Conclusions

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5. Conclusions

In this study, we use a unique futures dataset from April 2004 to March 2008 to

examine whether each type of investors engages in herding and feedback trading.

We have obtained several interesting results.

First, there are different trading patterns between individual investors and

institutional investors. Individual investors are positive feedback traders. They follow

market returns to get information. Institutional investors engage in herding because of

competition among them, and they are negative feedback traders.

On the other hand, we examine the effect of investors’ trade size. We find that large investors’ trading behavior is independent and different from trading behavior of

average investors who belong to their trader type. This may result from the fact that

large investors are the informed. However, Small investors’ trading behavior is

consistent with trading behavior of average investors who belong to their trader type.

Compared to large investors, they engage in herding and feedback trading more.

We think that they are less-informed traders, and they mimic informed traders and pay

more attention to public information such as market returns to get information.

Furthermore, we divide the entire sample period into a period of contraction and a

period of expansion. We find that investors react asymmetrically to periods of

contraction and expansion. Herding and feedback trading prevail more among small

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investors during a period of expansion than a period of contraction.

Finally, we find that only foreign institutional investors engage in herding. They

are more likely to follow the same type of institutional investors than different types

of institutional investors. The result accords with the result of Sias (2004). Besides,

only foreign institutional investors are significant negative feedback traders among all

types of institutional investors. Other types of institutional investors are neither

positive feedback nor negative feedback traders.

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Descriptive statistics per contract by trade type categories

The table presents descriptive statistics for four types of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) futures investors: (1) Individual investors; (2) Domestic institutional investors; (3) Proprietary firm investors; (4) Foreign institutional investors. The sample period is for 991 days, from April 2004 to March 2008.The sample period includes a full business cycle referring to Council for Economic Planning and Development (CEPD). A full business cycle contains a period of contraction and a period of expansion.

All Investors Individual Investors Domestic Institutional

Investors

Proprietary Firm Investors Foreign Institutional Investors

Total trading volume

Buy 34,489,065 25,213,151 315,771 6,567,695 2,392,448

Sell 34,560,103 25,381,306 319,098 6,421,414 2,438,285

Total 69,049,168 50,594,457 634,869 12,989,109 4,830,733

Percentage of total trading volume

Buy 100% 73.10% 0.92% 19.04% 6.94%

Mean 69,676.25 51,053.94 640.63 13,107.07 4,874.60

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Table 2

Descriptive statistics per contract by trade size categories

The table presents descriptive statistics for large and small size investors of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) futures investors: (1) Large individual investors; (2) Small individual investors; (3) Large institutional investors; (4) Small institutional investors. The sample period is for 991 days, from April 2004 to March 2008. The sample period includes a full business cycle containing a period of contraction and a period of expansion defined by Council for Economic Planning and Development.

Large Individual Investors Small Individual Investors Large Institutional Investors Small Institutional Investors Criteria to distinguish

Size ≥3,864 <3,864 ≥577,850 <577,850

Total trading volume

Total 25,299,096 25,295,361 9,650,271 8,804,440

Number of traders

Total 1,484 155,913 12 814

Average trading volume per person

Mean 17,048 162 804,189 10,816

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The table presents descriptive statistics for all dependent variables of VAR model for individual investors. The sample period includes a full business cycle for 991 days, from April 2004 to March 2008, a period of contraction for 226 days, from April 2004 to February 2005, a period of expansion for 765 days, from March 2005 to March 2008.

Business cycle is defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝐷𝑡 is the net buy orders by all individual investors.

𝐿𝐼𝑁𝐷𝑡 is the net buy orders by large individual investors. 𝑆𝐼𝑁𝐷𝑡 is the net buy orders by small individual investors.

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Table 4

Analysis for herding and feedback trading by individual investors for a full business cycle

The table analyzes herding and feedback trading by individual investors from April 2004 to March 2008. The sample period includes a full business cycle referring to Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝐷𝑡 is the net buy orders by all individual investors. 𝐿𝐼𝑁𝐷𝑡 is the net buy orders by large individual investors. 𝑆𝐼𝑁𝐷𝑡 is the net buy orders by small individual investors. *Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: individual investors

