時段分割在資訊交易機率估計上的應用

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陳采晴(Tsai-Ching Chen) 查詢紙本館藏

畢業系所

財務金融學系

論文名稱

時段分割在資訊交易機率估計上的應用
(The Application of Time Splitting in the Estimation of PIN)

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摘要(中)

本文應用時段分割方法(time-splitting method, TS method)，將日內交易資料切割為多個區間再進行估計，在當今交易量巨大和高頻交易盛行的情形下，能夠有效地增加資訊交易機率(PIN)估計的準確度。
　　本文以2014年TAQ全年資料，抽選的150檔證券作為全市場代表，以驗證時段分割法是否能提高PIN估計的準確度。本文加入傳統的未分割傳統方法(the CL method) 作為對照組，比較將一日分為多個切割區間是否能夠增加PIN的效度，並以均方根誤差(RMSE)衡量不同切割區間下PIN參數和PIN的表現。結果顯示切割時段愈短，PIN的均方根誤差也愈小。同時，使用時段分割法估計PIN參數相較未分割方法能夠有效避免產生靠近上下界的極端值。
　　另外，本文參考Brennan, Huh和Subrahmanyam (2016)，探討未預期盈餘和PIN的關係。透過檢測以time-splitting method (the TS method)估計發生在宣告日前的PIN，再和未預期盈餘的比較，發現在時段分割法下的結果和參考文獻一致。

摘要(英)

This thesis applies a time-splitting method (the TS method), which divides intraday transaction data into multiple intervals, to effectively increase the accuracy of estimated probability of informed trading (PIN) under the large trading volume and the prevalence of high-frequency trading nowadays.
By selecting 150 securities as a representative of the overall market from the 2014 TAQ data, Iverify whether the TS method improves the accuracy of PIN estimation. In this thesis, I add the traditional undivided-method (the CL method) as a control group to compare the increase the validity of PIN with the time-splitting method (the TS method). I also adopt the root mean square error (RMSE) to measure the performance of PIN parameters and PIN under different intervals. The results show that the shorter the splitting interval, the smaller the RMSE of PIN. Meanwhile, using the TS method for PIN parameters estimation can effectively avoid extreme values close to the upper and lower bounds compared with the undivided-method (the CL method).
In addition, this thesis follows Brennan, Huh and Subrahmanyam (2016) to discuss the relationship between earnings surprise and PIN of the previous quarter. By testing the time-splitting method (the TS method) to estimate the PIN that occurs before the earning announcement date and comparing it with earnings surprise, it is found that the results are consistent with the literature.

關鍵字(中)

★ 資訊交易機率
★ 盈餘宣告
★ 日內交易

關鍵字(英)

★ Probability of Informed Trading
★ Earning Announcements
★ Intraday trading

論文目次

摘要 i
Abstracts ii
Acknowledgements iii
Contents iv
1. Introduction 1
2. Literature Review 3
2.1. PIN estimation 3
2.2. Time splitting 7
2.3. Informed trading and earning surprise 7
3. Data and methods 8
3.1. Data 8
3.2. Methodology 9
3.2.1. Splitting intervals of the TS Method 9
3.2.2. Sampling 10
3.2.3. Root of mean square for PIN 11
4. Empirical results 13
4.1. PIN statistics of sampling data 13
4.1.1. Statistics 13
4.1.2. PIN and RMSE 15
4.2. Speed and computational error 20
5. Informed trading around earnings announcements 22
5.1. Earning surprise and information asymmetry 22
5.2. PIN around earnings announcements 23
6. Conclusion 26
References 27

參考文獻

陳采晴(2018)。資訊交易機率之估計方法比較。行政院科技部專題研究計畫(MOST 107-2813-C-008-003-H)。桃園市：國立中央大學。
Brennan, M.J., Huh S., Subrahmanyam, A., 2016. Asymmetric effects of informed trading on the cost of equity capital. Management Science 62(9), 2460-2480.
Cheng, T.C., Lai, H.N., 2017. Improvements for the estimation for the probability of informed trading models. Working Paper, National Cheng Chi University.
Cheng, T.C., Lai, H.N., 2020. Improvements in estimating the probability of informed trading models. Quantitative Finance, DOI: 10.1080/14697688.2020.1800805.
Easley, D., Hvidkjaer, S., O’Hara, M., 2002. Is information risk a determinant of asset returns? Journal of Finance 57, 2185–2221.
Easley, D., Kiefer, N., O′Hara, M., Paperman, J., 1996. Liquidity, information, and infrequently traded stocks. Journal of Finance 51, 1405–1436.
Easley D., Lopez de Prado, M., O’Hara, M., 2012. Flow toxicity and liquidity in a high-frequency world. The Review of Financial Studies 25, 1457–1493.
Easley, D., O’Hara, M., 1987. Price, trade size, and information in securities markets. Journal of Financial Economics 19, 69–90.
Easley, D., O’Hara, M., 1992. Time and the process of security price adjustment. Journal of Finance 47, 577–604.
Jackson, D., 2013. Estimating PIN for firms with high levels of trading. Journal of Empirical Finance 24,116–120.
Ke, W.C., Chen, H.L., Lin, H.W.W., 2014. Estimating PIN for firms with high levels of trading—A note. Available at SSRN: https://ssrn.com/abstract=2519897.
Lee, C., Ready, M., 1991. Inferring trade direction from intraday data. Journal of Finance 46, 733–746.
Lin, H.W., Ke, W.C., 2011. A computing bias in estimating the probability of informed trading. Journal of Financial Markets 14, 625–640.
Livnat J., Mendenhall R., 2006. Comparing the post-earnings announcement drift for surprises calculated from analysts and time series forecasts. Journal of Accounting Research 44, 177–205.
Pöppe, T., Aitken, M., Schiereck, D., Wiegand, I., 2016. A PIN per day shows what news convey: the intraday probability of informed trading. Review of Quantitative Finance and Accounting 47, 1187–1220.
Vega, C., 2006. Stock price reaction to public and private information. Journal of Financial Economics, Journal of Financial Economics 82, 103–133.
Yan, Y.X. , Zhang, S.J., 2012. An improved estimation method and empirical properties of the probability of informed trading. Journal of Banking & Finance 36, 454–467.
Yang, C., Zhang, B., Zhang, C., 2020. Is information risk priced? Evidence from abnormal idiosyncratic volatility. Journal of Financial Economics 135, 528–554.

指導教授

賴弘能(Hung-Neng Lai)

審核日期

2021-1-25

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