SCHOOL OF FINANCE AND ECONOMICS
UTS:BUSINESS
WORKING PAPER NO. 74
JULY, 1997
Individual Share Futures Contracts: The Economic Impact
of Their Introduction on the Underlying Equity Market
Maurice Peat
Micahael McCorry
ISSN: 1036-7373
http://www.business.uts.edu.au/finance/
Individual Share Futures Contracts: The Economic Impact
of their Introduction on the Underlying Equity Market *
Maurice Peat
Securities Industry Research Centre
of Asia-Pacific (SIRCA)
&
School of Finance and Economics
University of Technology, Sydney
Broadway, NSW 2007
AUSTRALIA
Email: maurice@finomics.bus.uts.edu.au
and
Michael McCorry
Securities Industry Research Centre
of Asia-Pacific (SIRCA)
&
Department of Finance
University of Sydney
Sydney, NSW 2006
AUSTRALIA
Email: mikem@prince.econ.su.oz.au
*
The authors would like to thank the Australian Stock Exchange (ASX) and the Sydney
Futures Exchange (SFE) for supplying data, and the Security Industry Research Centre of
Asia-Pacific (SIRCA) for technical assistance and data access.
Abstract
In May of 1994 (and on two subsequent dates), the Sydney Futures Exchange introduced
futures contracts on selected issues of common stock. These new contracts, known as
individual share futures (ISF’s), represent a unique type of derivative product. This paper
examines the impact of the introduction of ISF contracts on the trading behaviour of the
underlying equity market. Using prior literature (related to the introduction of both options
contracts and stock index futures contracts on various global markets), a number of
hypotheses are developed from models of market behaviour. These hypotheses are tested
empirically within the Australian context. In contrast to both option and stock index
futures introduction, the introduction of ISF’s results in a significant increase in both the
underlying market trading volume and volatility, with no discernible returns effect.
I. Introduction
In 1994 the Sydney Futures Exchange (SFE) expanded the product offerings of the
Australian equity derivatives market by introducing futures contracts on selected issues of
common stock. These contracts, commonly referred to as Individual Share Future (ISF)
contracts, were introduced to assist in the development of Australian capital markets. The
SFE saw that a “range of SFE equity products could assist in the development of a more
active secondary stock market by providing alternate hedging and trading tools for both
Australian and international investors.”1
The aim of this study is to investigate the introduction of ISF contracts on returns,
volatility, and the microstructure of the underlying securities. There have been numerous
studies concentrating on the effects of options listing on the underlying securities. A useful
summary of the US results can be found in Damodaran and Subrahmanyam (1992). They
found that the listing of call options was associated with positive excess returns, while put
options were associated with negative excess returns around the listing date. The volatility
of the underlying markets was reduced by options listings, as was the bid-ask spread, due
primarily to the transfer of speculative activity from the underlying market to the options
market. However, there was no significant impact on trading volume.
In the Australian context Aitken, Frino and Jarnecic (1994) studied listings on the
Australian Options Market, where both the put and call are listed simultaneously. They
found positive excess returns, a decline in volatility, and an increase in trading volume.
The introduction of stock index futures has consistently been surrounded with
controversy. Two competing hypotheses exists with respect to the resulting impact on
market volatility. The first argues that the introduction of stock index futures causes a
1
Janelle McKimm, Financial Writer - Marketing, SFE.
1
decrease in liquidity and depth in the spot market, thereby causing an increase in volatility.
The competing view is that the introduction causes a migration of speculative activity from
the spot market to the futures market, thereby causing an increase in price stability in the
underlying market. Empirically, however, the results have shown no significant change
(positive or negative), in underlying market volatility after the introduction of stock index
futures.
ISF contracts represent a new category of derivative security. The effects of their
introduction on the underlying asset market must be empirically evaluated to fully
understand their usefulness in the capital market. This study evaluates the impact of the
introduction of ISF contracts on the underlying markets and compares these results to
those of option and stock index futures listings.
The remainder of the paper is organised as follows. Section 2 outlines the theoretical
arguments and derives a set of testable hypotheses. Section 3 describes the data and
method, and Section 4 discusses the results.
The final section provides a summary
comparison of the ISF results with options and stock index futures listing results, and
discusses potential directions of future research.
II. Models of the Impact of Derivative Product Introduction on Spot Markets
Empirical studies that investigate the market impact of the introduction of derivative
products have traditionally focused on either the introduction of options contracts or stock
index futures contracts. While there are a few arguments that apply specifically to one
derivative type and not the other, the two main arguments apply to both derivative types,
as well as the new ISF contracts.