𝑅𝑡 0.0003 -0.0256 0.0059 0.0042

S.D. 0.0004 0.0352 0.0176 0.0070

𝐼𝑁𝐷𝑡 -0.0044*** 0.2678** -0.0027 -0.0603***

S.D. 0.0015 0.1171 0.0586 0.0231

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large individual investors

𝑅_𝑡 0.0003 -0.0342 0.0202* -0.0019 0.0003 0.0029

S.D. 0.0004 0.0358 0.0108 0.0097 0.0038 0.0037

𝐿𝐼𝑁𝐷_𝑡 -0.0009 -0.1582 -0.0870** 0.0795** -0.0084 0.0047

S.D. 0.0014 0.1178 0.0356 0.0318 0.0126 0.0123

Panel C: small individual investors

𝑆𝐼𝑁𝐷_𝑡 -0.0077*** 0.9345*** -0.2432*** -0.0011 -0.0284 -0.0939***

S.D. 0.0024 0.2010 0.0608 0.0542 0.0215 0.0209

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Table 5

Analysis for herding and feedback trading by individual investors during a period of contraction

The table analyzes herding and feedback trading by individual investors. Our sample period for 11 months, from April 2004 to February 2005 is 11^th contraction defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝐷𝑡 is the net buy orders by all individual investors. 𝐿𝐼𝑁𝐷𝑡 is the net buy orders by large individual investors. 𝑆𝐼𝑁𝐷𝑡 is the net buy orders by small individual investors. *Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: individual investors

𝑅𝑡 -0.0003 -0.0239 -0.0526 -0.0085

S.D. 0.0010 0.0697 0.0515 0.0188

𝐼𝑁𝐷𝑡 -0.0033 0.0380 0.2619* 0.0133

S.D. 0.0029 0.1979 0.1462 0.0534

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large individual investors

𝑅_𝑡 -0.0003 -0.0477 0.0128 -0.0316 -0.0034 -0.0023

S.D. 0.0010 0.0718 0.0269 0.0285 0.0090 0.0098

𝐿𝐼𝑁𝐷_𝑡 0.0000 -0.2598 -0.1137 0.1220 -0.0320 0.0026

S.D. 0.0030 0.2112 0.0792 0.0837 0.0265 0.0289

Panel C: small individual investors

𝑆𝐼𝑁𝐷_𝑡 -0.0071 0.6796* -0.2180* 0.1186 -0.0114 -0.0529

S.D. 0.0050 0.3481 0.1305 0.1380 0.0436 0.0477

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Table 6

Analysis for herding and feedback trading by individual investors during a period of expansion

The table analyzes herding and feedback trading by individual investors. Our sample period for 37 months, from March 2005 to March 2008 is 12^th expansion defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝐷𝑡 is the net buy orders by all individual investors. 𝐿𝐼𝑁𝐷𝑡 is the net buy orders by large individual investors. 𝑆𝐼𝑁𝐷𝑡 is the net buy orders by small individual investors. *Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: individual investors

𝑅𝑡 0.0005 -0.0185 0.0170 0.0055

S.D. 0.0005 0.0415 0.0184 0.0074

𝐼𝑁𝐷𝑡 -0.0047*** 0.3385** -0.0381 -0.0688***

S.D. 0.0017 0.1456 0.0646 0.0258

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large individual investors

𝑅_𝑡 0.0005 -0.0234 0.0201* 0.0032 0.0007 0.0030

S.D. 0.0005 0.0425 0.0119 0.0104 0.0042 0.0041

𝐿𝐼𝑁𝐷_𝑡 -0.0011 -0.1259 -0.0683* 0.0795** 0.0004 0.0093

S.D. 0.0016 0.1461 0.0410 0.0356 0.0145 0.0140

Panel C: small individual investors

𝑆𝐼𝑁𝐷_𝑡 -0.0077*** 1.0631*** -0.2364*** -0.0116 -0.0349 -0.0997***

S.D. 0.0028 0.2504 0.0702 0.0609 0.0249 0.0240

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Descriptive statistics of institutional investors

The table presents descriptive statistics for dependent variables of VAR model for institutional investors. The sample period includes a full business cycle for 991 days, from April 2004 to March 2008, a period of contraction for 226 days, from April 2004 to February 2005, a period of expansion for 765 days, from March 2005 to March 2008.

Business cycle is defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝑆𝑡 is the net buy orders by all institutional investors.

𝐿𝐼𝑁𝑆𝑡 is the net buy orders by large institutional investors. 𝑆𝐼𝑁𝑆𝑡 is the net buy orders by small institutional investors.

