Underwriting in the Australian IPO markets: Determinants and pricing

Abstract

We examine the factors that explain the underwriting decision and underwriting fees for Australian initial public offerings (IPOs). Using a sample of Australian IPOs, spanning the period 1999–2019, we document the following results. IPOs that allow oversubscription of the shares, bookbuild offers, and IPOs with a greater delay to listing, are less likely to be underwritten. We also find that more prestigious underwriters are associated with greater IPO underpricing, while charging lower percent underwriting fees. Prestigious underwriters capture side benefits associated with their reputational status by offering their clients or favoured investors with discounted shares.

JEL Classification:

G12, G19, G38

Keywords

Australian Securities Exchange bookbuild initial public offerings underwriting

1. Introduction

In this paper, we examine the determinants of underwriting decision and the underwriting fees for industrial initial public offerings (IPOs) listed on the Australian Securities Exchange (ASX).¹ We also examine the relation between the level of underpricing and the underwriter prestige. Our sample period covers IPOs over the period 1999–2019.

The motivation for this study is as follows. First, we extend prior research on ASX listed IPOs. Extant research that addresses underwriting decisions either focus entirely or include a substantial proportion of mining companies in their IPO sample (e.g. Dimovski and Brooks, 2008; Gilbey et al., 2021; Hartnett and Shamsuddin, 2020). Furthermore, the most recent IPOs in their respective sample listed on the ASX in December 1999 or earlier (e.g. Dimovski and Brooks, 2004; Dimovski et al., 2011; How and Yeo, 2000; Wyatt, 2014). The first comprehensive study to examine both the determinants of the decision to employ an underwriter and the level of underwriting fees for Australian IPOs is by How and Yeo (2000). Underwriters in the Australian market are typically large stockbroking firms, investment or commercial banks. How and Yeo (2000) report that underwriters systematically price their services based on firm-specific variables being the offer size, offer price, subscription period, the level of retained ownership by existing investors and whether options are part of the underwriters’ compensation. In this study, we find the overallotment option and the offer type (bookbuild versus fixed price offer) are significant determinants of underwriting fees.

Second, we examine if underwriting fees and IPO underpricing depend upon the level of underwriter prestige in the Australian market, where fixed price offers are more common over our sample period and there is less clustering of underwriter fees compared to the US market.² In the US market, Chen and Ritter (2000) find that the pricing of underwriting services clusters at around 7%.³ Due to the underwriting fee clustering at 7% for the majority of IPOs up to $100 million in size, Busaba and Restrepo (2022) document a significant positive relation between the underwriting spread and underpricing in book-built IPOs. By reducing the underwriting spread, IPO underpricing is reduced, implying that underwriters can influence IPO aftermarket price through the underwriting spread. To examine whether clustering of US IPO underwriting fees at 7% is anti-competitive, Fernando et al. (2015) examine the incentives for underwriters to invest in reputation building. They document that more prestigious underwriters receive a reputational premium from the IPO underwritten proceeds and the IPO firm receives benefits that include a higher offer price. In markets other than the US, Torstila (2003) examines IPO spreads for 27 countries, and notes that spreads across different markets may be due to the substantial differences in institutional arrangements.⁴ To explain the difference in spreads between the United States and European markets, Abrahamson et al. (2011) explore differences in legal costs, the nature of retail offerings, litigation risks, differences in sell-side analysts and the level of IPO underpricing. They find none of these institutional differences adequately explain the difference in spread levels between European markets and the United States and conclude that strategic pricing of IPOs may occur in the United States but not in Europe. In this current study and similar to How and Yeo (2000), we observe more limited clustering of underwriting fees in the Australian market in the range between 2% and 5%.

Third, the Australian market is an important global equity market. The ASX website states the following: ‘As the first major financial market open every day, ASX is a world leader in raising capital, consistently ranking among the top five exchanges globally’.⁵ The ASX has also been consistently ranked in the top five IPO markets by the number of listings each year since the global financial crisis of 2008.⁶

Fourth, the ASX market also has different institutional features compared to the United States and many other markets. In particular, the offer price for most of the IPOs in our sample is a fixed price once the prospectus is lodged with the market regulator (the Australian Securities and Investments Commission, ASIC) and the ASX, with this price set several weeks prior to the ASX listing date. In contrast, in the United States, IPOs usually list through a bookbuild process, with the offer price usually only finalised for US IPOs one or two days prior to the list date. In addition, only about half of all IPOs listed on the ASX in the period between January 1999 and December 2019 are underwritten. Similarly, Dimovski and Brooks (2008) find that only slightly more than half of Australian gold mining IPOs in their sample of ASX listed resources IPOs between 1994 and 2004 are underwritten, whereas the proportion of underwritten IPOs increases to 63% when all ASX IPOs between 1994 and 2004 are considered. Conversely, in more recent periods, a larger proportion of mining exploration IPOs listed on the ASX were not underwritten. This is confirmed by Gilbey et al. (2021) who document that almost two-thirds of their sample of ASX listed IPOs between 1999 and 2019 (which also includes mining and mining exploration companies) are not underwritten. This is in stark contrast to the US setting, where a large majority of IPOs are underwritten and more than 90% of underwritten offers are bookbuild IPOs (Ritter, 2021).⁷ We therefore explore the decision to underwrite an offer and to incur the costs of underwriting in a specific IPO environment where both underwritten offers and bookbuild IPOs are substantially less common than in the US equity market. Finally, any overallotment option to sell additional shares into the IPO, if investor demand is strong, is at the option or discretion of the IPO firm and not the underwriter. In contrast, in the United States, the underwriter holds the overallotment option.⁸ Ellis et al. (2000) and Aggarwal (2000) find that underwriters employ the overallotment option (in combination with trading strategies such as a short position in IPOs prior to listing) to provide price support for IPOs in the United States and to minimise their costs of price support.⁹ In the Australian market, however, any price support of the IPO in the initial aftermarket is not legally permitted by the Corporations Act. Our study examines if the presence of the overallotment option plays a role in the decision to underwrite the IPO, the level of underwriting fees, and degree of underpricing for underwritten IPOs.

Our findings can be summarised as follows. First, we find IPOs allowing overallotments and those offered under a bookbuild process are less likely to be underwritten. Underwritten IPOs exhibit a shorter time interval between the lodgement of the IPO prospectus and the listing date. Second, we find evidence that more prestigious underwriters charge lower underwriting fees. Third, similar to the results of Dimovski et al. (2011), Wyatt (2014) and Hartnett and Shamsuddin (2020), we find some evidence of a positive association between our measures of underwriter prestige and the level of initial underpricing. For underwritten offers, initial returns are lower for IPOs that allow oversubscription of the shares and for IPOs with a big 4 auditor. However, underwritten IPO initial returns are higher for bookbuild IPO, and are also higher the greater the retained ownership by pre-IPO investors (or lower the offer size).

Our paper makes at least three contributions to the literature on the determinants of the underwriting decision, underwriting fees, and IPO underpricing. First, we contribute to the IPO literature on the role of the underwriter, where the institutional framework and ASX listing rules are quite distinct from those in North America, Asia and Europe. Second, we explore the use of the overallotment option and the impact of the offer type on the decision to underwrite and level of underwriting fees. The overallotment option is of interest because the exercise of the IPO overallotment option in the Australian context is typically at the discretion of the company itself, rather than the underwriter. Third, we explore the relation between underwriter prestige, underwriter fees and IPO listing day returns. Overall, the results suggest that competition by prestigious underwriters for high-quality IPO firms may lead to lower underwriting fees. In turn, more prestigious underwriters of Australian IPOs charge lower underwriting fees but capture side benefits associated with their reputational status by offering discounted shares to their clients or favoured investors.

2. Literature review and hypothesis development

2.1. Decision to underwrite and underwriting fees

The distinct institutional features of the IPO market in Australia provide motivation to first test for the factors associated with the decision to underwrite an IPO and the level of issuance fees to undertake an IPO which include: (1) underwriting fee, (2) management fee, (3) handling fees, and (4) legal and accounting fees.¹⁰ There is still debate in the literature as to why many firms choose to have the issue underwritten and incur higher direct costs compared to a non-underwritten issue.

Aggarwal (2000) notes that, in an IPO characterised with relatively weak investor demand, underwriters tend to restrict the supply of shares in order to provide indirect price support for an IPO. While underwriters in Australia are prevented from providing direct price support for the IPO in the immediate aftermarket via purchases of IPO shares through the ASX, we predict the overallotment option plays an important consideration in the underwriting decision for Australian IPOs. Firms seeking to list as an IPO would exercise this overallotment if there is sufficiently high demand for the offer and additional shares can be sold to investors.

