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ADVANCES IN QUANTITATIVE ANALYSIS OF
FINANCE AND
ACCOUNTING
vOLUME 6

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N E W J E R S E Y
•
L O N D O N
•
S I N G A P O R E
•
B E I J I N G
•
S H A N G H A I
•
H O N G K O N G
•
TA I P E I
•
C H E N N A I
World Scientic
Editor
Cheng-Few Lee
Rutgers University, USA
Volume 6
6741 tp.indd 2 2/1/08 9:14:30 AM

publication designed to disseminate developments in the quantitative analy-
sis of finance and accounting. The publication is a forum for statistical and
quantitative analyses of issues in finance and accounting as well as applica-
tions of quantitative methods to problems in financial management, financial
accounting, and business management.The objective is to promote interaction
between academic research in finance and accounting and applied research in
the financial community and the accounting profession.
The chapters in this volume cover a wide range of topics. In this volume
there are 12 chapters, three of them are corporate finance and debt manage-
ment: 1. Collateral Constraints, Debt Management, and Investment Incen-
tives, 2. Thirty Years of Canadian Evidence on Stock Splits, Reverse Stock
Splits, and Stock Dividends,and3. Corporate Capital Structure and Firm
Value: A Panel Data Evidence From Australia’s Dividend Imputation Tax
System. There are two of the other nine chapters which cover earnings man-
agement: 1. Why is the Value Relevance of Earnings Lower for High-Tech
Firms? and 2. Earnings Management in Corporate Voting: Evidence from
Anti-Takeover Charter Amendments.
Three of the other seven chapters discuss equity markets: 1. Evaluating
the Robustness of Market Anomaly Evidence, 2. Intraday Volume–Volatility
Relation of the DOW: A Behavioral Interpretation,and3. Determinants of
Winner–Loser Effects in National Stock Markets. Two of the other four chap-
ters analyze options and futures: 1. The Pricing of Initial Public Offerings: An
Option Apporach and 2. The Momentum and Mean Reversion Nikkei Index
Futures: A Markov Chain Analysis.
The remaining two chapters are related to portfolio diversification and
quadratic programming: 1. A Concave Quadratic Programming Marketing
Strategy Model with Product Life Cycles and 2. Corporate Capital Structure
and Firm Value: A Panel Data Evidence from Australia’s Dividend Imputation
Tax System. In sum, this annual publication covers corporate finance and debt
management, earnings management, options and futures, equity market, and

Chapter 7 The Pricing of Initial Public Offerings: An Option
Approach 127
Sheen Liu, Chunchi Wu and Peter Huaiyu Chen
vii

February 18, 2008 16:14 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 fm
viii Contents
Chapter 8 Determinants of Winner–Loser Effects
in National Stock Markets 143
Ming-Shiun Pan
Chapter 9 Earnings Management in Corporate Voting:
Evidence from Antitakeover Charter Amendments 159
Chun-Keung Hoi, Michael Lacina and
Patricia L. Wollan
Chapter 10 Deterministic Portfolio Selection Models,
Selection Bias, and an Unlikely Hero 179
Herbert E. Phillips
Chapter 11 Corporate Capital Structure and Firm Value:
A Panel Data Evidence from Australia’s Dividend
Imputation Tax System 205
Abu Taher Mollik
Chapter 12 The Momentum and Mean Reversion of Nikkei
Index Futures: A Markov Chain Analysis 239
Ke Peng and Shiyun Wang
Index 253

February 18, 2008 16:14 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 fm
List of Contributors
Chapter 1
Elettra Agliardi

Cindy Hsiao-Ping Peng
Yu Da College of Business, Taiwan
Tel: 011886 34226134
Email: [email protected]
Ken Hung
Department of Finance
National Dong Hua University
Hua-lien, Taiwan
Tel: 360 715 2003
Email: [email protected]
Chapter 3
W illiam D. Brown, Jr.
Department of Business Administration
Stonehill College
Easton, MA 02357
Tel: (508) 565-1256
Fax: (508) 565-1444
Email: [email protected]
Erin A. Moore
Department of Accounting
College of Business and Economics
Lehigh University
621 Taylor Street
Bethlehem, Pennsylvania 18015-3117
Tel: (610) 758-4962
Fax: (610) 758-6429
Email: [email protected]

February 18, 2008 16:14 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 fm
List of Contributors xi

Chapter 5
Vijay Jog
Professor of Finance
Eric Sprott School of Business
Carleton University
1125 Colonel By Drive
Ottawa, Ontario, Canada, K1S 5B6
Tel: (613) 520-2600 Ext. 2377
Email: [email protected]
PengCheng Zhu
Ph.D. candidate
Eric Sprott School of Business
Carleton University
Email: [email protected]
Chapter 6
Ali F. Darrat
Department of Economics and Finance
Louisiana Tech University
Ruston, LA 71272
Shafiqur Rahman
School of Business Administration
Portland State University
P. O. Box 751
Portland, OR 97207-0751
Tel: (503) 725-3715
Fax: (503) 725-5850
Email: [email protected]
Maosen Zhong
UQ Business School
The University of Queensland

