1) Though simple realized volatility estimator is the largest estimator in absolute level, price deviation does not play as an important role as other estimator is.
Because simple realized volatility is an accumulation of noise, we know that noise structure is consistent in the sampling period.
2) Investors in two markets are sensitive to different factors. Shanghai market investors are more sensitive to market liquidity and policy, showing 2011 most volatile. Hong Kong market investors are sensitive to global market, showing volatile in 2008 and 2014.
3) We should not only focus on the level realized volatility, but also 2nd 3rd 4th moments of volatility. Increase of standard deviation, skewness and kurtosis sometimes is a sing of increasing realized volatility.
4) The normal-distribution-like distribution of tickcounts in Shanghai market imply that Shanghai market investors choose stocks more randomly. This is a proof for irrational investing behaviors in Shanghai stock market.
5) Noise includes efficient information also. In Hong Kong market, the farer relation between noise and simple realize information, implies that simpler realized volatility is not only an accumulation of noise, making noise closer related with realized volatility estimator when sampling interval expending.
This phenomenon certifies the statement of Bandi and Russel on 2006.
6) Simple realized volatility is an efficient realized volatility estimator in Hong Kong market. This is surprisingly because it is widely believed that simple realized volatility is full of noise. But it is totally inefficient in Shanghai market. This phenomenon can be explained by the fact that the noise of a market which is composed of institutional investors contains more information since rational investment.
7) 15 minutes realized volatility is the only realized volatility is efficient from 2008 to 2014 in two markets. 15 minutes realized volatility is also an estimator
which is suitable to do forecasting work.
There are several distributions of this research.
1) This is the first research taking all listed stocks on the marked into consideration. A lot of researchers worked hard on index to compare investors in different markets. But it is far from enough. Recently the phenomenon called 3-7 stocks lasted several times. It means that index stocks keep increasing, but 70% stocks decrease. The opposite price movement in the makes the risk not aware if only taking do index analysis.
2) The second contribution is it is the first time to calculate the Bandi Optimal Sampling Frequency realized volatility in Shanghai stock market. The limited research on Shanghai stock market depending on frequency data never take this estimator into account, because of the difficult access to large amount of data, and calculation difficulty. Though it does not outperform over other realized volatility, it still ranks high sometimes.
There are still imperfections in this research.
1) I do not incorporate more HAR family models in my consideration., Multi-HAR-RV model and Multi-HAR-RV-J models show better forecasting ability in previous research. Because we calculated too many stocks, it will take much more time on calculating covariance and detect jumps among stocks.
2) Another regret is that we do not take Two Time Scale Estimator into my research. I planned to take this estimator in my research, but I spent too much time on bandi Optimal Sampling frequency realized volatility estimator, because it dynamic sampling was involved.
3) We check the lag order of each stock, and confirm the robustness of HAR (1,5,22) model.
References
D &) 0 &)
&..& ) 8 & ),
& : : [ 9 &
)(
& (( & &,
] &)
C A _ (( & & - & .
D - C 77
( ))
&) C F &)
- C 6 113
9 & C 425
Andersen, T. G., & Teräsvirta, T. (2009). Realized volatility. Handbook of financial time series, 555-575.
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (1999). Realized volatility and correlation.
Andersen, T. G., Dobrev, D., & Schaumburg, E. (2011). Integrated quarticity estimation: Theory and practical implementation. Working paper.
Baker, M., Bradley, B., & Wurgler, J. (2011). Benchmarks as limits to arbitrage:
Understanding the low-volatility anomaly. Financial Analysts Journal, 67(1), 40-54.
Bandi, F. M., & Russell, J. R. (2006). Separating microstructure noise from volatility. Journal of Financial Economics, 79(3), 655-692.
Bandi, F. M., & Russell, J. R. (2006). Separating microstructure noise from volatility. Journal of Financial Economics, 79(3), 655-692.
Barber, B. M., & Odean, T. (2007). All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. The Review of Financial Studies, 21(2), 785-818.
Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., & Shephard, N. (2009). Realized kernels in practice: Trades and quotes. The Econometrics Journal, 12(3).
Bernardi, M., & Catania, L. (2015). The Model Confidence Set package for R.
Bollerslev, T., & Zhou, H. (2006). Volatility puzzles: a simple framework for gauging return-volatility regressions. Journal of Econometrics, 131(1), 123-150.
Bollerslev, T., Hood, B., Huss, J., & Pedersen, L. H. (2016). Risk everywhere:
Modeling and managing volatility.
Bollerslev, T., Litvinova, J., & Tauchen, G. (2006). Leverage and volatility feedback effects in high-frequency data. Journal of Financial Econometrics, 4(3), 353-384.
Bomfim, A. N. (2003). Pre-announcement effects, news effects, and volatility:
Monetary policy and the stock market. Journal of Banking & Finance, 27(1), 133-151.
Campbell, J. Y., Grossman, S. J., & Wang, J. (1993). Trading volume and serial correlation in stock returns. The Quarterly Journal of Economics, 108(4), 905-939.
Chae, J. (2005). Trading volume, information asymmetry, and timing information. The journal of finance, 60(1), 413-442.
Chan, K., & Fong, W. M. (2000). Trade size, order imbalance, and the volatility–
volume relation. Journal of Financial Economics, 57(2), 247-273.
Chen, H., Wang, H., & Zhou, H. (2014). Stock return volatility and capital structure decisions.
