- Email: [email protected]
Institutional investor preferences for lodging stocks
ARTICLE IN PRESS
International Journal of Hospitality Management 27 (2008) 3–11 www.elsevier.com/locate/ijhosman
Institutional investor preferences for lodging stocks Seonghee Oaka,, Michael C. Dalborb,1 a
Hospitality & Tourism Administration, School of Business, North Carolina Central University, P.O. Box 19716, Durham, NC 27707, USA b William F. Harrah College of Hotel Administration, University of Nevada, 4505 Maryland Parkway, Las Vegas, NV 89154, USA
Abstract Although investments from institutions such as banks, insurance companies and pension funds in the lodging industry increased enormously in the 1990s, there has been no empirical research that has examined institutional preferences for lodging stocks. Understanding institutional investment patterns can help provide easier access to the capital markets for hoteliers who make large capital expenditures. This study identifies the characteristics preferred by institutional investors and also assesses whether the different institutions have heterogeneous preferences. Our results show that, in general, institutions prefer the stock of large lodging firms. They also prefer lodging firms with high capital expenditure-to-asset ratios and high debt ratios. r 2007 Elsevier Ltd. All rights reserved. Keywords: Institutional investment; Lodging stocks
1. Introduction There is some evidence that institutional investor interest in the lodging industry has been increasing (Corgel and DeRoos, 2003; Leung and Lee, 2005; Ciochetti et al., 2002). Although institutional investment patterns regarding lodging properties in the private real estate market have been investigated by some researchers (Corgel and DeRoos, 1994, 2003; Singh and Schmidgall, 2000), there has been no research regarding institutional investment preferences for the stock of lodging firms. The purpose of this research is to examine factors that may influence the behavior of the institutional investor that holds the stock of lodging firms. Moreover, we also assess any potential differences in these preferences across different institutions. One of the important reason of this research is as institutional investors are firms that help bring together suppliers and users of funds in the marketplace (Andrew and Schmidgall, 1993). They are fiduciaries who make investments on behalf of others (Tong and Ning, 2004). Corresponding author. Tel.: +1 919 530 6239; fax: +1 919 530 7865.
E-mail addresses: [email protected] (S. Oak), [email protected] (M.C. Dalbor). 1 Tel.: +1 702 895 3848; fax: +1 702 895 4870. 0278-4319/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2007.06.003
Examples of institutional investors include banks, insurance companies and pension funds. Their role in raising financial capital is critical to growth in the lodging industry. Institutional investors are different from individuals because they are generally better informed. They have greater access to company information and are in a position to monitor the performance of corporate managers more effectively. Since this study is the first to examine institutional holding preferences for the stock of lodging firms, we will assess the potential relationship between institutional holding preferences and financial or accounting characteristics of lodging firms targeted for potential investment. We believe the lodging industry may warrant special attention in this area because of the unique nature of the industry. A hotel represents not only a parcel of real estate but also an operating business. Moreover, hotels usually require investments in capital expenditures on a regular basis. This is because most hotel companies are fixed asset intensive, meaning that most of their assets are tied up in items such as building and equipment. These assets will wear out over time and need to be replaced. Additionally, the lodging industry is highly leveraged from both the use of debt and the high amount of fixed costs. These two
ARTICLE IN PRESS 4
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
factors help increase the risk associated with hotel investments. Furthermore, these conditions may result in different institutional preferences for the lodging industry as compared with other industries. Finally, we believe that studying the hotel industry as a subsample may yield some interesting results. This is analogous to the belief of Myers (2001) in regards to capital structure. Testing theories on broad heterogeneous samples can sometimes be uninformative. Therefore, an investigation of smaller samples or specific industries can be warranted. 2. Literature review Institutional holdings have increased in both the general equity market and the hospitality sector in recent years (Leung and Lee, 2005). In the hospitality sector, institutional holdings (as measured by the percentage of total shares outstanding held by all institutions) in the 1990–1999 period (26.1%) are significantly higher than that in the 1981–1989 period (16.1%). Compared to other hospitality sectors, the hotel industry has the highest increase in institutional holdings (increasing from 16.7% during the 1981–1989 period to 30.4% in the 1990–1999 period). Since institutional investors have increased their funding of the lodging industry, it is important to know their preferences. Institutional holdings have increased in the Real Estate Investment Trust (REIT) industry. Institutions have increased their investment in hotel REITs from 0% in 1993 to 2.6% of total REIT market capitalization in 1998 (Ciochetti et al., 2002). For hotel REITs, pension funds, banks and trust companies have about 0.6% higher ownership than mutual funds and insurance companies. This change is due to poor performance in other property sectors during the mid- to late 1990s (Ciochetti et al., 2002). Thus, the lodging sector can serve as a substitute for other sectors that may perform differently. The liquidity needs of institutional investors may be the motivation for their aggressive bidding for lodging REITs in the 1990s (Corgel and DeRoos, 2003). Despite great interest by institutions, there are only a few studies that have investigated institutional investment behavior in the lodging industry (Corgel and DeRoos, 1994, 2003; Leung and Lee, 2005). This study will focus on what drives institutional investors to choose lodging stocks. Since institutions act as agents for other investors, their investment patterns may be different from individual investors. The prudent-man law limits the freedom of an institution’s risk-taking behavior and is intended to protect beneficiaries by allowing them to seek damages from a fiduciary who fails to act in their best interest. In the case of litigation, the courts accept a prudent investment based on the characteristics of assets in isolation, but ignore the role these assets play in a portfolio (Del Guercio, 1996). The prudent-man law may affect the stock preferences of institutional investors in differing degrees. Because of these