Fax: 717-477-4067
Email: [email protected]

February 18, 2008 16:14 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 fm
xiv List of Contributors
Chapter 9
Chun-Keung Hoi
Rochester Institute of Technology
106 Lomb Memorial Drive
Rochester, NY 14623-5608
Phone: (585)-475-2718
Fax: (585)-475-6920
Email: [email protected]
Michael Lacina
University of Houston-Clear Lake
2700 Bay Area Boulevard
Houston, TX 77058-1098
Tel: (281) 283-3171
Fax: (281) 283-3951
Email: [email protected]
Patricia L. Wollan
Rochester Institute of Technology
106 Lomb Memorial Drive
Rochester, NY 14623-5608
Phone: (585)-475-4419 (Phone)
Fax: (585)-475-6920 (Fax)
Email: [email protected]
Chapter 10
Herbert E. Phillips
Professor of Finance

Tel: +86 (0)28 87099197
Email: [email protected]

February 18, 2008 16:14 spi-b567 Adva nces in Quantitative Analysis of Finance and Accounting: Vol.6 edtbd
Advances in Quantitative Analysis of Finance and Accounting
Editorial Board
Mike J. Alderson University of St. Louis, USA
James S. Ang Florida State University, USA
K. R. Balachandran New York University, USA
Thomas C. Chiang Drexel University, USA
Thomas W. Epps University of Virginia, USA
Thomas J. Frecka University of Notre Dame, USA
Robert R. Grauer Simon Fraser University, Canada
Puneet Handa University of lowa, USA
Der-An Hsu University of Wisconsin, Milwaukee, USA
Prem C. Jain Georgetown University, USA
Jevons C. Lee Tulane University, USA
Wayne Y. Lee Kent State University, USA
Scott C. Linn University of Oklahoma, USA
Gerald J. Lobo University of Houston, USA
Yaw Mensah Rutgers Unversity, USA
Thomas H. Noe Tulane University, USA
Thomas Noland University of Houston, USA
Fotios Pasiouras University of Bath, UK
Oded Palmon Rutgers University, USA
Louis O. Scott Morgan Stanley Dean Witter, USA
Andrew J. Senchak University of Texas, Austin, USA
David Smith Iowa State University, USA
K. C. John Wei Hong Kong Technical University, Hong Kong
William W. S. Wei Te mple University, USA

risks and is subject to collateral constraints. The model considered here is a
sovereign debt one, with default risk and endogenous collateral.
Collateral is typically used to secure loans. Since the article by Kiyotaki
and Moore (1997), it has been pointed out that if collateral is endogenous,
then the debt capacity of firms is altered, causing fluctuations in output
(Krishnamurthy, 2003). In this chapter, a model is discussed where the use of
1

February 19, 2008 10:10 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 ch01
2 E. Agliardi & R. Andergassen
hedging instruments may affect collateral values and thus, the debt capacity
of the debtor.
In most literature relating to the 1980s debt c risis and following the Bulow
and Rogoff models (1989, 1991), a given proportion of output or exports are
assumed to be available for repayment of outstanding debt. This means that
repayment is modeled as an output tax and actual repayment is the minimum
of this amount and debt. Alternatively, in other models (Eaton and Gersowitz,
1981; Eichengreen, 2003; Thomas, 2004) a fixed sanction is established in the
case of default, which is not a direct claim on the country’s current resources
and is not received by the creditors, but may represent the future losses due
to diminished reputation. In this chapter, a model is developed where the
amount of repayment by the debtor country is determined endogenously by an
optimizing choice of the debtor and where the two above mentioned aspects of
the repayment contract are present. Indeed, the debt contract is a collateralized
one, where profits on internationally tradable goods can be used forrepayment,
constituting the endogenous collateral; additionally, in the case of default, a
sanction is imposed which affects nontradable goods, which represents the
cost to the debtor of defaulting. Within this framework, hedging may be driven
by the desirability to reduce expected default costs. As Smith and Stulz (1985)
have shown, by hedging a debtor is able to reduce the likelihood of default by

