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Wee, Marvin. "Institutional versus retail traders : a comparison of their order flow and impact on trading on the Australian Stock Exchange." UWA Business School, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0026.
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The objective of the thesis is to examine the trading behaviour and characteristics of retail and institutional traders on the Australian Stock Exchange. There are three aspects of these traders that are of particular interest to this study: (1) the information content of their trades, (2) their order placement strategies, and (3) the impact of their trading on share price volatility. Trades made on the basis of private information such as those by institutional traders are found to be associated with larger permanent price changes while trades by uninformed traders such as retail traders are found to be associated with smaller changes. In addition, institutional trades are found to have smaller total price effect compared to retail trades suggesting retail traders incur higher market impact costs. In order to profit from potentially short-lived information advantage, informed traders are expected to place more aggressive orders. The analysis of the order price aggressiveness showed institutions are more aggressive than other traders. In addition, retail traders are found to be less aware of the state of the market when placing aggressive orders. The analysis of the limit order book found significant differences between the contributions of institutional and retail traders to the depth of the limit-order book, with retail standing limit orders further from the market. This is consistent with the conjecture that uninformed traders such as retail traders have greater expected adverse selection costs. The effect of trading by retail and institutional traders on price volatility are also investigated. There is some evidence that retail traders are more active and institutional traders are proportionally less active after periods of high volatility. Also, the effect of the order activity from different trader types on volatility differs depending on the measure of order activity used.
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Silva, Kesley Leandro da. "Estratégias de momentum no mercado cambial." reponame:Repositório Institucional do FGV, 2016. http://hdl.handle.net/10438/15773.
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Utilizo dados semanais para investigar a lucratividade de estratégias de momentum no mercado de câmbio baseadas em dois diferentes métodos de extração da tendência, possivelmente não linear. Comparo a performance com as tradicionais regras de médias móveis, método linear bastante utilizado pelos profissionais do mercado. Eu encontro que o desempenho de todas as estratégias é extremamente sensível à escolha da moeda, às defasagens utilizadas e ao critério de avaliação escolhido. A despeito disso, as moedas dos países do G10 apresentam resultados médios melhores com a utilização dos métodos não lineares, enquanto as moedas dos países emergentes apresentam resultados mistos. Adoto também uma metodologia para o gerenciamento do risco das estratégias de momentum, visando minimizar as 'grandes perdas'. Ela tem êxito em diminuir as perdas máximas semanais, o desvio-padrão, a assimetria e curtose para a maior parte das moedas em ambas as estratégias. Quanto ao desempenho, as operações baseadas no filtro HP com gestão do risco apresentam retornos e índices de Sharpe maiores para cerca de 70% das estratégias, enquanto as baseadas na regressão não paramétrica apresentam resultados melhores para cerca de 60% das estratégias.
I use weekly data to investigate the profitability of momentum strategies in the currency market based on two different methods of trending extraction, possibly nonlinear. I compare the performance with the traditional moving averages rules, linear method of trading broadly used by market professionals. I find that the performance of all strategies is extremely sensitive to the choice of currency, lags parameters and the evaluation criteria. Nevertheless, the G10 currencies show better average results with the nonlinear methods, while the emerging market currencies show mixed results. I also adopt a methodology for managing the risk of momentum strategies to minimize the “worst crashes”. It works to lower the maximum weekly losses, the standard deviation, the skewness and the kurtosis for most currencies in both strategies. In terms of performance, HP filter with risk-managed momentum shows higher return and Sharpe ratio for about 70% the observations, while those based on nonparametric regression show higher numbers for about 60% the observations.
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Coufalík, Jan. "Opční strategie a oceňování měnových opcí." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-199783.
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The aim of this diploma thesis is to analyze and implement selected option pricing models using statistical software. The first chapter introduces theoretical basics of options as financial instruments ideal for hedging and speculation. The second chapter constitutes the core part of this thesis since it unveils theoretical concepts of risk-neutral pricing and at the same time analyze some basic, as well as highly sophisticated option pricing models. In addition, each model is accompanied by a practical example of their effective implementation. The final chapter characterize the most widely used option trading strategies and defines the ideal expected market development linked to each strategy.