varying restrictions, institutions are divided into five major groups: banks, insurance firms, mutual funds, brokerage firms, and pension funds. According to Gompers and Metrick (2001), ‘‘banks are the only institutions governed by the common-law prudent-man rule, which is interpreted more strictly than the written regulations governing the investment behavior of other institutions. However, empirical studies imply that many non-bank institutions also consider prudence characteristics’’.2 For example, Del Guercio (1996) shows that while banks tend to prefer the stock of prudent firms (large firms with low book-tomarket ratios), mutual funds do not. Institutions have their own particular reasons for selecting the companies in which they wish to invest. According to previous research, institutional investors prefer to hold stock in large companies with high liquidity (Gompers and Metrick, 2001). Since large firms distribute more information to the financial community and more financial analysts follow those firms, there will be less information asymmetry associated with the large firms. Falkenstein (1996) finds that except for the small-cap sector which specializes in small firms, mutual funds are averse to small firms. Thus, in terms of lodging stocks and the stock of companies in other industries, institutions should prefer larger firms because of their high liquidity. Investment managers often divide firms into value and glamour stocks (Fama and French, 1998). Value stocks with high book-to-market, earnings to price and cash flow to price ratios tend to have consistently low earnings. On the other hand, glamour stocks with low book-to-market, earnings to price and cash flow to price ratios tend to be growth firms with high earnings. Institutions also prefer glamour stocks because they may be shown to be prudent investments (Lakonishock et al., 1994). Glamour stocks have had good performance in the past and are unlikely to be distressed in the near future. After adjusting for a mutual fund’s investment style, managers of glamour stock funds perform better on average than one of value funds (Chan et al., 2002). Thus, prudent investment rules should dictate that institutions prefer low book-to-market value stocks of all industries, including the lodging industry. All investors are interested in sales and earnings growth. However, growth opportunities will vary among industries. These opportunities include not only research and development expenditures, but also capacity expansion and acquisitions. In terms of measuring growth opportunities, the literature utilizes ratios such as market value to book value to reflect the market’s expectation of firm growth. Gaver and Gaver (1993) utilize a number of measures for growth opportunities such as the ratio of market value of the firm to book value of assets, market value of equity to book value of equity, and the ratio of earnings to price. A low market value to book value of assets ratio indicates the presence of more assets-in-place, and thus, lowers invest2 Gompers and Metrick (2001, p. 239) analyzed institutional investor’s preference for stock characteristics.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
ment options for growth. Currently, there is no consensus on the best proxy to measure growth opportunities of the firm. Furthermore, as discussed by Smith and Watts (1992) firms make specialized investments in physical and human capital, thus creating variations in the investment opportunity set for different firms. Growth opportunities in the lodging industry may be different from other industries (i.e. pharmaceutical or high technology firms) with high research and development expenditures. For lodging firms, growth opportunities are represented by capital expenditures or acquisitions. Research in the lodging industry indicates that institutions are willing to invest in luxury and upscale hotels which require significant capital expenditures (Singh and Schmidgall, 2000). Institutions prefer firms with a high capital expenditure to asset ratio since capital expenditures can signal the good performance of public firms (Tong and Ning, 2004). In both lodging and other industries, institutions should prefer firms with high capital expenditure to asset ratios. Because of the effect of debt payments on cash flows, firms with significant growth opportunities (i.e. potential future investments in projects that will dramatically increase revenues and cash flows) will shy away from the use of debt. Hovakimian et al. (2004) provide empirical evidence that there is a negative relationship between debt ratios and growth opportunities. The negative relationship between long-term debt and growth opportunities was confirmed in the restaurant industry (Dalbor and Upneja, 2002). The presence of debt in a firm’s capital structure may influence the institutional investor. Furthermore, the presence of institutional ownership of equity may substitute as a monitoring agent for debt. Tong and Ning (2004) suggest that institutions are worried that too much debt may signal trouble to these investors. They find that institutions prefer firms with short-term debt (as opposed to long term). Thus, institutional investors in other industries prefer firms with low debt ratios. Firms with high institutional ownership have lower longterm debt to capital ratios than those with low institutional ownership (Chaganti and Damanpour, 1991). However, it is possible that institutions may prefer the stock of lodging firms with high long-term debt ratios because of the fixed asset nature of the lodging industry. Furthermore, firms with more tangible assets use higher debt (Myers, 2001). US lodging firms have, on average, 41% of their assets backed by long-term debt alone and have a positive relationship between long-term debt and growth opportunities (Dalbor and Upneja, 2004). Thus, in the lodging industry, institutions should prefer firms with high debt ratio. Since lodging firms have both business and real estate components, it is important to have high return of assets (ROA) for operating and managerial efficiency. However, empirical studies on institutional preference regarding ROA are mixed. Kang and Stulz (1997) find that non-
5
Japanese investors in Japanese firms prefer firms with a high ROA. However, the ROA ratio is marginally important for a U.S. investment manager’s domestic stock choices due to local bias (Coval and Moskowitz, 1999). Thus, it is an empirical question whether or not institutional managers prefer high ROA firms. If institutional investors need to trade frequently, they may be sensitive to transaction costs due to larger bid-ask spread percentages for low-priced stocks (Schwartz and Shapiro, 1992). There is a strong correlation between low prices and large bid-ask spreads (Conrad and Kaul, 1993; Kothari et al., 1995). A study by Falkenstein (1996) indicates an institutional aversion for stocks with low prices. Thus, the previous literature indicates support for the notion that in both lodging and other industries, institutional investors should prefer high priced stocks. A ‘‘momentum’’ trading strategy that buys stocks with good returns in previous years and sells stocks with poor prior returns generates significant positive returns over a 3–12-month holding period (Jegadeesh and Titman, 1993). Another trading strategy is a contrarian strategy (buying past losers and selling past winners) which yields higher abnormal returns than merely holding past winning stocks in the same period (De Bondt et al., 1985; Thaler and De Bondt, 1987). Gompers and Metrick (2001) find evidence that is the opposite from the momentum strategy and tends to support the contrarian strategy. They find that large institutions choose stocks with low returns during the previous year. Thus, there is uncertainty regarding the institutional preference for lodging stocks based on past returns. The frequency of stock purchases and subsequent sales is referred to as stock turnover. It also appears to be an important consideration to institutional investors. Institutions prefer firms with high turnover because this means that other investors find the stock attractive, indicating that it is a prudent investment. Previous studies find a positive relationship between institutional ownership and turnover ratio (Eakins et al., 1998). Research indicates that a portfolio with a high turnover rate has higher returns than a portfolio with low turnover (Rouwenhorst, 1999). Hu (1997) proposes that a high turnover of stock reduces transaction costs and thus lowers the total cost of investing. Thus, in both lodging and other industries, institutional investors should prefer stocks with high turnover. While returns are obviously important to investors, the risk, or volatility of returns is important as well. Del Guercio (1996) finds a negative relationship between total risk of a stock and institutional ownership. He posits that fiduciaries may be charged for a loss on a single security and thus this is a motivation to invest less money in risky stocks. In addition to Del Guercio, Falkenstein (1996) shows that mutual fund holdings are negatively related to variance of monthly return during 24–60 months. Thus, in both lodging and other industries, institutional ownership should be negatively related to stock volatility.
