卓孟君. "The relationship between futures trading activity and price volatility in Taiwan stock index futures and stock index." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/75183593021079668949.
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碩士長庚大學
企業管理研究所
95
This paper examines the relationship between futures trading activity and volatility for the stock index futures in Taiwan futures market. And also divided futures trading activity into two groups as expected and unexpected parts. GARCH models are employed to examine the relationship between futures trading activity and volatility, and it also employed to examine unexpected trading activity and volatility of asymmetric. From empirical results, we find that unexpected volume has a significant positive relation between price volatility and open interest of expected and unexpected has a significant negative relation between stock volatility. In asymmetric effects, finds that volume has a significant asymmetric effect and a significant positive relation between unexpected volume and price volatility, and the impact of positive unexpected volume shocks on price volatility is larger than the impact of negative shocks. We also finds that a significant negative relation between unexpected volume and price volatility, and there has no significant asymmetric effect in unexpected open interest.
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Chen, Chih-Yung, and 陳智永. "The Index Selections of the Taiwan Stock Index Futures." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/41549001283207073321.
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碩士國立臺灣大學
財務金融學系
86
In January 1997, Taiwan Stock Index Futures were introduced by SIMEX and CME respectively. It was also introduced by Hong Kong this May. Taiwan Mercantile Exchange has already been established, and its first future contract will be "Capitalization Weighted Index Future." Under the consideration of the hedging demand of the institution investors, this article aims to examine the hedging efficiency of SIMEX MSCI Future and Capitalization Weighted Index Future. Are these two index futures the best? Our selection criteria are "the sensitivities of indices," "the correlation between index returns and fund returns," "manipulations," "the difficulties of arbitrages," and "the correlation between indices." Two conclusions are drawn from our empirical studies: (1) Capitalization Weighted Index Future and MSCI Index Future are not the best objective indices for mutual funds hedging. Besides Capitalization Weighted Index Future, Taiwan Mercantile Exchange can consider to introduce "Electrical Index Future" and "Non- Financial Index Future." (2) As the OTC Market grows up, we can also consider to introduce "OTC Index Future" as the hedging tool for OTC mutual funds.
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Wu, Ju-Ping, and 烏汝蘋. "The Relationship between Taiwan Index Futures and Stock Index." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/22932994433915028958.
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碩士東吳大學
企業管理學系
95
The price discovery role of stock index futures was concerned by investors gradually since Taiwan's stock index futures has launched in 1998. This paper examines the relationship between Taiwan Stock Index and Taiwan Stock Index Futures by Unit Root Test, Cointegration Test, Vector Error Correction Model and Granger Causality Test. The data is every-five-minute price measured from October 2,2006 to March 30,2007. The empirical results are as following: 1.After first difference all the series are stable so that they are I(1) series. 2.There exists a long-term cointegration vector between series so that there is a long-term balance relationship between two series. 3.In the long term, the series are adjusted toward the equilibrium. 4. Taiwan Stock Index and Taiwan Stock Index Futures affect each other. 5. There are many studies about Taiwan Stock Index and Taiwan Stock Index Futures by daily data. However, the study about affection of different quarters is the exception and this is the main point of my study.
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Chen, Yu-jen, and 陳育仁. "A STUDY OF THE PRICE DISCOVERY AMONG TAIWAN STOCK INDEX, TAIWAN STOCK INDEX FUTURES AND MSCI TAIWAN STOCK INDEX FUTURES--APPLICATIONS OF THRESHOLD MODELS." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/6k78fa.
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碩士南華大學
財務管理研究所
95
Previous analyses using linear approach had failed to describe the asymmetrical dynamics between stock index and stock index futures. This study uses the threshold cointegration model and the multiple threshold model to investigate the asymmetry of long-run equilibrium among Taiwan stock index (TS), Taiwan stock index futures (TX), and MSCI Taiwan stock index futures (MX), and to explore the determined process of price discovery. The empirical results indicate a threshold cointegration and a nonlinear relationship exist among TS, TX, and MX. MX is the best indicator in price discovery process while TS is the worst. The finding suggests MX is the leading indicator of price fluctuation and informative in investing or hedging.
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Lee, Chun-Shen, and 李俊杉. "A Multivariate GARCH-M Approach to Investigating Price Discovery Processes of Taiwan Stock Index, Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/00497955856033404712.
