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This paper explores whether and how allocation to individual investors affects IPO pricing in Japan. The empirical results support U.S. book-building theories of IPO underpricing in Japan. Why have the underwriters allocated individual investors 70-80% of IPO shares in Japan? This fact is a puzzle.
Moreover, IPO pricing is affected by investor sentiment. Future research adds analysis for post-IPO activities. For example, previous studies relate allocations to long-run performance after IPO (Boehmer, Boehmer and Fishe, 2006), and the generation of subsequent trading commissions (Loughran and Ritter, 2004; Reuter, 2006; Nimalendran, Ritter and Zhang, 2007; Ritter and Zhang, 2007).
REFERENCESAggarwal, R. (2000), “Stabilization Activities by Underwriters after IPOs,” Journal of Finance 55, pp.1075-1103.
Aggarwal, R. (2003), “Allocation of Initial Public Offerings and Flipping Activity,” Journal of Financial Economics 68, pp.111-135.
Aggarwal, R., Prabhala, N. R. and Puri, M. (2002), “Institutional Allocation in Initial Public Offerings:
Empirical Evidence,” Journal of Finance 57, pp.1421-1442.
Amihud, Y., Hauser, S. and Kirsh, A. (2003), “Allocations, Adverse Selection, and Cascades in IPOs:
Evidence from the Tel Aviv Stock Exchange,” Journal of Financial Economics 68, pp.137-158.
Benveniste, L. M. and Spindt P. A. (1989), “How Investment Bankers Determine the Offer Price and Allocation of New Issues,” Journal of Financial Economics 24, pp.343-361.
Benveniste, L. M. and Wilhelm, W. J. (1990), “A Comparative Analysis of IPO Proceeds under Alternative Regulatory Environments,” Journal of Financial Economics 28, pp.173-207.
Boehmer, B., Boehmer, E., and Fishe, R. P. H. (2006), “Do Institutions Receive Favorable Allocations in IPOs with Better Long Run Returns?,” Journal of Financial and Quantitative Analysis 41, pp.809-828.
Cornelli, F. and Goldreich, D. (2001), “Bookbuilding and Strategic Allocation,” Journal of Finance 56, pp.2337-2369.
Derrien, F. (2005), “IPO Pricing in “Hot” Market Conditions: Who Leaves Money on the Table?,” Journal of Finance 60, pp.487-521.
Hanley, K. W. (1993), “The Underpricing of Initial Public Offerings and the Partial Adjustment Phenomenon,” Journal of Financial Economics 34, pp.231-250.
Hanley, K. W. and Wilhelm, W. J. (1995), “Evidence on the Strategic Allocation od Initial Public Offerings,” Journal of Financial Economics 37, pp.239-257.
Helwege, J. and Liang, N. (2004), “Initial Public Offerings in Hot and Cold Markets,” Journal of Financial and Quantitative Analysis 39, pp.541-569.
Jenkinson, T. and Jones, H. (2004), “Bids and Allocations in European IPO Bookbuilding,” Journal of Finance 59, pp.2309-2338.
Jenkinson, T. and Jones, H. (2009), “IPO Pricing and Allocation: A Survey of the Views of Institutional Investors,” Review of Financial Studies 22, pp.1477-1504.
Jenkinson, T. and Ljungqvist, A. (2001), Going Public, 2nd edition, Oxford University Press.
Kutsuna, K. (2008), Price Formation on the IPO Markets, Chuokeizai-Sha, Inc. (in Japanese) Lee, P. J., Taylor, S. L. and Walter, T. S. (1999), “IPO Underpricing Explanations: Implications from Investor Application and Allocation Schedules,” Journal of Financial and Quantitative Analysis 34, pp.425-444.
Ljungqvist, A. (2007), IPO Underpricing, Handbook of Corporate Finance, Vol.1, Chapter 7, pp.375-422.
Ljungqvist, A. and Wilhelm, W. J. (2002), “IPO Allocations: Discriminatory or Discretionary?,” Journal of Financial Economics 65, pp.167-201.