Gilbey et al. (2021) who include all industrial and mining company IPOs listed on the ASX between 1999 and 2019, report that approximately two-thirds of IPOs are not underwritten, while initial underpricing in their sample amounts to 18.5% on average. Murgulov et al. (2019) report that IPO underpricing is significantly negatively related to the presence of an overallotment option. This may reflect that where the overallotment option is exercised, the greater supply of new shares means a lower post-issue trading price. Lower initial expected underpricing and subsequent market pricing of the issue increases the risk to underwriters. Underwriters may also decline to underwrite IPOs where they cannot offer their investor clients shares in the IPO at a ‘cheap’ price and face reputational risk if after-market returns are poor. These risks are higher in the Australian market, where the underwriter is prohibited from providing any direct price support in the immediate after-market period, exacerbating the risk of IPO ‘overpricing’ and materialisation of negative after-market returns by subscribing investors. We predict:

H1: IPOs with an overallotment option are less likely to be underwritten compared to IPOs with no overallotment option.

We also predict the offer type may explain the underwriting decision. In the bookbuild approach, the offer price is adjusted according to investor’ demand in an offer and is only finalised close to the IPO completion (Benveniste and Spindt, 1989). Crain et al. (2021) examine the role of information contained in the IPO prospectus and uncertainty of pricing book-built IPOs. Their results suggest that greater uncertainty of IPO share value may necessitate increased information production and that the pre-IPO due diligence by the underwriter in conjunction with a book-building processes can help facilitate production of additional relevant information. A fixed price offer in contrast increases the risk of offer undersubscription and failure compared to the bookbuild process.¹¹ Firms that wish to avoid sunk costs associated with failure of the issue have greater incentives to have the issue underwritten when the IPO is issued by way of a fixed offer price compared to IPOs issued under a bookbuild process.

On the other hand, Welch (1991) argues that the risks faced by an underwriter are likely to be higher under a fixed price offer (as opposed to a bookbuild) and where there is an expected greater delay or time period between the date of execution of the underwriting agreement and the listing of the IPO. Thus, to entice underwriters to underwrite higher risk IPOs when the offer is a fixed price offer or there is an expected greater time period to the list date, underwriting fees will be higher. This is notwithstanding that underwriters typically seek to reduce their risks by writing force majeure clauses into the underwriting agreements, which limit or remove their underwritten obligation in the event of specific new adverse information on the firm or if there is a significant fall in the market wide index. We predict,

H2: IPOs issued by way of a fixed offer price are less likely to be underwritten compared to book built IPOs.

H3: IPOs with an expected greater delay to listing are less likely to be underwritten.

Heinkel and Schwartz (1986) argue that high quality or undervalued firms are willing to bear the exogenous investigation costs associated with an underwritten issue to credibly signal their quality to the market. Carter and Manaster (1990) hypothesise that high quality firms attempt to signal their quality by choosing prestigious underwriters. Underwriters with high prestige or standing in the market may signal firm quality through provision of the underwriter’s reputation to the IPO process. IPOs issuers may also be attracted to more prestigious underwriters and prepared to pay higher underwriting costs if this leads to greater analyst coverage post the IPO listing date. Thus, high prestige underwriters may be able to charge higher underwriting fees compared to fees charged by less prestigious underwriters (Benveniste and Spindt, 1989; Booth and Smith, 1986). In China, Fang (2005) documents that more reputable underwriters charge higher underwriting fees in the debt markets, while Lyu et al. (2022) find that IPO underwriters achieve lower offering yields for corporate debt issues as part of their effort to protect their reputation as an underwriter. Ong et al. (2020) report that, in Malaysia, more reputable underwriters achieve higher IPO valuation for their client firms. Koda and Yamada (2018) show that underwriters in Japan discount fees for both small and large IPOs to expand their underwriting market shares. On the other hand, Fernando et al. (2005, 2013) posit that in a competitive market, firms compete for the services of an underwriter and underwriters compete for deals. Risk averse and prestigious underwriters concerned about their reputation will seek to only underwrite high quality IPO firms (Colombo et al., 2019; Fernando et al., 2005, 2013). Thus, competition by prestigious underwriters for high-quality IPO firms may lead to lower underwriting fees. We test and predict the null hypothesis that:

H4: For underwritten IPOs, there is no relation between the level of underwriter prestige and underwriting fees.

2.2. Underwriter prestige and IPO underpricing

Underwriting could be viewed as a strategy used by issuing firms to ensure offer success (i.e. full subscription) and to potentially reduce indirect costs to the firm associated with IPO underpricing. IPO underpricing costs can be large, in particular for young firms (Ritter, 1984, 1987), small size offers (Beatty and Ritter, 1986), low offer price IPOs (Bradley et al., 2006) and for IPO firms that employ lower quality underwriters (Carter and Manaster, 1990). High quality firms, on the other hand, will seek prestigious underwriters and be willing to incur underwriting costs where the benefits of underwriter certification signal greater firm quality and enable a higher offer price or less IPO underpricing (Colombo et al., 2019; Fernando et al., 2005, 2013). In contrast, Loughran and Ritter (2004) argue that the allocation of hot IPOs by underwriters to executives of the issuing IPOs means firms seek underwriters with a reputation for greater underpricing.¹² Furthermore, Jenkinson et al. (2018) document that investors who provide useful information to the underwriter during the book building process (via step bids and limit bids) are favoured in IPO share allocations. Likewise, institutional investors are likely to be favoured in allocations of IPO shares if they already generate revenues to underwriters via other investment banking business.

In the Australian market, Dimovski and Brooks (2004) report that industrial company IPOs over the period 1994 to 1999, who used an underwriter, left more money on the table (consistent with greater underpricing) compared to non-underwritten IPOs. This may reflect underwriters deliberately underpricing offers or exploiting pre-IPO companies and their shareholders to benefit their favoured clients with cheap shares (Finn and Higham, 1988; Ritter, 1984). In a later study, Dimovski et al. (2011) report that IPOs underwritten by more prestigious underwriters were associated with higher levels of underpricing. Similarly, Wyatt (2014) finds that both underwriter and auditor quality is positively associated with underpricing for smaller companies. Wyatt (2014) suggests that certification of IPO quality is not sufficient to avoid underpricing for small firms. Hartnett and Shamsuddin (2020) report that underwriter quality is significantly positively associated with IPO listing day returns.¹³ The above discussion leads to our last hypothesis.

H5: For underwritten IPOs, there is no relation between the level of underwriter prestige and initial IPO returns.

3. Data, methods and summary statistics

3.1. Data, variables and empirical models

We obtain the data from ASX company announcements, individual company websites, and the Connect4 and Morningstar’s DatAnalysis databases. We obtain the share price data from the Securities Industry Research Centre of Asia-Pacific (SIRCA). Our sample consists of industrial IPO firms that were admitted to the official list of the ASX between January 1999 and December 2019. During the sample period, we identify 548 industrial IPOs listed on the ASX and where we can obtain a complete data set.¹⁴ Appendix 1 lists the data sources. Variable definitions are presented in Appendix 2. We employ a binary probit model to identify the determinants of the decision to underwrite an IPO. Our probit regression model is¹⁵

\begin{array}{l} {Underwritten}_{i} = β_{0} + β_{1} {Overallot}_{i} + β_{2} {Offertype}_{i} + β_{3} {Delay}_{i} + β_{4} {Offersize}_{i} \\ + β_{5} {Age}_{i} + β_{6} {VC}_{i} + β_{7} {RetOwn}_{i} + β_{8} {Invprice}_{i} + β_{9} {Auditor}_{i} \\ + β_{10} {Earnings}_{i} + β_{11} {CF_ops}_{i} + β_{12} {Location}_{i} + ε_{i} \end{array}

(1)

where:

Underwritten_i is one if the IPO for company i is underwritten and zero otherwise. The independent variables are discussed below following the presentation of our regression models. Following How and Yeo (2000) and Ahn et al. (2007), we use firm level OLS regressions to test the determinants of underwriting fees for IPOs that are underwritten. Our regression model for firm i is

\begin{array}{l} {UWFee}_{i} = β_{0} + β_{1} {UnderprestValue}_{i} + β_{2} {UnderprestVolume}_{i} \\ + β_{3} {Overallot}_{i} + β_{4} {Offertype}_{i} + β_{5} {Delay}_{i} + β_{6} {Offersize}_{i} \\ + β_{7} {Age}_{i} + β_{8} {VC}_{i} + β_{9} {RetOwn}_{i} + β_{10} {Invprice}_{i} + β_{11} {Auditor}_{i} \\ + β_{12} {Earnings}_{i} + β_{13} {CF_ops}_{i} + β_{14} {Location}_{i} + ε_{i} \end{array}

(2)

where

UWFee_i is the underwriting fee as a percentage of the offer value.