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jhong, yang-jhih, and 鍾志揚. "The Value at Risk to Research of TAIFEX Taiwan Stock Index Futures and MSCI Taiwan Stock Index Futures." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/98466295253995388204.
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碩士朝陽科技大學
財務金融系碩士班
92
Abstract This article content is to utilizes the VaR(Value at Risk) the quantification, which provides a set of risk management for derivative financical commodity to the weight target. This article will use of the Taiwan Futures Exchange and the MSCI Taiwan Stock Index Futures to estimate the volatility parameter method, and then this article will union the Bootstrapping method which estimate VaR to establish a set of risk management for investor to be more precise. This research take Taiwan Futures Exchange and MSCI Taiwan Stock Index Futures as the research object, which use the different measurement statistics pattern to discuss the Index Futures settlement price volatility relations , and the hope achieves the goal: First, Taiwan Futures Exchange and the MSCI Taiwan Stock Index Futures are obtains to estimate the volatility parameter, and the discuss Taiwan Futures Exchange and MSCI Taiwan Stock Index Futures which have the asymetrical effect, and existence influence direction. Second, this research will take different measurement pattern for Taiwan Futures Exchange and MSCI Taiwan Stock Index Futures to annotate result of volatility relations. Third, this research use the VaR to provide the VaR sector for risk management tube pattern. Real diagnosis result as follows: 1st, in the volatility trend analyse, model capture bid the price volatility by the GJR GARCH to be best, which responded the actual data have the volatility clustering effect, the leptokurtosis characteristic, as well as the the asymmetrical effect,etc. Although the Taiwan Futures Exchange and MSCI Taiwan Stock Index Futures the have asymmetrical effect by no means extremely obvious, but MSCI Taiwan Stock Index Futures model capture bid the volatility effect to be best in the GJR GARCH. 2nd, in the VaR sector analyse, the different GARCH model union the Bootstrapping method to figure out the VaR sector. When we analyse VaR sector change, along with the confidence standard change (95% confidence standard with 99% confidence standard), which let GARCH(1,1)-T union the Bootstrapping method VaR sector displacement direction to have the different result. when the model use differently ,which influense of the VaR scope size. GARCH (1,1)-T model can revise the GARCH model wave mobility too noisily to dye the effect, as well as the describe data of the leptokurtosis characteristic, and GARCH (1,1)-T model can bid VaR sector position and the scope to be more precise. keypoint：GARCH model、Bootstrapping method、VaR
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Huang, Po-kai, and 黃柏凱. "Three Empirical Essays on Stock Index Futures." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/23032943608367881860.
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博士國立中正大學
財務金融所
96
This dissertation focuses on three important topics in stock index futures: speculative trading, optimal hedge ratios, and volatility transmission. We expect that through investigating the experience of U.S., U.K, and Japan, our results can provide a guide for the future development of Taiwan's futures markets. The first chapter, titled "Speculative Trading and Volatility in Stock Index Futures Markets", studies the relationship between speculative trading and intraday volatility in the S&P 500 stock index futures market over the period from 1982 to 2003. We propose a proxy variable for speculative activities to remove hedgers’ trading activities from volume. We find that that our proxy for speculative futures trading has a more powerful influence on futures intraday volatility than the ratio of the volume to the open interest and the volume itself. In addition, the results indicate that there is a positive and significant relationship between futures intraday volatility and speculative trading. It suggests that speculation destabilizes financial markets and that imposing regulatory limits on speculation appears to be necessary for improving market condition. The second chapter, titled "The Stock Index Futures Hedge Ratio with Structural Changes", estimates the optimal stock index futures hedge ratio for S&P 500, FTSE 100, and Nikkei 225 stock indexes using bivariate GARCH model with structural changes (bivariate ICSS-GARCH). We use ICSS (Iterated Cumulative Sums of Squares) algorithm proposed by Inclan and Tiao (1994) to identify time points of structural changes in the financial time series. Our results show that except for FTSE 100, the bivariate ICSS-GARCH model does not outperforms the OLS and OLS-CI models. However, the bivariate ICSS-GARCH model has better performance than the bivariate GARCH model for all three markets. Our finding suggests the necessity to incorporate structural changes in GARCH models and shows the importance to consider structural changes when estimating the hedge ratios. The third chapter, titled "Volatility Transmission across Stock Index Futures When There are Structural Changes in Return Variance", investigates volatility transmission process between the U.S., U.K., and Japanese stock index futures markets. Most importantly, we examine that whether structural changes have effect on volatility transmission process. We use ICSS (Iterated Cumulative Sums of Squares) algorithm proposed by Inclan and Tiao (1994) to identify time points of structural changes exiting in the financial time series. Our results show that there is no common structural change in variances for three futures returns. This implies that diversification across stock index futures markets is possible. We find that volatility in three stock index futures markets are directly affected by its own lagged volatility. There are asymmetric volatility transmission effects between between Japan and U.K. and Japan and U.S. In addition, there are bidirectional cross market volatility transmission between U.K. and U.S. However, this relation does not hold after controlling for structural changes in the bivariate GARCH model. We find that the measure of volatility transmission differs in intensity from that otherwise estimated. These findings support that structural changes in variance and GARCH model misspecification influence information flow and hence the scheme of transmission.