Chordia, T., Roll, R., & Subrahmanyam, A. (2002). Order imbalance, liquidity, and market returns. Journal of Financial economics, 65(1), 111-130.
Ciarreta, A., Muniain, P., & Zarrage, A. (2016). Modelling and forecasting realised volatility in German-Austrian continuous intraday electricity auction prices.
Cohen, W. M., & Levin, R. C. (1989). Empirical studies of innovation and market structure. Handbook of industrial organization, 2, 1059-1107.
Lipták, Š. (2012). Forecasting realized volatility: Do jumps in prices matter?
Corsi, F., Mittnik, S., Pigorsch, C., & Pigorsch, U. (2008). The volatility of realized volatility. Econometric Reviews, 27(1-3), 46-78.
Dow, J., & Gorton, G. (1997). Noise trading, delegated portfolio management, and economic welfare. Journal of Political Economy, 105(5), 1024-1050.
Doyne Farmer 5, J., Gillemot, L., Lillo, F., Mike, S., & Sen, A. (2004). What really causes large price changes? Quantitative finance, 4(4), 383-397.
Dufour, J. M., Garcia, R., & Taamouti, A. (2012). Measuring high-frequency causality between returns, realized volatility, and implied volatility. Journal of Financial Econometrics, 10(1), 124-163.
Engle, R. F., Hansen, M., & Lunde, A. (2011). And now, the rest of the news: Volatility and firm specific news arrival. Unpublished Working Paper, CREATES.
Fleming, J., & Paye, B. S. (2011). High-frequency returns, jumps and the mixture of normals hypothesis. Journal of Econometrics, 160(1), 119-128.
Grinblatt, M., & Keloharju, M. (2000). The investment behavior and performance of various investor types: a study of Finland's unique data set. Journal of financial economics, 55(1), 43-67.
Hameed, A., & Ting, S. (2000). Trading volume and short-horizon contrarian profits:
Evidence from the Malaysian market. Pacific-basin finance Journal, 8(1), 67-84.
Hansen, P. R., Huang, Z., & Shek, H. H. (2012). Realized garch: a joint model for returns and realized measures of volatility. Journal of Applied Econometrics, 27(6), 877-906.
Hastie, T., & Tibshirani, R. (1990). Generalized additive models. John Wiley & Sons, Inc..
Hibbert, A. M., Daigler, R. T., & Dupoyet, B. (2008). A behavioral explanation for the negative asymmetric return–volatility relation. Journal of Banking &
Finance, 32(10), 2254-2266.
Corsi, F., Audrino, F., & Renó, R. (2012). HAR modeling for realized volatility forecasting.
Jones, C. M., Kaul, G., & Lipson, M. L. (1994). Transactions, volume, and volatility. The Review of Financial Studies, 7(4), 631-651.
Kang, W., Ratti, R. A., & Yoon, K. H. (2015). The impact of oil price shocks on the stock market return and volatility relationship. Journal of International Financial Markets, Institutions and Money, 34, 41-54.
Kim, O., & Verrecchia, R. E. (1994). Market liquidity and volume around earnings announcements. Journal of accounting and economics, 17(1-2), 41-67.
Lipton, A., Pesavento, U., & Sotiropoulos, M. G. (2013). Trade arrival dynamics and quote imbalance in a limit order book. arXiv preprint arXiv:1312.0514.
Liu, C., & Maheu, J. M. (2005). Modeling and forecasting realized volatility: the role of power variation. University of Toronto technical report (November 2005).
Liu, L. Y., Patton, A. J., & Sheppard, K. (2015). Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes. Journal of Econometrics, 187(1), 293-311.
McAleer, M., & Medeiros, M. C. (2008). Realized volatility: A review. Econometric Reviews, 27(1-3), 10-45.
Musmeci, N., Aste, T., & Di Matteo, T. (2016). Interplay between past market correlation structure changes and future volatility outbursts. Scientific reports, 6.
Nartea, G. V., & Wu, J. (2013). Is there a volatility effect in the Hong Kong stock market? Pacific-Basin Finance Journal, 25, 119-135.
Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46.
Podolskij, M., & Vetter, M. (2009). Bipower-type estimation in a noisy diffusion setting. Stochastic processes and their applications, 119(9), 2803-2831.
Ponzi, A., Lillo, F., & Mantegna, R. N. (2009). Market reaction to a bid-ask spread change: A power-law relaxation dynamic. Physical Review E, 80(1), 016112.
Qu, H., & Ji, P. (2016). Modeling Realized Volatility Dynamics with a Genetic Algorithm. Journal of Forecasting, 35(5), 434-444.
Qu, H., & Ji, P. (2016). Modeling Realized Volatility Dynamics with a Genetic Algorithm. Journal of Forecasting, 35(5), 434-444.
Scrucca, L. (2016). Genetic algorithms for subset selection in model-based clustering.
In Unsupervised Learning Algorithms (pp. 55-70). Springer International Publishing.
Shen, D. (2015). Order Imbalance Based Strategy in High Frequency Trading (Doctoral dissertation, oxford university).
Srikanth, P., & Aparna, K. (2012). Global stock market integration-a study of select world major stock markets. Researchers World, 3(1), 203.
Zhang, Q., & Jaffry, S. A. (2015). High frequency volatility spillover effect based on the Shanghai-Hong Kong Stock Connect Program. Investment Management and Financial Innovations, 12(1), 8-15.