Ljungqvist, A., Nada, V. and Singh, R. (2006), “Hot Markets, Investor Sentiment, and IPO Pricing,” Journal of Business 79, pp.1667-1702.
Loughran, T. and Ritter, J. R. (2002), “Why don’t Issuers Get upset about Leaving Money on the Table in IPOs?,” Review of Financial Studies 15, pp.413-443.
Loughran, T. and Ritter, J. R. (2004), “Why Has IPO Underpricing Changed over Time?,” Financial Management 33, pp.5-37.
Nimalendran, M., Ritter, J. R. and Zhang, D. (2007), “Do Today’s Trades Affect Tomorrow’s IPO Allocations?,” Journal of Financial Economics 84, pp.87-109.
Okamura, H. (2013), Japanese IPO Markets, Toyo Keizai, Inc. (in Japanese) Reuter, J. (2006), “Are IPO Allocations for Sale?: Evidence from Mutual Funds,” Journal of Finance 61, pp.2289-2324.
Ritter, J. R. and Welch, I. (2002), “A Review of IPO Activity, Pricing, and Allocations,” Journal of Finance 57, pp.1795-1828.
Ritter, J. R. and Zhang, D. (2007), “Affiliated Mutual Funds and the Allocation of Initial Public Offerings,” Journal of Financial Economics 86, pp.337-368.
Rock, K. (1986), “Why New Issues are Underpriced?,” Journal of Financial Economics 15, pp.187-212.
Sherman, A. (2000), “IPOs and Long-term Relationships: An Advantage of Bookbuilding,” Review of Financial Studies 13, pp.697-714.
Sherman, A. and Titman, S. (2002), “Building the IPO Order Book: Underpricing and Participation Limits with Costly Information,” Journal of Financial Economics 65, pp.3-29.
Takahashi, Y. (2009), “Is Internet Message Board Informative?: Evidence from Japanese IPOs,” Annuals of Society for the Economic Studies of Securities 44, pp.153-158. (in Japanese) GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 319 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 Yamada, K. and Takahashi, Y. (2010), “Effects of Investor Sentiment on IPO Pricing: Evidence from the Japanese Auction Method,” Proceedings of the 6th International Conference on Asian Financial Markets, Published in CD-ROM.
Zhang, D. (2004), “Why do Underwriters Allocate Extra Shares that They Have to Buy Back?,” Journal of Financial and Quantitative Analysis 39, pp.571-594.
BIOGRAPHYYoji Takahashi is Associate Professor at Gifu Shotoku Gakuen University. He can be reached at Gifu Shotoku Gakuen University, 1-38 Nakauzura, Gifu, JAPAN, 5008288.
GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 320 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1
The paper analyzes the effect of housing assets and mortgage debt on a household’s asset portfolio based on data from The Survey of Household Finances and Living Conditions in Korea. To solve endogeneity problem and to find various cross-sectional variations, we use an individual household’s housing value and mortgage debt as instrument variables and two-stage least squares regression for our analysis. In conclusion, we confirm that an increase in mortgage debt has a negative effect on the household’s portfolio’s stock ratio and simultaneously, an increase in housing value has a significant positive effect on the portfolio’s risk-asset ratio for Korean households.
JEL: D1 KEY WORDS: Portfolio, Housing Asset, Mortgage debt, 2SLS
INTRODUCTIONany households own their own homes as well as other real estate and this housing asset generally represents the largest share of a household’s assets. However, although housing is an important part of a household’s assets, there has not been much research on a household’s portfolio considering the housing asset.
Theoretical conclusions currently suggested by major research imply that owning a house generally decreases demand for risky assets because of the increase in household risk and illiquidity from housing ownership (Fratantoni, 1998, Heaton and Lucas, 2000, Yamashita, 2003, Cocco, 2005). In general, empirical studies show mixed results; however, recent research by Chetty and Szeild (2014) provides clear empirical evidence for the relationship between house ownership and a household’s portfolio choices. Our study explores the relationship between the housing asset and portfolio choices by examining Korean household micro finance data. In Korea, most housing assets represent the largest share of a household portfolio. This is of particular interest to the real estate market and to the economy as a whole. As suggested by Chetty and Szeild (2014), we use an empirical model driven by theory to test the relationship between housing ownership and portfolio choices. We also pursue an analysis using instrument variables to solve the endogeneity problem through the estimation process.