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Wang, Jin-Bao, and 王金保. "Zipf analysis of Taiwan stock Index Futures." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/26736376711506623533.
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碩士國立高雄師範大學
物理學系
102
In this thesis, the time series of Taiwan Stock Index Futures was transformed to a symbolic sequence composed of “up”, “down” and “unchanged” states. The symbolic sequence was characterized by the K-tuple Zipf Analysis proposed by R.N. Mantegna et. al. We found that distinct plateaus appear in a Zipf-plot. The plateaus can be explained by cross over due to short repeats in the symbolic sequence. Furthermore, as a "up"("down") state with exceed trading volume occurs, the probability of the following "down"("up") state is larger than that of the following "up"("down") state after 2006.
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Chun, Lu Yi, and 盧易駿. "Taiwan Stock Index Futures Markets Efficiency Tests." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/86392025501170092368.
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碩士靜宜大學
企業管理學系
88
Abstract Taiwan stock index futures contracts are traded in the futures markets in Hong Kong、Singapore and USA, showing that foreign investor much needing Taiwan stock index futures contracts to manage their investment risk. This thesis presents some evidence of market efficiency on Taiwan stock index futures in Taiwan (TAIMAX) and Singapore(SIMEX). This study employs ADF and PP unit root tests to examine stationary of the time series data of the stock index futures prices, and examines the lead-lag relationship by cointegration analysis and Error-Correction Model(ECM). In addition, GARCH(1,1)-M model is utilized to examine the existence of risk premium, and to test the efficiency in the two futures markets. SIMAX’s sample period start from 8/1/1997 to 2/25/2000, having 693 observations. TIMAX’s sample period start from 7/21/1998 to 2/25/2000, totaling 426 observations. The observations are the daily settlement prices. The empirical findings can be summarized as following: 1. The four time series data have first-order differences. The spot and future prices of SIMAX and TIMAX can be characterized random walk. 2. The SIMAX future and spot prices have cointegration relationship. TIMAX futures and spot prices also have cointegration relationship. Those results satisfy the necessary condition of the efficient market hypothesis. 3. In Granger Causality, the SIMAX futures and spot prices have feedback relationship. However, the TIMAX futures and spot prices don’t have feedback or spontaneous relationship. 4. For lead-lag relationship, the SIMAX futures prices and SIMAX spot prices lead each other, but TIMAX futures prices just lead TIMAX spot prices. To compare the two futures markets, SIMAX lead TIMAX. 5. Since there is no risk premium found from the GARCH(1,1)-m model test, results are largely supportive of weak efficiency in two Taiwan stock index future market.
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Lee, Tzong-Haw, and 李宗皓. "Dynamic Linkage of International Stock Index Futures." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/45911186965405945821.
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碩士國立暨南國際大學
國際企業學系
89
Because of the growing globalization and integration of the world financial markets, increased research attention onto how financial disturbances transmit from one market to another, especially after the global crash of stock markets in October 1987. Since many empirical evidences strongly indicate that the futures prices almost consistently lead the stock index movements and thus perform an informational role. In this thesis, dynamic linkage across the U.S., U.K., and Japan equity markets are substitutive by observing the dynamic linkages of stock index futures daytime (open-to-close) returns and returns volatility over the period of September 1988 to May 1999. Applying the two-stage GARCH model and multivariate GARCH (BEKK-tGARCH) model, all of these three markets, conspicuously, are most influenced by their own-volatility spillovers of both innovations (ARCH effect) and conditional variance (GARCH effect) parts. While the Japanese market goes its own way to contrast the other two inseparable markets, the U.S. market reflects the innovation caused from the U.K. in a weak extent and it is tenable contrariwise. ARCH effect, GARCH effect, and leverage effect are statistically significant in all of the three markets; however, the most ARCH effect in Japan is caused by leverage effect. Furthermore, Both the two-stage GARCH model and BEKK-tGARCH(1,1) model have successfully diminished the serial correlation phenomenon, indicating that ARCH-type specification is adequate to catch the time-varying residual variance.