Next, we test the relation between the level of initial IPO underpricing for IPOs that are underwritten and underwriter prestige.

\begin{array}{l} Underprice = β_{0} + β_{1} {UnderprestValue}_{i} + β_{2} {UnderprestVolume}_{i} \\ + β_{3} {Overallot}_{i} + β_{4} {Offertype}_{i} + β_{5} {Delay}_{i} + β_{6} {Offersize}_{i} \\ + β_{7} {Age}_{i} + β_{8} {VC}_{i} + β_{9} {RetOwn}_{i} + β_{10} {Invprice}_{i} + β_{11} {Auditor}_{i} \\ + β_{12} {Earnings}_{i} + β_{13} {CF_ops}_{i} + β_{14} {Location}_{i} + ε_{i} \end{array}

(3)

The variable Underprice is the initial listing day return to subscribing investors measured using the first trading day closing price and the initial public offer price, which is a measure of IPO underpricing. In the Australian market, the underwriter will assess the risk of failure in the IPO taking into consideration the offer price, which will typically be determined in consultation between the firm and the underwriter, and other firm specific risk factors and market conditions. Greater ex-ante underpricing will lower the risk to the underwriter.

All variables in equations (1)–(3) are winsorized at the 1% and 99% level to mitigate the impact of outliers. Standard errors are also clustered by industry GICS code and the year of IPO listing. The remaining variables in regression models (1) to (3) are defined as follows.

3.1.1. Underwriter prestige

To determine if greater underwriter prestige enables the IPO firm to obtain a higher offer price, we regress the variable Underprice against the variables UnderprestValue and UnderprestVolume. We define UnderprestValue as the inflation adjusted value of the offer size of IPOs underwritten by the lead underwriter divided by the total inflation adjusted dollar value of the offer size of all IPOs underwritten in the immediate 3-year period prior to the underwritten offer.¹⁶ The variable UnderprestVolume is the number of IPOs underwritten by the lead underwriter divided by the total number of all IPOs that were underwritten in the immediate 3-year period prior to the underwritten offer. Our sample period of IPOs start in 1999. Thus, the sample period where we obtain measures of UnderprestValue and UnderprestVolume spans the years 2002 and 2019.

In addition, we seek to control for potential endogeneity between the level of underwriting fees, other firm specific variables and underwrite prestige by also employing the lagged measure for underwriter prestige in regressions models (2) and (3) as follows: (Lag)UnderprestValue or (Lag)UnderprestVolume. The variable (Lag)UnderprestValue is the inflation adjusted value of the offer size of IPOs underwritten by the lead underwriter divided by the total inflation adjusted dollar value of the offer size of all IPOs underwritten in years –4 to –1 prior to the underwritten offer. Similarly, the variable (Lag)UnderprestVolume is the number of IPOs underwritten by the lead underwriter divided divided by the total number of all IPOs that were underwritten in years –4 to –1 prior to the underwritten offer. Using these lagged values, the sample period spans the 2003 to 2019 years.

3.1.2. Overallotment

Overallot is a dichotomous variable equal to one for IPOs that allow oversubscription of shares in the offer and zero otherwise.

3.1.3. Offer type

Loughran et al. (1994) argue that a fixed price offer can result in larger underpricing compared to the bookbuild approach. This is where the underwriter sets a low fixed offer price, and there is no price adjustment upwards on account of unexpected changes in demand for shares by subscribing investors. To differentiate between a fixed price offer and a book build process, we use a dichotomous variable, Offertype, defined as one if the offer type is a book build and zero otherwise.¹⁷

3.1.4. Delay

We measure risk to the underwriter by the time period between the lodgement of the IPO prospectus and the initial listing date of the IPO (Ljungqvist et al., 2003; Loughran et al., 1994). We expect underwriters who anticipate a long delay between the prospectus lodgement date and listing date to be less willing to underwrite an IPO issue and/or charge a higher underwriter fee. Delay is defined as the natural logarithm of the number of days between the prospectus lodgement date and the listing date.

3.1.5. Venture capital backing

Venture Capital (VC) backed IPOs are likely to be smaller, less profitable, younger and more risky companies compared to non-VC backed IPOs. VC backed IPOs are also more likely to be in high-tech industries such as software, technology hardware, pharmaceuticals, medical equipment, or biotechnology (Murgulov et al., 2019).¹⁸ Thus, VC backed IPOs may have greater incentives to both underwrite their IPOs and bear higher underwriting costs to avoid the sunk costs of the IPO failure and to ensure the VC successfully exits their investment. Moreover, VC backing of a company may signal additional quality and hence attract an underwriter to underwrite the IPO, who may also want to establish a long-term relationship with the VC party. These arguments suggest both VC backed IPOs and younger IPO firms are more likely to seek to engage an underwriter and be willing to incur higher underwriting fees. We use a binary variable, VC, which equals one if the IPO is backed by a venture capitalist and zero otherwise.

3.1.6. Offer size

Underwriters are expected to charge higher underwriting fees for IPOs that are riskier. A large offer size increases the risk of undersubscription in the IPO and the underwriter being required to take-up any unsubscribed shares. Conversely, fixed flotation costs as a proportion of the total issue size decrease with larger issues, where there are greater economies of scale (Bae and Levy, 1990; Booth and Smith, 1986; Hansen, 1986). Thus, underwriters may require a lower fee for larger IPO issues. Booth and Smith (1986) find evidence that larger issues have greater economies of scale. The variable Offersize is defined as the natural logarithm of the dollar amount sought in the IPO.

3.1.7. Age

Following Fernando et al. (2005, 2013), we use firm age as a proxy for the specific risk and firm quality of the issuer. Age is defined as the natural logarithm of the number of years between the company formation date and the listing date.

3.1.8. Retained ownership

Hansen and Torregrosa (1992) propose a negative relation between underwriting fees and the level of managerial ownership.¹⁹ A high level of retained ownership by managers reduces agency costs and underwriters perceive lower levels of underwriting risk. How and Yeo (2000) report lower underwriting fees the higher the level of retained ownership by pre-existing IPO investors.²⁰ We define the variable Retown as the percent of shares retained by pre-IPO investors at listing as a proportion of the total issued shares on the listing date.

3.1.9. Offer price

A high offer price may signal higher firm quality. Following How and Yeo (2000), we use the inverse of the offer price, Invprice, as an independent variable in our regression models.

3.1.10. Auditor

Du et al. (2018) find that a close relationship between auditors and underwriters has a positive effect on the incidence of earnings management and results in an inferior post-listing financial performance, where this negative effect is more pronounced for less reputable auditors and underwriters within the context of Chinese equity markets. For IPOs listed on the ASX, Chang et al. (2008) find that that auditor rank (top 4 auditing firms) are associated with more underpriced IPOs. Hartnett and Shamsuddin (2020) use auditor quality and find that top four auditors are associated with greater initial listing day returns. We re-examine the role of auditor quality as an IPO certification signal, where higher ranked auditors are expected to reduce ex-ante information asymmetry between the issuing firm and investors in a similar way as the underwriter and VC certification. A firm audited by one of the big 4 accounting firms may also signal higher firm quality. Auditor is a dummy variable if the company’s auditor is Deloitte, EY, KPMG or PwC.²¹

3.1.11. Earnings and cash-flows from operations

Brown et al. (2000), Firth (1997) and Chen et al. (2001, 2020) use earnings forecasts in their research on IPOs in Australia, New Zealand and other Commonwealth countries. Chen et al. (2020) use both earnings and cash flow forecasts, and while they find wide variations between forecasts and actual results, they do not find significant differences in forecast accuracy for earnings and cash flows. In line with Teoh et al. (1998) we argue that a record of positive cash flows from operations before an IPO is an important indicator of a potential for the future profitability of the soon to be listed company. Thus, we believe that this information would be of value to an underwriter to gauge IPO company risk in their decision whether to offer underwriting services to an IPO company. To control for a potential upwards bias in earnings forecasts (as documented by, for example, Chen et al., 2020) we use actual (reported) cash flows from operations. As both forecast earnings and actual (reported) cash flows from operations would be available to the potential underwriter prior to IPO, we argue that a combination of earnings forecast and actual cash flows from operating activities would provide additional risk indicators to a potential underwriter to better gauge the risk profile of an IPO company. IPO companies with positive earnings forecasts would also likely be preferenced by subscribing IPO investors, making it easier for an underwriter to fill the order book. We thus expect that companies forecasting positive earnings in their IPO prospectus, and companies reporting positive earnings from operating activities are likely to be perceived as less risky from investors’ and thus from an underwriter’s perspective.

We use forecast earnings, where Earnings variable has the value of one if positive earnings forecast is provided in the IPO prospectus for the post-offer year and zero otherwise.

We use actual cash flows from operations (as reported in the accounting information section of IPO prospectus) to supplement our earnings forecast variable. CF_ops is one if positive cash-flows from operations are reported in the IPO prospectus and zero otherwise.

3.1.12. Location of the IPO issuing firm

Finally, we also control for the location of the IPO firm. Wang et al. (2022) demonstrate that geographical proximity between the IPO firm and the underwriter increases listing day returns. We posit that firms located in the four largest financial centres in Australia (Melbourne, Sydney, Brisbane and Perth) may be able to more easily negotiate the services of an underwriter and to have their IPO underwritten at a lower cost due to proximity to a larger number of potential underwriters.²² Variable Location is equal to one if the location of the head office of the IPO firm is in Sydney, Melbourne, Brisbane or Perth and zero otherwise.

