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http://www.canberratimes.com.au/national/public-service/fear-of-counterfeit-drugs-in-38m-aid-projectGCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 312 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 for-papua-new-guinea-20131129-2yhhs.html World Health Organization (WHO), (2010). “Report of the situation of counterfeit medicines based on data collection tool. WHO regions for Africa and eastern Mediterranean,” WHO/ACM/3, 2010

BIOGRAPHY

B. Gurney has an MBA in Business Administration. Mr. Gurney’s primary research field is quality control and energy. He has publications in the Production and Inventory Management Journal and authored “Best Practices in Technology Transfer.” G. Amundson has been a faculty member at Montana State University Billings for 17 years. he is a recipient of numerous Outstanding Instructor of the Year Awards. He has served on the Inter University Benefits Committee for all higher education in Montana for 9 years. He formerly was Senior Vice President and Corporate Officer of a public company based in Montana for 12 years; and was an instructor in the College of Agriculture at the University of Arizona for 10 years.

S. Boumediene Has a PhD in Business Administration (Accounting). Dr. Boumediene has been publishing his research work in academic journals such as Journal of Modern Accounting and Auditing and the Journal of Management and Business Research among others. Dr. Boumediene published a book on statistical characteristics and quality of accounting information in 2013 - Corresponding author.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 313 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1

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This paper explores whether and how individuals’ allocation affects IPO pricing in Japan. IPO underpricing is a robust phenomenon that extends across equity markets in several countries and time periods. However, in U.S. versus Japan, the underwriters have allocated institutions versus individuals 70-80% of IPO shares. There is surprisingly little research on how initial gains are divided between these different investors. In Japan, we can use the valuable allocation data to individuals. In the context of asymmetric information, underwriters can favor preferred investors by allocating them more shares in ‘hot’ issues. In Japan, the preferred investors may be individuals. In contrast to book-building theories, some previous studies raise doubts as to the extent of information production. In cold market, if their bids are informative, individuals’ allocation has a positive effect on IPO underpricing. On the other hand, in the context of behavioral finance, individual investor sentiment has a positive influence on the price. However, pre-IPO individuals’ allocation reduces post-IPO sentiment. Therefore, in cold market, individuals’ allocation will be likely to decrease the underpricing. The results provide evidence that individuals’ allocation is likely to decrease the underpricing. We discuss the asymmetric information and behavioral finance implication on our findings.

JEL: G32 KEYWORDS: IPO Underpricing, Allocation, Institutional/Individual Investors

INTRODUCTION

This paper explores whether and how allocation to individual investors affect IPO pricing in Japan. It is well known that IPOs are underpriced on average. Underpricing is a robust phenomenon that extends across equity markets in several countries and time period (Jenkinson and Ljungqvist, 2001; Ritter and Welch, 2002; Ljungqvist, 2007). This phenomenon is the same in Japan (Kutsuna, 2008; Okamura, 2013).

However, there is surprisingly little research on how these initial gains are divided between different investors (institutions versus individuals), especially in Japan. The primary obstacle to empirical research has been the lack of data. The underwriters do not disclose the proportion of shares allocated to institutions versus individuals. In U.S., according to articles and previous research, underwriters have allocated institutional investors 70-80% of IPO shares. In contrast, in Japan, the underwriters have allocated individual investors 70-80% of IPO shares (Kutsuna, 2008; Okamura, 2013). In Japan, we can use the valuable allocation data to individual investors. However, no research has examined using the micro-data.

IPO pricing research has two different points of view: asymmetric information and behavioral finance (Ritter and Welch, 2002; Ljungqvist, 2007). In the context of asymmetric information, it’s necessary to make the initial gain for preferred investors. IPO underwriters play a central role in determining the division of initial gains between different investors. Underwriters possess substantial information about issue demand as a result of their information gathering activities during the book-building process. In principle, underwriters can favor preferred investors by allocating them more shares in ‘hot’ issues that are expected to trade up strongly in the aftermarket. Who are the preferred investors? In U.S., the preferred investors are institutions. In Japan, the preferred investors may be individuals. In contrast to bookbuilding theories, Jenkinson and Jones (2004, 2009) raise doubts as to the extent of information production.