When households choose to own a house as part of their portfolio, these decisions are affected by unobserved factors. As a result of this, there are estimation problems when we analyze the causal relationship effects for household portfolios using cross-sectional variation across the households. The basic idea of this approach is to separate the variation for unobserved decision factors orthogonal to the variation of mortgage debt and the housing asset under different variable assumptions when households make portfolio choices (Chetty and Szeild, 2014). By doing this, the current housing price index can present a strong prediction for housing property values for each household. Therefore, for this purpose, our study utilizes house prices for individual households as the instrument variable for mortgage debt and the housing asset. Compared to a study for U.S. households by Chetty and Szeild (2014), we use variations for metropolitan versus non-metropolitan areas and the average of the house price index to improve a weakness in state-level variations in their study.
In this study, we analyze the relationship between housing assets and household portfolios with instrument variables, using the data from the Survey of Household Finances and Living Conditions (SHFLC) for the GCBF ♦ Vol. 11 ♦ No. 1 ♦ 2016 ♦ ISSN 1941-9589 ONLINE & ISSN 2168-0612 USB Flash Drive 321 Global Conference on Business and Finance Proceedings ♦ Volume 11 ♦ Number 1 years 2010-2013. Specifically, using the two-stage least square estimate (2SLS), we examine the effect of debt mortgage and housing assets on the share of risky assets in a household’s portfolio. Empirical results find a significant effect of housing value on a household’s portfolio choices.
An increase in mortgage debt negatively affects the share of stocks to liquid assets, and, on the other hand, an increase in housing value has a significant positive effect on the ratio of risky assets (stocks) to liquid assets. The interpretation of this is that an increase of KRW 1,000M in debt (roughly, USD 10,000) generates a negative (1.70%) effect on the ratio of stock holdings to assets and an increase of KRW 1,000M in the housing asset has a positive 1.96% effect on the ratio of stock holdings. Our empirical results for Korean households are consistent with Chetty and Szeild’s (2014) results for U.S. households.
However, our study has some limitations. First, we use the current house price index because we could not utilize house prices for purchasing points as instrument variables since the data lack concrete information around the dates of the house purchases. Second, we do not have details around the locations of the houses, for example, state information. Therefore, to amend this weakness, we utilize information for metropolitan and non-metropolitan areas. Additionally, through the use of house prices for various house types, we can engender relatively smaller cross-sectional variations. Moreover, as pointed out by other studies, there are still possible correlations between household portfolio choices and other factors such as the condition of the labor market in the area. Ignoring this possibility may be a weakness in analyzing the empirical tests.
Although these limitations exist, our empirical results represent relatively new findings for Korean households. This study is the first empirical study derived from a theoretical model and extended to new, recent data. To fix the endogeneity problem, we use various house price indices for house types and areas, compared to existing Korean research. As a result, we think our empirical approach and results will contribute to the literature.
Research on portfolio choices has a long history that continues today. Specifically, in 1991, Grossman and Laroque (1990) presented the first theoretical paper in which housing became a part of the study of the household portfolio. In their study, they created a portfolio choice model under the assumption that unlimited existing investors consume one non-liquid durable consumption good. Flavin and Yamashita (2002) study the effect of portfolio constraints by house consumption demand, called “house constraint,” on the optimal decisions for an investor in financial assets. Further, Yamashita (2003) conducts empirical research on the relationship between house investments and stock-holdings, and finds that the ratio of house assets to net wealth and the share of stocks to financial assets are negatively correlated. Therefore, he explains that the phenomenon arises from a decrease in the household portfolio’s investments in risky assets to offset the increased risk from being highly leveraged in the house asset.