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Aichele, Markus Ferdinand [Verfasser], and Manfred [Akademischer Betreuer] Stadler. "Strategic Aspects of Forward Trading on the German Electricity Market. Consequences for Volatility, Competition, and Investment / Markus Ferdinand Aichele ; Betreuer: Manfred Stadler." Tübingen : Universitätsbibliothek Tübingen, 2016. http://d-nb.info/116401790X/34.
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Yang, Chin, and 楊蓁. "Low Volatility Portfolio Trading Strategy." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/7a7f4u.
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碩士國立中央大學
財務金融學系
105
The low risk asset will earn high return, which is contrary to the traditional financial theory, and this phenomenon is called low volatility anomaly. This paper is about the relationship between low volatility portfolio return and market risk. First, verifying whether Taiwan stock market has low volatility anomaly phenomenon and whether market risk can explain low volatility portfolio return. Then, testing whether low volatility portfolio can predict market risk. Finally, analyzing low volatility trading strategy. The results show that the Taiwan stock market indeed has low volatility anomaly phenomenon and market risk will influence low volatility portfolio return, so low volatility portfolio return can be an indicator to predict market risk. In addition, low volatility trading strategy belong to short-term strategy.
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Fu, chenghui, and 傅正輝. "Volatility forecasting and option trading strategy." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/03475530824255219107.
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碩士輔仁大學
金融與國際企業學系金融碩士班
99
Title of thesis：Volatility forecasting and option trading strategy Department of Finance and International Business(Master’s Program in Finance) Fu Jen University Student：Fu,chenghui Advisor：Tsai,liju Total pages：41 Key word：Black-Scholes option pricing model、 ARIMA model、Options volatility index of Taiwan、GARCH model、Implied volatility、Straddle The volatility in the Black-Scholes option pricing model is commonly assumed constant.However, the actual volatility of asset prices in the market often changes over time. Thus, this article tries to use the predicted values of volatility to seek the entry time of the implementation of options trading strategies and to investigate their profits. In this paper, we adopt three methods to predict the volatility. They are as follows: 1.using ARIMA model to predict the options volatility index (vix index) of Taiwan . 2.employing GARCH model to predict the volatility of the Taiwan stock index. 3. directly using implied volatility itself as the prediction of volatility. After predicting the volatility, this article investigates the performances of two trading strategies. The first strategy is buying a straddle when the changes of the predicted volatility are greater than some threshold values, such as one or two standard deviations, etc.; and clearing the position when the changes of the predicted volatility are lower than some threshold values. The second strategy is to execute the trading by utilizing the information that asset prices are often negatively correlated with their volatilities It is buying a put option when the changes of the predicted volatility are greater than some threshold values and buying a call option on the contrary.This article compares among the different combinations of the above two trading strategies with three volatility predicting model to investigate which one is the most profitable.
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Huang, Guo-lun, and 黃國綸. "Tail Risk Trading Strategy Using Volatility-of-volatility Index." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8b2e8h.
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碩士國立中山大學
財務管理學系研究所
106
The purpose of this paper is to use a new model-free measure to proxy for tail risk and exploit option induced order imbalance (OOIB) to predict the return of this tail risk indicator. Unlike VaR or VIX based literatures, this paper exploits the volatility of volatility as measured by the CBOE VVIX index to measure tail risk events. In this study, the option induced order imbalance (OOIB) is the dynamic hedging position from VIX option market makers. The OOIB positively and significantly predicts the return of VVIX index, and it was mainly contributed by at-the-money options. This result indicates that the order imbalance in VIX option market has the information and predictability toward market volatility of volatility and tail risk events, this paper then develops a long straddle position on VIX options to capture tail risk returns.
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Tung, Yu-Chien, and 童于倩. "TXO Trading Strategy – Application on Volatility Smile." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/57891773416807383290.