In cold market, if their bids are informative, allocation to individual investors has a positive effect on IPO underpricing. On the other hand, in the context of behavioral finance, individual investor sentiment has a GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 314 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 positive influence on the price. However, pre-IPO individuals’ allocation reduces post-IPO sentiment.

Therefore, individuals’ allocation will be likely to decrease the underpricing, especially in the cold market.

The results provide evidence that individuals’ allocation is likely to decrease the underpricing. We discuss the asymmetric information and behavioral finance implication on our findings. The rest of the paper is organized as follows: Section II describes different view of IPO pricing research and these hypotheses; the details of data and methodology in Section III; Section IV discusses the empirical findings; and conclusions are provided in Section V.

LITERATURE REVIEW AND HYPOTHESES

In the context of asymmetric information(Rock’s (1986) adverse selection indicates that uninformed investors are allocated greater quantities in overpriced IPOs and smaller quantities in underpriced IPOs.

Amihud, Hauser and Kirsh (2003) examine Rock’s theory using unique data from Israel), Benveniste and Spindt (1989) and Benveniste and Wilhelm (1990) indicate that underwriters use discretion to extract information from investors, which reduces average underpricing and increases proceeds to the issuers (Sherman (2000) and Sherman and Titman (2002) extend the framework to allow for costly information acquisition). Many related models are at least partly based on the notion that if IPOs are underpriced on average, investors have an incentive to acquire information about the firms to try and discern which will be underpriced the most. In Loughran and Ritter (2002), underwriters might intentionally leave more money on the table then necessary, and then allocate these shares to favored buy-side clients. Using U.S. data, Hanley and Wilhelm (1995) and Aggarwal, Prabhala and Puri (2002) find that institutions are favored, as do Cornelli and Goldreich (2001))using U.K. data, and Lee, Taylor and Walter (1999) using Singapore data. Moreover, Ljungqvist and Wilhelm (2002) find the same is true worldwide. They support bookbuilding theories of IPO underpricing. However, in Japan, the underwriters have allocated individual investors 70-80% of IPO shares (Kutsuna, 2008; Okamura, 2013). Are individuals favored?

H1: As allocation to individual investors increases, IPO underpricing is higher.

In contrast to book-building theories, Jenkinson and Jones (2004) find that investors perceived to be longterm holders of the stock are consistently favored in allocation and in out-turn profits, Aggarwal (2003) and Zhang (2004) think that allocations are directed toward investors who will. Moreover, they find little evidence that more informative bids receive larger allocations or higher profits. Jenkinson and Jones (2009) is based on a survey and raises doubts as to the extent of information production. In Japan, we don’t have known that whether their bids are informative. The primary obstacle to whether their bids are informative has been the lack of data. However, in cold market, we will find that whether their bids are informative. That is, in hot market, their bids may be uninformative, we don’t know that whether allocation to individual investors has a positive effect on IPO underpricing. On the other hand, in cold market, if their bids are informative, allocation to individual investors has a positive effect on IPO underpricing.

H2: In cold market, as allocation to individual investors increases, IPO underpricing is higher.

In the context of behavioral finance, IPO studies discuss the impact of investor sentiment on the post-IPO pricing (Helwege and Liang, 2004; Derrien, 2005; Ljungqvist, Nanda and Singh, 2006). Derrien (2005) and Ljungqvist, Nanda and Singh (2006) show that investor demand at the time of IPO has a positive effect on post-IPO investor demand. Helwege and Liang (2004) show that IPO pricing is affected by investor sentiment rather than firm specific characteristics in hot market. In Japan, many empirical papers find investor sentiment at the time of IPO has a positive effect on post-IPO pricing (Takahashi, 2009; Yamada and Takahashi, 2010; Okamura, 2013 etc). We think that allocation to individual investors has a negative effect on post-IPO pricing. That is, If investor sentiment has a large quantity, allocation to individual investors has almost no effect on post-IPO pricing. However, if investor sentiment has a given quantity (that is, in cold market) and the underwriters don’t adjust allocation, we think that allocation to individual investors has a negative effect on post-IPO pricing.

GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 315 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 H3: Given that the underwriters don’t adjust allocation, in cold market, as allocation to individual investors increases, IPO underpricing is lower.

DATA AND METHODOLOGY

We use data from IPO firms that went public between August 2006 and December 2014 in JASDAQ market. The reason to select this period is as follows. Japan Securities Dealers Association (JSDA) has published the allocation data to individual investors at IPO from August 2006 (/www.jsda.or.jp/shiryo/toukei/shinkikoukai/index.html ). Therefore, we restrict the data to after August

2006. Further, we use Trader’s web (www.traders.co.jp/ipo_info/ipo_info_top.asp ), IPO prospectuses to identify the IPO detailed information. Finally, we use 154 firms in the sample. We use OLS for H1, H2, H3. Dependent variable is IPO underpricing (= (initial price – offer price)/offer price*100, underpricing).

Other variables are defined as follow. Independent variables are 1) allocation to individual investors (= allocation to individual investors/issue shares, allocation), 2) favored allocation (= non-lottery allocation+1/allocation to individual investors, favor). Control variables are the natural logarithm of 1) firm age (= the number of months from start-up, ln_age), 2) the number of employee (In_employee), 3) sale in the previous IPO (In_sale), 4) IPO gross proceeds (= offer price*issue shares, In_lot), and 5) partial adjustment (= (offer price – midpoint of filing rage)/midpoint of filing range*100, part_adjust, Hanley, 1993), and Top 3 underwriters dummy (= NOMURA, DAIWA, SMBC NIKKO, sec_d), VC backed dummy (vc_d), year dummy. Table 1 shows the descriptive statistics (mean, S.D., min, max) for all variables.

Moreover, to test the above hypotheses, we classify hot/cold market by the number of IPO (see Figure 1).

Cold market is defined from 2008 to 2014.

Table 1: Descriptive Statistics

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ESTIMATION RESULTS

Table 2 shows OLS regression results in sample period. H1 is not support. The allocation has a statistically significant negative effect on IPO underpricing at the 1% level. The empirical results support U.S. book-building theories of IPO underpricing in Japan. The preferred investors are not individuals but institutions. Why have the underwriters allocated individual investors 70-80% of IPO shares in Japan?

This fact is a puzzle.

Table 2: OLS Regression Results in Sample Period

–  –  –

number of obs 154 underpricing is (initial price – offer price)/offer price*100. allocation is allocation to individual investors/issue shares. favor is non-lottery allocation+1/allocation to individual investors. 1) In_age, 2) In_employee, 3) In_sale, 4) In_lot, 5) part_adjust are the natural logarithm of 1) the number of months from start-up, 2) the number of employee, 3) sale in the previous IPO, 4) offer price*issue shares, and 5) (offer price – midpoint of filing rage)/midpoint of filing range*100. sec_d is Top 3 underwriters dummy, and vc_d is VC backed dummy. T-statistics (based upon robust standard errors) are in parentheses. ***, **, * Significant at the 1, 5, 10 percent level using a two-tailed test.

Table 3: OLS Regression Results in Cold Market (From 2008 to December 2014)

–  –  –

midpoint of filing rage)/midpoint of filing range*100. sec_d is Top 3 underwriters dummy, and vc_d is VC backed dummy. T-statistics (based upon robust standard errors) are in parentheses. ***, **, * Significant at the 1, 5, 10 percent level using a two-tailed test.

Table 3 shows OLS regression results in cold market (from 2008 to December 2014). H2 is not support, H3 is support. The allocation has a statistically significant negative effect on IPO underpricing at the 5% level. The empirical results find that institutional investors’ bids are informative. Moreover, allocation to individual investors decreases investor sentiment, and post-IPO pricing.

CONCLUSIONS



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