本篇論文分成三部份探討S&P 500選擇權市場投資人交易隱含資訊與日曆價差組合策略。第一部份主要經由選擇權標的資產波動、成交量、波動率指數、期貨報酬、期貨與現貨關係，研究買權與賣權之價內、價平與價外投資行為所反映投資人風險偏好、市場預期與交易動機。實證資料利用去除平均數方法降低到期效果之干擾，統計發現S&P 500選擇權市場投資人權衡價外較高風險與價內較高持有成本，實際傾向交易價平之選擇權，實證結果亦發現買權與賣權投資人皆具風險趨避偏好與市場反轉預期，賣權投資人交易動機為避險；而買權投資人交易動機則為投機。亦發現價內選擇權可以獲得較價外選擇權高之投資報酬。
    第二部份成功利用一階自我迴歸跳躍模型捕捉S&P 500選擇權買權與賣權之間價性距離變動跳躍的強度，藉此探討買權與賣權即多空部位投資人對市場資訊反應是否一致？實證結果發現77.33% 的反應是一致的，但也有22.67%的反應不一致，尤其當市場發生較大事件衝擊期間。後續利用標的資產價格、波動與無風險利率分析發現，當市場低度不確定性即風險較低時，買權與賣權投資人反應較一致；反之當市場高度不確定性即風險較高時，買權與賣權投資人反應較不一致。
    日曆價差是利用到期效果創造水平價差交易策略，第三部份計算連續120組S&P 500選擇權近月與次近月之買權與賣權，距到期日前7天至前3天之日曆價差績效，利用最小迴歸虛擬變數模型與數值解方法，估計最適靜態與動態交易策略。靜態交易策略實證結果發現價平的買權與賣權績效較價內與價外高，距到期日越遠日曆價差績效越好，距到期日前7天至前3天價平賣權績效皆較其他組合高；動態交易策略則經由前1日標的資產或波動率指數報酬變動作指標作為買權與賣權、價內與價外交叉組合，實證結果發現，雖然動態交易策略日曆價差績效皆較靜態交易策略佳，但其適用時點常必須當市場發生較大衝擊。

In the first part of this thesis measures option investors’ risk preferences and the motivations underlying option trading behavior by using the adjusted moneyness when initial moneyness has been influenced by the time-to-maturity effect in the contract month. The adjusted moneyness is calculated using the de-mean process by removing the average moneyness of each trading date prior to the expiration date for the minimization of anomalies. The statistics of the adjusted moneyness indicate that both call and put option investors essentially prefer to trade at-the-money options The regression estimation also confirm that both call and put option investors have significant risk-aversion preferences and market-reversion expectations. Furthermore, put option investors’ motivation underlying option trading behavior is hedge, but call option investors’ trading activity is motivated by speculation. In addition, another goal in this part of thesis is to determine the relationship between option returns and its moneyness. The finding confirms the option investors trade in-the-money options that can obtain larger capital gains than trade out-of-the-money options.
For measuring the option’s response against the market information, the second part of this thesis successfully captures the time-varying jump intensity of the range of option moneyness spread by the autoregressive conditional jump intensity (ARJI) model. This study finds the option investors’ response of 77.33% and 22.67% observations is consistent and inconsistent against the market information, respectively. Furthermore, the relationships between option investors’ response and underlying asset’s price variation and volatility, and risk-free interest rate are use to investigate the option investors’ expectation for the market trend. The option investors have similar expectations when the low degrees of market uncertainty, relative to the low degrees of market uncertainty, the high degrees of market uncertainty causes the option investors have dissimilar expectations. Therefore, the option investors are consistent or inconsistent response to the market information which follows their similar or dissimilar expectation for the market trend under conditions of the degrees of market uncertainty.
The calendar spreads often created when the option returns have anomalies that might occur close to the expiration date. In the final part of this thesis uses the least squares dummy variable (LSDV) model and numerical analysis to investigate performance of the optimal static and dynamic trading strategy of call and put option calendar spreads across time-to-maturity and option moneyness in the S&P 500 Index Options (SPX) market. This study finds that both the neutral calls and puts calendar spreads have the highest outperformance than bullish and bearish, and the premium payoffs are obvious declining along the time-to-maturity. By using the static trading strategy, the investors can create the neutral puts calendar spread to maximize their expected profits. Relative to the static trading strategy, the dynamic trading strategy respects to the underlying asset prices and market volatility can maximize the investors’ expected premium payoffs, despite the one-period lagged price variations of the underlying S&P 500 Stock Index and VIX may not be good signals because they merely operate when the high degrees of market shocks.

