行政院國家科學委員會專題研究計畫 期中進度報告
金融商品在不同交易場所價格發現的比較：以台指期貨與現
貨及新台幣匯率為例(1/2)
計畫類別： 個別型計畫 計畫編號： NSC94-2416-H-004-051- 執行期間： 94 年 08 月 01 日至 95 年 07 月 31 日 執行單位： 國立政治大學財務管理學系 計畫主持人： 張元晨 報告類型： 精簡報告 報告附件： 出席國際會議研究心得報告及發表論文 處理方式： 本計畫可公開查詢中 華 民 國 95 年 5 月 25 日
行政院國家科學委員會補助專題研究計畫成果期中
報告
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金融商品在不同交易場所價格發現的比較：以台指期貨與現貨及新台幣匯率為例(1/2)※
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計畫類別：;個別型計畫 整合型計畫
計畫編號：
NSC 94－2416－H－004－051執行期間：
94 年 08 月 01 日 至 95 年 07 月 31 日計畫主持人：張元晨
本成果報告包括以下應繳交之附件：
□赴國外出差或研習心得報告一份
□赴大陸地區出差或研習心得報告一份
□出席國際學術會議心得報告及發表之論文各一份
□國際合作研究計畫國外研究報告書一份
執行單位：國立政治大學財管系
中 華 民 國 95 年 5 月 25 日
行政院國家科學委員會專題研究計畫成果報告
國科會專題研究計畫成果報告撰寫格式說明
Preparation of NSC Project Reports
計畫編號：NSC 94－2416－H－004－051
執行期限：94 年 08 月 01 日 至 95 年 07 月 31 日
主持人：張元晨 國立政治大學財管系
共同主持人：
計畫參與人員： 林姿秀
一、中文摘要 本文嘗試利用 Hasbrouck (1995) 提出 的的資訊內涵比率比較我國股價指數現 貨、期貨與選擇權市場價格發現程度的差 異。實證資料使用台灣經濟新報所提供的 日內交易價格，同時本文也進一步分析造 成性質類似商品其價格發現程度差異的原 因，以提供市場參與者進行交易時的參 考。本文利用我國自 2002 年 1 月 2 日到 2004 年 3 月 19 日之間的日內交易價格。 本文的實證結果發現我國期貨市場較現貨 市場及選擇權市場具有較大的價格發現功 能，在選擇權市場交易中又以價外的選擇 權交易較有資訊內涵。因此可以得知資訊 較佳的投資人在選擇權交易中比較重視價 外的選擇權所帶來的槓桿效果。 關鍵字：資訊內涵比率、台灣股價指數現 貨、期貨與選擇權市場Abstract: This paper examines the
information processing among spot, futures, and option markets in an emerging market. Based on data from Taiwan's stock, futures, and options markets, we examine the information processing role of each market with particular attention to liquidity, option types, option moneyness, and market cycles. We conduct price effect analysis, weighted average price contribution analysis, and information share analysis to reveal the informational role of derivatives. We find that trades on futures contribute the most to price discovery and are the most costly in
executing information trading. The information role of options varies with moneyness and market cycles. Options are more informative during a downtrend period. Out-pf-the-money options have higher permanent price effects, greater price contributions, and larger information shares than other options, which suggests that informed traders are more concerned about an option's leverage than its delta or vega. We also document that informed traders are more likely to buy out-of-the-money calls than sell out-of-the-money puts in an uptrend market, and vice versa during a downtrend. Our results indicate that in-the-money options are less informative, and market cycles as well as option moneyness affect the informational role of options.
Keywords: Information share, Taiwan’s
options and futures markets.
二、研究動機
The informational role of derivatives markets in the price discovery process has drawn great attention from academicians and practitioners. Certain market structures may generate larger or more frequent temporary price distortions, or prone to error. It is our interest to investigate the quality of transaction prices among different markets and information contained in the transaction prices across different trading venues. We
explore the role of price discovery for derivatives in the Taiwan markets. We compare information contributions among the Taiwan stock spot index (TXI), the index futures (TXF), and the implied index price derived from the index options (TXO). We use the tick-by-tick and transaction data to analyze the price discovery process under different market cycles and option moneyness. We extend Chakravarty, Gulen, and Mayhew (2004) study to the Taiwan markets.