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Tung, Yu-Chien. "TXO Trading Strategy - Application on Volatility Smile." 2007. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-1607200712392200.
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劉易霖. "Intraday Option Implied Volatility Curve Trading Strategy." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/14982396536877799563.
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碩士國立政治大學
金融學系
104
Option’s implied volatility smile curves discontinuous phenomenon exists when general investors buy or sell options, they won’t buy in every strike’s options. This paper attempts to use Taiwan Index Options (trading code: TXO) to construct a trading strategy based on the implied volatility. We use curve fitting method to capture volatility smile curve’s instant discontinuous. Although we find out that the strategy won’t make a profit, there were several times when TXO market’s implied volatility smile curves were discontinuous, and the market option price will eventually go back to the theoretical price.
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Hsieh, Yu-Sheng, and 謝育昇. "Volatility Forecasting Model and Volatility Trading Strategy： Constructing Technology Indexes Approach." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/j8u2s3.
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碩士輔仁大學
金融與國際企業學系金融碩士班
102
This studies based on using one minute within a day of the TXO as an object. As a unit of 1K per 30 minutes, and as the MHV model arrange with the Granger causality test to pick out the technology index, the ATR, which included the different realized volatility HAR-RV、HAR-RV-J、HAR-RV-CJ and other logarithmic form and standard deviation. The results showed that by adding true technology index can possibly improve the model prediction of the volatility ability. Also, the model including logarithmic form of realized volatility has a better performance on prediction ability. According to the prediction sample, the prediction of the best forecasting model uses the TXO market mock trading to buy straddle trading strategy.The result showed that there was no profit gained in the year of 2011 to 2013. After analyzed, it was found that while the sale was 30 minutes of the long call, the probability of gaining will be more than 50%, but if it was over 30 minutes, the gaining will be decreasing. Since this studies used lessening of the model prediction forecasting to be the cover, therefore, it turned out to have phenomenon of long a call contract at a low point and long a call contract within a high point,which caused trading loss to occurred.
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Chung, Han-hsun, and 鍾函訓. "Trading strategy of implied volatility spread - Using technical analysis." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/75891015277335574399.
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碩士國立中央大學
財務金融學系
101
In this paper, we investigate the information asymmetry between option market and stock market, and we also investigate the characteristics of option price leading stock price. If informed trader has private information, first of all, they will invest high leverage financial product, such as option. By observing the implied volatility spread of near the money and recent month option, we use technical analysis to determine whether implied volatility spread will diverge from theory interval or not and basing on these information we will get a buy or sell signal. Finally, since the information in stock market will lag behind the option market, we can do statistics arbitrage by buying or selling ETF ( 0050 ) in stock market. Empirical results suggest that using strategy of implied volatility spread can earn abnormal return, especially for Bollinger band strategy and KD strategy. After considering about transaction cost (tax and fee), these strategies still make unexpected return higher than 10%. Since the data of implied volatility spread are public resources, it proves that the stock market in Taiwan is inefficiency.
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Hsiao, Su-Chun, and 蕭淑君. "The Applications of Volatility Indicators on Option Trading Strategy." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/31173484118949686903.
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碩士輔仁大學
金融研究所
97
This thesis employs three years TAIFEX option (TXO) data from 1 January, 2006 to December 31, 2008 on daily basis and calculates the implied volatilities of these at-the-money options. Moreover, this thesis constructs two technical indicators based on these implied volatilities and verifies their empirical results. Strategy One called moving average indicator, uses short-term and long-term average indicators as a trading signal. As far as the empirical result is concerned, there is only one of four groups which can make profit. Due to the fluctuations of the implied volatility does not have trend like their underlying, the use of trend indicators like moving average indicators fails to make profit. Strategy Two called William indicators, makes use of several different periods of anti-William daily indicators as a trading signal. According to the empirical results, five of six groups can make profit. As such, it seems to imply that the use of anti-market indicators based on the option volatility trading technical indicators should be able to make profit. In addition, this thesis also takes advantage of implied volatility with different period anti-William indicator as a directional trading signal. Four of six groups can make profit, whereas the other two groups lose. Therefore, the empirical results shows that using the anti-William indicators as trading signal on directional trading is likely to make profit. To sum up, as far as these technical indicators are concerned, the anti-William indicator is better than the moving average indicator. However, the choice of different periods of anti-William indicators as a trading signal does have a great influence on the performance result. Besides, evidence also shows that the use of anti-William indicator on call options is better than on put options with the same period.