3.2. Summary statistics

Table 1 shows the sample breakdown of IPOs by industry sector and the percentage of IPOs underwritten. The sample includes ASX listed IPOs in the period 1999 to 2019. The sample of IPOs mostly comprise more conventional industries, such as diversified financials (22.4% of the sample), and commercial services and supplies (9.7%) and capital goods (9.5%). In the more high-tech or innovative sectors the largest group is software and services industry group (6.9% of the sample).

Table 1.

IPOs by GICS industry group.

GICS industry group	All		Underwritten
GICS industry group	N	Percent	N	Percent
Automobiles and components	4	0.7%	4	0.7%
Banks	5	0.9%	3	0.5%
Capital goods	52	9.5%	30	5.5%
Chemicals	6	1.1%	2	0.4%
Commercial Services and Supplies	53	9.7%	40	7.3%
Construction materials	5	0.9%	4	0.7%
Consumer durables and apparel	18	3.3%	7	1.3%
Consumer services	31	5.7%	22	4.0%
Containers and packaging	3	0.5%	3	0.5%
Diversified financials	123	22.4%	26	4.7%
Energy	10	1.8%	5	0.9%
Food beverage and tobacco	26	4.7%	12	2.2%
GICS code not applicable	10	1.8%	5	0.9%
Health Care Equipment and Services	24	4.4%	13	2.4%
Household and personal products	5	0.9%	2	0.4%
Insurance	9	1.6%	4	0.7%
Media	15	2.7%	11	2.0%
Metals and mining	7	1.3%	2	0.4%
Paper and forest products	8	1.5%	4	0.7%
Pharmaceuticals and Biotechnology and Life Sciences	9	1.6%	5	0.9%
Real estate	14	2.6%	7	1.3%
Retailing	31	5.7%	24	4.4%
Software and Services	38	6.9%	23	4.2%
Technology hardware and equipment	11	2.0%	5	0.9%
Telecommunication services	15	2.7%	10	1.8%
Transportation	10	1.8%	7	1.3%
Utilities	6	1.1%	2	0.4%
Total	548	100%	282	51%

GICS: global industry classification standard.

Table 1 presents the IPOs listed on the Australian Securities Exchange between 1999 and 2019. GICS is the Global Industry Classification Standard used by ASX; N is the number of observations; Percent is the number of offers in a particular industry group as a proportion of total IPOs. Note that ‘Metals and Mining’ classified IPOs are industrial companies that provide services to the mining industry and are not mineral exploration or mining companies that extract minerals, oil and gas or other resources.

Table 2 shows the sample split between underwritten and non-underwritten offers by year. For the IPO sample, 51% of the offers were underwritten. There are fewer IPOs (both underwritten and non-underwritten) between 2008 and 2012, these years being associated with the height and immediate aftermath of the global financial crisis. This likely reflects risk-aversion to new IPOs and underwriters being unwilling to underwrite any IPO in this period of rapidly falling share prices and greater financial constraints being placed on the underwriting firms.

Table 2.

Non-underwritten and underwritten IPOs.

Year	No. of IPOs
Year	Non-under-written	Underwritten	Total	% underwritten
1999	9	33	42	79%
2000	18	34	52	65%
2001	4	5	9	56%
2002	4	6	10	60%
2003	18	8	26	31%
2004	25	15	40	38%
2005	17	21	38	55%
2006	15	13	28	46%
2007	24	23	47	49%
2008	2	1	3	33%
2009	4	4	8	50%
2010	8	5	13	38%
2011	7	4	11	36%
2012	1	2	3	67%
2013	12	12	24	50%
2014	22	27	49	55%
2015	27	27	54	50%
2016	16	11	27	41%
2017	16	13	29	45%
2018	10	4	14	29%
2019	7	14	21	67%
Total	266	282	548	51%

Table 2 presents the sample for the IPOs listed on the Australian Securities Exchange between 1999 and 2019.

Table 3 provides the descriptive statistics of the variables used to determine the underwriting decision and level of underpricing for the sample of IPOs. The table shows that the mean (median) level of underpricing for non-underwritten offers is 10.9% (4.8%), compared to 21.4% (10.7%) for underwritten offers. The difference in the mean (median) level of underpricing is significant at the 1% level. While our results are in contrast to international evidence on underwritten IPOs, they are consistent with other studies of ASX listed IPOs; for example, How (2000), Dimovski et al. (2011) and Gilbey et al. (2021), who also report higher initial underpricing for underwritten IPOs compared to non-underwritten offers. Table 3 also shows that underwritten offers are significantly less likely to have an overallotment option and be offered by way of a bookbuild. Underwritten IPOs experience on average less time delay between the prospectus lodgement date and the listing date. Underwritten offers are not significantly larger in size. IPOs are more likely to be underwritten for firms that are older (more established), for firms where there is a greater existing shareholder retained ownership, a higher IPO offer price and for firms with a big 4 auditor. Underwritten IPOs are significantly more likely to report (current) positive cash flows from operations and are also significantly more likely to forecast positive earnings in their IPO prospectus. Proximity to potential underwriters (company location) variable is not significant.

Table 3.

Descriptive statistics.

Variable	Non-underwritten				Underwritten				t-stat	Wilcoxon test
Variable	No.	Mean	Median	Standard Dev	No.	Mean	Median	Standard Dev	t-stat	Wilcoxon test
UWfee	n.a.	n.a.	n.a.	n.a.	282	0.034	0.033	0.012	n.a.	n.a.
Underprice	266	0.109	0.048	0.238	282	0.214	0.107	0.371	(–3.93)^***	<0.001^***
UnderprestValue	n.a.	n.a.	n.a.	n.a.	210	0.070	0.036	0.079	n.a.	n.a.
UnderprestVolume	n.a.	n.a.	n.a.	n.a.	210	0.061	0.047	0.056	n.a.	n.a.
Overallot	266	0.318	0.000	0.467	282	0.068	0.000	0.252	(7.71)^***	<0.001^***
Offertype	266	0.129	0.000	0.336	282	0.025	0.000	0.157	(4.57)^***	<0.001^***
Delay	266	3.749	3.710	0.649	282	3.267	3.300	0.508	(9.60)^***	<0.001^***
VC	266	0.053	0.000	0.225	282	0.043	0.000	0.203	(0.54)	0.586
Offersize	266	17.389	17.217	1.942	282	19.492	18.000	1.323	(–0.73)	0.244
Age	266	0.606	0.457	1.734	282	1.171	1.520	1.824	(–3.69)^***	<0.001^***
Retown	266	0.466	0.559	0.382	282	0.567	0.598	0.218	(–3.31)^***	0.047^*
Invprice	266	1.678	1.000	1.597	282	1.140	1.000	0.944	(4.74)^***	0.006^***
Auditor	266	0.394	0.000	0.490	282	0.602	1.000	0.49	(–4.95)^***	<0.001^***
CF_ops	266	0.327	0.000	0.47	282	0.596	1.000	0.492	(–6.54)^***	<0.001^***
Earnings	266	0.613	1.000	0.488	282	0.826	1.000	0.38	(–5.69)^***	<0.001^***
Location	266	0.914	1.000	0.282	282	0.897	1.000	0.304	(0.653)	0.653

VC: venture capital.

Table 3 presents the sample of IPOs listed on the Australian Securities Exchange between 1999 and 2019. Underwriting fee is the underwriting fee as a percent of the IPO offer value. Underprice is the initial listing day return measured as the difference between the first trading day closing price and the initial public offer price divided by the initial offer price. T-tests and Wilcoxon tests are also conducted on the difference in means and medians between underwritten and non-underwritten IPOs. T-stats are in parentheses. ^*, ^**, ^*** denotes significance at 10%, 5% and 1% levels respectively. Variable definitions are presented in Appendix 2.

4. Empirical results

The results of our multivariate analysis wherein we examine the determinants of the underwriting decision, underwriting fees and IPO initial underpricing are presented in Tables 4 to 6.

Table 4.

Determinants of the decision to underwrite.

