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This paper aimed to explore the effect of a regulatory change pertaining to earnings forecasts disclosure from a mandatory to a voluntary regime on the valuation of Malaysian initial public offerings (IPOs).

The study employed ordinary least square (OLS) regression and quantile regression to analyse the impact of disclosure of earnings forecasts regulation on the valuation of IPOs which comprised 458 IPOs reported for the period 2000–2017 on Bursa Malaysia.

This paper revealed that the regulatory change in forecasted earnings disclosure from a mandatory to a voluntary regime, effective from 1 February 2008, had a negative impact on the valuation of IPOs. The regime change did not improve the transparency of firms issuing IPOs. In fact, the absence of forecasted earnings information in most IPO prospectuses caused ex ante uncertainties to increase. Voluntary disclosure, however, had a significant positive relationship with the valuation of the IPOs issued during the global financial crisis period (2008–2010). Firms concealed their poor qualities by excluding forecasted earnings information from their prospectuses in order to have a fair valuation.

The findings may be used by policymakers as guidance in improving the existing regulation regarding the disclosure of forecasted earnings.

This paper provides new insight on the effect of a regulatory change pertaining to earnings forecasts disclosure from a mandatory to a voluntary regime on the valuation of Malaysian IPOs. It also provides evidence that the regulatory change of earnings forecast disclosure affects the IPOs' values listed during the global financial crisis period.

This study aims to investigate the valuation accuracy of Malaysian initial public offerings (IPOs) by using price-multiple methods.

Cross-sectional data including 467 IPOs listed on the Malaysian stock exchange were used for the period of 2000–2017. This study used univariate ordinary least square (OLS) regression to analyse the relationship between IPOs’ price-multiples and comparable firms’ price-multiples. The test of valuation accuracy was conducted via computing valuation errors by segregating the sample into two groups: fixed-price IPOs and book-built IPOs. Furthermore, multiple OLS regression was used to examine the influence of IPO valuation on underpricing.

The findings of the results suggested that IPOs price-to-earnings (P/E), price-to-book (P/B) and price-to-sales (P/S) multiples were positively related to the median P/E, P/B and P/S multiples of five comparable firms matched by industry and revenues. The P/S multiple was shown to be the most significant valuation method, specifically in book-built IPOs. The findings indicated that those firms that had a lower valuation in comparison to the comparable firms were inclined to underprice their IPOs to allure investors to subscribe IPOs. In addition, book-built IPOs that had fair valuations were inclined to generate higher initial returns for investors.

The findings of this study observed implications for underwriters in avoiding the mis-valuation issue by considering the book-building mechanism.

This study attempted to explore the suitability of the valuation method to value IPOs in Malaysia.

The purpose of this study is to examine the influence of underwriter reputation on the valuation of Malaysian initial public offerings (IPOs).

This study employed cross-sectional multiple regression models to analyse the relationship between underwriter reputation and IPO valuation that included 466 IPOs listed on Bursa Malaysia from 2000 to 2017.

The results revealed that underwriter reputation had a significant negative association with IPO valuation. Firms that engaged the services of reputable underwriters had their IPO offer prices set lower than the intrinsic values during the listing. After incorporating firms' size, this study found a positive relationship between underwriter reputation and IPO valuation. Big firms (high quality) hired reputable underwriters for certification purposes as issuers were aware that the cost of hiring a reputable underwriter would be justified by increased transparency after listing. Therefore, firms that engaged reputable underwriters had approximately fair values since issuers assumed that the price would be close to the intrinsic value following enhanced transparency post-listing.

Future studies should focus on other non-financial factors, such as auditor reputation.

The present study provides new insights into the certification role of underwriters in valuing IPOs in the Malaysian market.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

The case illustrates the application of the prospect theory to risk-seeking investor behavior. It also provides an example that standard valuation methods such as discount cash flow), discount divided model and price multiples are not always applicable to value a stock. The students are exposed to a real situation where investors turn risk-seeking. The case offers insights into why irrational investors are attracted to risky assets and their probable socio-demographics.

This case illustrates a case when investors become risk-seeking and how the prospect theory explains the investors’ risk appetite. Energy Earth PCL is a coal importer and distributor incorporated in Thailand. Its shares had been suspended for trading before the Stock Exchange of Thailand allowed temporary trading in July 2019. A series of unfavorable events leading up to the temporary trading period suggest that the company’s financial health was severely distressed. Its book value was presumably negative and its going concern was threatened. However, investors still bought the shares with the hope of hitting the jackpot. The case presents an example of the psychological aspects of humans when investing in a stock market. With an application of the prospect theory, irrational risk-seeking behavior explains the motivation to invest in risky stocks.

Introductory finance course.

Teaching notes are available for educators only.

CSS: 1 Accounting and Finance.