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Yao, Weng-Hung, and 翁鴻堯. "Arbitrage Opportunities of TAIMEX Stock Index Futures." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/78312990931435761585.
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碩士國立臺灣科技大學
管理研究所企業管理學程
87
Since Taiwan International Merchantile Exchange (TAIMEX) began to trade Taiwan stock index futures on July 21st in 1998, provided the investors a way of arbitrage. However using the strategy of arbitrage, the first step is to discover the opportunities of arbitrage --- a significant factor to get chance. According to the related studies imply to benefit between spot and futures by arbitrage trading, while the market is inefficiency. This article investigates the relative equilibrium between Taiwan stock index futures and stock market to analysis the arbitrage opportunities. The purpose of this study are stated as follow: (1) Investigating the timing that arbitrage occurred possibly include which section of intraday and which day of maturity. (2) To examine the features of arbitrage opportunities include: whether arbitrage opportunities are random , how long for persisting. (3) To demonstrate the effects between arbitrage opportunities and good or bad information. Result presented in this paper are based on the Taiwan stock index futures contracts of TAIMEX and composite stock index of TSE for the period from August to December 1998. We get the following results: (1) The different arbitrage opportunities exist in opening, middle and settlement of intraday. Even though the most frequencies of mispricing appear in opening, the degree of mispricing is not the highest .The most frequency of mispricing is in settlement; the most degree of mispricing is in middle. (2) The arbitrage opportunities diminish as the expiration day approaches. The frequency of mispricng trend to diminish as expiration approaches, especially before the second week or one-month. The degree of mispricing diminishes is similar to wave as expiration approaches, although it doesn’t constantly decrease. The most degree is the period of 1st-5th, 11th-15th,and over 30th days. (3) The appearances of arbitrage opportunities that seem to have a trend aren’t randomness, and also will continue 15-20 minutes. (4) The results show the good or bad information is independent from the frequency of arbitrage opportunities. So arbitrageurs don’t change their minds with information. Whenever good information that is before or present will not affect the degree of arbitrage opportunities. The results also show the degree of arbitrage opportunities will affect by the bad current information. Thus, it appears that the relationship between bad information and arbitrage opportunities is so obviously.
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Liu, Kai-Ping, and 劉凱萍. "Spread Trading in Taiwan Stock Index Futures." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/37362407981284721910.
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碩士淡江大學
財務金融學系
87
Spread trading of futures contracts is an essential futures market activity, providing an important component of market liquidity, particularly in the deferred contract month. Despite the practical relevance of spreading trading, treatment of this subject in the academic literature is incomplete and, typically, imprecise. A primary objective of this study to examine the extent to which intramarket and intermarket stock index futures spreads are priced consistent with the cash of carry model. The study uses daily transaction data of SIMEX MSCI Taiwan Index futures and Taiwan Stock Exchange Capitalization Weighted Stock Index futures to examine the abnormal price relationships, the results show significant deviations. Under several spread trading strategies, we investigate the frequency and profits of index spread trading. Trading restrictions and transaction costs will be considered in developing spread trading strategies. Evidence is also presented on the performance of risky spreads consisting of simply spreading strategies. The overall evidence strongly indicates that stock index futures spreads are inefficiently priced.
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Chang, Che-yu, and 張哲宇. "The Hedge Ratio of Stock Index Futures." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/38149083564414453144.
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lin, gow-ping, and 林國平. "price discovery function of stock index futures." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/19262902131392136278.