ARTICLE IN PRESS 6
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
In summary, the literature indicates a number of potential motivating factors for institutional investor interest in stocks. Institutions tend to prefer large firms that offer a high degree of liquidity as well as growth firms or ‘‘glamour’’ stocks with high earnings. Since growth in the lodging industry typically involves fixed asset investment, investors may prefer companies that make significant capital expenditures. Moreover, given that many capital expenditures in the lodging industry are financed with debt, it may be that investors in hotel stocks prefer firms with high debt ratios. This is contrary to the literature in that some investors worry that too much debt will be problematic for the firm. In terms of performance and price, the literature indicates that investors prefer firms with high ROA ratios because this ratio is an indication of management efficiency (Kang and Stulz, 1997). Previous research indicates that institutions have an aversion to low-priced stocks and tend to own higher-priced issues (Schwartz and Shapiro, 1992). While prices of issues are important to investors, the returns in previous years also are a consideration. The literature indicates that some institutions prefer firms with high returns in previous years, while there is also evidence of a ‘‘contrarian’’ strategy where investors are interested in purchasing the stock of a firm with poor performance in previous years (Jegadeesh and Titman, 1993; De Bondt et al., 1985; Thaler and De Bondt, 1987). One measure of the interest in a stock is measured by turnover. High turnover stocks are popular, and the literature indicates that institutional investors are interested in these popular stocks (Eakins et al., 1998; Hu, 1997). Risky stocks, however, do not show particular favor with institutional investors, particularly mutual funds (Del Guercio, 1996). Previous research measures this risk (volatility) as the variance of monthly returns (Falkenstein, 1996).
Table 1 Variables used in the hypothesis tests and expected signs Independent variables
Dependent variable (log of institutional holdings) Predicted sign
Size BVA/MVA CAP EXP/AS DR ROAa Price Momentuma Turnover Volatility
Hotel industry
Other industries
+ + + ? + ? +
+ + ? + ? +
Note: The dependent variable is calculated as the log of the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, institutional holding of the firm becomes zero. Size is the natural log of market value of a firm’s equity in millions of dollars at the end of year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year; DR is the ratio of total debt to total assets at the end of the year. ROA is net income divided by total assets at the end of the year. Price is price per share (closing price at the end of the year). Momentum is previous period’s net returns. Turnover is computed by volume dividend by share outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for a 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability. a Institutional investor preference is indeterminate.
uncertain what the signs will be for these variables for this study. Other variables are expected to have the same sign for both lodging and other industries.
3. Models and expected signs of the coefficients
4. Data and methodology
Based upon our review of the literature, we will assess whether there is difference in investment determinants of institutional investors between the lodging industry and other industries. The following model is the full model for the regression analysis: Institutional holdings ¼ intercept+b1size+b2book-tomarket ratio+b3capital expenditure to assets+b4debt ratio+b5ROA+b6Price+b7momentum+b8turnover+b9volatility+error term of the regression. The variables for investment determinants and the expected relationships with the dependent variable are shown in Table 1. The signs of the coefficients for the variables for other industries were derived from the literature. When institutional holdings of lodging industry are compared with holdings in other industries, only bookto-market values are expected to show a different sign. Since the momentum strategy and ROA variable have proven to be indeterminate in previous studies, it is
Data for institutional holdings are from the Thompson Financial Spectrum database. SEC regulations state that all institutions with over $100 million in discretionary funds under management and all positions in individual stocks greater than $200,000 or 10,000 shares need to file form 13(f) within 45 days after the last day of each quarter. These forms are available in electronic form dating back to 1980 in the CDA/Spectrum 13(f) Institutional Stock Holdings (Spectrum). Quarterly institutional ownership in Spectrum is categorized into five groups: banks, insurance companies, mutual funds, brokerage firms and pension fund. We compile a lodging sample by using either firm CUSIP numbers or stock symbols for the years 1981–2003. We restrict our study to the common stock of lodging firms found in the annual Compustat files in order to match firm characteristics. Data from the Compustat and Spectrum databases are subsequently merged using the respective stock symbols or CUSIP numbers.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
We use pooled regression models to test the expected relationships found in Table 1. The dependent variable is the natural log of institutional holdings. The log of institutional holdings for a specific stock in the given quarter represents the log of the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, the institutional holding for that firm is determined by zero. The independent variables for this study are the firm’s characteristics: size (log of market value of equity in millions), book-to-market value, the ratio of capital expenditure-to-assets, total debt ratio, ROA, price, momentum, turnover and volatility. Since the dependent variable uses institutional holdings at the end of the quarter, the independent variables are size, book-to-market value, the ratio of capital expenditure-toassets, total debt ratio, ROA and price at the end of year. Momentum, turnover and volatility use previous periods. A full description of the variables can be found in Table 2. Regression models are selected based on the stepwise regression method. 5. Results Table 2 shows the descriptive statistics for the variables. The mean of institutional holdings in lodging firms is 30.7%. This means that nearly a third of lodging company stock is held by institutional investors. The total debt ratio
