In this paper, the attempt is to find whether investor sentiment indicators can be used to explain market returns and market liquidity. The former has been tested by many other studies. The latter is a new issue which has seldom been mentioned in previous research. The market-based and survey-based investor sentiment indicators are simultaneously used in this study. The study hopes to discover the practical usefulness of investor sentiment indicators not only for forecasting the fluctuation of the market but also for providing a reference to the authorities, market makers and the related practitioners.
In our study, we amend the liquidity model of Chordia et al ―(2002) by adding investor sentiment indicators. The first hypothesis posits that the amended model can increase the explanatory power. Although the empirical result proves this hypothesis, the relationship between investor sentiment indicators and market returns seems to have room for further discussion.
In the second hypothesis, some factors are chosen to catch the variation of the market liquidity variables, particularly investor sentiment indicators. The second hypothesis postulates that market liquidity variables, percentage spread and OIBNUM, can be explained by investor sentiment indicators. The empirical result shows that investor sentiment indicators have little explanatory power in market liquidity variables despite the fact that the other independent variables in equation 2 and 3 seem to have better explanatory power on the market liquidity variables, especially on the percentage spread. These unanswered questions in the second hypothesis still need more thorough research in the future.
Overall, the research covering investor sentiment is relative new. There are unknown dimensions which are waiting to be discovered. This paper provides evidence to prove that investor sentiment can be used to predict market returns but maybe not be useful for predicting market liquidity. So far, the research into the relationship between investor sentiment and market liquidity is still incomplete. The field of investor sentiment requires more research to thoroughly explore the possibility.
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Appendix: Data process flow
1. Deleting the unnecessary and wrong data:
a. If the quote prices and quote volumes retrieved in the same second is identical to another set, then one set is deleted.
b. If the bid or ask price is equal to or less than zero, the datum is deleted.
c. If the bid or ask volume is equal to or less than zero, the datum is deleted.
d. If the traded price or volume is equal to or less than zero, the datum is deleted.
e. The quote datum with bid-ask spread <0 or bid-ask spread>4 is deleted.
f. Pt is trade price. If
P
t P
t1 / P
t1 0 . 1
, the datum is deleted.Note: The t and t-1 refer two adjacent trades because the trades are viewed as continuous trades. The following g and h are the same. We only compare these three criteria in the trading time (9:30:00~16:01:00).
g. at is ask price. If
t
t1 /
t1 0 . 1
, the datum is deleted.h. bt is bid price. If
b
t b
t1 / b
t1 0 . 1
, the datum is deleted.i. All trades and quotes which are beyond the trading time are deleted. Here we adopt 9:30:00~16:01:00 as our trading time. We choose 16:01:00 because there are still many large trades occurring after 16:00:00, and we need to cover those trades.
j. If there are quoting data in one day but no trading data in the same day, the additional quoted datum is deleted.
2. Merging data:
a. If there are many trading data in the same second, only the first one is reserved.
b. According to the trading data, we merge the quoting data by matching the time of the quoting data before one second or the older time of the trading data.
c. If there are many quoting data in one second, the quote with the largest quantity,
which is the largest sum of the bid quantity and ask quantity, is chosen. If that still cannot choose the single quote, the one with the smallest bid-ask spread is selected.
d. If there are no one-second-old quoting data, the first trading datum with the last-one-second or older quoting datum of the trading day before this trading day is merged.
e. Attention. For alleviating the work of the next section of distinguishing the orders, we need to reserve the five-second-old or older quoting data (comparing the time of the trading data). As a result, some quoting data before the time of the trading (before 9:30:00) should be reserved.
f. We only reserve the quoting data which is the largest quantity in every point of time.
3. Distinguishing the buyer-initiated or seller-initiated orders:
In this section, we compare the traded price with the midpoint of the ask and bid prices at least five seconds earlier. It is possible that the two traded price match the same midpoint of the ask and bid prices occurring at least five-second-old.
a. If the traded price is higher than the middle of the quote price occurring at least five seconds earlier, this trade is classified as being buyer-initiated.
b. If the traded price is lower than the middle of quote price occurring at least five seconds earlier, this trade is classified as being seller-initiated.
c. If the traded price is equal to the middle of quote price occurring at least five seconds earlier, we do the tick test. This is used to compare the traded price at time t with the traded price at time t-1.
Tick test 1: Here P
t and Pt-1 are compared. Pt is the current traded price. Pt-1 is the previous traded price.If Pt is higher than Pt-1, the trade is classified as buyer-initiated.
If Pt is lower than Pt-1, the trade is classified as seller-initiated.