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碩士國立台灣工業技術學院
管理技術研究所
85
AbstractHedge and price discovery are major functions of futures. The research for price discovery function of futures always focuses on whether futures prices can forecast spot prices efficiently. The most popular methodology is to examine the causality (lead-lag) relationship between futures prices and spot prices.This thesis employs the unit root test﹑ cointegration﹑error correction model ﹑traditional Granger causality test and Garbade & Silber model to examine the price discovery function of stock index futures.Daily closing price of S&P 500 stock index futures and Nikkei 225 stock index futures were collected as samples from Jan. 1996 to Dec. 1996.The empirical results can be summarized as follows:1﹑All of price series are I(1).2﹑Both S&P 500 and Nikkei 225 stock index, Futures prices are cointegrated with spot prices in the long- run.3﹑Using error correction model to examine causality relationship find that futures prices lead spot prices significantly in both stock indexes.4﹑Using traditional Granger causality test and Garbade & Silber model also finds that futures prices lead spot prices.
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Chang, Sen-Kuei, and 張森魁. "The Determinants of Taiwan Stock Index Futures." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/01973107692333635218.
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碩士大葉大學
管理學院碩士在職專班
102
In recent years, with the increasingly sophisticated derivatives markets and the futures posses the funtions of speculative, hedging, arbitrage and price discovery, the futures market has become the new financial killing fields in finance. In this study, TAIEX futures open interest, TAIEX Taiwan Stock Index Futures futures trading volume and net foreign reserve position in the amount of ups and downs on the impact of Taiwan Stock Index Futures and using Unit root tests and Generalized Autoregressive Conditional Heteroskedasticity (GARCH model), to understand the TAIEX index futures open interest, Taiwan stock index futures trading volume and net foreign reserve position changes on the number of TAIEX Futures change the dynamic effects. The time span of this study is January 1, 2010 to June 30, 2013, a total of 865 daily data to analyze the research. This study also takes bull or bear market into account. Overall, whether bull or bear market, Taiwan Stock Index Futures net foreign reserve position change and TAIEX index futures Change has a positive correlation and be indicative of the role; Taiwan stock index futures open interest change and TAIEX index futures trading volume change is not indicative of the role.
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Jiang, Wen Chiang, and 江文強. "Hedging Effective Studies for Stock Index Futures." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/95081158858467628548.
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LIU, MICKEY, and 劉生璋. "Stock Index Futures -Theories and International Investment." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/99987599185626582864.
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Kuo, Chen-Yu, and 郭鎮宇. "LSTM-Based Taiwan Stock Index Futures Prediction." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/xam4d3.
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碩士國立臺灣大學
經濟學研究所
107
This study uses the price data of Taiwan stock index futures and several common technical indicators to create RNN and LSTM model to predict futures’ price data. LSTM model is a RNN model for processing time series data. Due to its special structural design, LSTM models are more suitable for data with long time periods or long delays, and are mostly used in image recognition and speech recognition. The price data in the financial market also has similar characteristics. This study attempts to apply deep learning models on futures price market to predict future futures prices.
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Lai, Meng-chen, and 賴孟辰. "Taiwan Futures Market Price Discovery Process-the Case of Taiwan Stock Index Futures and Mini Index Futures." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/26591607925965010853.
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碩士國立中央大學
財務金融研究所
99
Two futures contracts which have the same underlying asset do not have the simultaneous price reactions toward new information due to the differences in trader composition, contract specification, trading cost, and so on. The leading contract can reflect the new information in its price earlier. This article compares the information reaction efficiency and price discovery ability of the TX with MTX, the two important futures contracts traded in Taiwan Futures Exchange. Empirical results from pricing error model and relative information efficiency method suggest that two contracts have similar degree of random walk approximation. However, TX is shown to have better price discovery ability than MTX has. The article also finds that the local traders have better price discovery ability than foreign traders. The frequency and the trading volume of local traders are both much greater than foreign traders’, and this will decrease the explanation power of information share model.
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Lin, Guan-Hsien, and 林官賢. "Price Discovery Process-the Case of Taiwan Stock Index Futures and Mini Index Futures." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/77242996978416370122.
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碩士國立中央大學
財務金融研究所
96
This article examines the trading cost hypothesis by using Taiwan stock index futures and mini index futures. Empirical results show that Taiwan stock index futures, which has a lower trading cost than mini index futures, plays a dominant role in the price discovery process. The results suggest that trading cost hypothesis is supportive in Taiwan futures market. Moreover, the empirical results also find that, the institutional investors move the price of Taiwan stock index futures more than the individual investors do. In other words, the informed traders in Taiwan futures market are institutional investors, which is consistent with the findings in the European and American financial markets.