Mean S.D. Min. Max. Skewness Kurtosis

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Table 8

Analysis for herding and feedback trading by institutional investors for a full business cycle

The table analyzes herding and feedback trading by institutional investors from April 2004 to March 2008. The sample period includes a full business cycle referring to Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝑆𝑡 is the net buy orders by all institutional investors. 𝐿𝐼𝑁𝑆𝑡 is the net buy

orders by large institutional investors. 𝑆𝐼𝑁𝑆𝑡 is the net buy orders by small institutional investors.*Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: institutional investors

𝑅𝑡 0.0003 -0.0256 0.0059 0.0042

S.D. 0.0004 0.0352 0.0176 0.0070

𝐼𝑁𝑆𝑡 0.0094*** -0.8180*** 0.1924 0.2249***

S.D. 0.0036 0.2922 0.1461 0.0577

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large institutional investors

𝑅_𝑡 0.0003 -0.0342 0.0202* -0.0019 0.0003 0.0029

S.D. 0.0004 0.0358 0.0108 0.0097 0.0038 0.0037

𝐿𝐼𝑁𝑆_𝑡 0.0089* 0.9977** -0.1005 -0.0554 0.0787* -0.0576

S.D. 0.0048 0.3929 0.1189 0.1060 0.0419 0.0409

Panel C: small institutional investors

𝑆𝐼𝑁𝑆_𝑡 0.0100 -3.1938*** 0.9920*** 0.0966 0.0808 0.3445***

S.D. 0.0064 0.5241 0.1586 0.1414 0.0559 0.0546

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Table 9

Analysis for herding and feedback trading by institutional investors during a period of contraction

The table analyzes herding and feedback trading by institutional investors. Our sample period for 11 months, from April 2004 to February 2005 is 11^th contraction defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝑆𝑡 is the net buy orders by all institutional investors. 𝐿𝐼𝑁𝑆𝑡 is the net buy

orders by large institutional investors. 𝑆𝐼𝑁𝑆𝑡 is the net buy orders by small institutional investors.*Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: institutional investors

𝑅𝑡 -0.0003 -0.0239 -0.0526 -0.0085

S.D. 0.0010 0.0697 0.0515 0.0188

𝐼𝑁𝑆𝑡 0.0091 -0.2855 -0.2308 0.0990

S.D. 0.0081 0.5519 0.4076 0.1489

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large institutional investors

𝑅_𝑡 -0.0003 -0.0477 0.0128 -0.0316 -0.0034 -0.0023

S.D. 0.0010 0.0718 0.0269 0.0285 0.0090 0.0098

𝐿𝐼𝑁𝑆_𝑡 0.0153 1.6800** 0.2848 0.1675 0.1456* -0.0466

S.D. 0.0099 0.6969 0.2613 0.2763 0.0874 0.0955

Panel C: small institutional investors

𝑆𝐼𝑁𝑆_𝑡 0.0025 -3.2533*** 0.9254** -0.4891 0.0159 0.2234

S.D. 0.0150 1.0520 0.3944 0.4170 0.1319 0.1441

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Table 10

Analysis for herding and feedback trading by institutional investors during a period of expansion

The table analyzes herding and feedback trading by institutional investors. Our sample period for 37 months, from March 2005 to March 2008 is 12^th expansion defined by Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐼𝑁𝑆𝑡 is the net buy orders by all institutional investors. 𝐿𝐼𝑁𝑆𝑡 is the net buy orders by large institutional investors. 𝑆𝐼𝑁𝑆𝑡 is the net buy orders by small institutional investors. *Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐼𝑁𝐷𝑡−1 𝐼𝑁𝑆𝑡−1