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Huang, Chun-Wei, and 黃君煒. "The empirical study on trading strategy form by implied volatility." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/08740604642661645509.
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Cho, Sfeng-Yuan, and 周聖淵. "An Empirical Study of Volatility Index Trading Strategy in Stock Market." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/55192666940391058587.
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碩士國立暨南國際大學
管理學院經營管理碩士學位學程碩士在職專班
100
This article uses the U.S. S & P index VIX composed of 16 kinds of trading strategies，view the U.S. S & P index，the Taiwan Weighted Index，the Hong Kong Hang Seng Index and Japan's Nikkei 225 index from 1993-2012 in four different regions of the rate of return effect. And the Monte Carlo method (Monte Carlo Simulation) simulation of the optimum parameters. The study found that the profitability of the Hong Kong Hang Seng Index in 2000，2000 Taiwan's Weighted index of profitability best. Which day less significant by 225 profitability. In addition，we found that the financial theory and empirical research consistent trading strategy，VIX index volatility the greater the more profit for investors.
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Yang, Shu-Jui, and 楊書睿. "Applying Linear Programming to Options Trading Strategy and Forecasting Implied Volatility." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/g5ydww.
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碩士國立臺灣大學
國際企業學研究所
105
Along with the popularization of the knowledge of options, many investors already know how to use different combinations of options to obtain profits. However, most of the strategies so far are based merely on the expectation of the underlying asset price. The options trading strategy that profit from volatility changes is still less used by investors. In general, the options trading strategies that profit from volatility changes can be split into the “options trading strategy” and the “volatility forecasting model”. In terms of options trading strategy, the most common portfolios are straddle and strangle. However, in the practice of real transactions, the way these strategies use their funds are not the most efficient, and these strategies can not completely offset the price risk. In terms of volatility forecasting model, most of the time series forecasting model has a low correctness in direction, which makes the options trading strategy unable to obtain positive return. This study will establish multiple options trading strategies, including the strategies that use linear programming to construct their portfolio. In addition, this study will build multiple volatility forecasting models, and consider several economic variables as the exogenous variables of the models. By combining all the strategies and models to carry out the backtesting, we can examine whether the options trading strategy that profit from volatility changes can generate profits or not, and find the most suitable options trading strategy and volatility forecasting model for it. The result of the study shows that it is possible to obtain positive return, whether it is a long volatility trading or a short volatility trading, or both. The best combination of options trading strategy and volatility forecasting model in the long volatility trading has the annualized return of 57.3%; and the best combination in the short volatility trading has the annualized return of 27.6%. If combine these two strategies, the strategy that trades both long and short volatility has the annualized return of 90.0%, and winning rate of 58.3%. In terms of options trading strategy, in the long volatility trading, the strategies that applied linear programming perform better than strangle strategies, and in the short volatility trading, there is no obvious advantages and disadvantages. In terms of volatility forecasting model, Using the 500 days rolling samples and one-step-ahead forecasts of the ARIMA (1,1,1) model, which takes TAIEX futures, S&P 500, Taiwan dollar exchange rate and GARCH (1,1) process into account, to conduct the backtesting can generate best trading result.
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Hung, Kuo-Sheng, and 洪國勝. "THE TRADING STRATEGY OF TAIWAN SECURITIES MARKET BASED ON VOLATILITY INDEX." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/59510023552616013908.