I came to Tohoku University on Nov. 2011, when I was in my senior year, thanks to the communication program between Tohoku University and Hunan University. From now on, I have been in Sendai for 6 years. Without any doubt, Sendai has become my second hometown.
I am obliged now because in this 6 years’ life in Sendai, and 5 years’ research career.
I was helped by professors so much that I do not know how to express my appreciations.
Firstly, I would like to express my my sincere gratitude to my advisor Dr. Suzuki for the continuous support for my Ph.D study and related research. For his patience, motivation, and immense knowledge. His guidance helped me in all the time of research and writing of this thesis. I could not have imagined having a better advisor and mentor for my Ph.D study.
Besides my advisor, I would like to thank the rest of my thesis committee: Dr.
Matsuda and Dr. Muroi. Dr. Matsuda provides me with other alternatives for my research, broadening my horizon. Dr. Muroi is not only the committee member of my doctor thesis, but also the committee member of my master thesis. With the incentive and criticism of Dr. Muroi I keep learning statistics and programming.
I thank my senior, Dr. Liu, who have graduated from Tohoku university, because he introduced Dr. Suzuki to me, and gave me advise when I fell puzzled about research and career ladder.
Last but not least, I would like to thank my family: my parents for supporting me spiritually throughout writing this thesis and the whole educational career as long as 21 years
Table I Result for HAR model of 15 minutes Realized Volatility in Hong Kong Market
Code Beta RV1 RV5 RV22 R Square
0001 0.0341 0 0 -0.0164 0
0002 0* -0.0442 0.2463* 0.2458* 0.03
0003 0* 0.0869* 0.049 0.3363* 0.0327
0004 0* -0.0841* 0.5403* 0.1645* 0.1304
0005 0 0.0015 0.1203 0.054 0.0044
0006 0* -0.0402 0.2815* 0.3565* 0.0529
0008 0* 0.0392 0.3242* 0.2649* 0.0841
0010 0* 0.0719* -0.198* 0.7834* 0.0593
0011 0* -0.0675* 0.1844* 0.6325* 0.0988
0012 0* 0.1805* 0.1172 0.5007* 0.2131
0013 0 0.0092 0.3219* 0.501* 0.2091
0014 0* -0.0255 0.0207 0.6448* 0.0511
0016 0 0.0598 0.4325* 0.237* 0.181
0017 0* -0.2121* 0.6135* 0.2565* 0.1267
0019 0* -0.0279 0.491* 0.2818* 0.2143
0020 1e-04* -0.0075 -0.0213 0.6857* 0.0677
0023 0* -0.1183* 0.415* 0.3807* 0.1152
0027 0 0.0912* 0.488* 0.2829* 0.3406
0031 1e-04* 0.0388 0.3727* 0.4816* 0.3613
0038 0* 0.1108* 0.0155 0.762* 0.2729
0041 0* 0.108* 0.1304 0.4451* 0.0979
0054 0* 0.0524 0.1509* 0.605* 0.1499
0066 0* 0.2021* 0.1003 0.4057* 0.1403
0069 1e-04* 0.0087 0.0888 0.0901 0.0037
0076 3e-04* 0.3284* 0.2944* 0.2263* 0.3912
0082 1e-04* 0.0346 0.3974* 0.481* 0.4182
0083 0* -0.0633* 0.3223* 0.2603* 0.0444
0101 0* -0.099* 0.3411* 0.3778* 0.0966
0107 0* 0.0595 0.2591* 0.5465* 0.2806
0123 0 -0.0171 0.3338* 0.63* 0.5125
0135 0* 0.0442 -0.0123 0.7933* 0.1675
0142 0* 0.1073* 0.2306* 0.3231* 0.1014
0144 0* -0.0247 0.1898* 0.4936* 0.0643
0148 1e-04* -0.087* 0.32* 0.2765* 0.04
0151 0 0.14* 0.1724* 0.6204* 0.3182
0152 1e-04* 0.1262* 0.3773* 0.3664* 0.3362
0165 0* 0.1161* -0.0634 0.7827* 0.1836
0168 0* -5e-04 0.141 0.5912* 0.0939
0173 0 0.1256* 0.2002* 0.6142* 0.4761
Code Beta RV1 RV5 RV22 R Square