7
and long-term debt ratio are not significantly different in terms of mean and standard deviation. Accordingly, to help alleviate any problems with multicollinearity the total debt ratio was used in the regression models. The mean of the book-to-market value ratio is 1.17, which is greater than 1. This may be due to the notion that pension funds tend to hold high book-to-market stocks. Regression model 7 in Table 3 shows all other institutions prefer stocks with low book-to-market values. Thus, institutional investors except pension funds prefer glamour stocks (those with a low book-to-market value ratio). The results of the regression models are shown in Table 3. The dependent variable in the regressions is the natural log of the institutional holdings in the lodging industry. Log of institutional holdings is the log of the percentage of shares owned by the institutional investor divided by the number of total outstanding shares. The regression models were first checked for multicollinearity by examining variance inflation factors (VIF). Since all the VIF’s are lower than 2, multicollinearity is not considered to be a problem. When observations from all types of institutions are included, institutions increase their holdings in large lodging firms with high capital expenditures relative to assets and high total debt (regression model 1 in Table 3). Moreover, institutions prefer lodging firms with high stock prices. Accordingly, institutional holdings have a significantly positive relationship with firm size, capital expenditure-to-assets, debt ratio and price. While studies on other industries indicate a negative relationship between institu-
Table 2 Descriptive statistics for the samplea Variable
N
Mean
Standard deviation
Median
Institutional holdings Log of institutional holdings Size BVA/MVA CAP EXP/AS DR LTDR ROA Price Momentum3,0 Momentum12,3 Turnover Volatility
1981 1932 1875 1875 1791 1888 1888 1882 1981 1648 1484 1575 363
0.307 1.930 4.804 1.165 0.090 0.479 0.423 0.406 17.691 0.034 0.069 0.565 0.016
0.261 1.767 2.172 1.198 0.121 0.794 0.794 19.771 16.287 0.336 0.525 1.078 0.015
0.249 1.338 4.596 1.024 0.055 0.450 0.407 0.022 13.500 0.012 0.020 0.337 0.011
Note: Institutional holdings for a specific stock in the given quarter are determined by the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, institutional holding of the firm becomes zero. Size is the natural log of the market value of a firm’s equity in millions of dollars at the end of the year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year. DR is the ratio of total debt to total assets at the end of the year. Institutional holdings are the ratio of the holdings of all reporting institutions to the outstanding shares for the firm; LTDR is the ratio of long-term debt to total assets at the end of the year. ROA is net income dividend by total assets at the end of the year. Price is price per share at the end of the year; Momentum 3,0 is past 3-month gross return. This is the percentage return earned in the current quarter (i.e. 31 March–30 June return for 30 June 13F filing). Momentum12,3 is the 9-month gross return preceding the quarter of filing (i.e. 30 June–31 March, return for 30 June 13F filing in the following year). Turnover is computed by volume dividend by shares outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability. a Please note that the sample size is different because Spectrum, Compustat and CRSP data have a different number of observations.
8
No. of observations R2 (%) Adjusted R2 (%)
Model 2
Model 3
Model 4
Model 5
Model 6
Model 7
All Institutions
Banks
Insurance
Mutual fund
Brokerage firms
Pension fund
Institutions except pension fund
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
5.12 0.16*** 0.27 2.44*** 0.95*** 0.05 0.01** 0.24 0.06 0.12 7.84
0.00 0.00 0.16 0.00 0.00 0.96 0.04 0.40 0.48 0.14 0.13
4.66 0.154** 0.52** 0.62 0.04 1.70 0.02*** 0.76* 0.05 0.21 7.50
0.00 0.02 0.07 0.52 0.93 0.20 0.00 0.09 0.72 0.11 0.24
6.97 0.27*** 0.74 5.08*** 1.43* 1.26 0.01 0.11 0.03 0.20 9.53
0.00 0.01 0.12 0.00 0.06 0.69 0.46 0.90 0.89 0.28 0.54
3.10 0.08 1.74*** 4.88*** 2.31*** 2.25 0.01 0.24 0.41** 0.10 31.28
0.01 0.41 0.00 0.00 0.00 0.29 0.45 0.76 0.03 0.59 0.05
3.83 0.10 0.71** 4.48*** 0.9* 0.28 0.02** 0.96*** 0.05 0.18 13.7*
0.00 0.13 0.03 0.00 0.10 0.87 0.02 0.01 0.76 0.22 0.10
8.35 0.55*** 1.90*** 2.51* 0.45 0.23 0.01 1.81*** 0.24 0.51*** 6.02
0.00 0.00 0.00 0.08 0.54 0.93 0.32 0.01 0.19 0.01 0.64
4.23 0.07 0.88*** 3.56*** 0.96*** 0.11 0.01*** 0.65** 0.13 0.02 10.46**
0.00 0.11 0.00 0.00 0.00 0.91 0.00 0.03 0.14 0.78 0.05
1209 9.20 8.40
301 26.20 23.60
190 18.30 13.80
191 29.70 25.70
294 27.50 23.10
233 31.50 28.40
976 15.10 14.20
Dependent variable ¼ log of the percentage of institutional holdings.Note: Size is the natural log of the market value of a firm’s equity in millions of dollars at the end of the year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year. DR is the ratio of total debt to total assets. Institutional holdings are the ratio of the holdings of all reporting institutions to the outstanding shares for the firm at the end of the year. ROA is net income dividend by total assets at the end of the year. Price is price per share at the end of the year. Momentum3,0 is the past 3-month gross return. This is the percentage return earned in the current quarter (i.e. 31 March–30 June return for 30 June 13F filing). Momentum12,3 is the 9-month gross return preceding the quarter of filing (i.e. 30 June–31 March, return for 30 June 13F filing in the following year). Turnover is computed by volume dividend by share outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability.*Significant at 10%.**Significant at 5%.***Significant at 1% level.