The first set of arguments generally put forward are based upon the notion that as
markets become more complete, investors are better off.
2
This is a decidedly “pro-
derivative” view. In contrast, the second school of thought is based upon the assumption
that derivative securities, which are typically highly leveraged, encourage market
destabilising speculation. This “anti-derivative” view has become increasingly popular in
the wake of several international financial markets crises caused by abuses of derivative
products and/or markets.
The theory of market completeness was formally introduced in 1977 by Ross. Put
forth in a succinct manner, the theory states that the introduction of the derivative
securities expands the investment opportunity set faced by market participants, thereby
providing investment opportunities that were not previously available. In turn, it is argued
that the expansion of the investment opportunity set increases the utility of all investors,
reducing required rates of returns which leads to the increase in the price of the underlying
assets. Market completeness was one of the stated aims of the SFE when they made the
decision to introduce ISF contracts.
One component of market completeness is the concept of risk transference. Since
market participants have varying levels of risk aversion, and vastly different investment
objectives, derivative products allow for both the reduction of risk and the increased
exposure to risk depending upon the specific objectives of market participant.
In the presence of interaction between the prices of underlying assets and derivative
securities, DeTemple and Selden (1988) show that the introduction of options contracts
allows less risk adverse investors, who believe that the volatility of the asset will be high,
to shift to the options market. More risk adverse investors with lower volatility estimates
will move to the asset market. These shifts, combined with the increase in utility caused by
the expansion of the investment opportunity set, should cause the volume in both markets
to increase and the volatility of the underlying market to decrease.
3
The effect of information asymmetry between market participants is examined by
Grossman (1988) in a model of the volatility of the underlying asset with market frictions,
with and without options contracts trading on the spot asset. The market with options
trading is found to be less volatile than the market without options trading. This is due to
the fact that the options market allows for diverse opinions about the level of volatility and
incorporates these diverse opinion in options prices.
The “anti-derivative” arguments, which support the notion that the introduction of
derivative securities destabilises the underlying asset market, are frequently cited, but not
empirically supported.
Two factors which are said to cause this destabilisation are
speculative activity which causes “bubbles” and program trading systems which increase
the speed of response of market participants. Bubbles are caused when speculative activity
drives prices away from fundamental values. With respect to program trading, automated
response is often blamed for a lack of rationality with respect to pricing. The quick
response may cause an over-reaction to a given event (ie. a chain reaction that sends prices
plummeting) which effectively drives prices away from fundamentals. Irrespective of
which of these two factors impact the market, it is argued that the net effect is increased
volatility, greater uncertainty, and a resultant increase in the cost of capital for these issues.
A formal model which demonstrates the destabilising effect of options was developed
by Stein (1987). In this model, the speculation in derivative assets has two possible effects
that basically represent both the “pro-derivative” and “anti-derivative” positions. The first
effect allows investors to deal with risk more efficiently, which leads to price stability. The
other is that speculators with inferior information can affect the information content of
prices adversely. It is possible in Stein's model for the second effect to outweigh the first
and cause net destabilisation in the market.
4
From these models it is possible to derive a set of testable hypotheses to establish
which of the two competing frameworks better explains the economic consequences of the
introduction of ISF’s in the Australian market. If markets move towards completion and
stabilisation, the following market reactions should be observed:
H1A: There should be a one-time increase in stock prices and lower required returns
after the introduction of ISF contracts.
H2A: Trading volume should increase in the spot market.
H3A: There should be a decrease in volatility in the spot market after the introduction
of the ISF contracts.
If, however, the market is destabilised by the introduction of the ISF contracts, the market
reaction should be as follows:
H1B: There should be a one-time decrease in stock prices with increased required rates
of return.
H2B: The volume of trading should decrease in the spot market as orderflow migrates
to the ISF market.
H3B: The volatility of the underlying market should increase after the introduction of
ISF’s.
Whether the introduction of ISF contracts is a stabilising factor in the marketplace (set of
hypotheses A) or destabilising (set B) is an empirical issue that is tested in the following
section.