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碩士國立臺北大學
國際財務金融碩士在職專班
100
This dissertation aims to study the relationships between volatility index and Taiwan securities market, and try to establish the long and short-term trading strategies of Taiwan securities market based on volatility index collected during the period of January 1, 2004 to October 31, 2011. In addition to the models chosen based on the forecasting capability inferred from quantitative methods, the author further adopts empirical methods to validate the feasibility and profit and loss of each trading strategy. The conclusions of this dissertation can be summarized as follows: 1. The long-term long trading strategy, which is to buy Taiwan 50ETF (Stock Code: 0050) when volatility index is greater than 35 or 40 and sell when volatility index is less than 25, should be able to guarantee certain returns. The average holding period of stocks, however, will take a bit longer (about 140 days). 2. The short-term long trading strategy, which is to offset futures or options contracts after 2 days from opening long futures positions or nearby, at-the-money call options when volatility index is greater than 35 or 40 and its rate of change is greater than 5%, should be able to bring a better return. By carrying out such strategy, the trader will have a higher funds turnover rate and shorten the holding period to 2 days. 3. Regardless of any trading strategy, however, the positions can only be opened in the rapidly falling market with high volatility. We can further conclude that the trading strategies studied in this dissertation will only be implemented during the financial market crisis (such as the periods of the financial tsunami or the European debt crisis, etc.). The historical data also indicates that the strategies studied in this dissertation should be able to bring in excessive returns.
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Huang, Li-Chun, and 黃立群. "An Empirical Study of TAIEX Options Implied Volatility and Trading Strategy." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/15135628981738948348.
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碩士國立雲林科技大學
財務金融系碩士班
95
This thesis constructs the market volatility index of which underlying asset is Taipei Stock Exchange Capitalization Weighted Stock Index (TAIEX) and TAIEX futures respectively. In the research period, TAIEX was usually lower than TAIEX futures. The average implied volatility of call of which underlying asset is TAIEX is lower than of which underlying asset is TAIEX futures, and the average implied volatility of put is opposite. We also observe that the spread of implied volatility between call and put was lager when we used TAIEX as underlying asset. Using TAIEX futures as underlying asset would make the spread smaller. Even so, the difference between volatility index calculated by TAIEX and by TAIEX futures is negligible. Because the volatility index (VIX) is constructed by call and put, this procedure would make bias smaller. Besides, the other results of this research are as follow： 1. The changes of VIX negatively correlated with the market return, and there is asymmetric characteristics between VIX and the market return. 2. The average intraday VIX went up as the minutes ticked away. 3. According to the mean reverting characteristic of VIX, we constructed timing strategy for options market.After considering transaction costs, the strategy could not get abnormal returns. However, the control group of timing strategy could increase the rate of return per risk.
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KO, CHING-YU, and 柯青佑. "Trading Strategy and Investment performance of Volatility Index：Evidence from Taiwan Stock Market." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/res789.
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碩士世新大學
財務金融學研究所(含碩專班)
105
Investors are always influenced by their emotions and unable to make rational investment decision-makings. They follow the market trend blindly and always buy high and sell low and suffer losses. Past research showed relations of investor sentiment, asset price, and market return. Therefore, this study takes VIX as a proxy of investor sentiment and investigates the relation between VIX and the TAIEX using VAR model and Granger Causality test. Further, we construct feasible trading strategies according to the lead-lag relationship and then combine technical analysis indicators to derive investors’ feasible trading strategies. Finally, we use tradable ETF commodities to evaluate the investment performance of our strategies by using historical data. The results show positive returns and over 50 % winning chance for almost all the trading strategies except for the mid-capitalization 100 ETF. Therefore, we suggest that VIX combines with technical analysis indicators can help investors make better decisions.
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Chuang, Po-Hsiang, and 莊博翔. "An Application of Volatility and Grey Relational Analysis on Taiex Options Trading Strategy." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/x4b278.