ARTICLE IN PRESS
Constant Size BVA/MVA CAP EXP/AS DR ROA Price Momentum3,0 Momentum12,3 Turnover Volatility
Model 1
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
Table 3 Institutional holdings by institution type
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
tional holdings and the total debt ratio, the lodging industry shows a positive relationship. On the other hand, institutional holdings have no significant relationship with book-to-market value ratios, ROA, momentum, turnover or volatility. The institutional preference for stock of large firms is consistent with previous studies since institutions expect high liquidity and less information asymmetry (Gompers and Metrick, 2001). While previous research finds institutional preferences for firms with low book-to-market value ratios (Del Guercio, 1996), our study shows institutional investors with all the observations have no preference for lodging firms with low book-to-market value ratios. However, when the regressions are run for specific institutional investors, they show that banks, mutual funds and brokerage firms have a negatively significant sign for book-to-market value ratios. Insurance company holdings indicate an insignificant coefficient with a negative sign for book-to-market value ratios. Upon examination of the regression model that includes all institutions except pension funds, the book-to-market value coefficient has a negative sign (regression model 7 in Table 3). Thus, institutional investors prefer firms with a low book-tomarket value ratio. Additionally, lodging firms with high debt ratios may have less information asymmetry since lenders can act as monitoring agents of the firm. Banks tend to prefer larger lodging firms with low bookto-market value ratios (regression model 2 in Table 3). They prefer firms with high liquidity and high growth opportunities. Since banks are restricted by the prudentman law, they may have a preference for lodging firms with growth opportunities. In addition, banks prefer stocks with high prices and low prior returns. Banks can save on transaction costs by choosing high-price stocks since low price stocks have larger percentage bid-ask spreads. Banks apparently do not make investment decisions based on a momentum strategy. The findings support the notion that they buy past losers and sell past winners. Insurance companies prefer large lodging firms with high capital expenditure-to-asset and high debt ratios (regression model 3 in Table 3). This means that institutional investors prefer lodging companies with high growth opportunities that are financed with debt. Firms with high debt ratios have less information asymmetry. Also previous research supports the notion that lodging firms with growth opportunities tend to be financed with debt (Dalbor and Upneja, 2004). Mutual funds prefer lodging stocks with low book-tomarket value ratios and high capital expenditures-to-sales as well as those with high debt ratios (regression model 4 in Table 3). Once again, this finding supports the idea that institutional investors look for lodging firms with high growth opportunities financed with debt. Additionally, stocks with high returns for the previous 9 months are preferred by mutual funds. Since mutual fund managers are thought to chase highly liquid stocks (Shyam-Sunder and Myers, 1999), our results showing the size variable to
9
be insignificant is inconsistent with previous studies. It could be that growth opportunities are a greater consideration when choosing lodging stocks for these fund managers. Mutual funds tend to use momentum strategies that buy past winners and sell past losers. The regression results indicate that brokerage firms tend to prefer lodging firms with low book-to-market value ratios, high capital expenditures-to-assets, high debt ratios, high price and low past returns (regression model 5 in Table 3). This result implies that they prefer lodging firms with high growth opportunities. Lodging firms with high growth opportunities are likely to be financed by debt (Dalbor and Upneja, 2004). Moreover, brokerage firms prefer high-priced stocks in order to avoid transaction costs due to large bid-ask spreads. Finally, brokerage firms appear to not use a momentum strategy, tending to prefer lodging stocks with lower total risk (volatility). Pension funds prefer larger lodging firms and those with high book-to-market value and low capital expenditure-toasset ratios, high past 3 months returns and high turnover (regression model 6 in Table 3). The debt ratio coefficient is insignificant for pension funds. This implies that these institutions look for lodging firms with high liquidity and are not as concerned about growth opportunities. Since pension funds have a long-term investment horizon rather than a short-term active investment strategy, they may choose value stocks (high book-to-market value ratio). Also since pension funds tend to hold their assets longer than other types of institutions, assets in their portfolio have increased over time and they became value stocks after a certain period. It appears that pension fund managers use a momentum strategy that involves buying past winners and selling past losers. 6. Conclusions and implications for further research The results show that there are some differences in institutional investor preferences for stock of lodging firms and stock of firms in other industries. This research utilizes a number of key accounting and financial indicators found in the empirical literature to assess any potential differences. While institutions prefer lodging industry stocks with high debt ratios, they prefer stocks of companies in other industries with low debt ratios. We believe that this is because of the fixed asset nature of most lodging firms. Unlike other industries, the institutional preference for lodging stocks does not have any significant relationship with turnover or volatility. Moreover, the results of this research indicate that there may be different preferences for the stock of lodging firms based on the type of institutional investor. For example, while banks, insurance companies and pension funds tend to prefer large lodging companies, mutual funds and brokerage firms do not. In terms of the book-to-market value ratio, pension funds tend to choose firms with high ratios, but other institutions (banks, mutual funds and brokerage firms) prefer low ratios. This ratio does not
ARTICLE IN PRESS 10
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
appear to a significant differentiating factor for insurance companies. As previously discussed, lodging firms rely heavily on capital expenditures. The results indicate that pension funds tend to choose lodging firms with low capital expenditure-to-asset ratio, while other institutions (insurance, mutual fund and brokerage firms) choose the opposite. The lodging industry also relies upon debt financing. While debt ratios appear to be important to insurance companies, mutual funds and brokerage firms, they do not appear to be important to banks. This important difference between these institutions could be a potential topic for additional research. As discussed in the literature, some institutions make use of a momentum investment strategy that focuses on past returns. Our results indicate a positive relationship between this momentum strategy and holdings for pension funds, but a negative relationship for banks and brokerage firms. Institutions often use a momentum strategy when they enter and purchase stocks but they use a contrarian strategy at both exit and adjustment (Badrinath and Wahal, 2002). Thus, pension funds with long-term holding periods use a momentum strategy and banks and brokerage firms with shorter holding periods show contrarian strategies during adjustment and selling periods. Turnover is followed by institutional fund managers as an indication of the interest in a particular stock. Our results indicate a positive relationship between institutional holdings and turnover for pension funds. This is because pension funds are under more pressure to make prudent investment choices. The price of the stock may also be an indicator of a successful firm. Our findings indicate that these higherpriced stocks are preferred by banks and brokerage firms. The last variable we examine is volatility of return, and this appears to not be important to most institutions. There is only modest support for the notion of brokerage firms avoiding firms with high total risk (volatility). Further research should be conducted into the preferences of two specific institutions. First, it appears that pension funds prefer lodging stocks with high book-tomarket value ratios. On the other hand, mutual funds and brokerage firms prefer the opposite. This would imply that, unlike other institutions, pension funds may prefer lodging firms with fewer growth opportunities. This could mean that pension funds prefer firms with stable dividend payout policies. While lodging REITs tend to distribute 90% of earnings as dividends, lodging corporations (on average) have a dividend payout ratio of approximately 7%. Examining the institutional holdings in lodging REITs and lodging corporations could provide some insight into the relationship between institutional preferences and dividend payout policies. Another key difference between major institutions is the behavior of pension funds and brokerage firms in terms of the momentum strategy. Our results indicate that these two institutions have opposite preferences when investments in