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Wu, Yawen, and 吳亞雯. "The Study of Relationship between Stock Index and Stock Index Futures in Taiwan." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/75045703849242023603.
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碩士中國文化大學
國際企業管理研究所
99
Because of continued integration of the financial markets, it makes the international liquidity improve and the degree of mutual influence in market increase. In the other hand, the investment tools become more innovation and diversification. The scale of Taiwan’s futures market is smaller than other countries. The Financial crisis made our government to cut the tax of futures in October 6, 2008 and change the Futures settle-ment in December 17, 2008. Our government wants to expand the scale of Taiwan’s fu-tures market and increase Taiwan’s futures market’s competitiveness. This report wants to approach the relevance between Taiwan stock market and futures market after government cut the tax of futures, and set up three main point-in-time, one period is Lehman Brothers collapsed in September 15, 2008, the other period is our government cut the tax of futures in October 6, 2008, another period is our government changed the Futures settlement in December 17, 2008. We divide the period to six sub-periods and Use time series methods to approach tax cuts how to influence the re-levance between Taiwan stock market and futures market and come to analysis the change of before and after tariff reduction. Research results show that futures to bring Price Discovery function after Futures tax cut.
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Wang, Wen-Shang, and 王文聖. "The Pricing of Stock Index Futures during the Early Period after Listing of Stock Index Futures: Evidence from the SGX FTSE Xinhua China A50 Index Futures." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/k9ca5x.
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碩士國立高雄第一科技大學
金融營運所
96
The subject of this study is SGX FTSE Xinhua China A50 Index Futures. The purpose of this study are (1) to compare the performance of pricing model of stock index futures, including cost of carry model, Hemler and Longstaff model(1991) and pricing model of stock index futures in imperfect markets. The volatility of stock index in Hemler and Longstaff model(1991) using four GARCH volatility models to estimate, then testing which GARCH model can enhance the performance of the Hemler and Longstaff model(1991).(2)to test whether the price performance of pricing model is significantly related to stock volatility, time to maturity and rate by using multiple regression analysis. The empirical results can be summarized as follows: (1)The pricing model of stock index futures in imperfect markets have the best performance among the pricing model of stock index futures and the cost of carry model is the worst. (2)The mean absolute percentage errors of the Hemler and Longstaff model(1991) do not differ significantly for four GARCH volatility model. (3)The stock volatility is significantly positive related to the three pricing model of stock index futures. It means that the more the stock volatility is, the more degree of the mean absolute percentage errors is.
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Yeh, Tsai-Jung, and 葉財榮. "The Dynamic Relationships between Stock Index and Stock Index Futures under Time-Varying Correlation Volatility Model: A Case of Taiwan Weighted Stock Index Futures Market." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/99459363691159217624.
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碩士真理大學
管理科學研究所
95
A multivariate EC-EGARCH model with dynamic conditional correlation is used to study the dynamic relationships between stock index and index futures on daily data from July 21, 1998 to December 31, 2006. The results reveal that Taiwan stock index and index futures price have long-run equilibrium relationships.When Taiwan stock index and index futures price deviate from long-run equilibrium relationshihs, it returns to equilibrium relationships through adjustment of stock index futures price. Taiwan stock index futures returns has price discovery function .Both the lag-one return volatility of Taiwan stock and index futures have influence on each current return volatility, and also have asymmetric influence on own return volatility. The return volatility of Taiwan stock index futures has cross-market volatility asymmetry spillovers effects on the one of stock index, but the return volatility of Taiwan stock index have not on the one of stock index futures Additionally, the dynamic conditional correlation between Taiwan stock index futures and stock index is affected by lag-one innovation residual, and also has persistence to the next period.The results of this study can afford a reference to investors.
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Hsuan-Yu, Lin, and 林軒宇. "A study of the Return and Volatility Interrelationship among the Taiwan Stock Index, the Taiwan Stock Index Futures and the MSCI Taiwan Stock Index Futures." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/84319325047245307225.
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Chen, Mei-Chuan, and 陳美娟. "A Study on the Relationship between Stock Index Futures and Stock Index - Emperical Case of Taiwan Stock Index." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/43256522725399775183.