If Pt is equal to Pt-1, the tick test 2 is done.
Tick Test 2: Here P
t and Pt-2 are compared. Pt-2 is traded price before the previous traded price.If Pt is higher than Pt-2, this trade is classified as being buyer-initiated.
If Pt is lower than Pt-2, this trade is classified as being seller-initiated.
If Pt is equal to Pt-2, this trade is deleted.
4. Printing out liquidity variables (daily data):
a. Percentage spread: After deleting the unnecessary and wrong trades and quote from the data, the percentage spread is calculated. The formula is ask price − bid price ask price + bid price /2 . Every percentage spread is summarized in every second and then the average is calculated to be a daily data.
b.OIBNUMt (Net buying pressure): The buyer-initiated orders are assigned +1, and the seller-initiated orders are assigned -1. Then the trade volumes are multiplied and they are summarized on a daily basis. This is the second liquidity variable.
Table 1 Summary Statistics for Equation 1
This table provides the descriptive statistics and correlation coefficients for the variables in equation 1. The variables include returns, contemporaneous and lagged excess buy and sell orders, lagged positive and negative returns, and investor sentiment indicators. The data range covers from 1995 to 2003 for SPY, and from 2001 to 2003 for QQQQ. Panel A reports the description statistics for SPY, and Panel B for QQQQ. Panel C reports the correlation coefficients for SPY, and Panel D for QQQQ. In Panel C and D, p-values are in parentheses. *, **, and *** indicate that the coefficient estimates are statistically significant at the 0.1 level, 0.05 level, and 0.01 levels, respectively.
Panel A: SPY
Variable N Mean Median Std Minimum Maximum
Return 2061 0.0003 0.0006 0.0129 -0.0752 0.0580
Excess buy orders(t) 2061 568255 55600 1080225 0 16571300
Excess sell orders(t) 2061 -507585 0 999907 -11302000 0
Excess buy orders(t-1) 2061 567214 54100 1080391 0 16571300
Excess sell orders(t-1) 2061 -509092 0 1000888 -11302000 0
Lagged positive returns 2061 0.00494 0.0005 0.0077 0 0.0580
Lagged negative returns 2061 -0.00463 0 0.0078 -0.0752 0
VIX 2061 23.0745 22.02 5.9359 10.36 45.74
pcratio 2061 0.6931 0.68 0.1588 0.3 1.36
AAII 2061 1.9797 1.74 1.1567 0.3636 8.3349
Panel B: QQQQ
Variable N Mean Median Std Minimum Maximum
Return 728 -0.0008 0.0007 0.0255 -0.0889 0.1016
Excess buy orders(t) 728 911882.47 0 1982138 0 21868500
Excess sell orders(t) 728 -1420806.35 -476200 1962749 -13450900 0
Excess buy orders(t-1) 728 909128.77 0 1982556 0 21868500
Excess sell orders(t-1) 728 -1431541.65 -480900 1972096 -13450900 0
Lagged positive returns 728 0.0094 0.0009 0.0149 0 0.1016
Lagged negative returns 728 -0.0102 0 0.0155 -0.0889 0
VXN 728 43.6440 44.07 11.4186 23.34 71.72
pcratio 728 0.7740 0.76 0.1521 0.46 1.36
AAII 728 1.8613 1.4708 1.2127 0.3636 8.3349
Panel C: SPY Return Excess buy
(0.0007)*** (0.081)* (<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)***
VIX -0.1297 0.0951 -0.2520 0.0945 -0.2415 0.1045 -0.3090 1.0000
(<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)***
pcratio -0.2712 -0.0324 -0.1982 -0.0700 -0.1654 -0.1244 -0.2554 0.2099 1.0000
(<0.0001)*** (-0.141) (<0.0001)*** (0.0015)*** (<0.0001)*** (<0.0001)*** (<0.0001)*** (<0.0001)***
AAII -0.0015 -0.0101 0.0677*** -0.0006 0.0552** -0.0870*** 0.0502** -0.2722*** -0.1679*** 1.0000
(0.9475) (-0.6463) (0.0021) (0.7722) (0.0122) (<0.0001) (0.0227) (<0.0001) (<0.0001)
Panel D: QQQQ Return Excess buy
Table 2 Estimated Empirical Results of Equation 1
The dependent variable is the daily return on the SPY or QQQQ, donated Rt. Explanatory variables include contemporaneous and lagged positive and negative daily order imbalances measured in number of trades, lagged positive and negative ETF returns, and investor sentiment indicators. The model is divided by the model with sentiment and the model without sentiment. The figures in this table have been standardized. The data range covers 1995-2003 for SPY, and 2001-2003 for QQQQ.