lodging firms are considered. Further research could provide insight as to this result. References Andrew, W., Schmidgall, R., 1993. Financial Management for the Hospitality Industry. American Hotel & Lodging Association. Badrinath, S., Wahal, S., 2002. Momentum trading by institution. Journal of Finance 57 (6), 2449–2478. Chaganti, R., Damanpour, F., 1991. Institutional ownership, capital structure, and firm performance. Strategic Management Journal 12, 479–491. Ciochetti, B., Craft, T., Shilling, J., 2002. Institutional investor’s preferences for REIT stocks. Real Estate Economics 30, 567–593. Conrad, J., Kaul, G., 1993. Long-term market overaction or biases in computed returns. Journal of Finance 48, 39–64. Corgel, J., DeRoos, J., 1994. Buying high and selling low in the lodgingproperty market. Cornell Hotel and Restaurant Administration Quarterly 35, 33–39. Corgel, J., DeRoos, J., 2003. Buying high and selling low revisited: the quiet industry. Cornell Hotel and Restaurant Administration Quarterly 44, 76–80. Coval, J., Moskowitz, T., 1999. Home bias at home: local equity preference in domestic portfolio. Journal of Finance 54, 2045–2073. Dalbor, M., Upneja, A., 2002. Factors affecting the long-term debt decision of restaurant firms. Journal of Hospitality and Tourism Research 26, 422–434. Dalbor, M., Upneja, A., 2004. The investment opportunity set and the long-term debt decision of U.S. lodging firms. Journal of Hospitality and Tourism Research 28, 346–355. De Bondt, W, Werner, W., Thaler, R., 1985. Does the stock market overreact? Journal of Finance 40, 793–805. Thaler, R., De Bondt, W., 1987. Further evidence of investor overreaction and stock market seasonality. Journal of Finance 42, 557–581. Del Guercio, D., 1996. The distorting effect of the prudent-man laws on institutional equity investments. Journal of Financial Economics 40, 31–62. Eakins, S., Stansell, S., Wertheim, P., 1998. Institutional portfolio composition: an examination of the prudent investment hypothesis. Quarterly Review of Economics and Finance 38, 93–109. Falkenstein, E., 1996. Preference for stock characteristics as revealed by mutual fund portfolio holdings. Journal of Finance 51 (1), 111–135. Fama, E., French, K., 1998. Value versus growth: the international evidence. Journal of Finance 53 (6), 1975–1999. Gaver, J., Gaver, K., 1993. Additional evidence on the association between the investment opportunity set and corporate financing, dividend, and compensation policies. Journal of Accounting and Economics 16, 125–160. Gompers, P., Metrick, A., 2001. Institutional investors and equity price. Quarterly Journal of Economics 116 (1), 229–259. Hovakimian, A., Hovakimian, G., Tehranian, H., 2004. Determinants of target capital structure: the case of dual debt and equity issues. Journal of Financial Economics 71, 517–540. Hu, S., 1997. Trading turnover and expected stock returns: the trading frequency hypothesis and evidence from the Tokyo stock exchange. Working Paper, National Taiwan University and University of Chicago. Jegadeesh, N., Titman, S., 1993. Returns to buying winners and selling losers: implications for stock market efficiency. Journal of Finance 48, 65–92. Kang, J., Stulz, R., 1997. Why is there a home bias? An analysis of foreign portfolio equity ownership in Japan. Journal of Financial Economics 46, 3–28. Kothari, S., Shanken, J., Sloan, R., 1995. Another look at expected stock returns. Journal of Finance 50, 185–224. Lakonishock, J., Shleifer, A., Vishny, R., 1994. Contrarian investment, extrapolation, and risk. Journal of Finance 49, 1541–1578.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11 Leung, W., Lee, T., 2005. Institutional investors and the Monday effect on tourism stocks. International Journal of Hospitality Management 25 (3), 348–372. Myers, S., 2001. Capital structure. Journal of Economic Perspectives 15, 81–102. Rouwenhorst, K., 1999. Local return factors and turnover in emerging markets. Journal of Finance 54, 1439–1464. Schwartz, R., Shapiro, J., 1992. The challenge of institutionalization of the equity market. In: Saunders, A. (Ed.), Recent Developments in Finance. Salomon Center, New York, pp. 31–45.
11
Shyam-Sunder, L., Myers, S., 1999. Testing static tradeoff theory against pecking order models of capital structure. Journal of Financial Economics 51, 219–244. Singh, A., Schmidgall, R., 2000. Financing lodging properties. Cornell Hotel and Restaurant Administration Quarterly 41, 39–47. Smith Jr., C., Watts, R., 1992. The investment opportunity set and corporate financing, dividend, and compensation policies. Journal of Financial Economics 32, 263–292. Tong, S., Ning, Y., 2004. Does capital structure affect institutional investor choices? Journal of Investing 13, 53–66.
International Journal of Hospitality Management 27 (2008) 3–11 www.elsevier.com/locate/ijhosman
Institutional investor preferences for lodging stocks Seonghee Oaka,, Michael C. Dalborb,1 a
Hospitality & Tourism Administration, School of Business, North Carolina Central University, P.O. Box 19716, Durham, NC 27707, USA b William F. Harrah College of Hotel Administration, University of Nevada, 4505 Maryland Parkway, Las Vegas, NV 89154, USA
Abstract Although investments from institutions such as banks, insurance companies and pension funds in the lodging industry increased enormously in the 1990s, there has been no empirical research that has examined institutional preferences for lodging stocks. Understanding institutional investment patterns can help provide easier access to the capital markets for hoteliers who make large capital expenditures. This study identifies the characteristics preferred by institutional investors and also assesses whether the different institutions have heterogeneous preferences. Our results show that, in general, institutions prefer the stock of large lodging firms. They also prefer lodging firms with high capital expenditure-to-asset ratios and high debt ratios. r 2007 Elsevier Ltd. All rights reserved. Keywords: Institutional investment; Lodging stocks
1. Introduction There is some evidence that institutional investor interest in the lodging industry has been increasing (Corgel and DeRoos, 2003; Leung and Lee, 2005; Ciochetti et al., 2002). Although institutional investment patterns regarding lodging properties in the private real estate market have been investigated by some researchers (Corgel and DeRoos, 1994, 2003; Singh and Schmidgall, 2000), there has been no research regarding institutional investment preferences for the stock of lodging firms. The purpose of this research is to examine factors that may influence the behavior of the institutional investor that holds the stock of lodging firms. Moreover, we also assess any potential differences in these preferences across different institutions. One of the important reason of this research is as institutional investors are firms that help bring together suppliers and users of funds in the marketplace (Andrew and Schmidgall, 1993). They are fiduciaries who make investments on behalf of others (Tong and Ning, 2004). Corresponding author. Tel.: +1 919 530 6239; fax: +1 919 530 7865.