	(1)	(2)	(3)	(4)	(5)
Intercept	5.0601 (9.86)^***	4.1894 (7.55)^***	4.4443 (3.87)^***	4.4943 (7.64)^***	4.1880 (6.58)^***
Overallot	–0.8876 (–4.09)^***	–0.7362 (–3.63)^***	–0.7597 (3.30)^***	–0.7207 (3.46)^***	–0.6929 (3.12)^***
Offertype	–1.4227 (–3.15)^***	–1.7106 (–3.97)^***	–1.6544 (3.53)^***	–1.6626 (–3.65)^***	–1.6618 (–3.58)^***
Delay	–0.9363 (–4.79)^***	–0.7604 (–3.84)^***	–0.7964 (–4.08)^***	–0.7689 (–3.92)^***	–0.7634 (–3.80)^***
VC			–0.1493 (–0.54)		–0.0627 (–0.22)
Offersize			–0.0232 (–0.41)
Age			0.0216 (0.54)		0.0075 (0.19)
Retown					0.5988 (2.37)^**
Invprice		–0.0913 (–0.99)		–0.1001 (–1.00)	–0.1331 (–1.49)
Auditor		0.3709 (3.16)^***	0.4187 (3.69)^***	0.3191 (2.99)^***	0.3183 (3.15)^***
Earnings		0.6296 (3.34)^***	0.6497 (5.09)^***
CF_ops				0.3931 (3.29)^***	0.3299 (2.40)^**
Location			0.0001 (0.02)		0.0070 (0.14)
Industry GICS code and year dummies	Yes	Yes	Yes	Yes	Yes
No. of Observations	548	548	548	548	548
Likelihood Ratio χ²	162.28^***	194.96^***	195.88^***	186.60^***	193.85^***
R- squared	0.2338	0.2868	0.2901	0.2758	0.2953

VC: venture capital; GICS: global industry classification standard.

Table 4 presents the sample of IPOs listed on the Australian Securities Exchange between 1999 and 2019. The dependent variable is Underwritten, equal to one if the IPO is underwritten and zero otherwise. The independent variables are defined in Appendix 2. Z-values in parentheses. Standard errors are clustered by industry GICS code and the year of IPO listing. *, **, *** denotes significance at 10%, 5% and 1% levels respectively. Variable definitions are presented in Appendix A2.

Bold significance ***p(z) < 0.01; **p(z) < 0.05; *p(z) < 0.1.

4.1. Determinants of the underwriting decision

Table 4 presents the results of our probit regression on the determinants of the underwriting decision for the sample of IPOs. For the full sample the variable Offersize is correlated with Invprice on the right-hand side (RHS) of equation (1); this is also the case between Earnings variable and cash flows from operations (CF_ops) variable. We therefore run alternative regressions in Table 4 to control for potential multicollinearity. We find that the coefficients on Overallot, Offertype and Delay are negative and significant at the 1% level in all regressions. IPOs that allow oversubscription of the shares and/or issued by way of a bookbuild are less likely to be underwritten. If a firm exercises the overallotment option, the greater supply of new shares may lead to a lower post-issue trading price. Low after-market returns may damage underwriter reputation and mean underwriters are less able to offer their investor clients shares in the IPO at a ‘cheap’ price. The negative coefficient on Offertype is consistent with a fixed price offer increasing the risk of offer undersubscription and failure compared to the bookbuild process. Firms therefore have greater incentives to have the issue underwritten in a fixed offer price compared to IPOs issued under a bookbuild process. This is to avoid high sunk costs if the issue fails. We also find that the coefficient on Delay is negative and significant in all regressions. Issues with a longer delay between the prospectus lodgment date and the listing date are higher risk and less likely to be underwritten.

The coefficient on Auditor, Earnings and CF_ops are positive and significant at the 1% or the 5% level in regressions (2) to (5). IPO firms with a big-4 auditor, firms forecasting positive earnings post-IPO, and firms reporting positive cash flows from operations are significantly more likely to be underwritten. The coefficient on Invprice, VC, Offersize, Age and Location are not significant in any regressions in Table 4. There is no evidence that firms with a low offer price are more (or less) likely to be underwritten. IPOs are also not more likely to be underwritten based on their offer size or company age. Similarly, VC-backed IPOs, or firms located in Sydney, Melbourne, Brisbane or Perth are not more likely to be underwritten.

4.2. Determinants of underwriting fees

In Table 5, we report the results of regressions for the determinants of the level of underwriting fees. Within the underwritten IPO sub-sample, there are strong correlations between Offersize and Invprice (–0.6637), between Offersize and Retown (–0.5120), between Offersize and Delay (–0.5175), and also between Earnings and CF_ops (0.4554) on the RHS in equations (2) and (3). Our base case model regressions in Tables 5 and 6 therefore exclude the variable Offersize and CF_ops. The alternative model regressions in Tables 5 and 6 exclude the variables Invprice, Retown, Delay and Earnings.

Table 5.

Determinants of underwriting fees using UnderprestValue or UnderprestVolume as measure of underwriter prestige.

Panel A: “Base case model”
Column	(1)	(2)	(3)	(4)
Intercept	0.0072 (0.63)	0.0798 (0.71)	0.0063 (0.57)	0.077 (0.78)
UnderprestValue	–0.0252 (–5.99)^***
(Lag)UnderprestValue		–0.0224 (–1.98)^*
UnderprestVolume			–0.0284 (–3.69)^***
(Lag)UnderprestVolume				–0.0338 (–3.38)^**
Overallot	0.0004 (0.16)	0.0007 (0.29)	0.0023 (0.08)	0.0014 (0.05)
Offertype	0.0067 (1.67)	0.0067 (1.54)	0.0067 (1.63)	0.0066 (1.53)
Delay	0.0026 (0.94)	0.0022 (0.74)	0.0026 (1.00)	0.0022 (0.77)
VC	0.0050 (1.35)	0.0026 (1.17)	0.0049 (1.28)	0.0022 (0.99)
Age	0.0003 (0.79)	0.0003 (0.77)	0.0003 (0.58)	0.0003 (0.76)
Retown	0.0081 (2.20)^*	0.0080 (2.07)^*	0.0095 (2.74)^**	0.0094 (2.66)^**
Invprice	0.0021 (3.57)^***	0.0022 (3.00)^**	0.0023 (3.66)^***	0.0024 (3.31)^**
Auditor	–0.0011 (–1.83)	–0.0017 (–2.55)^**	–0.0012 (–1.60)	–0.0018 (–2.04)^*
Earnings	0.0003 (0.10)	0.0002 (0.05)	0.0002 (0.05)	0.0002 (0.07)
Location	0.0002 (0.50)	0.0002 (0.55)	0.0002 (0.73)	0.0002 (0.68)
Industry GICS code and year dummies	Yes	Yes	Yes	Yes
No. of Observations	210	204	210	204
Adjusted R²	0.3277	0.3330	0.3193	0.3311
Panel B: “Alternative model”
Intercept	0.0748 (3.17)^**	0.0731 (3.00)^**	0.0812 (3.56)^***	0.0780 (3.37)^**
UnderprestValue	–0.0215 (–4.91)^***
(Lag)UnderprestValue		–0.0185 (–1.70)
UnderprestVolume			–0.0252 (–3.51)^***
(Lag)UnderprestVolume				–0.0271 (–3.00)^**
Overallot	0.0019 (0.92)	0.0024 (1.21)	0.0017 (0.82)	0.0020 (0.91)
Offertype	0.0083 (1.53)	0.0082 (1.48)	0.0085 (1.48)	0.0083 (1.45)
VC	0.0050 (1.49)	0.0031 (1.36)	0.0048 (1.38)	0.0027 (1.18)
Offersize	–0.0031 (–2.34)^*	–0.0030 (–2.26)^*	–0.0034 (–2.74)^**	–0.0033 (–2.72)^**
Age	0.0004 (0.94)	0.0004 (0.87)	0.0004 (0.78)	0.0004 (0.90)
Auditor	–0.0008 (–1.02)	–0.0016 (–1.94)^*	–0.0008 (–1.00)	–0.0016 (–1.83)
CF_ops	–0.0007 (–0.46)	–0.0012 (–0.62)	–0.0006 (–0.39)	–0.0012 (–0.59)
Location	0.0001 (0.21)	0.0001 (0.32)	0.0000 (0.32)	0.0001 (0.40)
Industry GICS code and year dummies	Yes	Yes	Yes	Yes
No. of Observations	210	204	210	204
Adjusted R²	0.3234	0.3253	0.3394	0.3439

VC: venture capital; GICS: global industry classification standard.

Table 5 presents the sample of IPOs listed on the Australian Securities Exchange between 1999 and 2019. The dependent variable is UWFee. UWFee is the underwriting fee as a percent of the IPO offer value. T-values in parentheses. Standard errors are clustered by industry GICS code and the year of IPO listing. ^*, ^**, ^*** denotes significance at 10%, 5% and 1% levels respectively. Variable definitions are presented in Appendix 2.

Bold significance ***p(t) < 0.01; **p(t) < 0.05; *p(t) < 0.1.

Table 6.

Determinants of underpricing using UnderprestValue or UnderprestVolume as measure of underwriter prestige.