The t statistics are in parentheses. *, **, and *** indicate that the coefficient estimates are statistically significant at the 0.1 level, 0.05 level, and 0.01 levels, respectively.
SPY SPY QQQQ QQQQ
Excess sell orders, 0.2409 0.1662 0.3372 0.2921
- |Min [0,OIBNUMt]| (10.98) *** (7.66) *** (9.38) *** (8.41) ***
Lagged excess buy orders, 0.0063 0.0189 -0.0156 -0.0269
Max[0,OIBNUMt-1] (0.28) (0.88) (-0.42) (-0.76)
Lagged excess sell orders, -0.0265 -0.0652 -0.0312 -0.0364 -|Min[0,OIBNUMt-1]| (-1.16) (-2.96) *** (-0.81) (-0.99) Lagged positive return, max[0,Rt-1] 0.0296 0.0469 0.043 0.027
(1.27) (2.06) ** (1.13) (0.69) Lagged negtive return, min[0,Rt-1] -0.0993 -0.1981 -0.0501 -0.1372
(-4.22) *** (-8.33) *** (-1.27) (-3.33)
Table 3 Descriptive Statistics for Equation 2 and 3
This table reports the descriptive statistics for the four models of equation 2 and 3.
The variables include contemporaneous and one-term-lagged market liquidity, Ln(sigma), Ln(volume), and investor sentiment indicators. The data range covers from 1995 to 2003 for SPY, and from 2001 to 2003 for QQQQ. Panels A and B are for percentage spread models, and Panel C and D are for OIBNUM models. The difference of the number of observations is because of the quantity of data.
Panel A: SPY (Percentage Spread)
Variable N Mean Median Std Minimum Maximum
Percentage spreadt 2055 0.0015 0.0013 0.0017 0.0002 0.0159
Lnσ 2055 -4.6090 -4.5223 0.2477 -5.2628 -4.3640
Ln(volume) 2055 15.7268 15.8220 1.3650 11.0413 18.4886
Return 2055 0.0003 0.0006 0.0129 -0.0752 0.0580
Percentage spreadt-1 2055 0.0015 0.0013 0.0017 0.0002 0.0159
VIX 2055 23.1004 22.0300 5.9249 10.3600 45.7400
pcratio 2055 0.693 0.6800 0.1598 0.3000 1.5862
AAII 2055 1.9787 1.7350 1.1591 0.0005 8.3349
Panel B: QQQQ (Percentage Spread)
Variable N Mean Median Std Minimum Maximum
Percentage spreadt 727 0.0015 0.0013 0.0007 0.0005 0.0044
Lnσ 727 -3.2269 -3.231 0.0777 -3.36 -3.0941
Ln(volume) 727 18.1524 18.1704 0.3002 16.43 19.2076
Return 727 -0.0008 0.0009 0.0256 -0.0889 0.1016
Percentage spreadt-1 727 0.0015 0.0013 0.0007 0.0005 0.0044
VXN 727 43.6272 44.06 11.4174 23.34 71.72
pcratio 727 0.7771 0.76 0.1662 0.46 2.6001
AAII 727 1.8593 1.4708 1.2138 0.3636 8.3349
Panel C: SPY (OIBNUM)
Variable N Mean Median Std Minimum Maximum
OIBNUMt 2060 60672.4248 55350 56860.73 -11302000 16571300
Lnσ 2060 -4.6106 -4.5224 0.2494 -5.2628 -4.3640
Ln(volume) 2060 15.7204 15.8208 1.3695 11.0413 18.4886
Return 2060 0.0003 0.0006 0.0129 -0.0752 0.0580
OIBNUMt-1 2060 58174.0752 54450 57757.14 -11302000 16571300
VIX 2060 23.0794 22.0250 5.9331 10.3600 45.7400
pcratio 2060 0.6930 0.6800 0.1588 0.3000 1.3600
AAII 2060 1.9799 1.7350 1.1570 0.3636 8.3349
Panel D: QQQQ (OIBNUM)
Variable N Mean Median Std Minimum Maximum
OIBNUMt 727 -504960 -475600 3221625 -13450900 21868500
Lnσ 727 -3.2269 -3.2310 0.0777 -3.3600 -3.0952
Ln(volume) 727 18.152 18.1704 0.3010 16.4300 19.2076
Return 727 -0.0007 0.0009 0.0255 -0.0889 0.1016
OIBNUMt-1 727 -517877 -476800 3228861 -13450900 21868500
VXN 727 43.6285 44.0600 11.4188 23.3400 71.7200
pcratio 727 0.7743 0.7600 0.1521 0.4600 1.3600
AAII 727 1.8603 1.4708 1.2133 0.3636 8.3349
Table 4 Pearson Correlations Matrix for Equations 2 and 3
This table represents the correlation coefficients for the four models of equation 2 and 3. The variables include contemporaneous and one-term-lagged market liquidity, Ln(sigma), Ln(volume), and investor sentiment indicators. The data range covers from 1995 to 2003 for SPY, and from 2001 to 2003 for QQQQ. Panels A and B are for percentage spread models, and Panels C and D are for OIBNUM models. *, **, and
*** indicate that the coefficient estimates are statistically significant at the 0.1 level, 0.05 level, and 0.01 level, respectively. The p-values are in parentheses.