E-mail addresses: [email protected] (S. Oak), [email protected] (M.C. Dalbor). 1 Tel.: +1 702 895 3848; fax: +1 702 895 4870. 0278-4319/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2007.06.003
Examples of institutional investors include banks, insurance companies and pension funds. Their role in raising financial capital is critical to growth in the lodging industry. Institutional investors are different from individuals because they are generally better informed. They have greater access to company information and are in a position to monitor the performance of corporate managers more effectively. Since this study is the first to examine institutional holding preferences for the stock of lodging firms, we will assess the potential relationship between institutional holding preferences and financial or accounting characteristics of lodging firms targeted for potential investment. We believe the lodging industry may warrant special attention in this area because of the unique nature of the industry. A hotel represents not only a parcel of real estate but also an operating business. Moreover, hotels usually require investments in capital expenditures on a regular basis. This is because most hotel companies are fixed asset intensive, meaning that most of their assets are tied up in items such as building and equipment. These assets will wear out over time and need to be replaced. Additionally, the lodging industry is highly leveraged from both the use of debt and the high amount of fixed costs. These two
ARTICLE IN PRESS 4
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
factors help increase the risk associated with hotel investments. Furthermore, these conditions may result in different institutional preferences for the lodging industry as compared with other industries. Finally, we believe that studying the hotel industry as a subsample may yield some interesting results. This is analogous to the belief of Myers (2001) in regards to capital structure. Testing theories on broad heterogeneous samples can sometimes be uninformative. Therefore, an investigation of smaller samples or specific industries can be warranted. 2. Literature review Institutional holdings have increased in both the general equity market and the hospitality sector in recent years (Leung and Lee, 2005). In the hospitality sector, institutional holdings (as measured by the percentage of total shares outstanding held by all institutions) in the 1990–1999 period (26.1%) are significantly higher than that in the 1981–1989 period (16.1%). Compared to other hospitality sectors, the hotel industry has the highest increase in institutional holdings (increasing from 16.7% during the 1981–1989 period to 30.4% in the 1990–1999 period). Since institutional investors have increased their funding of the lodging industry, it is important to know their preferences. Institutional holdings have increased in the Real Estate Investment Trust (REIT) industry. Institutions have increased their investment in hotel REITs from 0% in 1993 to 2.6% of total REIT market capitalization in 1998 (Ciochetti et al., 2002). For hotel REITs, pension funds, banks and trust companies have about 0.6% higher ownership than mutual funds and insurance companies. This change is due to poor performance in other property sectors during the mid- to late 1990s (Ciochetti et al., 2002). Thus, the lodging sector can serve as a substitute for other sectors that may perform differently. The liquidity needs of institutional investors may be the motivation for their aggressive bidding for lodging REITs in the 1990s (Corgel and DeRoos, 2003). Despite great interest by institutions, there are only a few studies that have investigated institutional investment behavior in the lodging industry (Corgel and DeRoos, 1994, 2003; Leung and Lee, 2005). This study will focus on what drives institutional investors to choose lodging stocks. Since institutions act as agents for other investors, their investment patterns may be different from individual investors. The prudent-man law limits the freedom of an institution’s risk-taking behavior and is intended to protect beneficiaries by allowing them to seek damages from a fiduciary who fails to act in their best interest. In the case of litigation, the courts accept a prudent investment based on the characteristics of assets in isolation, but ignore the role these assets play in a portfolio (Del Guercio, 1996). The prudent-man law may affect the stock preferences of institutional investors in differing degrees. Because of these
varying restrictions, institutions are divided into five major groups: banks, insurance firms, mutual funds, brokerage firms, and pension funds. According to Gompers and Metrick (2001), ‘‘banks are the only institutions governed by the common-law prudent-man rule, which is interpreted more strictly than the written regulations governing the investment behavior of other institutions. However, empirical studies imply that many non-bank institutions also consider prudence characteristics’’.2 For example, Del Guercio (1996) shows that while banks tend to prefer the stock of prudent firms (large firms with low book-tomarket ratios), mutual funds do not. Institutions have their own particular reasons for selecting the companies in which they wish to invest. According to previous research, institutional investors prefer to hold stock in large companies with high liquidity (Gompers and Metrick, 2001). Since large firms distribute more information to the financial community and more financial analysts follow those firms, there will be less information asymmetry associated with the large firms. Falkenstein (1996) finds that except for the small-cap sector which specializes in small firms, mutual funds are averse to small firms. Thus, in terms of lodging stocks and the stock of companies in other industries, institutions should prefer larger firms because of their high liquidity. Investment managers often divide firms into value and glamour stocks (Fama and French, 1998). Value stocks with high book-to-market, earnings to price and cash flow to price ratios tend to have consistently low earnings. On the other hand, glamour stocks with low book-to-market, earnings to price and cash flow to price ratios tend to be growth firms with high earnings. Institutions also prefer glamour stocks because they may be shown to be prudent investments (Lakonishock et al., 1994). Glamour stocks have had good performance in the past and are unlikely to be distressed in the near future. After adjusting for a mutual fund’s investment style, managers of glamour stock funds perform better on average than one of value funds (Chan et al., 2002). Thus, prudent investment rules should dictate that institutions prefer low book-to-market value stocks of all industries, including the lodging industry. All investors are interested in sales and earnings growth. However, growth opportunities will vary among industries. These opportunities include not only research and development expenditures, but also capacity expansion and acquisitions. In terms of measuring growth opportunities, the literature utilizes ratios such as market value to book value to reflect the market’s expectation of firm growth. Gaver and Gaver (1993) utilize a number of measures for growth opportunities such as the ratio of market value of the firm to book value of assets, market value of equity to book value of equity, and the ratio of earnings to price. A low market value to book value of assets ratio indicates the presence of more assets-in-place, and thus, lowers invest2 Gompers and Metrick (2001, p. 239) analyzed institutional investor’s preference for stock characteristics.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