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碩士國立臺灣科技大學
資訊工程系
100
This paper is mainly using the GRA(Grey Relational Analysis) at history volatility’s daily variation value and moving average’s daily variation value and design many trading strategies of Taiex option market by decision tree analyzing the relation between correlation and correlation degree, the design process including training, prediction and performance check. History volatility is a financial markets risk indicator of stock price’s standard deviation in the recent past. Moving average is the average cost of the market in the past. However, both history volatility and moving average are the smooth curve, the response time is easily to delay. So we take their daily variation value to analyze, it could decrease mistakes because reflects the market change in current time. Finally, the GRADT trading strategies only bull signal make a stable profit by simulation experiments and prediction result, so it prove the research to provide investors an operating reference in Taiex option market.
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Chou, Hsiao-Hsuan, and 周孝軒. "An Empirical Study of The Trading Strategy by Volatility Cone Threshold Estimator on TXO." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/17395525573782915072.
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碩士銘傳大學
財務金融學系碩士在職專班
102
Since the volatility forecasting is very important to derivative pricing, we consider that estimation of volatility is affected by the time to maturity (τ). By using the concept of the volatility cone derive from Burghardt & Lane (1990), we generate an empirical distribution of τ-Based historical volatility through the different horizon with various time intervals before the day to expiration of the option contracts to capture the time to mature volatility. Additionally, we consider the reverting effect of implied volatility that revert to the median of the historical volatility, and propose a threshold estimator. We explored the results that come from the option contract of index in TXO. Empirical data are from 2005-2014 Taiwan Economic Journal database. Based on The mean absolute error (MAE)、root mean square error (RMSE) 、Regression analysis and Trading strategy criterions. We find the new estimator of volatility will reduce the bias compare with the usual. The new estimator generates smaller forecast errors of realized volatility and is the basis of a profitable trading strategy.
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Wu, Yung Hui, and 鄔永輝. "The Empirical Study of Multi-Periods Volatility Breakout Trading Strategy on Taiwan Stock Market." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/92964532247164834952.
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碩士長庚大學
管理學院碩士學位學程在職專班經營管理組
99
This study proposes a new volatility breakout trading strategy and applied to Taiwan Stock Market , the trading rules refer to Lars Kestner (2003) - 「New volatility breakout logic」.The concept of the research is as followed: when short or medium-term stock price fluctuates abnormally, it may appear the same trend in the future. In this research, we design eight multi-periods volatility breakout trading strategies and follow them to invest in Taiwan Stock Market. To see if these strategies are good enough, we use average return and winning ratio to evaluate the performance. Finally, we use sharpe ratio to take these trading strategies compare with Buy-and-Hold strategy. The research chooses 95 stocks from Taiwan Stock Market, and the research period is from 2000/1/5 to 2009/12/31. This research will analyze the performance of stocks under the test period after adding the transaction costs. The results of the research are as followed: First, after adding the transaction costs, trading strategies proposed in this study couldn’t obtain abnormal return in-between the risk adjustment. Next, “trading filter” is the key of trend following strategy in this research and has enhanced the ability to filter the trading noises and to determine the market trend. Finally, the results also indicated that some kinds of stocks could obtain abnormal return by using the volatility breakout trading strategies.
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"The Impacts of Margin Trading on Rate of Return and Volatility in the Stock Market: A Study using the SVAR Model and Panel Regressions." Doctoral diss., 2018. http://hdl.handle.net/2286/R.I.49142.
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abstract: Although margin trading has significant impacts on the stock market, extant research has mainly focused on its effect on stock price volatility and has rarely examined its influence on the rate of returns. In addition, little systematic research has examined the differential effects of margin trading under different circumstances. This thesis examines the effects of margin trading in bull market, bear market, balanced market and among stocks included in main board, SMEs(small and medium-sized enterprises) board, GEM(growth enterprises board), as well as large-cap and small-cap in China. I further studied the long-, medium-, and short-term influences of margin trading on the volatility of stock price, return rate, and liquidity of the market by both using the SVAR model and conducting panel data analyses.