0177 0 -0.101* 0.3015* 0.6099* 0.1821
0178 0 0.1116* 0.2203* 0.5562* 0.3399
0179 0* 0.0626 0.2701* 0.4895* 0.2045
0182 3e-04* -0.0086 0.4673* 0.3179* 0.1775
0196 1e-04* 0.1608* 0.1327* 0.5482* 0.2349
0200 0 0.0299 0.0874 0.7393* 0.2518
0210 0* 0.0752* 0.3391* 0.4116* 0.2239
0220 0* 0.3786* 0.1124* 0.3813* 0.3748
0242 0 -0.0183 0.1845* 0.6648* 0.1608
0257 0 0.1588* 0.5996* 0.1636* 0.5575
0267 0* 0.0182 -0.003 0.3543* 0.0111
0268 0* -0.0614* 0.4013* 0.5092* 0.2313
0270 0* 0.0316 -0.0245 0.6364* 0.0504
0272 0* 0.125* 0.2237* 0.5161* 0.2918
0276 4e-04* 9e-04 -4e-04 0.344* 0.0078
0285 0* 0.0432 0.3008* 0.457* 0.2031
0291 0* 0.0118 0.0868 0.5364* 0.0607
0293 5e-04 -2e-04 -1e-04 -0.0138 0
0297 0* 0.0664* 0.2748* 0.5936* 0.4857
0302 0* 0.0622* -0.1377 0.7573* 0.0641
0303 0 -0.0312 -0.0523 0.8978* 0.0868
0308 0* 0.1113* 0.4092* 0.3842* 0.4297
0316 0* -0.0807* 0.6047* 0.2391* 0.1922
0317 0* 0.2838* 0.0789 0.4164* 0.2097
0321 0* 0.3363* 0.0905 0.3457* 0.2473
0322 0* 0.0138 0.0607 0.3211* 0.0133
0323 0* -0.0466 0.6478* 0.2051* 0.2558
0330 0* 0.234* 0.0203 0.2638* 0.0851
0336 6e-04 1e-04 8e-04 -0.0131 0
0338 0* 0.0685* 0.485* 0.3223* 0.3766
0347 0* 0.0162 0.2818* 0.4695* 0.1268
0363 0* -0.1128* 0.5433* 0.1155 0.0629
0368 0* 0.0322 0.1513* 0.6312* 0.1634
0384 7e-04 8e-04 -0.001 -0.0021 0
0386 0* -0.0338 0.2304* 0.4281* 0.0589
0388 0 -0.0825* 0.4883* 0.3254* 0.1527
0390 0* -0.0313 0.2394* 0.6386* 0.2214
0392 0* -0.0016 -0.1247 0.7821* 0.0514
0397 2e-04 0.3231* 0.4594* 0.1465* 0.645
0405 0 0.1073* -0.0422 0.8363* 0.2811
0410 0 0.0952* 0.154 0.5769* 0.1863
Code Beta RV1 RV5 RV22 R Square
0435 0* 0.1983* 0.0401 0.645* 0.2949
0440 0* 0.1676* 0.0951 0.5195* 0.1878
0488 1e-04* 0.1995* 0.3843* 0.2918* 0.3752
0489 0* 0.0366 0.2158* 0.3976* 0.07
0493 0 0.1471* 0.3653* 0.4342* 0.5748
0494 0* -0.0923* 0.4885* 0.2103* 0.0956
0506 0* 0.2061* 0.1827* 0.5256* 0.3725
0511 0* -0.0319 0.0963 0.515* 0.04
0522 0 -0.0261 0.1457* 0.732* 0.1629
0525 0* 0.1009* 0.32* 0.3799* 0.2022
0538 0* -0.014 0.4722* 0.3722* 0.2604
0548 0* 0.1225* 0.2549* 0.505* 0.3061
0551 0* 0.1124* 0.2443* 0.2809* 0.098
0552 0* -0.0369 -0.1602* 0.9822* 0.1252
0555 2e-04* 0.0462 0.435* 0.3138* 0.2214
0576 0* 0.0192 -0.028 0.7331* 0.0852
0589 1e-04* 0.1409* 0.0259 0.3502* 0.0478
0598 5e-04* -0.0025 0.0419 0.0688 0.0009
0604 0* 0.0297 0.4323* 0.4086* 0.3244
0606 0* 0.07* 0.0112 0.7463* 0.186
0639 0 0.0867* 0.2882* 0.4961* 0.29
0656 0* 0.0902* 0.3344* 0.414* 0.2585
0658 0* 0.0533 -0.066 0.7849* 0.1361
0659 1e-04* -0.0157 0.1955* 0.5294* 0.0895
0669 0* 0.1639* 0.2643* 0.3158* 0.1689
0670 0 0.4023* -0.0463 0.5542* 0.4096
0683 0* 0.0018 0.2319* 0.4582* 0.0819
0688 0* 0.0089 0.0119 0.5409* 0.0306
0689 2e-04* 0.0092 0.4514* 0.3545* 0.2459
0691 1e-04 0.2257* 0.1458* 0.4515* 0.2512
0696 1e-04* 0.1692* -0.0541 0.6423* 0.1297
0697 1e-04* 0.1023* 0.539* 0.2793* 0.5226
0700 0* 0.0694* 0.1761* 0.4923* 0.161
0709 0 0.0822* 0.2895* 0.5505* 0.4026
0716 1e-04 0.0683* 0.6547* 0.162* 0.4028
0728 0* 0.3544* 0.1039* 0.2385* 0.2038
0735 3e-04* 0.2569* 0.2812* 0.1582* 0.2106
0737 0* 0.0658* 0.2769* 0.406* 0.1396
0743 1e-04* 0.1273* 0.2134* 0.3263* 0.1081
0751 1e-04 0.0272 0.2867* 0.5388* 0.2752