Panel A: “Base case model”
Column	(1)	(2)	(3)	(4)
Intercept	–0.2024 (–2.29)^*	–0.2702 (–2.54)^**	–0.2445 (–3.06)^**	–0.3012 (–3.16)^**
UnderprestValue	0.2409 (1.19)
(Lag)UnderprestValue		0.2403 (2.93)^**
UnderprestVolume			0.6146 (2.28)^*
(Lag)UnderprestVolume				0.6747 (2.24)^*
Overallot	–0.2527 (–4.50)^***	–0.2718 (–4.32)^***	–0.2378 (–3.88)^***	–0.2544 (–3.86)^***
Offertype	0.1258 (2.04)^*	0.1220 (1.86)	0.1362 (2.46)^**	0.1319 (2.35)^*
Delay	0.0129 (0.40)	0.0430 (1.03)	0.0173 (0.56)	0.0045 (1.15)
VC	–0.0107 (–0.19)	–0.0367 -(0.54)	–0.0008 (–0.01)	–0.0277 (–0.42)
Age	–0.0056 (–0.61)	–0.0043 (–0.51)	–0.0056 (–0.63)	–0.0045 (–0.54)
Retown	0.3872 (3.79)^***	0.3853 (3.63)^***	0.3663 (3.72)^***	0.3594 (3.58)^***
Invprice	0.0315 (0.61)	0.0337 (0.61)	0.0230 (0.61)	0.0332 (0.63)
Auditor	–0.0896 (–3.43)^**	–0.0850 (–3.20)^**	–0.0896 (–3.37)^**	–0.0830 (–3.18)^**
Earnings	–0.0286 (–0.87)	–0.0320 (–1.00)	–0.0223 (–0.71)	–0.0295 (–0.99)
Location	0.0117 (1.26)	0.0065 (0.84)	–0.0115 (–1.30)	0.0066 (0.88)
Industry GICS code and year dummies	Yes	Yes	Yes	Yes
No. of Observations	210	204	210	204
Adjusted R²	0.2186	0.2365	0.2323	0.2526
Panel B: “Alternative model”
Intercept	1.1419 (2.70)^**	1.3110 (2.66)^**	1.0366 (2.76)^**	1.2216 (2.72)^**
UnderprestValue	0.2995 (1.24)
(Lag)UnderprestValue		0.2926 (2.71)^**
UnderprestVolume			0.7151 (2.68)^**
(Lag)UnderprestVolume				0.8376 (3.02)^**
Overallot	–0.2459 (–3.16)^**	–0.2750 (–2.81)^**	–0.2279 (–2.71)^**	–0.2517 (–2.49)^**
Offertype	0.1626 (6.03)^***	0.1614 (5.06)^***	0.1728 (6.39)^***	0.1727 (5.32)^***
VC	–0.0408 (–1.34)	–0.0619 (–2.49)^**	–0.0273 (–0.88)	–0.0476 (–1.96)*
Offersize	–0.0615 (–2.75)^**	–0.0681 (–2.71)^**	–0.0579 (–2.97)^**	–0.0659 (–2.94)^**
Age	–0.0002 (–0.03)	–0.0006 (–0.08)	–0.0003 (–0.04)	–0.0000 (–0.00)
Auditor	–0.0837 (–2.87)^**	–0.0804 (–2.68)^**	–0.0850 (–2.83)^**	–0.0777 (–2.61)^**
CF_ops	–0.0409 (–1.70)	–0.0651 (–2.61)^**	–0.0068 (–1.50)	–0.0593 (–2.22)^*
Location	0.0107 (0.94)	0.0050 (0.41)	0.0108 (0.98)	0.0051 (0.44)
Industry GICS code and year dummies	Yes	Yes	Yes	Yes
No. of Observations	210	204	210	204
Adjusted R²	0.1815	0.1985	0.1990	0.2228

VC: venture capital; GICS: global industry classification standard.

The sample includes IPOs listed on the Australian Securities Exchange between 1999 and 2019. The dependent variable is Underprice. Underprice is the initial listing day return measured as the difference between the first trading day closing price and the initial public offer price. T-values in parentheses. Standard errors are clustered by industry GICS code and the year of IPO listing. ^*, ^**, ^*** denotes significance at 10%, 5%, and 1% levels, respectively. Variable definitions are presented in Appendix 2.

Bold significance ***p(t) < 0.01; **p(t) < 0.05; *p(t) < 0.1.

The dependent variable in Table 5 is UWFee, which is the underwriting fee as a percent of the IPO offer value. The measure of underwriter prestige is UnderprestValue (regression 1) or UnderprestVolume (regression 3). We also employ the lagged measure for underwriter prestige: (Lag)UnderprestValue (regression 2) or (Lag)UnderprestVolume (regression 4).²³

Panel A of Table 5 indicates that the coefficient on UnderprestValue, (Lag)UnderprestValue, UnderprestVolume and (Lag)UnderprestVolume are negative and significant at between the 1% and 10% levels. The results are consistent with the notion that more prestigious underwriters charge lower underwriting fees. This may reflect greater market competition by more prestigious underwriters to underwrite IPOs that are higher quality, which have a greater offer size and public profile. There is no evidence that underwritten fees are higher for IPOs with an overallotment option and under the bookbuild process compared to a fixed price offer, or for those offers that experience longer delays to listing. Furthermore, underwriter fees are not higher for VC-backed IPOs. Likewise, no significant underwriter fee increase is evident for the more recently incorporated IPO companies. Retown is positive and significant (at the 10% level) in the regressions in columns (1) and (2) and significant (at the 5% level) in the regressions in columns (3) and (4), indicating that IPOs with larger proportion of shares retained by the original owners are also associated with higher (percent) underwriter fees. It is plausible that underwriters perceive the low offer size (greater retained ownership by the pre-IPO investors) is a proxy for higher IPO risk. Invprice has a positive coefficient (at between 1% and 5% level), indicating that lower priced offers have significantly higher underwriting costs. The regressions in columns (2) and (4) also indicate that the Auditor variable is significant (at the 5% and 10% level) and negative, suggesting that hiring a reputable external auditor may significantly reduce IPO underwriting fees. However, Earnings and Location variables do not significantly contribute to explaining underwriting fees. Underwritten IPOs are very likely to predict positive earnings for the post-offer year and positive earnings forecasts within this sub-sample do not significantly contribute to a reduction in underwriting fees. Likewise, IPO companies headquartered in the major financial centre locations in Australia (Sydney, Melbourne, Brisbane and Perth) are not gaining a competitive cost advantage due to this proximity to potential underwriters compared to their more regionally located peers.

Panel B of Table 5 presents the results of equation (2) with Offersize and CF_ops but excluding the Retown, Delay and Earnings variables.The results for our underwriter prestige measures remain negative and significant at between 1% and 5% levels (except for (Lag)UnderprestValue in column 2 which is not significant at the conventional levels). The coefficient on Offersize is negative and significant at the 5% or 10% level in all regressions in columns (1) to (4). Underwriting fees are lower for offers of larger size, which is consistent with underwriter economies of scale for larger IPOs (and with the results for the Retown variable as presented in Panel A of Table 5).

4.3. Determinants of IPO underpricing

The results of the regressions for equation (3), where the dependent variable is the level of IPO underpricing, are presented in Table 6. We present the results in two panels. As already noted, to mitigate multicollinearity concerns, in Panel A, the base case model excludes the Offersize and CF_ops. In Panel B, we use Offersize and CF_ops but exclude Invprice, Retown, Delay and Earnings.

Our results in Panel A show that the coefficients on (Lag)UnderprestValue, UnderprestVolume and (Lag)UnderprestVolume are positive and significant at between the 5% and 10% levels in the regressions in columns (2), (3) and (4) while UnderprestValue is not significant at conventional levels. We therefore find some support that more prestigious underwriters are associated with a more positive listing day returns; or in other words, IPOs underwritten by the more prestigious underwriters are more likely to experience underpricing. The variable Overallot indicates that existence of an overallotment option is significant and negative (at the 1% level) in all regressions in Panel A, implying that those IPOs that plan to use overallotment of shares in their IPO have significantly lower underpricing. The variable Offertype is positive and significant at the 5% and 10% levels in the regressions in columns (1), (3) and (4), indicating that book-built IPOs have greater positive listing day returns. In contrast, Benveniste and Busaba (1997) demonstrate that average expected underpricing should be lower for bookbuild IPOs compared to the fixed price offer method. In a bookbuild IPO the underwriter may favour institutional investors from which they obtain information that is useful in pricing the IPO (Jenkinson et al., 2018). Ex-post, the presence of institutional investors in bookbuild IPOs may ‘crowd out’ a proportion of retail investors willing to subscribe for the IPO shares; this unsatisfied retail demand for the IPO would then ‘spill-over’ into buying of shares on the first trading day on the ASX.

Retown is positive and significant at the 1% level in all regressions, indicating that IPOs with a high proportion of pre-IPO shares held by the original owners experience more positive listing day returns, meaning that the pre-IPO shareholders are willing to incur the costs of higher underpricing to capture the benefits of a high share price post the IPO. In contrast, IPOs of companies whose accounts were audited by one of the top four external auditing companies are significantly less underpriced, with coefficient significantly negative at the 5% level for the Auditor variable in all regressions. Our findings are contrary to previous research (see, for example, Chang et al., 2008; Hartnett and Shamsuddin, 2020)²⁴ but are consistent with the auditor quality certification role where quality auditors are associated with IPOs engaging in less offer price discounting. VC backing, company age, delay to list, offer price (Invprice), forecast earnings and company location do not have a significant effect on listing day returns.