III. Data and Method
The first group of ISF contracts were introduced on 16 May, 1994. Since that date, two
additional groups of ISF’s have been introduced. Table 1 lists the ISF introduction dates,
the spot securities, and contract details for all currently trading ISF's. The contracts are all
of similar structure. Initial margins are set by the SFE clearing house according to the
5
volatility of the underlying stock.2 There are no position limits or daily price limits on
these contracts. Each contract is for 1000 shares of the underlying stock. The price of the
contract is quoted in cents per share with a one cent (1c) movement in the share price
equating to a ten dollar ($10) movement in the value of the futures contract. Open
positions are marked-to-market at the end of each trading day against the closing price of
the underlying stock on the ASX (eg. the midpoint of the closing bid-ask quote from
SEATS).3 All contracts are cash settled on the day of expiry. The settlement price is the
average of the spread midpoints extracted from SEATS over the last 120 one-minute
intervals of trading on the settlement day.
Underlying equities data was extracted from the ASX database at the Securities
Industry Research Centre of Asia-Pacific (SIRCA) for 100 days before and after each
contract listing. There are ten ISF contract listings available for use in this study. All ten
are examined.
The raw trading volume for each of the ten companies with ISF listings are examined.
The average volume is calculated for 100 days before and after the ISF listing. Consistent
with prior studies there is no control for possible market wide effects.
The behaviour of returns on the underlying assets are examined using a marketadjusted event study approach. The expected return on the assets is assumed to be the
return on the market, as measured by returns on the All Ordinaries Index. The excess
return is then the difference between the realised and expected returns. Excess returns are
calculated in event time for 21 days, 10 days prior to listing and 10 days after listing. The
2
As of January 1996, initial margins range from $50 to $750 per contract.
3
SEATS is the Stock Exchange Automated Trading System on the ASX.
6
excess returns are aggregated over this period to provide an overall picture of the return
effects of the listings.4
Volatility changes are analysed using average volatility and market adjusted average
volatility both for 10 and 20 days before and after listing. Volatility is defined to be the
average of the squared returns over the previous five days.5 The market adjustment was
effected by subtracting the matching volatility of the index from the stock’s volatility.
Regression analysis and t-statistics are used to examine whether there has been a
significant change in volatility after ISF listings. As there is a known relationship between
volatility and trading volume [see French and Roll (1986)], the regression approach
controls for the volume effect in testing for a significant change in the average volatility of
the stocks.
IV. Results
Table 2 reports the results of the aggregate raw trading volume analysis around the listing
of the ISF contracts. Each of the 10 listed stocks is tracked for 100 days before and after
listing.
Table 2 indicates that on average the mean trading volume increases after the listing of
the ISF contract. The difference is significant at the 5% level of a t-test for differences in
mean. Six of the ten firms considered in the study experience an increase in trading volume
post-ISF listing. These results are in line with the findings of the studies of option listings
on underlying assets.
The analysis of average trading volume for the individual companies for 100 days
before and after the ISF listing is presented in Table 3. The results show that 6 of the 10
4
See Bowman (1983) for an exposition of the event study methodology.
7
companies display an increase in trading volume after contract listing. However, only three
of these increases are statistically significant. Of the four companies who experience a
decrease in trading volume, three experience statistically significant decreases. It would
appear that the aggregate result of a significant increase in trading volume is being driven
by the highly significant increases in CRA and FBG.
Table 4 lists the results of the mean returns analysis. The average excess day-to-day
returns, the average raw return per trade, their standard deviations, and a t-score for a test
against a zero mean for the 10 days before and after the ISF listing are presented in this
table. It shows that there is one day where the average abnormal returns are significantly
different from zero. On all other days there are no significant returns of either type. This
finding is not consistent with the results on option listings, where positive abnormal returns
were observed before and after the listing events and a one-off increase in price, reflected
by a jump in the CAR plot on day 0 ( the event day ) or day 1, is evident. As this result is
an average over the 10 listings at the individual stock level, a significant effect may be
observed.
Figure 1 graphs the cumulative abnormal excess returns over the study period. A
one-off price increase should appear as a step-up in the CAR graph close to the listing day
(day 0 or day 1) if the “set A” (stabilising hypotheses) were supported. There is no such
observable increase. The graph exhibits negative CAR’s after the listing date, which is
consistent with the set “B” hypotheses, or an increase in the required return for market
participants. However, Table 4 shows that none of the returns are significantly different
from zero, so we can draw no strong conclusions from this analysis.
5
See Merton 1980 appendix A.
8
Tables 5 and 6 contain the results of the univariate analysis of the changes in
volatility around the listing dates. The average volatility and excess volatility calculated
over 10 and 20 days before and after the ISF listings are compared using a t-test. Over a 20
day period five firms have an increase in volatility, eight firms show an increase in excess
volatility. Volatility and excess volatility decreases for two firms. Over a 10 day period
four firms have a significant increase in volatility, one has a decrease. Over the same time
four firms have an increase in excess volatility, one has a decrease.