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碩士中國文化大學
國際企業管理研究所
86
The study takes the SIMEX Taiwan Stock Index Futures and Taiwan Stock Index as the objectives. The major purpose focused on examine the relationship between these two markets'' prices, discussing the causality between these two markets with VAR( Vector Auto-Regressive) model, and providing some suggestions for investing in these two markets. The data was covered from Jan. 9, 1997 through Mar. 16, 1998, with total 332 sets of market price data. The results showed that the closing index of Taiwan Stock Index Futures andthe opening index of Taiwan Stock Index existed a co-integration. From the lagof the VAR model, we found that the closing index of Futures and the closing index of Stock showed a feedback relationship; the closing index of Futures ledthe first period and the 5th period of opening index of Futures; the closingindex of Futures led the 2nd period and the 5th period of opening index ofStock; the closing index of Stock and the opening index of Futures wereindependent; and the opening index of Futures led the 4th period of openingindex of Stock. From the Decomposition of Variance analysis, we found that no matter whichTaiwan Stock Index Futures opening and closing Index or Taiwan Stock Index opening and closing index were mainly affected by the closing index of Taiwan Stock Index Futures. From the impulse response function analysis, we found that only the closing index of Taiwan Stock Index Futures showed a positiveresponse, indexes showed both positive and negative response.
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Peng, Shi-Shu, and 彭喜樞. "The Influence of Stock Index Futures'' Introduction on Stock Market." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/67714010841656783556.
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Sheu, Maw Sheng, and 許茂盛. "Selection of Underlying Index for Stock Index Futures in Taiwan." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/91717582479669724517.
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Tsai, Chui-Chun, and 蔡垂君. "An Empirical Analysis of Taiwan Stock Index and Index Futures." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/09711912019494877487.
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博士國立臺北大學
企業管理學系
91
ABSTRACT This thesis includes six chapters to investigate the relationship between Taiwan stock index and nearby-month stock index futures. The major contents are from chapter two to chapter five. These topics are price discovery function, price-volume relationship, maturity effect and day-of-the-week effect. We apply VECM-Bi-EGARCH model, Mann-Whitney test, ANOVA and Kruskal-Wallis test to demonstrate. The data of return is measured by five-minute, intra-day, open-to-open, close-to-close and overnight; the volume data is measured by five-minute and total amount in a day from January 2, 2001 to June 30, 2002. Chapter two investigates the price discovery function, asymmetric volatility and cross-market volatility transmission on Taiwan stock index and index futures. We apply VECM-Bi-EGARCH model to test the relationship of return between stock index and nearby-month stock index futures. Three major findings obtain regarding the price discovery function: (1) Taiwan stock index futures leads stock market by ten minutes to two days when five-minute data, intra-day and overnight data are tested. (2) Negative shocks on index futures markets result in higher volatility in spot market. (3) Unexpected shocks on the spot market induce higher volatility in the futures market, and vice versa. Chapter three investigates the price-volume relationship, asymmetric volatility and price-volume volatility transmission on Taiwan stock index and nearby-month index futures by VECM-Bi-EGARCH model. Four major findings obtain regarding the price-volume relationship: (1) Five-minute trading volume leads price by as long as ten minutes both spot and futures market alike. (2) The immediate inference would be that five-minute futures trading volume leads futures price, which in turn leads five-minute spot return. (3) Bad news occurred in both spot and futures markets tend to enlarge volatility of both markets. (4) Unexpected changes in the trading volume of spot and futures market closely interact with the returns of both markets, with most significant interaction found between trading volume and return volatility. Chapter four investigates the maturity effect on Taiwan stock index and nearby-month index futures by VECM-Bi-EGARCH model and Mann-Whitney test. Three major findings obtain regarding the maturity effect: (1) Near the maturity day, the volatility of return and volume on stock index and index futures are larger. The result is the same as Samuelson Hypothesis (1965,1967). (2) On the last hour of maturity day, only the volume of stock index is larger. The result is the same as Stoll & Whaley (1987, 1990b, 1991). (3) In the first exchange hour of next morning, the price and volume reversal. The return and volume of stock index and index futures is larger than the last hour. The result is also the same as Stoll & Whaley (1987, 1990b, 1991). Chapter five investigates the day-of-the-week effect on Taiwan stock index and nearby-month index futures by VECM-Bi-EGARCH model, ANOVA and Kruskal-Wallis test. Two major findings obtain regarding the day-of-the-week effect: (1) On Mondays, the return and volume are negative and smaller than the other exchange day. (2) Even in the maturity weeks, the return and volume are also negative and smaller on Mondays. The result is the same as French (1980).