Panel A: institutional investors

𝑅𝑡 0.0005 -0.0185 0.0170 0.0055

S.D. 0.0005 0.0415 0.0184 0.0074

𝐼𝑁𝑆𝑡 0.0098** -1.0128*** 0.2468 0.2441***

S.D. 0.0041 0.3546 0.1573 0.0629

Intercept 𝑅_𝑡−1 𝐿𝐼𝑁𝐷_𝑡−1 𝑆𝐼𝑁𝐷_𝑡−1 𝐿𝐼𝑁𝑆_𝑡−1 𝑆𝐼𝑁𝑆_𝑡−1

Panel B: large institutional investors

𝑅_𝑡 0.0005 -0.0234 0.0201* 0.0032 0.0007 0.0030

S.D. 0.0005 0.0425 0.0119 0.0104 0.0042 0.0041

𝐿𝐼𝑁𝑆_𝑡 0.0073 0.5839 -0.2210 -0.1168 0.0590 -0.0494

S.D. 0.0055 0.4870 0.1365 0.1185 0.0483 0.0466

Panel C: small institutional investors

𝑆𝐼𝑁𝑆_𝑡 0.0118* -3.1147*** 0.9562*** 0.2034 0.0921 0.3572***

S.D. 0.0070 0.6264 0.1756 0.1524 0.0622 0.0599

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Table 11

Descriptive statistics of all types of institutional investors

The table presents descriptive statistics for all dependent variables of VAR model for all types of institutional investors. The sample period includes a full business cycle referring to Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐷𝑂𝑀𝐸𝑡, 𝑃𝑅𝑂𝑃t, 𝐹𝑂𝑅𝐸𝑡 are the net buy orders by domestic institutional investors, proprietary firm investors, foreign institutional investors in day 𝑡, respectively.

Mean S.D. Min. Max. Skewness Kurtosis

𝑅𝑡 0.0003 0.0140 -0.0699 0.0616 -0.5668 3.5496

𝐷𝑂𝑀𝐸𝑡 -0.0121 0.2727 -0.8398 0.8356 0.0484 0.1497

𝑃𝑅𝑂𝑃_𝑡 0.0126 0.1270 0.5290 -0.4529 0.1303 1.0683

𝐹𝑂𝑅𝐸_𝑡 0.0183 0.4085 1.0000 -0.9907 0.0342 -0.3764

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Table 12

Analysis for herding and feedback trading by different types of institutional investors

The table analyzes herding and feedback trading by different types of institutional investors from April 2004 to March 2008. The sample period includes a full business cycle referring to Council for Economic Planning and Development. 𝑅𝑡 is TAIEX Futures return in day 𝑡. 𝐷𝑂𝑀𝐸𝑡, 𝑃𝑅𝑂𝑃t , 𝐹𝑂𝑅𝐸𝑡 are the net buy orders by domestic institutional investors, proprietary firm investors, foreign institutional investors in day 𝑡, respectively. *Significant at the 10%. **Significant at the 5%. ***Significant at the 1%.

Intercept 𝑅𝑡−1 𝐷𝑂𝑀𝐸𝑡−1 𝑃𝑅𝑂𝑃𝑡−1 𝐹𝑂𝑅𝐸𝑡−1

Panel A: returns

𝑅𝑡 0.0003 -0.0179 0.0001 -0.0013 0.0008

S.D. 0.0004 0.0360 0.0016 0.0041 0.0012

Panel B: domestic institutional investors

𝐷𝑂𝑀𝐸𝑡 -0.0123 -0.9809 -0.1146*** -0.0540 -0.0112

S.D. 0.0086 0.7105 0.0322 0.0800 0.0228

Panel C: proprietary firm investors

𝑃𝑅𝑂𝑃𝑡 0.0123*** 0.3183 -0.0070 0.0510 -0.0151

S.D. 0.0040 0.3293 0.0149 0.0371 0.0106

Panel D: foreign institutional investors

𝐹𝑂𝑅𝐸𝑡 0.0129 -3.3876*** 0.0515 0.0423 0.3164***

S.D. 0.0124 1.0210 0.0463 0.1150 0.0328

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evidence. International Review of Financial Analysis 19, 313–322.

在文檔中以台灣指數期貨市場為例-研究各類投資人從眾行為與回饋交易行為及交易量大小之資訊效果 - 政大學術集成 (頁 34-49)

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5. Conclusions

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Descriptive statistics per contract by trade type categories

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Table 2

Descriptive statistics per contract by trade size categories

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Table 4

Analysis for herding and feedback trading by individual investors for a full business cycle

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Table 5

Analysis for herding and feedback trading by individual investors during a period of contraction

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Table 6

Analysis for herding and feedback trading by individual investors during a period of expansion

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Descriptive statistics of institutional investors

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Table 8

Analysis for herding and feedback trading by institutional investors for a full business cycle

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Table 9

Analysis for herding and feedback trading by institutional investors during a period of contraction

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Table 10

Analysis for herding and feedback trading by institutional investors during a period of expansion

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Table 11

Descriptive statistics of all types of institutional investors

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Table 12

Analysis for herding and feedback trading by different types of institutional investors

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