0753 0* -0.0167 -0.0676 0.7002* 0.0217
Code Beta RV1 RV5 RV22 R Square
600000 0* 0.1132* 0.1522* 0.5081* 0.1559
600004 0* 0.0766* 0.3839* 0.3422* 0.2105
600005 0 -0.025 0.3256* 0.6667* 0.6522
600006 0.0012 0 0 -0.0141 0
600007 0* 0.0064 0.244* 0.4782* 0.105
600008 0* 0.1206* 0.0759 0.6362* 0.2015
600009 0* -0.1046* 0.5699* 0.3729* 0.2636
600010 0* 0.0629* 0.5037* 0.3697* 0.5635
600011 0* 0.1366* 0.2431* 0.3586* 0.1542
600012 0.0014 0 0 -0.014 0
600015 0* 0.0511 0.2075* 0.5965* 0.2297
600017 0.0019 0 0 -0.0141 0
600018 0* -0.0871* 0.61* 0.3544* 0.3463
600019 0* 0.0399 0.1686* 0.6885* 0.328
600020 6e-04 -1e-04 0 -0.0155 0
600021 0* 0.0539 0.2259* 0.5723* 0.2362
600022 0 0.0032 0.3197* 0.6525* 0.7328
600026 0* 0.0144 0.2465* 0.5816* 0.2237
600027 0* 0.0387 0.1983* 0.6* 0.2083
600028 0* 0.0848* 0.2311* 0.5876* 0.366
600029 0 0.024 0.3012* 0.6403* 0.6475
600031 0* 0.063* 0.1384* 0.6437* 0.2096
600033 0 0.0867* 0.0368 0.8497* 0.6876
600035 0* 0.0683* 0.181* 0.6037* 0.2302
600036 0* -0.018 0.2535* 0.3115* 0.041
600048 0* 0.0413 -0.0811 0.8655* 0.1525
600052 0* 0.007 0.0911 0.7619* 0.2211
600054 2e-04 0 -5e-04 -0.0127 0
600055 0* 0.0969* 0.2808* 0.3213* 0.1266
600056 0* -0.0034 0.0087 0.095 0.0005
600059 0* 0.0426 0.2045* 0.3909* 0.0751
600060 0* 0.0857* 0.111 0.6626* 0.2349
600062 0.0016 0 0 -0.0139 0
600064 0* 0.0269 0.304* 0.4553* 0.1654
600066 5e-04 0 0 -0.014 0
600070 0* 0.09* 0.4012* 0.3312* 0.253
600071 0* 0.0933* 0.1849* 0.5635* 0.2163
600073 1e-04 0 -3e-04 -0.0157 0
600075 0* 0.0112 0.1183 0.4363* 0.0363
600076 5e-04 -2e-04 6e-04 -0.0171 0
600077 0* 0.0585 0.2518* 0.5455* 0.2505
600078 0* -0.0522 0.2589* 0.6081* 0.1626
Code Beta RV1 RV5 RV22 R Square
600079 0* 0.1377* 0.0515 0.5689* 0.1192
600080 0* 0.0916* -0.0948 0.9073* 0.2782
600081 0* 0.011 0.0729 0.2285* 0.0081
600082 0* 0.0078 0.1117 0.6175* 0.1012
600083 0* 0.0172 0.2239* 0.4726* 0.0934
600085 0* -0.013 0.0964 0.5842* 0.063
600086 8e-04 0 0 -0.0146 0
600089 0* 0.1722* 0.1711* 0.5261* 0.2976
600091 0* 0.0958* 0.2391* 0.4056* 0.1326
600093 0* 0.0637* 0.2493* 0.2881* 0.0685
600095 0* 0.0231 0.4679* 0.354* 0.272
600096 0* 0.2049* 0.0561 0.3809* 0.1509
600097 0 0.2026* 0.1109 0.6075* 0.4263
600098 0* 0.075* 0.2984* 0.4343* 0.2072
600099 0* 0.1223* 0.2027* 0.373* 0.1175
600100 0* 0.0182 0.108 0.5529* 0.0695
600101 0* 0.083* 0.2283* 0.5202* 0.2155
600103 0* 0.0401 0.2529* 0.65* 0.5162
600104 0* 0.0576* 0.1861* 0.5951* 0.2034
600105 1e-04 -2e-04 0.0012 -0.0208 0
600106 0* -0.0125 0.2937* 0.4713* 0.1278
600107 0* 0.0473 0.1553* 0.455* 0.0702
600108 0* 0.0088 0.2963* 0.5953* 0.3407
600110 0* 0.0048 0.1533* 0.5782* 0.1002
600111 0* -0.0552 0.227* 0.6846* 0.2518
600112 0* 0.2714* 0.1215* 0.4152* 0.2514
600113 0* 0.2419* 0.2* 0.3809* 0.254
600114 0* 0.1781* 0.2619* 0.4121* 0.2952
600115 0* 0.081* 0.223* 0.6354* 0.4784
600116 0* 0.0284 0.3445* 0.5153* 0.3316
600117 0* 0.0222 0.2019* 0.5768* 0.1569
600118 0* -0.0266 0.4695* 0.4411* 0.3521
600119 0* 0.0163 0.1651* 0.3231* 0.031
600120 0* 0.0266 0.4591* 0.3508* 0.2565
600121 0* 0.0356 0.2749* 0.5702* 0.2947
600122 0* 0.1062* 0.4615* 0.221* 0.2541
600123 0.0035 0 0 -0.0136 0
600125 0* 0.0205 0.046 0.5862* 0.0578
600126 0* 0.1702* 0.1285* 0.4578* 0.1602
