Identification and Measurement of Variables for Regression

To ascertain the major determinants of the short-run and long-run market performance, this study developed binary and multiple regression models. The explanatory variables of these regression models were identified under the three categories of issue-specific characteristics, firm-specific characteristics and market-specific characteristics. Issue- specific characteristics were defined as offer-related characteristics, such as offer size, offer price and total listing period (TOTP). Firm-specific characteristics are such factors as firm size, book value and ownership structure. Market-specific characteristics are those specific to the stock market, such as MV, MR, MS and HMs. Most of the issue and firm characteristics were identified using the IPO companies’ prospectuses and market characteristics were identified using market information. These characteristics provided information on the issues, firms and markets, which might help to explain the short-run and long-run market performance of Australian IPOs. All the variables except the IPOP and WICP in this study were identified and measured using the literature. IPOP and WICP, which have not been tested in previous Australian studies, were used as new explanatory variables in this study. The IPOP is defined as the period that is given to initial investors to invest. This period is measured in calendar days, and covers the period from opening to closing days of the offer. This variable was used as proxy to measure the informed or uninformed demand. The WICP variable indicates whether the IPO companies used issued equity capital to finance working capital requirements. This indicates the company’s financing/investment policy, which shows that long-term funds are used for short-term investment. This variable measures future uncertainty about the company.

Following other researchers, the first-day PRIM, SECON and post-day MR were specially tested in the long-run models as explanatory variables. The PRIM measures the returns from the issuing date to the beginning of the listing date and it was tested for the investor overoptimism or market overreaction hypotheses. The SECON measures the returns from the beginning of the first listing date to the closing, which tests the signalling hypothesis. The MR measures the post-day MR using the market index for the same return interval as the dependent variable. The regression coefficient of the MR variable shows the average beta of the sample companies, which measures the market risk. All the explanatory variables (issue-, firm- and market-specific characteristics) with their measurements, expected signs and relevant theories are given in Table 3.3.

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Table 3.3: Selected Explanatory Variables with Measurement, Expected Sign and Relevant Theories

Explanatory variables Variable in

the model

Variable measure Expected sign Variable proxy for theory

Issue-specific characteristics Short-

run

Long- run IPO period (time given to invest) IPOP Period from opening to closing days of the offer measured in

calendar days

– Rock hypothesis

Issue price (PRICE) Offer price of the issue – Signalling hypothesis/uncertainty hypothesis

Offer size (OSIZE) The number of offered shares times the issue price – + Uncertainty hypothesis Listing delay LISD Time period between the proposed listing date and the actual

listing date measured in business days

+/– Uncertainty hypothesis/Rock hypothesis

Total listing period (time to listing)

TOTP Time period between the issued date and the listed date measured in business days

– Rock hypothesis Issue cost ratio ICOR Total issue cost including ASIC fee, ASX fee, broker

commission, manager fee, annual report fee, legal cost, industry report fee, printing fee, other costs relative to the total offer proceeds

+ – Uncertainty hypothesis

Total net proceeds ratio TNPR 1 minus issue cost ratio – + Uncertainty hypothesis Underwriter availability UWRA Dummy variable, which denotes 1 for ‘underwritten IPOs’ and 0

for ‘otherwise’

+ + Signalling hypothesis

Attached share option availability ATOA Dummy variable, which denotes 1 for ‘attached share option with the offer’ and 0 for ‘otherwise’

– Agency cost hypothesis Oversubscription option

availability

OVSO Dummy variable, which denotes 1 for oversubscription accepted by issuing company and 0 for otherwise

+ + Signalling hypothesis/Rock hypothesis

Recovery of working capital WICP Dummy variable, which denotes 1 for ‘issuing company recovers the short-term working capital requirement from the initial issue capital’ and 0 for ‘otherwise’

+ – Uncertainty hypothesis

Firm-specific characteristics

Book value per share (BOOKV) Total equity capital divided by the number of equity shares + Signalling hypothesis

Original ownership OWSH Percentage of shares retained by original owners +/- + Signalling/agency-cost/ownership dispersion hypothesis

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Firm age (1+FAGE) Number of years between the year of creation and listing – + Uncertainty/overoptimistic hypothesis Firm size (FSIZE) Total assets at the end of the year preceding the IPO of an

issuing firm

– + Uncertainty hypothesis Primary market return* (PRIM) The first-day primary market measures the returns from the

issuing date to the beginning of the listing date**

– Overoptimistic hypothesis Secondary market return* (SECON) The first-day secondary market measures the returns from the

beginning of the first listing date to the closing**

+ Signalling hypothesis

Market-specific characteristics

Market volatility MV Standard deviation of daily market returns over the periods before the closing date of the offer

+ + Uncertainty hypothesis

Average market return RETU Square value of the average daily market returns over the periods before the closing date of the offer

+ Uncertainty hypothesis

Market sentiment MS Changes in the All Ordinary Index (AOX) from the date of the issue to the AOX to the day of the listing

+ – Uncertainty/signalling/window of opportunity hypothesis

Hot issue market HC Hot issue market was identified as issue year using IPO volume and first-day return where number of IPOs and average first-day returns (in the sample) are greater than the sample’s average. Dummy variable, which denotes 1 for ‘hot issue market’ and 0 for ‘otherwise’

+ – Hot issue market/window of opportunity hypothesis

Post-day market returns* (MR) Post-day market return was calculated based on the All Ordinary Index for the same return interval as the dependent variable

+ Risk-return theory

In addition to the explanatory variables, the industry and listing year based dummy variables were tested with the developed models with a view to capturing the industry and year effect. Year-based dummy variables were used only for long-run models because the year is an important determinant of the long-run performance (Cai, Liu & Mase 2008; Chi, Wang & Young 2010; Ritter 1991).