The findings show that: a)Volatility. Margin trading can effectively curtail the medium- and short-term volatility of the share price under any market condition but has no prominent influence on long-term volatility. b)Profitability. Margin trading enhances profitability in the bull market with an apparent leverage effect while having no significant effects on short-term profitability in the balanced market and the bear market. c) Individual shares with different attributes. The influences of margin trading on the large-cap and small-cap shares, shares with high vs. low PE ratio, shares included in the main board and SMEs stocks vary in different types of market. d) Liquidity. The influences of margin trading on the fluidity of market are significantly different in the bull, bear, and balanced markets.
Finally, I set up a new trading strategy based on the above conclusions. The result from hypothetical trading demonstrates that the newly-created trading strategy works better than the long-term holding strategy, highlighting the practical implications of this thesis in addition to its implications for researchDissertation/Thesis
Doctoral Dissertation Business Administration 2018
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Wu, Jia-sheng, and 吳家陞. "The Signaling of Option Implied Volatility Spread and The Relevant Trading Strategy: Evidence from Taiwan Option Market." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/53102413569301725181.
Full textAbstract:
碩士國立中央大學
財務金融學系
101
Extending from Cremers and Weinbaum (2010), this paper mainly examines the implied volatility spread of options, which is viewed as a leading indicator, impling the informed information and the expectation of the investors to the future. This paper uses leading indicator, the implied volatility spread of options, to construct two different strategies. The first strategy tries to see that whether the option market react the informed information pior to the stock market. It buys stocks when the implied volatility spread of options indicates an upward trend and short stocks when the implied volatility spread of options indicates a downward trend. The empirical results are mixed with the different measurements of the implied volatility spread of options. And there are no positive abnormal returns under this strateg when the trading cost is considered. For the first strategy indicates that the stock market and the option market might have different reaction to the same informed information in Taiwan market, this paper directly uses the implied volatility spread of options in pairs trading of options as the second strategy. The result shows that the second strategy produces high returns due to the highly-leveraged characteristic of options. Although the returns go down obviously as the trading cost is considered, they still beat the market over half of the years in the sample period.
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Hsu, Kai-Ning, and 許凱甯. "The Lead-Lag Relationship between the Implied Volatility and the Historical Volatility and the Related Trading Strategy – On the Basis of Taiwan Stock Index and Taiwan Stock Index Option." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/26630423853798802642.
Full textAbstract:
碩士國立成功大學
會計學系碩博士班
94
This research investigates the relationship between Taiwan stock index and Taiwan stock index options. The historical volatility of the return on Taiwan stock index and the implied volatility of the at-the-money call and put are measured based on the intraday data of Taiwan stock index and the close data of the at-the-money call and put corresponding to each trading day which are selected from 2002 to 2005. This research applies unit root test to see if the data generation processes of the three volatilities are stationary and vector auto-regression models to establish the lead-lag relationship between the historical and implied volatility. Impulse response function and forecast error variance decomposition , then , are used to explore the degree of the impacts by the two volatility have on each other . In addition, this research simulates two trading strategy: buying the call／put that the implied volatility is under-valued while selling the put／call that is over-valued, according to the closing implied volatility of the at-the-money call and put through 2005 forecasted by the VAR models described above. The empirical results are as follow: the data generation processes of the historical volatility of the return on Taiwan stock index and the implied volatilities of the at-the-money call and put are stationary; contemporaneous relationship exists between the historical volatility of the return on Taiwan stock index and the implied volatility of the at-the-money call while the implied volatility of the at-the-money put lead the historical volatility. Generally speaking, implied volatility is affected by its own shock which has only short-term effect while the historical volatility of the return on Taiwan stock index will response to the shock by its own and the implied volatility gradually equally . For the trading strategies under the consideration of trading cost, we still earn a positive profit on average no matter buying the call that the implied volatility is under-valued and selling the put that is over-valued or vice versa. The result means that the implied volatility of the at-the-money option has the property of mean reverse, according with the stationary data generation process of it.