600127 0* 0.0233 0.0904 0.7243* 0.1867
600128 0* 0.1075* 0.3193* 0.1066 0.0824
600129 0* 0.0149 0.449* 0.3347* 0.2219
Code Beta RV1 RV5 RV22 R Square
600130 0* -0.0131 0.3347* 0.5818* 0.3415
600131 0* 0.0257 0.2146* 0.4628* 0.0948
600132 0 0.0241 0.169* 0.7028* 0.3006
600135 0* 0.0617* 0.2621* 0.5442* 0.2845
600137 0* 0.0812* 0.0575 0.5028* 0.0668
600138 0* 0.0474 0.1587* 0.4778* 0.0841
600139 0 -0.0248 0.1972* 0.714* 0.2959
600143 0* -0.048 0.4486* 0.3744* 0.1755
600145 0* 0.0722* 0.2038* 0.4404* 0.1097
600148 0* -0.01 0.1801* 0.6023* 0.1318
600149 0* 0.0584 0.2737* 0.4464* 0.1603
600150 0* 0.0443 0.1207 0.5324* 0.1024
600151 0* -6e-04 0.0092 0.0401 0.0001
600152 0* -0.0177 0.2111* 0.6696* 0.222
600153 0* 0.0164 0.3491* 0.409* 0.1584
600157 0* 0.0898* 0.2551* 0.4981* 0.2509
600158 1e-04 -3e-04 3e-04 -0.0126 0
600159 0* 0.0874* 0.144* 0.5295* 0.1307
600160 0* 0.2075* 0.1593* 0.5337* 0.3583
600161 0* 0.0109 -0.0022 0.5234* 0.0314
600162 0* 0.0777* 0.4143* 0.2831* 0.1917
600163 0* 0.0324 0.0945 0.3539* 0.0254
600165 0* 0.1021* 0.3016* 0.4394* 0.2518
600166 0* 0.029 0.2193* 0.5642* 0.1831
600168 0* 0.1446* 0.2041* 0.4707* 0.2233
600171 0* 0.0103 0.3507* 0.5431* 0.3651
600172 0* -0.0422 0.4795* 0.4624* 0.3805
600173 0* 0.0738* 0.188* 0.5932* 0.2361
600175 0* 0.0965* 0.2254* 0.5626* 0.2919
600176 0* 0.0833* 0.2042* 0.537* 0.2019
600177 0* 0.0393 0.2704* 0.4648* 0.1529
600178 0* 0.1391* 0.1653* 0.3747* 0.1094
600179 0* 0.0615* 0.2951* 0.384* 0.1361
600182 1e-04* 0.001 -0.0029 0.0028 0
600183 0* -0.0444 0.2895* 0.291* 0.0449
600184 0.0011 1e-04 -1e-04 -0.0132 0
600185 0* 0.0747* 0.1616* 0.547* 0.1479
600186 0* -0.0348 0.5143* 0.4651* 0.5588
600188 0.003 0 0 -0.0138 0
600189 0* 0.0495 0.2809* 0.3041* 0.0812
600190 1e-04 4e-04 -0.0023 -0.0152 0
0001 1317.5878 0 0 -0.0164 0
0002 0.6579* -0.0442 0.2463* 0.2458* 0.0301
0003 0.5879* 0.0869* 0.049 0.3363* 0.0327
0004 0.3646* -0.0841* 0.5404* 0.1645* 0.1305
0005 2.4825 0.0015 0.1203 0.0541 0.0044
0006 0.4937* -0.0402 0.2815* 0.3565* 0.0529
0008 0.1684* 0.0553 0.4834* 0.3165* 0.3114
0010 0.3018* 0.072* -0.1983* 0.7838* 0.0593
0011 1.2885* -0.0274 0.0454 0.4061* 0.0117
0012 0.239* 0.214* 0.1472* 0.5027* 0.3149
0013 0.1881 0.0092 0.3219* 0.501* 0.2091
0014 0.2775* -0.0254 0.0204 0.6455* 0.0512
0016 0.373 0.0598 0.4325* 0.237* 0.181
0017 0.2777* -0.2121* 0.6135* 0.2566* 0.1267
0019 0.2211* -0.0279 0.491* 0.2818* 0.2143
0020 0.3084* -0.0075 -0.0212 0.6857* 0.0677
0023 0.3996* -0.0496 0.2919* 0.4384* 0.1041
0027 0.2676 0.0912* 0.488* 0.2829* 0.3406
0031 0.1544* 0.1785* 0.3463* 0.3495* 0.3711
0038 0.1404* 0.1981* 0.3177* 0.3986* 0.4778
0041 0.2102* 0.1097* 0.1279 0.4461* 0.0983
0054 0.2009* 0.0662* 0.3136* 0.4693* 0.2505
0066 0.1524* 0.202* 0.1005 0.4057* 0.1404
0069 0.7729* 0.0087 0.0889 0.0903 0.0037
0076 0.1251* 0.3284* 0.2943* 0.2264* 0.3912
0082 0.1451* 0.0219 0.4501* 0.428* 0.3933
0083 0.8437* -0.0223 0.2852* 0.2529* 0.0438
0101 0.2996* -0.099* 0.3411* 0.3779* 0.0966
0107 0.1023* 0.0596 0.259* 0.5465* 0.2809
0123 0.0549 0.1606* 0.4641* 0.3416* 0.7156
0135 0.1484* 0.0441 -0.0123 0.7934* 0.1675
0142 0.3638* 0.1073* 0.2305* 0.3232* 0.1014
0144 0.3655* -0.0072 0.1636* 0.6047* 0.107