There is evidence that volatility is positively related to trading volume. This
suggests the need to control for the increase in trading volume observed. Regressions of
volatility against a constant, a dummy variable, which is zero up to the listing date and
one for the listing day and the post listing period and trading volume are reported in Tables
7 and 8.
These results are consistent with the univariate analysis. Over 20 days five firms
show an increase in volatility, one a decrease. Eight firms have an increase in excess
volatility, one a decrease. The results for the 10 days before and after the listings have four
firms with an increase in volatility, two with a decrease. Five firms have an increase in
excess volatility, one a decrease.
These results are not consistent with a strong market completion effect being
associated with ISF listings.
V. Conclusion
The listing of ISF contracts is associated with a significant positive increase in trading
volume in the underlying market, no significant change in the underlying price level or
level of returns, and an increase in underlying volatility. These results are not consistent
9
with a market completing theory. They do, however, indicate a week destabilisation of the
underlying market stemming from the introduction of the ISF contracts.
These results are substantially different to those reported in Aitken, Frino and Jarnecic
for option listings. They found a strong market completing effect. Volume increased, there
was a one-off price effect, and volatility decreased when options trading was introduced
for a given stock. The reason for the differences in results may be attributed the difference
in liquidity between the two markets.
10
References
Aitken M., Frino A. and Jarnecic E. (1994), “Option Listings and the Behaviour of
Underlying Securities: Australian Evidence,” SIRCA Working Paper.
Bowman R. (1983), “Understanding and Conducting Event Studies,” Journal of Business
Finance & Accounting. 10(4), 561-584.
Brailsford, T. (1994), “Stock Market Volatility: A Review Essay,” Accounting Research
Journal 7, 43-63.
Brailsford, T. and Cusack A. (1995), “Individual Share Futures: An Examination of a New
Derivative,” University of Melbourne Working Paper.
Damodaran A. and Subrahmanyam M. (1992), “The Effects of Derivative Securities on the
Markets for the Underlying Assets in the United States,” Financial Markets,
Institutions and Instruments. 1, 1-22.
DeTemple J. and Selden L. (1988), “Option Listing and Stock Returns,” First Boston
Working Paper Series, Columbia University.
French K. and Roll R. (1986), “Stock return variances: The arrival of information and the
reaction of traders,” Journal of Financial Economics 12, 279-283.
Grossman S. (1988), “An Analysis of the Implications for Stock and Futures Price
Volatility of Program Trading and Dynamic Hedge Strategies,” Journal of Business
61, 275-298.
Merton R. (1980), “On estimating the expected return on the market: An exploratory
investigation,” Journal of Financial Economics 8, 323-361.
Ross S. (1977), “Options and Efficiency,” Quarterly Journal of Economics 4, 129-176.
Stein J. (1987), “Informational Externalities and Welfare-reducing Speculation,” Journal
of Political Economy 95, 1123-1145.
11
Table 1: ISF Introduction Dates
Listing Dates, ASX stock codes, SFE contract codes and contract
denominations for currently traded ISF contracts.
Options Listing Date Underlying Contract
Stock
Code
BHP
BP
16 May, 1994
NAB
NB
NCP
NU
ME
Contract
Unit
1000 shares
1000 shares
1000 shares
1420 shares
26 September, 1994
BTR
MIM
WBC
WMC
TR
IM
BC
WM
1000 shares
1000 shares
1000 shares
1000 shares
13 March, 1995
ANZ
CRA
FBG
AN
CR
FB
1000 shares
1000 shares
1000 shares
12
Table 2: Aggregate Raw Trading Volume Analysis
The total average over the 100 days prior to ISF listing is compared with the
average over the 100 days post listing for significant differences. A t-test for
differences in the mean and descriptive statistics are reported.
Pre-Introduction
Post-Introduction
Ratio (Pre/Post)
Trading Volume (Shares)
Mean
STD
Maximum Minimum
2,913,402
2,305,709
23,068,725 221,012
3,153,110
2,743,691
33,996,597 212,992
1.08
1.19
13
Table 3: Company Specific Volume Analysis
The average volume over the 100 days prior to ISF listing is compared with the
average over the 100 days post listing for significant differences. A t-test for
differences in the mean is reported.