三、研究方法與結果
We use three methods (the price effect analysis, the weighted average price contribution analysis, and the information-share analysis) to assess information flows among the equity, futures, and option markets. The price effect analysis compares the permanent, temporary, and total price effects of trades in different trading venues (e.g., Keim and Madhavan, 1996, and Booth, Lin, Martikainen, and Tse, 2002). The market with the greater permanent price effect and smaller temporary price effect should contain more information and less noise than other markets The weighted average price contribution analysis (WAPC) identifies which trades move price (e.g., Barclay and Warner, 1993, Huang, 2002) and it examines the venue contributing meaningful price movements and provides a single measure of price leadership. The information-share analysis, closely related to Hasbrouck's work (see, e.g., Hasbrouck, 1991, 1995, and 2003), estimates a trading venue's contribution to price discovery and traces the shares of information attributed to different markets. Controlling for market cycles, option types, and option's moneyness, we offer unique insights into how the information role of options varies under different options
characters and different market conditions.
Our results indicate that, regardless of market cycles, Taiwan's futures market has the largest permanent price effect, highest weighted average price contribution, and the largest information share. Thus, the trades on futures are the main driving force for in the price discovery process. The futures market is the price leader and it contains the greatest amount of information. However, it also has the highest total price effect. Hence, the futures market is more costly to Consistent with the previous findings
based on the mature markets, the Taiwan stock index futures market play the most significant role in price discovery. Regardless of market cycles, the futures transactions have greatest permanent price
effect, the highest weighted average contribution to price discovery, and largest information share among the index markets. Trading futures, however, is most costly in executing informed trades. With respect to options, when pooling options data together irrespective of options moneyness and market cycles, we find that options have small permanent price effects, possess low contribution to price changes, and account less than ten percent of information share. However, when options are classified according to different moneyness and controlled for market cycles, the test results vary across options' moneyness and market conditions. Out-of-the-money (OTM) options have more impacts on price discovery process than other options. The finding indicates that option leverage plays an important role in determining which option segments informed traders trade in the options market. Short-sale constraints and the price change limit rule in the Taiwan Stock Exchange make options more attractive to informed traders in a downtrend market. We also find that informed traders are more likely to buy OTM calls than sell OTM puts in a uptrend market, and vice versa during a downtrend. On the contrary, in-the-money (ITM) options do not contribute to price discovery in either uptrend or downtrend market. The findings in the option markets suggest that options' sensitivity to underlying asset movements is not a major factor affecting informed trading activities in Taiwan. For robustness results, we also control for liquidity in the option market. Although the price discovery contributions of options tend be positively related to options trading volume, option moneyness and market cycles still matter.
trade relative to other markets.
We also find that the options market contributes to price discovery as well. Nevertheless, in comparison with the futures trades, the transactions on options are less essential in price driving, have lower permanent price effects, and contribute less to price innovations. Interestingly, the empirical results suggest that the information content of options varies as market conditions change. During the downtrend period, options have greater permanent price effects, higher weighted average price contributions, and larger information shares that that of uptrend period. Thus, informed trading is more active in the option market during the downtrend period than the uptrend period. This may be due to the short-sale constraints and the price change limit rule in the Taiwan Stock Exchange.
When options are classified into different moneyness, the test results reveal that, irrespective of market cycles, OTM options have the highest permanent price effect, greatest price contribution, and largest information share among all the options. This finding is more pronounced for OTM call options during the uptrend and OTM puts during the downtrend period. These results suggest that an option's leverage outweighs its delta and vega in determining where informed traders trade. We also document that informed traders are more likely to buy OTM calls than sell OTM puts in an uptrend market, and vice versa during a downtrend market. On the other hand, ITM options are not informative. The results are robust with respect to different options' liquidity. Liquidity is positively related to the informational role of options, but it cannot fully explain all results. Moneyness and market cycles do matter for informed trading in the option market.