0148 0.4915* -0.087* 0.3201* 0.2766* 0.04
0151 0.083 0.0446 0.5303* 0.3872* 0.4588
0152 0.1133* 0.1219* 0.5137* 0.2608* 0.4443
0165 0.2313* 0.0722* 0.1118 0.6385* 0.1657
0168 0.2969* 0.0159 0.2971* 0.503* 0.1847
0173 0.103 0.3316* 0.234* 0.3821* 0.6231
0175 0.1703 -0.067* 0.6475* 0.3639* 0.5599
0177 0.2346* -0.0157 0.3719* 0.506* 0.2878
0178 0.1738 0.1178* 0.3246* 0.4772* 0.4575
0179 0.2049* 0.1925* 0.4212* 0.2879* 0.4684
0182 0.1198* -0.0069 0.4576* 0.3274* 0.1768
0196 0.2818* 0.1399* 0.1806* 0.5072* 0.2261
0200 0.1555 0.0669* 0.287* 0.5723* 0.4786
0210 0.6741* 0.0416 0.3005* 0.3678* 0.1125
0220 0.2074* 0.3452* 0.2223* 0.3258* 0.4399
0242 0.1312 -0.0182 0.1846* 0.6647* 0.1609
0257 0.1011 0.2756* 0.594* 0.0767* 0.723
0267 0.6741* 0.0115 0.1024 0.3934* 0.0287
0268 0.1467 -0.0568 0.4269* 0.5404* 0.3519
0270 0.2679* 0.0316 -0.0245 0.6365* 0.0504
0272 3.8865 -7e-04 -0.0015 0.0117 0
0276 0.6985* 0.0219 0.015 0.6708* 0.0693
0285 0.1809* 0.1313* 0.2796* 0.4782* 0.3531
0291 0.253* 0.0117 0.0871 0.5362* 0.0607
0293 6.5674 -2e-04 -1e-04 -0.0138 0
0297 0.0817 0.1197* 0.3848* 0.4581* 0.6742
0302 0.2973* 0.0622* -0.1384 0.7587* 0.0643
0303 0.3661 -0.0312 -0.0522 0.8978* 0.0869
0308 0.0809* 0.155* 0.4731* 0.3026* 0.5653
0316 0.1822* -0.0799* 0.6025* 0.2405* 0.192
0317 0.2292* 0.3222* 0.2306* 0.2957* 0.354
0321 0.483* 0.3002* 0.2123* 0.2714* 0.2716
0322 0.3917* 0.0137 0.0608 0.3211* 0.0133
0323 0.1428* 0.2537* 0.4924* 0.1552* 0.5323
0330 0.7445* 0.4071* -0.0233 0.1977* 0.19
0336 4.2234 4e-04 8e-04 -0.0033 0
0338 0.061* 0.0678* 0.485* 0.3229* 0.3765
0347 0.2476* 0.0423 0.3364* 0.4374* 0.197
0363 1.6326* -0.0031 0.0643 0.1264 0.0026
0368 0.1823* -0.0186 0.532* 0.3646* 0.3451
0384 4.5715 0.0012 -9e-04 0.0365 1e-04
0386 0.4156* -0.0338 0.2304* 0.4281* 0.059
0388 0.4533 -0.0825* 0.4883* 0.3255* 0.1527
0390 0.0944* -0.0313 0.2394* 0.6386* 0.2214
0392 0.501* -0.0084 0.0255 0.7522* 0.1237
0397 0.1275 0.3293* 0.4529* 0.1466* 0.6455
0405 0.0797 0.1074* -0.0421 0.8362* 0.2812
0410 0.1815 0.0584 0.1966 0.628* 0.2866
0425 1.0249* -0.0031 0.0421 0.1958 0.0037
0435 0.1815* 0.1115* 0.3752* 0.3863* 0.3374
0440 0.2259* 0.1676* 0.0959 0.5189* 0.1879
0488 0.1191* 0.1994* 0.3844* 0.2919* 0.3753
0489 0.3551* 0.0366 0.2158* 0.3976* 0.07
0493 0.0826 0.0959* 0.5337* 0.3387* 0.7354
0494 0.3436* -0.0922* 0.4885* 0.2104* 0.0956
0506 0.2327* 0.1172* 0.3631* 0.3927* 0.3162
0511 0.3769* -0.0322 0.0971 0.5145* 0.04
0522 0.2028 -0.0261 0.1457* 0.7321* 0.163
0525 0.1043* 0.1011* 0.3196* 0.38* 0.2022
0538 0.1436* -0.0142 0.4722* 0.3727* 0.2607
0548 0.0847* 0.1225* 0.2549* 0.505* 0.3061
0551 0.3721* 0.1162* 0.3533* 0.2636* 0.166
0552 0.13* -0.0371 -0.161* 0.9832* 0.1253
0555 0.1051* 0.0508 0.4285* 0.3159* 0.2211
0576 0.2647* 0.0239 0.087 0.7165* 0.1791
0589 0.5904* 0.1501* 0.1277* 0.4237* 0.1067
600000 0.1791* 0.1255* 0.2581* 0.4594* 0.2763
600004 0.1631* 0.2677* 0.2463* 0.3669* 0.3866
600005 0.0303 0.0409 0.3694* 0.57* 0.8044
600006 9.207 0 0 -0.015 0
600007 0.4002* 0.0384 0.2155* 0.4737* 0.1098
600008 0.1245* 0.1307* 0.2229* 0.5436* 0.3778
600009 0.3622* 0.0034 0.2242* 0.5681* 0.1531
600010 0.3309* 0.0092 0.1374* 0.5856* 0.0976
600011 0.2416* 0.1656* 0.3254* 0.3452* 0.2767