BHP
NAB
NCP
BTR
MIM
WBC
WMC
ANZ
CRA
FBG
Trading Volume (Shares)
Pre
Post
t-score
3,280,982
2,743,905
-2.35
2,668,650
2,873,481
0.93
3,131,762
2,599,341
-2.31
2,711,765
2,757,549
0.18
4,812,341
6,491,123
2.79
2,175,464
2,441,658
1.19
3,015,552
3,007,555
-0.03
3,416,727
2,821,051
-2.41
814,890
983,997
2.89
3,105,888
4,811,441
3.66
14
p-value
0.02
0.35
0.02
0.86
0.01
0.24
0.98
0.02
0.00
0.00
Table 4: Average Returns and Abnormal Returns around ISF Listing Days
The average excess return (return) for a period covering 10 days before to 10 days
after ISF listings are tested for significant difference from 0 using a t-test.
Excess Returns (%)
Day
Total
Average
Raw Returns (%)
Std
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0.0094
0.0276
0.0742
-0.0064
0.0083
-0.0634
-0.0215
-0.0197
0.0194
-0.0176
0.0009
0.0028
0.0074
-0.0006
0.0008
-0.0063
-0.0021
-0.0020
0.0019
-0.0018
0.0129
0.0099
0.0100
0.0137
0.0105
0.0120
0.0088
0.0068
0.0126
0.0117
t
(null=0)
0.2301
0.8773
2.3534
-0.1481
0.2488
-1.6723
-0.7708
-0.9119
0.4854
-0.4746
0
1
2
3
4
5
6
7
8
9
10
-0.0266
-0.0131
0.0001
-0.0165
-0.0429
-0.0288
0.0090
0.0130
0.0014
0.0730
0.0191
-0.0027
-0.0013
0.0000
-0.0016
-0.0043
-0.0029
0.0009
0.0013
0.0001
0.0073
0.0019
0.0147
0.0119
0.0126
0.0124
0.0101
0.0091
0.0115
0.0100
0.0095
0.0132
0.0063
-0.5720
-0.3479
0.0015
-0.4210
-1.3429
-1.0014
0.2489
0.4103
0.0456
1.7542
0.9647
15
Total
Average
Std
-0.0953
0.0641
0.0287
-0.0476
0.0213
-0.0658
-0.0287
-0.0260
0.0237
0.0143
-0.0095
0.0064
0.0029
-0.0048
0.0021
-0.0066
-0.0029
-0.0026
0.0024
0.0014
0.0079
0.0107
0.0117
0.0166
0.0099
0.0084
0.0090
0.0142
0.0133
0.0156
t
(null=0)
-0.1654
0.1626
0.0927
-0.0268
0.0563
-0.1114
-0.0359
-0.0884
0.0372
-0.0060
0.0665
-0.0727
0.0607
-0.0125
-0.0012
-0.0421
-0.0060
-0.0870
-0.0321
0.0847
0.0739
0.0066
-0.0073
0.0061
-0.0012
-0.0001
-0.0042
-0.0006
-0.0087
-0.0032
0.0085
0.0074
0.0191
0.0143
0.0126
0.0121
0.0113
0.0091
0.0160
0.0098
0.0088
0.0116
0.0111
0.0921
-0.1132
0.1097
0.0159
-0.0139
-0.0892
-0.0275
-0.1358
-0.0246
0.1519
0.1849
Table 5: Volatility Analysis
The average volatility (excess volatility) over the 20 days prior to ISF listing is compared
with the average over the 20 days post listing for significant differences. A t-test for
differences in the mean is reported.
Volatility
Average
BHP
NAB
NCP
BTR
MIM
WBC
WMC
ANZ
CRA
FBG
Excess Volatility
After
Before t-score p-value
0.0128 0.0123 0.7493 0.460
0.0132 0.0100 1.6650 0.111
0.0114 0.0075 4.1170 0.000
0.0154 0.0122 2.5740 0.014
0.0139 0.0240 -2.1812 0.041
0.0162 0.0133 2.0120 0.052
0.0125 0.0092 3.4744 0.001
0.0114 0.0174 -4.0057 0.001
0.0113 0.0089 2.7039 0.010
0.0098 0.0094 0.3704 0.714
0.0129 0.0113 1.6771 0.103
16
After
Before t-score p-value
0.0058 0.0038 2.5764
0.017
0.0055 0.0015 2.9510
0.007
0.0034 -0.0010 4.1302
0.000
0.0077 0.0036 2.5798
0.014
0.0080 0.0172 -2.0986
0.048
0.0103 0.0064 2.5076
0.017
0.0066 0.0023 3.2489
0.003
0.0054 0.0105 -3.9128
0.001
0.0036 -0.0017 2.9612
0.006
0.0021 -0.0012 2.0343
0.050
0.0053 0.0008 2.3393
0.028
Table 6: Volatility Analysis
The average volatility (excess volatility) over the 10 days prior to ISF listing is compared
with the average over the 10 days post listing for significant differences. A t-test for
differences in the mean is reported.