四、參考文獻
Barclay, M. J., and J. B. Warner, 1993. Stealth trading and volatility: which trades move prices? Journal of Financial Economics, 34, 281-305.
Bekaert, G., and G. Wu, 2000. Asymmetric volatility and risk in equity markets,
Review of Financial Studies, 13, 1-42.
Booth, G. G., R. W. So, and Y Tse, 1999. Price discovery in the German equity index derivatives markets, Journal of Futures Markets, 19, 619-643.
Booth, G. G., J.C. Lin, T. Martikainen, and Y. Tse, 2002. Trading and pricing in upstairs and downstairs stock markets, Review of Financial Studies, 15, 1111-1135.
Cao, C, E. Ghysels, and F. Hatheway, 2000. Price discovery without trading: Evidence from the Nasdaq preopening, Journal of Finance, 55, 1339-1365.
Chakravarty, S., H. Gulen, and S. Mayhew, 2004. Informed trading in stock and option markets, Journal of Finance, 58, 1235-1257.
Chan, K, 1992. A further analysis of the lead-lag relationship between the cash market and stock index futures market, Review of Financial Studies, 5, 123-152.
Chan, Kam. C., Y Chang, and P. Lung, 2005. Informed trading under different market conditions and moneyness: Evidence from TXO options, Working paper, University of Dayton.
Chan, Kam C., L. Cheng, and P. P. Lung, 2004. Net buying pressure, volatility smile, and abnormal profit of Hang Seng Index options, Journal of Futures Markets, 24, 1165-1194.
De Jong, C., K.C.G. Koedijk, and C.R. Schnitzlein, 2001. Stock market quality in the presence of a traded option, working paper, Erasmus University.
De Jong, F, and M. Donders, 1998. Intraday lead-lag relationship between futures-options, and stock market, European Finance Review, 1, 337-359.
Huang, R., 2002. The quality of ECN and Nasdaq market maker quotes, Journal of Finance, 52, 1285-1319
Iihara, Y., K. Kato, and T. Tokunaga, 1996. Intraday return dynamics between the cash and futures markets in Japan, Journal of Futures Markets, 16, 147-162.
Dickey, D, and W. A. Fuller, 1979. Distribution of the estimators for autoregressive time series with a unit root, Journal of American Statistical
Association, 74, 427-431. Johansen, S., 1988. Statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control, 12, 231-254.
Fleming, J., B. Ostdiek, and R.E. Whaley, 1996. Trading costs and the relative rates of price discovery in stock, futures, and option markets, Journal of Futures Markets, 16, 353-387.
Lockwood, L.J., and T.H. McInish, 1990. Tests of stability for variances and means of overnight/intraday returns during bull and bear markets, Journal of Banking and Finance 14, 1243-1253.
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Table 1
The trading activities for the Taiwan Index Options across moneyness
Call options
All ITM ATM OTM
Transactions Number per. minute Number per. minute Number per. minute Number per. minute
The entire sample period 1,850,088 15 278,221 2 894,090 7 677,777 6
The downtrend period 466,171 7 60,629 1 261,231 4 144,311 2
The uptrend period 1,383,917 27 217,592 4 632,859 12 533,466 10
Trading volume Number
per. minute Number per. minute Number per. minute Number per. minute
The entire sample period 11,134,540 92 1,223,131 10 4,836,003 36 5,075,406 42
The downtrend period 2,115,801 30 217,299 3 695,124 8 1,203,378 17
The uptrend period 9,018,739 176 1,005,832 20 4,140,879 73 3,872,028 76 Put options
All ITM ATM OTM
Transactions Number per. minute Number per. minute Number per. minute Number per. minute
The entire sample period 1,576,167 13 137,833 1 687,685 6 750,649 6
The downtrend period 369,641 5 42,732 1 165,450 2 161,459 2
The uptrend period 1,206,526 24 95,101 2 522,235 10 589,190 11
Trading volume Number
per. minute Number per. minute Number per. minute Number per. minute
The entire sample period 9,778,435 81 644,523 5 3,748,251 31 5,385,661 45
The downtrend period 1,640,688 24 216,897 3 531,395 8 892,396 13