600012 15.5385 0 -2e-04 -0.0142 0
600015 0.1838* 0.1266* 0.3395* 0.3907* 0.3089
600017 12.5419 0 0 -0.0146 0
600018 0.1058* 0.071* 0.5171* 0.3303* 0.4945
600019 0.0767* 0.0728* 0.3767* 0.483* 0.5134
600020 3.7974 -1e-04 -1e-04 -0.0178 0
600021 0.1099* 0.151* 0.246* 0.5104* 0.3847
600022 0.0295 0.0724* 0.4733* 0.4381* 0.8449
600026 0.1564* 0.0631* 0.2238* 0.5869* 0.2855
600027 0.1289* 0.1023* 0.2533* 0.5253* 0.3278
600028 0.0943* 0.0147 0.4368* 0.4726* 0.4739
600029 0.0341 0.0533 0.4498* 0.4745* 0.7781
600031 0.2008* 0.1199* 0.1607* 0.5715* 0.2421
600033 0.0437 0.0258 0.0871 0.853* 0.6096
600035 0.1372* 0.0691* 0.3345* 0.4794* 0.3398
600036 0.321* 0.0753* 0.1986* 0.4678* 0.12
600048 0.1268* 0.1401* 0.1963* 0.5623* 0.3635
600052 0.1082* 0.0898* 0.3131* 0.5077* 0.4189
600054 4.5069 1e-04 -9e-04 -0.0111 0
600055 0.3011* 0.0945* 0.3519* 0.3767* 0.2449
600056 1.2177* -0.0249 0.1417* 0.2932* 0.0159
600059 0.2894* 0.0501 0.34* 0.4154* 0.2268
600060 0.2748* 0.0788* 0.3137* 0.4421* 0.2436
600062 38.7045 0 0 -0.0141 0
600064 0.2067* 0.116* 0.3422* 0.3893* 0.2812
600066 13.3265 -1e-04 2e-04 -0.0141 0
600070 0.1676* 0.1574* 0.3507* 0.3887* 0.4063
600071 0.1548* 0.1572* 0.2623* 0.4817* 0.3867
600073 2.1437* -5e-04 1e-04 -0.0058 0
600075 0.2825* 0.063* 0.4556* 0.2779* 0.2353
600076 4.3761 -3e-04 0.0015 -0.0187 0
600077 0.1882* 0.0069 0.4941* 0.3896* 0.377
600078 1.0226* 0.0031 0.0197 0.2071 0.0033
600079 0.2489* 0.1719* 0.165* 0.4939* 0.2223
600080 0.1187* 0.0098 0.2013* 0.7068* 0.3661
600081 0.3939* 0.0506 0.2131* 0.4923* 0.1329
600082 0.1823* 0.019 0.3793* 0.4642* 0.283
600083 0.2708* 0.0159 0.5904* 0.2173* 0.2808
600085 0.2613* 0.0263 0.4679* 0.3475* 0.2698
600086 17.6876 0 0 -0.0152 0
600089 0.1516* 0.0751* 0.2231* 0.5748* 0.2839
600091 0.2713* 0.211* 0.2741* 0.3072* 0.2416
600093 0.2843* 0.1685* 0.3015* 0.3099* 0.2075
600095 0.1276* 0.0991* 0.549* 0.2581* 0.4832
600096 0.3247* 0.4245* 0.0966 0.2298* 0.3811
600097 0.1628 0.2185* 0.385* 0.3213* 0.5288
600098 0.1734* 0.1676* 0.3046* 0.4037* 0.3574
600099 0.2821* 0.1324* 0.2211* 0.4608* 0.2004
600100 0.2121* 0.0777* 0.2334* 0.5388* 0.2403
600101 0.1398* 0.135* 0.3698* 0.4014* 0.4308
600103 0.0481* 0.0976* 0.4464* 0.4175* 0.6955
600104 0.1316* 0.2467* 0.2322* 0.4382* 0.4677
600105 3.2047* 0 0.0022 -0.0188 0
600106 0.1662* 0.125* 0.2835* 0.4469* 0.284
600107 0.6845* 0.0208 0.1792* 0.2757* 0.0299
600108 0.0784* 0.0921* 0.3811* 0.4613* 0.5113
600110 0.1649* 0.2427* 0.0542 0.5838* 0.3302
600111 1.0801* 0.0065 0.0471 0.4738* 0.0276
600112 0.2136* 0.2459* 0.3589* 0.2754* 0.4371
600113 0.2049* 0.2294* 0.4142* 0.2593* 0.4745
600114 0.3653* 0.0498 0.281* 0.4576* 0.1689
600115 0.0597 0.0715* 0.2896* 0.5968* 0.6042
600116 0.1726* 0.0243 0.4764* 0.3937* 0.3795
600117 0.1907* 0.0292 0.3297* 0.4903* 0.244
600118 0.1476* 0.1114* 0.2492* 0.5471* 0.4243
600119 0.3093* 0.1191* 0.1841* 0.4773* 0.1589
600120 0.3538* 0.0383 0.3393* 0.4144* 0.1742
600121 0.1228* 0.0708* 0.418* 0.4184* 0.4236
600122 0.1928* 0.1053* 0.4579* 0.3111* 0.363
600123 132.139 0 0 -0.0137 0
600125 0.2329* 0.103* 0.387* 0.3184* 0.2453
600126 0.2005* 0.2658* 0.2367* 0.3336* 0.3121
600127 0.1129* 0.0907* 0.2669* 0.5433* 0.3666