The main purpose of this dissertation is to investigate the interaction among implied volatility, investor sentiment and market index from the behavioral finance point of view. An implied index from the options volatility is constructed under the Black-Scholes-Merton options pricing model which could serve as a proxy of the expected index level reflecting the investors‟ sentiment. The threshold model is applied to examine the extreme regimes of sentiment proxies and the causal relationship between investor sentiment and market index is examined under different market scenarios. Finally the forecasting model considering the information content of investor sentiment is performed and the options trading strategy is proposed. Based on the data of Taiwan stock market covering the period from 2003 to 2007, our results indicate that the information content of investor sentiment could be a leading indicator under overreaction and the strategy incorporating the sentiment proxies outperforms the other competitors.
Early papers (Friedman, 1953; Fama, 1965) argued that noise traders are unimportant in the financial price formation process because trades made by rational arbitrageurs drive prices close to their fundamental values. However, the market anomalies, for example, the under-reaction and overreaction of stock prices, challenge the efficient markets theory. De Long, Shleifer, Summers and Waldmann (DSSW (1990) hereafter) modeled the influence of noise trading on equilibrium prices and motivated empirical attempts to substantiate the proposition that „noise traders‟ risks influence price formation‟. Barberis, Shleifer and Vishny (1998) present a parsimonious model of investor sentiment. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values. If sentiment indicators are risk factors in the time series of returns, they will have the ability to predict the future returns on portfolios, even after appropriately adjusting for other risk factors. These findings support the need for research on the interaction between stock market returns, variation of price formation and indicators of investor sentiment.
Taiwan‟s equity market has long been an indispensable emerging market for international investors. Index options involving the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX index options, abbreviated as TXO)
were first traded on December 24, 2001. The TAIEX covers all of the listed stocks on the Taiwan Stock Exchange (TWSE) excluding preferred stocks, full-delivery stocks and newly-listed stocks, which are listed for less than one calendar month. The statistical data published in the 2007 annual report of the Futures Industry Association (FIA) show that the trading volume of Taiwan Stock Exchange Capitalization Weighted Stock Index options (TAIEX options) ranks twelfth in the world, which indicates its increasing importance for global asset management.1 The high trading percentage of individual traders in the Taiwan equity (about 70%) and derivatives (about 50%) markets might also imply that the noise trading or the investor sentiments might be the cause of the price variations. This study therefore proceeds to examine the rapidly-developing Taiwan stock market.
There are three parts in this essay. They present three independent papers, respectively. In the first part of the dissertation, the causal relationships between sentiment and returns under different market scenarios are investigated. In contrast to previous studies that subjectively identify the bullish and bearish markets, we apply a threshold model to detect the extreme level of investors‟ sentiment econometrically.
The empirical results show that most of the sentiment measures exhibit a feedback relationship with returns while ignoring different market states. However, sentiment could be a leading indicator if the higher or lower levels of sentiments were to be distinguished. Among them, the bullish/bearish indicator of ARMS, which is named after its creator, Richard Arms (1989), is a leading indicator if the market is more bearish (in the higher regime). Otherwise, the leading effect of the derivatives market sentiment indicators (the put-call trading volume and option volatility index) is discovered if the market is more bullish (in the lower regime). Our empirical findings further confirm the noise trader explanation that the causal direction would run from investors‟ sentiment to market behavior.
In the second part, the relationship between the information content implied by the options market-based volatility and the underlying stock index is analyzed through a threshold econometric model. A volatility index in line with the CBOE‟s new VIX is constructed by using intraday data for Taiwan‟s index options market as the research material. We then derive an implied equity index (TVII) from the Taiwan volatility
1 The FIA is the only association that is representative of all organizations having an interest in the futures market. The FIA has more than 180 corporate members, and reaches thousands of industry participants. Further information may be found on the website http://www.futuresindustry.org/.
index under the Black-Scholes-Merton options pricing scheme. We examine the co-movements and causalities between the TVII and the TAIEX (Taiwan stock exchange capitalization weighted stock index, TAIEX) through the vector error correction model (VECM) and threshold VECM (TVECM) in different market scenarios. The empirical results substantiate the claim that the nonlinear two-regime TVECM provides an appropriate fit for the dynamics between the TVII and the TAIEX.
Investors participating in the Taiwan stock market could rebalance their equity portfolios while the implied index derived from the call options (TVIIC) takes precedence over the TAIEX.
In the last part, an algorithm for an effective option trading strategy based on superior volatility forecasts using actual option price data for the Taiwan stock market is proposed. The forecast evaluation supports the significant incremental explanatory power of investor sentiments in the fitting and forecasting of future volatility in relation to its adversarial multiple-factor model, especially the market turnover and volatility index which are referred to as the investors‟ mood gauge and proxy for overreaction. After taking into consideration the margin-based transaction cost, the simulated trading indicates that a long or short straddle 15 days before the options‟
final settlement day based on the 60-day in-sample-period volatility forecasting recruiting market turnover achieves the best average monthly return of 15.84%. This study bridges the gap between option trading, market volatility, and the signal of the investors‟ overreaction through the simulation of the option trading strategy. The trading algorithm based on the volatility forecasting recruiting investor sentiments could be further applied in electronic trading and other artificial intelligence decision support systems.
The remainder of this paper is organized as follows. Chapter 1 introduces the dissertation with the organization. Chapter 2 briefly discusses the relevant literature.
Chapter 3 outlines the measurements of volatility and investor sentiment. Chapter 4 investigates the interaction between sentiment indicators and stock market returns under different market scenarios. Chapter 5 analyzes the interaction between the implied index from the options and the equity index in Taiwan. Chapter 6 proposes the options trading strategies based on volatility forecasting considering the investor sentiment. Finally, the conclusions drawn from this dissertation are presented in Chapter 7.