The results in Panel B (alternative model) are largely consistent with the results of Panel A, where we find that the coefficient on (Lag)UnderprestValue, UnderprestVolume and (Lag)UnderprestVolume are positive and significant at the 5% level in the regressions in columns (2), (3) and (4) while UnderprestValue is not significant at conventional levels. The results are consistent with the results in Panel A, the coefficients on Overallot and Auditor are negative and significant and negative at the 5% level in all regressions. This is also the case with Offersize, indicating that smaller offer sized IPOs tend to be more underpriced, with these results being consistent with the previous research on industrial IPOs in Australia by Murgulov et al. (2019). The coefficient on Offertype is positive and significant at the 1% level in all regressions in Panel B, providing further support that book-built IPOs tend to provide more positive listing day returns. Similar to the results in Panel A, Panel B indicates that company age at listing, delay to listing and the location of the company’s headquarters do not significantly contribute to explaining listing day returns. However, unlike the results in Panel A, regressions in columns (2) and (4) provide some indication that VC-backed IPOs and IPOs of companies that report positive cash flows from operations are less underpriced (with VC and CF_ops variables significant at the 5% and 10% levels).

Overall our findings in Tables 5 and 6 are consistent with the notion that more prestigious underwriters exert greater bargaining power in setting the issue price and rewarding their favoured clients by allocating cheap shares.²⁵ By rewarding the underwriters’ favoured clients and expecting to capture more business from these clients, the more prestigious underwriter is willing to offer lower underwriting fees (see, Table 5). Overall, our results partially support extant research (Dimovski et al., 2011; Hartnett and Shamsuddin, 2020; Wyatt, 2014), who document that more prestigious underwriters are associated with higher underpricing.

5. Conclusions

We study the determinants of the decision to underwrite and the level of underwriting fees for IPOs listed on the ASX. Specifically, we examine whether IPOs that allow oversubscriptions and book-built IPOs (as opposed to fixed priced offers) are more likely to be underwritten. We also examine any effect of the delay to listing on the likelihood of an offer being underwritten. Furthermore, for underwritten IPOs, we examine if underwriter prestige has any effect on underwriting costs and whether IPOs underwritten by more prestigious underwriters provide different listing day returns compared to other underwritten IPOs.

We find that IPOs that allow oversubscription of the shares and/or are issued by way of a bookbuild are less likely to be underwritten. We also find that non-underwritten IPOs experience longer delays to listing. For underwritten offers, we find evidence that more prestigious underwriters charge lower underwriting fees and furthermore that more prestigious underwriters are associated with greater IPO underpricing.

Overall, this study contributes to the literature on the determinants of the underwriting decision, underwriter quality and underwriting fees for Australian firms and their effects on listing day IPO returns. Our findings suggest that competition by prestigious underwriters for high quality IPO firms is associated with lower underwriting fees. In turn, more prestigious underwriter may have incentives to underprice offers to benefit their clients or favoured investors with underpriced shares.

Footnotes

Appendix 1

Variable	Source
Whether the company is a Commitments Test Entity	DatAnalysis database of company announcements (ASX signal G)
Whether the company is backed by Venture Capital	DatAnalysis database of company announcements (ASX signal G)
Share prices	SIRCA (Datastream for missing values)
An additional equity offering in the first three years of listing	ASX Company announcements
Offer price	Prospectus (Connect4 or DatAnalysis)
Offer size	Prospectus (Connect4 or DatAnalysis)
Time between prospectus lodgement and listing	(Connect4 and ASIC)
Company age at listing	Prospectus (Connect4 or DatAnalysis)
Company listing date	ASX signal G announcements
Underwritten offer	Prospectus (Connect4 or DatAnalysis)
Underwriting fee	Prospectus (Connect4 or DatAnalysis)
Retained ownership	Prospectus (Connect4 or DatAnalysis)
Lead underwriter name and other details	Prospectus (Connect4 or DatAnalysis)
Oversubscriptions (overallotment of shares allowed)	Prospectus (Connect4 or DatAnalysis)
Cash flows from operating activities	Prospectus (Connect4 or DatAnalysis)
Earnings forecast	Prospectus (Connect4 or DatAnalysis)
Company Australian headquarters location	DatAnalysis

ASX: Australian securities exchange; SIRCA: Securities Industry Research Centre of Asia-Pacific; ASIC: Australian securities and investments commission.

Appendix 2

Variable definitions.

Explanatory Variable	Variable Denoted by	Variable Measurement
Underwritten	Underwritten	One if the IPO is underwritten and zero otherwise
Underwriting fees	UWFee	Underwriting fee as a percent of the IPO offer value.
Level of initial underpricing	Underprice	Initial listing day return measured as the difference between the first trading day closing price and the initial public offer price.
Underwriter prestige	UnderprestValue	The inflation adjusted value of the offer size of IPOs underwritten by the lead underwriter divided by the total inflation adjusted dollar value of the offer size of all IPOs underwritten in the immediate 3-year period prior to the underwritten offer.²⁶ Our sample period of IPOs start in 1999. Thus, the sample period that we obtain measures of UnderprestValue spans the 2002 and 2019 years.
Underwriter prestige	(Lag) UnderprestValue	The inflation adjusted value of the offer size of IPOs underwritten by the lead underwriter divided by the total inflation adjusted dollar value of the offer size of all IPOs underwritten in years –4 to –1 prior to the underwritten offer.
Underwriter prestige	UnderprestVolume	The number of IPOs underwritten by the lead underwriter_i divided by the total number of all IPOs that were underwritten in the immediate 3-year period prior to the underwritten offer. Our sample period of IPOs start in 1999. Thus, the sample period that we obtain measures of UnderprestVolume spans the 2002 and 2019 years.
Underwriter prestige	(Lag) UnderprestVolume	The number of IPOs underwritten by the lead underwriter_i divided by the total number of all IPOs that were underwritten in years –4 to –1 prior to the underwritten offer.
IPO oversubscriptions	Overallot	Overallot is a dichotomous variable equal to one for IPOs that allow oversubscription of shares in the offer.
Offer type	Offertype	Offertype is dichotomous variable equal to one if the offer type is a book build and zero otherwise.
Offer Size	Offersize	Natural logarithm of the dollar amount sought in the IPO issue.
IPO Issuer-specific risks	Age	Natural logarithm of the number of years between the company formation date and the listing date.
	Delay	Natural logarithm of the number of days between the prospectus lodgement date and the listing date.
VC	VC	A binary variable equal to one if the IPO is backed by a Venture Capitalist and zero otherwise.
Retained ownership	Retown	Percent of shares retained by pre-IPO investors at listing as a proportion of the total issued shares on the listing date.
IPO Offer Price	Invprice	The inverse of the IPO initial offer price.
Auditor	Auditor	A dummy variable equal to one if the company’s auditor is Deloitte, EY, KPMG or PwC (or Arthur Andersen prior to its demise).
Cash-flows from operating activities	CF_ops	A dichotomous variable equal to one if positive cash flows from operating activities are reported in the IPO prospectus.
Earnings forecast	Earnings	A dichotomous variable equal to one if positive earnings were forecast for the post-offer year in the IPO prospectus.
Head office of the IPO firm	Location	A binary variable equal to one if the location of the head office of the IPO firm is in Sydney, Melbourne, Brisbane or Perth and zero otherwise.

IPO: initial public offerings; VC: venture capital.

Acknowledgements

The authors acknowledge the helpful comments from participants at the 59th AFAANZ conference in Brisbane in July 2019, the NZ Finance Colloquium in 2020 and seminar participants at Victoria University Wellington on an earlier version of this paper. All remaining errors are our own.

Final transcript accepted 1 November 2022 by Tom Smith (AE Finance).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: S Ghon Rhee is grateful for the 2020 Summer Research Grant of the Shidler College of Business.

ORCID iD

Zoltan Murgulov

Notes

References

Abrahamson

Jenkinson

Jones

(2011) Why don’t US issuers demand European fees for IPOs? The Journal of Finance 66: 2055–2082.

Aggarwal

(2000) Stabilization activities by underwriters after initial public offerings. The Journal of Finance 55: 1075–1103.

Ahn

Kim

Son

(2007) The pricing of underwriting services in the Korean IPO market: Characteristics and determinants. Asia-Pacific Journal of Financial Studies 36: 731–764.

Bae

Levy

(1990) The valuation of firm commitment underwriting contracts for seasoned new equity issues: Theory and evidence. Financial Management 19: 48–59.

Baron

(1982) A model of the demand for investment banking advising and distribution services for new issues. The Journal of Finance 37: 955–976.

Barry

Muscarella

Peavy

III , et al. (1990) The role of venture capital in the creation of public companies: Evidence from the going-public process. Journal of Financial Economics 27: 447–471.