Panel A: SPY (Percentage Spread)
Percentage spreadt Lnσ Ln(volume) Return Percentage spreadt-1 VIX pcratio AAII
Percentage spreadt 1.0000
Lnσ 0.0001 1.0000
(0.9974)
Ln(volume) -0.0526 0.8943 1.0000
(0.0171) ** (<.0001) ***
Return -0.0331 -0.0253 -0.0347 1.0000
(0.1334) (0.2521) (0.1155)
Percentage spreadt-1 0.6760 0.0016 -0.0609 0.0151 1.0000
( <.0001) *** (0.941) (0.0058) *** (0.4950)
VIX 0.1390 0.5290 0.5847 -0.1302 0.1373 1.0000
(<.0001) *** ( <.0001)*** ( <.0001) *** (<.0001 )*** ( <.0001) ***
pcratio -0.1253 -0.0103 0.2069 -0.2692 -0.1504 0.2096 1.0000
(<.0001) *** (0.6406) (<.0001)*** ( <.0001)*** (<.0001) *** (<.0001)***
AAII -0.0700 0.0307 -0.0412 -0.0012 -0.0650 -0.2717 -0.1722 1.0000
(0.0015) ** (0.1648) (0.0618) * (0.9579) (0.0032) *** (<0.0001)*** (<0.0001)***
Panel B: QQQQ (Percentage Spread)
Percentage spreadt Lnσ Ln(volume) Return Percentage spreadt-1 VXN pcratio AAII Percentage spreadt 1.0000
Lnσ 0.5294 1.0000
(<.0001) ***
Ln(volume) 0.0546 -0.1233 1.0000
(0.1413) (0.0009) ***
Return -0.0695 -0.0651 0.0622 1.0000
(0.0611) * (0.0796) * (0.094) *
Percentage spreadt-1 0.8760 0.5302 0.0264 0.0031 1.0000 (<.0001) *** (<.0001) *** (0.4777) (0.9340)
VXN 0.6197 0.8216 0.1215 -0.0815 0.6177 1.0000
(<.0001) *** (<.0001) *** (0.001) *** (0.0280)** (<.0001) ***
pcratio 0.0131 -0.1433 0.1600 -0.3222 -0.0140 0.0225 1.0000
(0.7243) (0.0001) *** (<.0001 )
*** (<.0001)*** (0.706) (0.5446)
AAII -0.3053 -0.2517 -0.0642 -0.0046 -0.3306 -0.4535 -0.0675 1.0000
(<.0001) *** ( <.0001)*** (0.0841) * (0.9009) (<.0001) *** (<.0001)*** (0.0691) *
Panel C: SPY (OIBNUM)
OIBNUMt Lnσ Ln(volume) Return OIBNUMt-1 VIX pcratio AAII
OIBNUMt 1.0000
Lnσ -0.0271 1.0000 (0.2192)
Ln(volume) -0.04284 0.8950 1.0000 (0.0519) * (<.0001)***
Return 0.3317 -0.0249 -0.0343 1.0000 (<.0001) *** (0.2585) (0.1198)
OIBNUMt-1 0.0628 -0.0277 -0.0738 -0.0096 1.0000 (0.0044) *** (0.2091) (0.0008)
*** (0.6649)
VIX -0.0902 0.5325 0.5873 -0.1299 -0.0844 1.0000
(<.0001) *** (<.0001)*** (<.0001)*** (<.0001) *** (0.0001) ***
pcratio -0.1408 -0.0112 0.2060 -0.2712 -0.1454 0.2105 1.0000 (<.0001) *** (0.6128) (<.0001)
*** ( <.0001)*** (<.0001)*** (<.0001)***
AAII 0.0342 0.0278 -0.0428 -0.0015 0.0292 -0.2727 -0.1678 1.0000 (0.1203) (0.2068) (0.0523) * (0.9471) (0.1859) (<.0001)
*** (<.0001) ***
Panel D: QQQQ (OIBNUM)
OIBNUMt Lnσ Ln(volume) Return OIBNUMt-1 VXN pcratio AAII
OIBNUMt 1.0000
Lnσ -0.0453 1.0000 (0.2222)
Ln(volume) -0.0355 -0.1251 1.0000 (0.3386) (0.0007) ***
Return 0.4009 -0.0601 0.0574 1.0000 (<.0001)*** (0.1054) (0.122)
OIBNUMt-1 0.0358 -0.0487 -0.0392 -0.0290 1.0000 (0.3346) (0.1899) (0.2908) (0.4347)