In this chapter optimal investment and hedging decisions are characterized.
It is shown that the decision to use nonlinear hedging strategies in addition
to futures contracts can be optimal in relation to market conditions and finan-
cial constraint of the economy. In particular, it is shown in which way the
optimal hedging decision is affected by the cost of default. In addition to a
short position in futures, either concave or convex hedging with options is
optimal, depending on the size of default costs. In particular, it is found that
if default costs are sufficiently large, options are used for financing purposes,
that is, to increase financial resources when these are needed for investment
purposes. If default costs are sufficiently low, options are employed for spec-
ulative motives, i.e., financial resources are reduced when they are needed for
investment purposes. The present results are thus closely related to those of
Adam (2002, 2004) who shows how firms employ nonlinear hedging strategies
to match financial resources against financial needs at different time periods.
The remainder of the chapter is organized as follows. Section 2 describes
the model and the hedging problem of the economy. Section 3 contains the
optimal hedging choices of a futures and straddles. Section 4 concludes. All
proofs are in the Appendix.
2. The Model
The model is a two-period model of sovereign debt with default risk.
1
Con-
sider an economy having access to a technology producing an internationally
tradable and a nontradable good, denoted by y
T
and y
NT
, respectively. In the
1
For a survey of the literature about sovereign debt, see Eaton and Fernandez (1995), in Hand-

At time 2, when price uncertainty is resolved, the usual profit maximization
yields:
g(z, p) = max
y
T
{py
T
− c
1
(y
T
, z)}
where c
1
(y
T
, z) is the variable costfunction which is conditionalonthe levelof
z. In what follows, it is assumed that the production function is y
T
=
˜
Az
β
2
L
1
2
,
where L is labor and 0 <β<1. Therefore, g(z, p) = p
2

˜αqy
NT
− c
2
(y
NT
, k)

in case of default
where c
2
(y
NT
, k) is a twice continuously differentiable function with positive
first and second derivative in y
NT
and c
2
(0, k) = 0 . To simplify the exposition,
the following production function y
NT
=
˜
Bk
1−η
L
η
has been considered,

February 19, 2008 10:10 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 ch01

∗
|),andv =|p − p
∗
|,wherep
∗
is the strike
price. Then, the collateral constraint requires π(p) ≥ 0. Notice that for s > 0,
i.e., a short position in straddles, the economy increases its financial resources
available for investment in the first period at the cost of reducing them in the
second period, while for s < 0, i.e., a long position in straddles, the opposite
occurs. Since in the present model the economy has no initial endowments,
for s > 0 straddles are used for financing purposes since shortening straddles
reduces financial constraints in the first period where investment decisions
have to be taken. For s < 0 straddles are used for speculative purposes since
financial resources are reduced when these are needed for investment pur-
poses, while financial constraints are alleviated in the second period when
repayments are due. The same argument holds true for short and long posi-
tions in futures.
Gi ven the collateral constraint, at time 1 when the price uncertainty has
not been solved yet, the problem is specified as follows:
max
k,z,x,s
(k,α,χ)≡ Bk[1 − (1 −α)(1 − χ)] (2)
2
A long/short straddle is a portfolio which consists of a long/short put and a long/short call on
the same asset with the same strike price and exercise time.

February 19, 2008 10:10 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 ch01
6 E. Agliardi & R. Andergassen
where χ =

Benchmark
Consider the case where the price of the collateral is known with certainty,
and equal to its average value, i.e., p =
p,where p = E(p). The problem
reduces to:
max
z
{p
2
Az
β
−rz}
From the first-order condition z
0
=

β
−2
p
A
r

1
1−β
is obtained and thus, optimal
k is obtained from condition π(
p) = 0 which yields k
0
=
1−β

Az
β
−rz − rk +
p
2
s +[2
pAz
β
− x − s]ε + Az
β
ε
2
π(−ε) = p
2
Az
β
−rz − rk +
p
2
s −[2
pAz
β
− x − s]ε + Az
β
ε
2
The following result can be obtained.
Proposition 1. A short futures position x = g
p
(z, p) = 2 pAz

s + Az
β
ε
2
π(ε) ≥ 0 for values external to the two roots:
ε
1,2
=
s ±

s
2
− 4 [p
2
Az
β
−r (z + k) +
p
2
s]Az
β
2Az
β
(3)
where δ =
s
s
∗
and s
∗

∗
(β, δ) the optimal choice is δ = 1 and c = 0, while for α
∗
(β, δ) < α ≤ 1
the optimal choice is δ =−δ and c ∈ (
1
2
, 1], where α
∗
(β, δ) is a decreasing

February 19, 2008 10:10 spi-b567 Advances in Quantitative Analysis of Finance and Accounting: Vol.6 ch01
8 E. Agliardi & R. Andergassen
function of β and δ and is strictly positive for β<β(δ) and 0 otherwise,
where β

(δ) < 0.
Proposition 2 states that optimality requires nonlinear hedging. For s uf-
ficiently low values of α, i.e., sufficiently large costs of default, optimality
requires a short position of s
∗
≡ pAz
β
straddles. Moreover, in this regime, the
economy is induced never to default. The intuition for this result is as follows.
Short selling straddles increases financial resources a vailable for investment
in the first period while it increases financial constraints in the second period.
Thus, if default costs are sufficiently large, borrowing constraints are tighter,
and thus the economy uses straddles to reduce these constraints in the first
period and chooses not to default. Thus, in this regime straddles are used for

emerging markets, which point out that if collateral is endogenous, then the
debt capacity of an economy is altered.