Beatty

Ritter

(1986) Investment banking, reputation, and the underpricing of initial public offerings. Journal of Financial Economics 15: 213–232.

Benveniste

Busaba

(1997) Bookbuilding vs. fixed price: An analysis of competing strategies for marketing IPOs. Journal of Financial and Quantitative Analysis 32: 383–403.

Benveniste

Spindt

(1989) How investment bankers determine the offer price and allocation of new issues. Journal of Financial Economics 24: 343–361.

10.

Bøhren

Eckbo

Michalsen

(1997) Why underwrite rights offerings? Some new evidence. Journal of Financial Economics 46: 223–261.

11.

Booth

Smith

(1986) Capital raising, underwriting and the certification hypothesis. Journal of Financial Economics 15: 261–281.

12.

Bradley

Cooney

Dolvin

, et al. (2006) Penny stock IPOs. Financial Management 35: 5–29.

13.

Brown

Clarke

How

JCY

, et al. (2000) The accuracy of management dividend forecasts in Australia. Pacific-Basin Finance Journal 8: 309–331.

14.

Busaba

Restrepo

(2022) The ‘7% solution’ and IPO (under)pricing. Journal of Financial Economics 144: 953–971.

15.

Carter

Manaster

(1990) Initial public offerings and underwriter reputation. The Journal of Finance 45: 1045–1067.

16.

Chang

Gygax

Oon

, et al. (2008) Audit Quality, auditor compensation and initial public offering underpricing. Accounting and Finance 48: 391–416.

17.

Chen

Firth

Krishnan

(2001) Earnings forecast errors in IPO prospectuses and their associations with initial stock returns. Journal of Multinational Financial Management 11: 225–240.

18.

Chen

H-C

Ritter

(2000) The seven percent solution. The Journal of Finance 55: 1105–1132.

19.

Chen

H-C

Fok

RCW

Wang

(2006) Why do underwriters charge low underwriting fees for initial public offerings in Taiwan? Journal of Business Finance & Accounting 33: 979–1005.

20.

Chen

Hay

Zhuang

(2020) Initial public offering prospectus forecast errors and mandatory explanations: Evidence from New Zealand. Accounting and Finance 60: 2167–2202.

21.

Colombo

Meoli

Vismara

(2019) Signaling in science-based IPOs: The combined effect of affiliation with prestigious universities, underwriters, and venture capitalists. Journal of Business Venturing 34: 141–177.

22.

Cornelli

Goldreich

(2001) Bookbuilding and strategic allocation. The Journal of Finance 56: 2337–2369.

23.

Crain

Parrino

Srinivasan

(2021) Uncertainty, prospectus content, and the pricing of initial public offerings. Journal of Empirical Finance 64: 160–182.

24.

Dimovski

Brooks

(2004) Do you really want to ask an underwriter how much money you should leave on the table? Journal of International Financial Markets, Institutions & Money 14: 267–280.

25.

Dimovski

Brooks

(2008) The underpricing of gold mining initial public offerings. Research in International Business and Finance 22: 1–16.

26.

Dimovski

Philavanh

Brooks

(2011) Underwriter reputation and underpricing: Evidence from the Australian IPO market. Review of Quantitative Finance and Accounting 37: 409–426.

27.

Liu

, et al. (2018) Underwriter–Auditor relationship and pre-IPO earnings management: Evidence from China. Journal of Business Ethics 152: 365–392.

28.

DuCharme

Rajgopal

Sefcik

(2001) Why was Internet IPO underpricing so severe? Working paper, University of Washington, Seattle, WA, 1 September.

29.

Eckbo

Masulis

(1992) Adverse selection and the rights offer paradox. Journal of Financial Economics 32: 293–332.

30.

Ellis

Michaely

O’Hara

(2000) When the underwriter is the market maker: An examination of trading in the IPO aftermarket. The Journal of Finance 55: 1039–1074.

31.

Fang

(2005) Investment bank reputation and the price and quality of underwriting services. The Journal of Finance 60: 2729–2761.

32.

Fernando

Gatchev

Spindt

(2005) Wanna dance? How firms and underwriters choose each other. The Journal of Finance 60: 2437–2469.

33.

Fernando

Gatchev

Spindt

(2013) Two-sided matching: How corporate issuers and their underwriters choose each other. Journal of Applied Corporate Finance 25: 103–115.

34.

Fernando

Gatchev

May

, et al. (2015) Prestige without purpose? Reputation, differentiation, and pricing in US equity underwriting. Journal of Corporate Finance 32: 41–63.

35.

Finn

Higham

(1988) The performance of unseasoned new equity issues-cum-stock exchange listings in Australia. Journal of Banking & Finance 12: 333–351.

36.

Firth

(1997) An analysis of the stock market performance of new issues in New Zealand. Pacific-Basin Finance Journal 5: 63–85.

37.

Gilbey

Marsh

Purchase

(2021) ASX small firm/microcap listings: The IPO ‘Pop’ and two decades of subsequent returns. Accounting and Finance 62: 3285–3318.

38.

Hansen

(1986) Evaluating the costs of a new equity issue. Midland Corporate Finance Journal 4: 42–55.

39.

Hansen

Torregrosa

(1992) Underwriter compensation and corporate monitoring. The Journal of Finance 47: 1537–1555.

40.

Hartnett

Shamsuddin

(2020) Initial public offer pricing, corporate governance and contextual relevance: Australian evidence. Accounting and Finance 60: 335–372.

41.

Heinkel

Schwartz

(1986) Rights versus underwritten offerings: An asymmetric information approach. The Journal of Finance 41: 1–18.

42.

How

JCY

(2000) Initial and long-run performance of mining IPOs in Australia. Australian Journal of Management 25: 95–118.

43.

How

JCY

Yeo

(2000) The pricing of underwriting services in the Australian capital market. Pacific-Basin Finance Journal 8: 347–373.

44.

Jenkinson

Jones

Suntheim

(2018) Quid pro quo? What factors influence IPO allocations to investors? The Journal of Finance 73: 2303–2341.

45.

Koda

Yamada

(2018) Determinants of underwriting fees by new entrant banks: Evidence from the Japanese IPO underwriting market. Financial Management 47: 285–307.

46.

Lee

Taylor

Walter

(1996) Australian IPO pricing in the short and long run. Journal of Banking & Finance 20: 1189–1210.

47.

Ljungqvist

Jenkinson

Wilhelm

(2003) Global integration in primary equity markets: The role of US banks and US investors. Review of Financial Studies 16: 63–99.

48.

Loughran

Ritter

(2004) Why has IPO underpricing changed over time? Financial Management 33: 5–37.

49.

Loughran

Ritter

Rydqvist

(1994) Initial public offerings: International insights. Pacific-Basin Finance Journal 2: 165–199.

50.

Lyu

Wang

, et al. (2022) Individual investment bankers’ reputation concerns and bond yield spreads: Evidence from China. Journal of Banking & Finance 140: 106508.

51.

Megginson

Weiss

(1991) Venture capitalist certification in initial public offerings. The Journal of Finance 46: 879–903.

52.

Murgulov

Marsden

Rhee

, et al. (2019) Venture capital-backed and commitments test entity initial public offerings on the ASX. Accounting and Finance 59: 1265–1297.

53.

Muscarella

Vetsuypens

(1989) A simple test of Baron’s model of IPO underpricing. Journal of Financial Economics 24: 125–135.

54.

Ong

Mohd-Rashid

Taufil-Mohd

(2020) Underwriter reputation and IPO valuation in an emerging market: Evidence from Malaysia. Managerial Finance 46: 1283–1304.

55.

Ritter

(1984) The ‘hot issue’ market of 1980. Journal of Business 57: 215–240.

56.

Ritter

(1987) The costs of going public. Journal of Financial Economics 19: 269–281.

57.

Ritter

(2021) IPO data/IPO statistics. Available at: https://site.warrington.ufl.edu/ritter/ipo-data/ (accessed 11 April 2022).

58.

Schultz

Zaman

(2001) Do the individuals closest to internet firms believe they are overvalued. Journal of Financial Economics 59: 347–381.

59.

Teoh

Welch

Wong

(1998) Earnings management and the long-run market performance of initial public offerings. The Journal of Finance 53: 1935–1974.

60.

Torstila

(2003) The clustering of IPO gross spreads: International evidence. Journal of Financial and Quantitative Analysis 38: 673–694.

61.

Wang

Chai

Yan

, et al. (2022) Effect of geographical distance between underwriters and listed companies on IPO underpricing: Evidence from China’s A-share market. International Review of Economics & Finance 79: 340–352.

62.

Welch

(1991) An empirical examination of models of contract choice in initial public offerings. Journal of Financial and Quantitative Analysis 26: 497–518.

63.

Wyatt

(2014) Is there useful information in the ‘use of proceeds’ disclosures in IPO prospectuses? Accounting and Finance 54: 625–667.