This chapter addresses the general process of determining the value of a particular company, with additional detail on how valuation processes might be adapted to produce credible value conclusions of emerging technology ventures. There are three primary approaches to business valuation. There is the income approach, which indicates that value is a product of expected future cash flows – cash flows that are discounted to equate them to dollars in-hand (present value). There is the market approach, which attempts to draw conclusions of value based on the market prices of similar companies in the public and/or private markets. Finally, there is the asset approach, which indicates that the value of a company is equal to the sum of the values of its net assets. Specific adjustments are appropriate with respect to each of these approaches where the value of an emerging technology company is concerned. Professional valuation standards require that all of these approaches be considered in the valuation, even if the available information does not permit their credible application. Often, multiple approaches and techniques can be applied. The results of applying multiple techniques often do not overlap, and it is the analyst’s very important task to reconcile differing valuation results, or to decide which result or results should be discarded.

Both American and International Accounting Standards lead to the invisibility of most brand values in financial statements, as these standards recognize only those brands acquired externally either through a purchase or a merger. Nonetheless, over the last several decades, it has become increasingly evident that company value is primarily driven by intangible assets such as brands and other intellectual property. As such, in a knowledge-based economy, it is increasingly important for companies to develop these assets. Empirical evidence produced by prior research also demonstrates that brand values are market value relevant, that is, knowledge about their existence and value is important to investors. Consequently, and in tangent with the increased use of fair value measurements based on projected future cash flows, we argue in this chapter that it might be time to end the invisibility of brands.

This study aims to highlight the accuracy, performance and selection of the IPO valuation methods in the Islamic Republic of Iran’s emerging market.

The authors performed accurate ex ante evaluations based on a pre-IPO data set obtained from valuation institutions. This study considered valuation methods through correlations, Mann–Whitney U tests and regression analysis, using a sample of 83 IPOs from January 2017 to March 2021.

The authors found that the dividend discount model (DDM) was the most popular in Iran. Even after controlling firm characteristics and market circumstances, the IPO price was highly correlated to pre-IPO reports’ estimates. The results showed that firms’ age, size and profitability affected the selection of valuation methods. The valuers did not apply forward P/E in a volatile market. Firm size affected the weights assigned to free cash flow to the firm, and the valuers considered the asset-in-place intensity to determine the weights of DDM, P/E and net asset value, and they mainly used the P/E to value old firms. Finally, this study estimated the accuracy of the pre-IPO report at 61% and found the highest accuracy to be associated with DDM.

IPO pricing in emerging markets constitutes a more significant dilemma than in developed markets. This paper provides empirical evidence of IPO pricing focusing on valuation methods used in the context of an emerging market – the Islamic Republic of Iran.

Empirical examinations of initial public offering (IPO) initial returns often rely heavily on linear regression models. However, these models can prove inefficient owing to their susceptibility to outliers, a common occurrence in IPO data. This study introduces a machine learning method, known as random forest, to address issues that linear regression may struggle to resolve.

The study’s sample comprises 352 fixed-priced IPOs from the year 2004 until 2021. A unique aspect of this research is its application of the random forest method. The accuracy of random forest in comparison to other methods is evaluated. The findings indicate that the random forest model significantly outperforms other methods in all of the evaluated aspects.

The variable importance measure indicates that investors’ demand, divergence of opinion among investors and offer price are the most crucial predictors of IPO initial returns. These determinants hold particular significance due to the widespread use of the fixed-price method in Malaysia, as this method amplifies the information asymmetry in the IPO market.

To the best of the authors’ knowledge, this study is among the pioneering works in Malaysian literature to apply the random forest method to address the constraints of conventional linear regression models. This is achieved by considering a more extensive array of factors and acknowledging the influence of outliers. Additionally, this study adds value to Malaysian literature by ranking and identifying the ex-ante information that best signals the issuing firm’s quality. This contribution facilitates prospective investors’ decision-making processes and provides issuing firms with effective means to communicate their value and quality to the IPO market.

This study aims to investigate the moderating role of investor demand on the relationship between the investors' divergence of beliefs and the first-day initial public offering (IPO) return.

The study sample covers the period from 2010 to 2019 and consists of 117 IPOs that are priced using the fixed price and listed on the Malaysian stock exchange (Bursa Malaysia). This study employed both the ordinary least square (OLS) and the quantile regression (QR) methods.

Investor demand, proxied by the over-subscription ratio (OSR), plays a moderating role in increasing the effect of investors' divergence of beliefs on initial return, and the moderation effects vary across the quantile of initial return. Pure moderation effects are observed at the bottom and top quantiles, suggesting that investor demand is necessary for divergence of beliefs to influence IPO initial return. However, at the middle quantile of initial return, investor demand is a quasi-moderator. That is, the OSR not only moderates the relationship between the divergence of beliefs and initial return but also has a positive effect on the initial return.

Investors' excessive demand for an IPO issue exacerbates the IPO under-pricing issue induced by a divergence of beliefs amongst investors, thus rendering greater equity market inefficiency.

To the authors' knowledge, this study is amongst the first to empirically investigate the moderating role of investor demand on the investors' divergence of beliefs and IPO initial return relationship.