VXN -0.0888 0.8217 0.1196 -0.0788 -0.0929 1.0000
(0.0166) ** (<.0001)*** (0.0012)*** (0.0338) ** (0.0122) **
pcratio -0.1839 -0.1885 0.2060 -0.3169 -0.1389 0.0060 1.0000 (<.0001)*** ( <.0001)*** (<.0001)*** (<.0001)*** (0.0002)
*** (0.8714)
AAII 0.0160 -0.2497 -0.0660 -0.0046 -0.0025 -0.4521 -0.0687 1.0000 (0.6676) (<.0001) *** (0.0755) * (0.9008) (0.9474) (<.0001) *** (0.0642) *
Table 5 The Empirical Results for Equation 2 and 3
This table provides the empirical results for equation 2 and 3. The dependent variables are percentage spread for Panel A, and OIBNUM for Panel B. In each panel, it is separated two parts, SPY and QQQQ, respectively. *, **, and *** indicate that the coefficient estimates are statistically significant at the 0.1 level, 0.05 level, and 0.01 level, respectively. The t-statistics are in parentheses. All figures have been standardized.
Panel A: Percentage Spread
SPY SPY SPY QQQQ QQQQ QQQQ
Dependent variable: Percentage spreadt
Intercept 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
(1.70) * (2.03) ** (0.98) (1.01) (1.01) (-0.55)
Lnσ 0.0479 0.0591 0.0119 0.0933 0.0924 0.0204
(1.31) (1.6) (0.29) (1.01) *** (4.39) *** (0.57)
Ln(volume) -0.0559 -0.0675 -0.0617 0.0486 0.0482 0.0283
(-1.53) (-1.82) * (-1.44) (4.46) *** (2.70) *** (1.46)
Return -0.044 -0.0441 -0.0471 -0.069 -0.0689 -0.0636
(-2.71) *** (-2.72) *** (-2.76) *** (-2.74) *** (-3.92) *** (-3.39) ***
Percentage spreadt-1 0.6732 0.6705 0.6542 0.8255 0.8236 0.8055
(2.71) *** (40.75) *** (38.8) *** (39.82) *** (38.58) *** (36.03) ***
VIX 0.0778
(3.58) ***
VXN 0.1034
(2.59) ***
pcratio -0.0459 0.00007
(-2.34) ** (0)
AAII -0.0311 -0.0172 -0.007 0.0146
(-1.88) * (-0.99) (-0.37) (0.72)
Adjusted R2 0.4584 0.4591 0.463 0.7787 0.7778 0.7793
Number of observations 2055 2055 2055 727 727 727
Panel B: OIBNUM
SPY SPY SPY QQQQ QQQQ QQQQ
Dependent variable: OIBNUMt
Intercept 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
(0.98) (0.71) (0.08) (1.02) (1.03) (1.25)
Lnσ 0.0349 0.02495 -0.0058 -0.0265 -0.0244 0.034
(0.75) (0.53) (-0.11) (-0.77) (-0.68) (0.49)
Ln(volume) -0.0581 -0.04793 0.0037 -0.0603 -0.0595* -0.0336
(-1.24) (-1.01) (0.07) (-1.76) * (-1.72) (-0.98)
OIBNUMt-1 0.0626 0.0622 0.0574 0.0439 0.0441 0.0329
(3.00) *** (2.98) *** (2.73) *** (1.29) (1.29) (0.95)
Return 0.3312 0.3313 0.3182 0.4040 0.4041 0.3846
(15.95) *** (15.96) *** (14.51) *** (11.35) *** (11.85) (10.51) ***
VIX -0.0301
(-0.11)
VXN -0.0874
(-1.18)
pcratio -0.0375 -0.0449
(-1.49) (-1.15)
AAII 0.0302 0.0189 0.0079 -0.0185
(1.44) (0.85) (0.22) (-0.47)
Adjusted R2 0.1136 0.1141 0.1148 0.1622 0.1611 0.1626
Number of observations 2060 2060 2060 727 727 727