TABLE OF CONTENTS

Page
Acknowledgement  i
Abstract in Chinese  ii
Abstract in English  iii
Table of Contents  v
List of Tables  vii
List of Figures  viii

PART I

The option moneyness in relation to measurement of the investors’ risk preferences and motivations underlying the trading behavior  1
Abstract  2
1. Introduction  3
2. The data and option moneyness and returns definitions  12
2.1 The data  13
2.2 Option moneyness and return definitions  14
3. Hypotheses and empirical models  22
3.1 Hypotheses  23
3.2 Empirical models  28
4. Empirical findings and following discussions  30
5. Conclusions  35
References  38

PART II

Is the option investors’ response consistent against the market information?  42
Abstract  43
1. Introduction  44
2. The data and option moneyness definitions  47
2.1 The data  47
2.2 Option moneyness definitions  49
3. The ARJI model  53
4. Results for the ARJI model  57
5. Discussion of the option investors’ expectation for market trend  62
6. Conclusions  65
References  68

PART III

The optimal static and dynamic trading strategy of the calendar spread in the S&P 500 Index Options market  71
Abstract  72
1. Introduction  72
2. The performance measurement models  76
2.1 The static trading strategy  77
2.2 The dynamic trading strategy  78
3. The data  82
4. Empirical findings  85
5. Conclusions  91
References  93
 
LIST OF TABLES

PART I
Page
Table 1 Descriptive statistics for call and put options  21
Table 2 Empirical results of the adjust moneyness and option returns  35

PART II

Table 1 Descriptive statistics  53
Table 2 Estimation results of the ARJI model for the range of option moneyness spread  61
Table 3 The events relevant to the higher maximum of the jump intensity  62
Table 4 Regression results in equation  65

PART III

Table 1 The descriptive statistics for the profits of the entire calls and puts calendar spreads 84
Table 2 The estimated expected premium payoffs by using the static trading strategy of calls and puts calendar spreads of each the trading day before the expiration date and of each option moneyness  88
Table 3 The estimated expected premium payoffs by using the static trading strategy of calls and puts calendar spreads across the trading day before the expiration date and option moneyness  89
Table 4 The estimated expected premium payoffs and optimal threshold values by using the dynamic trading strategy of calls and puts calendar spreads across the trading day before the expiration date and option moneyness  90

LIST OF TABLES
PART I
Page
Table 1 Descriptive statistics for call and put options…………………………….21
Table 2 Empirical results of the adjust moneyness and option returns…………35
PART II
Table 1 Descriptive statistics……………………………………………………….53
Table 2 Estimation results of the ARJI model for the range of option moneyness
spread..61
Table 3 The events relevant to the higher maximum of the jump intensity…….62
Table 4 Regression results in equation.65
PART III
Table 1 The descriptive statistics for the profits of the entire calls and puts
calendar spreads 84
Table 2 The estimated expected premium payoffs by using the static trading
strategy of calls and puts calendar spreads of each the trading day before the
expiration date and of each option moneyness……………………………………88
Table 3 The estimated expected premium payoffs by using the static trading
strategy of calls and puts calendar spreads across the trading day before the
expiration date and option moneyness…………………………………………….89
Table 4 The estimated expected premium payoffs and optimal threshold values
by using the dynamic trading strategy of calls and puts calendar spreads across
the trading day before the expiration date and option moneyness………………90

LIST OF FIGURES
PART I
Page
Fig. 1 Average option moneyness for each trading date before expiration date in
the near-term contract month……………………………………………………...21
Fig. 2 The daily adjust normal moneyness for call options spans sample periods
from December 20, 1999 to December 19, 2009…………………………………...22
Fig. 3 The daily adjust normal moneyness for put options spans sample periods
from December 20, 1999 to December 19, 2009…………………………………...22
PART II
Fig. 1 Average option moneyness for each trading date before expiration date in
the near-term contract month……………………………………………………...53
Fig. 2 Time-varying jump intensity for the range of option moneyness spread
during the sample period…………………………………………………………...61
PART III
Fig. 1 The time-vary premium payoffs of calls and puts calendars associated with
bullish, neutral and bearish………………………………………………………...85

PART I

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PART II

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Cao, C., Chen, Z., Griffin, J.M., 2005. Information content of option volume prior to takeovers. Journal of Business 78, 1073-1109.
Chakravarty, S., Gulen, H., Mayhew, S., 2004. Informed trading in stock and option markets. Journal of Finance 59, 1235-1257.
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Chan, W.H., Maheu J.M., 2002. Conditional jump dynamics in stock market returns. Journal of Business and Economic Statistics 20, 377-389.
Chan, K., Chung, Y.P., Fong, W.M., 2002. The informational role of stock and option volume. Review of Financial Studies 15, 1049-1075.
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PART III

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