Average
BHP
NAB
NCP
BTR
MIM
WBC
WMC
ANZ
CRA
FBG
Volatility
Excess Volatility
After
Before t-score p-value
0.0135 0.0144 -1.4016 0.184
0.0197 0.0108 3.8685 0.003
0.0107 0.0078 2.6252 0.025
0.0142 0.0161 -1.8017 0.093
0.0140 0.0370 -3.6904 0.004
0.0173 0.0125 2.5797 0.026
0.0114 0.0102 0.8410 0.416
0.0110 0.0149 -2.0373 0.069
0.0127 0.0099 2.6918 0.020
0.0121 0.0111 1.6423 0.119
0.0121 0.0135 -1.1882 0.252
After
Before t-score p-value
0.0062 0.0062 -0.0379
0.970
0.0101 0.0025 4.7874
0.000
0.0011 -0.0006 1.7132
0.109
0.0045 0.0078 -2.0262
0.068
0.0081 0.0299 -3.9709
0.003
0.0114 0.0054 2.4595
0.026
0.0055 0.0031 1.1035
0.291
0.0051 0.0078 -1.5470
0.140
0.0058 0.0006 2.8878
0.010
0.0053 0.0017 2.5604
0.028
0.0053 0.0042 0.5410
0.598
17
Table 7: Volatility Regression Analysis
The volatility (excess volatility) over the 20 days pre- and post-ISF listing is the dependant
variable, a constant, a dummy for the ISF listing and volume are the indepentant variables.
The coefficient, t-score and p-value of the ISF listing dummy are reported.
Volatility
Average
BHP
NAB
NCP
BTR
MIM
WBC
WMC
ANZ
CRA
FBG
Coefficient
0.0004
0.0044
0.0036
0.0028
-0.0077
0.0024
0.0033
-0.0060
0.0028
0.0006
0.0016
Excess Volatility
t-score p-value
0.6043
0.549
2.3048
0.027
3.5588
0.001
2.1179
0.041
-1.7786
0.083
1.6670
0.104
3.3297
0.002
-3.8019
0.001
3.2254
0.003
0.4730
0.639
1.6455
0.108
18
Coefficient t-score p-value
0.0045
2.2442
0.031
0.0050
3.6083
0.001
0.0045
3.8210
0.000
0.0039
2.2630
0.029
-0.0066 -1.6531
0.107
0.0033
2.1818
0.035
0.0043
3.1917
0.003
-0.0050 -3.6506
0.001
0.0058
3.2028
0.003
0.0036
2.1584
0.037
0.0048
2.4792
0.018
Table 8: Volatility Regression Analysis
The volatility (excess volatility) over the 10 days pre- and post-ISF listing is the dependant
variable, a constant, a dummy for the ISF listing and volume are the indepentant variables.
The coefficient, t-score and p-value of the ISF listing dummy are reported.
Volatility
Average
BHP
NAB
NCP
BTR
MIM
WBC
WMC
ANZ
CRA
FBG
Coefficient
-0.0008
0.0106
0.0038
-0.0017
-0.0190
0.0046
0.0007
-0.0040
0.0027
0.0010
-0.0017
Excess Volatility
t-score p-value
-1.2376
0.233
5.0705
0.000
2.7050
0.015
-1.5790
0.133
-2.8124
0.012
2.4989
0.023
0.5034
0.621
-2.0050
0.061
2.5847
0.019
1.4328
0.170
-1.3646
0.190
19
Coefficient t-score p-value
-0.0001 -0.2261
0.824
0.0089
5.4299
0.000
0.0031
2.4235
0.026
-0.0026 -1.5703
0.134
-0.0180 -3.0277
0.007
0.0055
2.2233
0.039
0.0017
0.7189
0.481
-0.0020 -1.1108
0.281
0.0040
2.9318
0.009
0.0021
2.6531
0.016
-0.0007 -0.5822
0.568
Figure 1: Average Day-to-Day Excess Returns
Average Day-to-Day Excess Returns
1.5
1
CAR (%)
0.5
0
-10
-8
-6
-4
-2
0
-0.5
-1
-1.5
Days
20
2
4
6
8
10