ment options for growth. Currently, there is no consensus on the best proxy to measure growth opportunities of the firm. Furthermore, as discussed by Smith and Watts (1992) firms make specialized investments in physical and human capital, thus creating variations in the investment opportunity set for different firms. Growth opportunities in the lodging industry may be different from other industries (i.e. pharmaceutical or high technology firms) with high research and development expenditures. For lodging firms, growth opportunities are represented by capital expenditures or acquisitions. Research in the lodging industry indicates that institutions are willing to invest in luxury and upscale hotels which require significant capital expenditures (Singh and Schmidgall, 2000). Institutions prefer firms with a high capital expenditure to asset ratio since capital expenditures can signal the good performance of public firms (Tong and Ning, 2004). In both lodging and other industries, institutions should prefer firms with high capital expenditure to asset ratios. Because of the effect of debt payments on cash flows, firms with significant growth opportunities (i.e. potential future investments in projects that will dramatically increase revenues and cash flows) will shy away from the use of debt. Hovakimian et al. (2004) provide empirical evidence that there is a negative relationship between debt ratios and growth opportunities. The negative relationship between long-term debt and growth opportunities was confirmed in the restaurant industry (Dalbor and Upneja, 2002). The presence of debt in a firm’s capital structure may influence the institutional investor. Furthermore, the presence of institutional ownership of equity may substitute as a monitoring agent for debt. Tong and Ning (2004) suggest that institutions are worried that too much debt may signal trouble to these investors. They find that institutions prefer firms with short-term debt (as opposed to long term). Thus, institutional investors in other industries prefer firms with low debt ratios. Firms with high institutional ownership have lower longterm debt to capital ratios than those with low institutional ownership (Chaganti and Damanpour, 1991). However, it is possible that institutions may prefer the stock of lodging firms with high long-term debt ratios because of the fixed asset nature of the lodging industry. Furthermore, firms with more tangible assets use higher debt (Myers, 2001). US lodging firms have, on average, 41% of their assets backed by long-term debt alone and have a positive relationship between long-term debt and growth opportunities (Dalbor and Upneja, 2004). Thus, in the lodging industry, institutions should prefer firms with high debt ratio. Since lodging firms have both business and real estate components, it is important to have high return of assets (ROA) for operating and managerial efficiency. However, empirical studies on institutional preference regarding ROA are mixed. Kang and Stulz (1997) find that non-
5
Japanese investors in Japanese firms prefer firms with a high ROA. However, the ROA ratio is marginally important for a U.S. investment manager’s domestic stock choices due to local bias (Coval and Moskowitz, 1999). Thus, it is an empirical question whether or not institutional managers prefer high ROA firms. If institutional investors need to trade frequently, they may be sensitive to transaction costs due to larger bid-ask spread percentages for low-priced stocks (Schwartz and Shapiro, 1992). There is a strong correlation between low prices and large bid-ask spreads (Conrad and Kaul, 1993; Kothari et al., 1995). A study by Falkenstein (1996) indicates an institutional aversion for stocks with low prices. Thus, the previous literature indicates support for the notion that in both lodging and other industries, institutional investors should prefer high priced stocks. A ‘‘momentum’’ trading strategy that buys stocks with good returns in previous years and sells stocks with poor prior returns generates significant positive returns over a 3–12-month holding period (Jegadeesh and Titman, 1993). Another trading strategy is a contrarian strategy (buying past losers and selling past winners) which yields higher abnormal returns than merely holding past winning stocks in the same period (De Bondt et al., 1985; Thaler and De Bondt, 1987). Gompers and Metrick (2001) find evidence that is the opposite from the momentum strategy and tends to support the contrarian strategy. They find that large institutions choose stocks with low returns during the previous year. Thus, there is uncertainty regarding the institutional preference for lodging stocks based on past returns. The frequency of stock purchases and subsequent sales is referred to as stock turnover. It also appears to be an important consideration to institutional investors. Institutions prefer firms with high turnover because this means that other investors find the stock attractive, indicating that it is a prudent investment. Previous studies find a positive relationship between institutional ownership and turnover ratio (Eakins et al., 1998). Research indicates that a portfolio with a high turnover rate has higher returns than a portfolio with low turnover (Rouwenhorst, 1999). Hu (1997) proposes that a high turnover of stock reduces transaction costs and thus lowers the total cost of investing. Thus, in both lodging and other industries, institutional investors should prefer stocks with high turnover. While returns are obviously important to investors, the risk, or volatility of returns is important as well. Del Guercio (1996) finds a negative relationship between total risk of a stock and institutional ownership. He posits that fiduciaries may be charged for a loss on a single security and thus this is a motivation to invest less money in risky stocks. In addition to Del Guercio, Falkenstein (1996) shows that mutual fund holdings are negatively related to variance of monthly return during 24–60 months. Thus, in both lodging and other industries, institutional ownership should be negatively related to stock volatility.
ARTICLE IN PRESS 6
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
In summary, the literature indicates a number of potential motivating factors for institutional investor interest in stocks. Institutions tend to prefer large firms that offer a high degree of liquidity as well as growth firms or ‘‘glamour’’ stocks with high earnings. Since growth in the lodging industry typically involves fixed asset investment, investors may prefer companies that make significant capital expenditures. Moreover, given that many capital expenditures in the lodging industry are financed with debt, it may be that investors in hotel stocks prefer firms with high debt ratios. This is contrary to the literature in that some investors worry that too much debt will be problematic for the firm. In terms of performance and price, the literature indicates that investors prefer firms with high ROA ratios because this ratio is an indication of management efficiency (Kang and Stulz, 1997). Previous research indicates that institutions have an aversion to low-priced stocks and tend to own higher-priced issues (Schwartz and Shapiro, 1992). While prices of issues are important to investors, the returns in previous years also are a consideration. The literature indicates that some institutions prefer firms with high returns in previous years, while there is also evidence of a ‘‘contrarian’’ strategy where investors are interested in purchasing the stock of a firm with poor performance in previous years (Jegadeesh and Titman, 1993; De Bondt et al., 1985; Thaler and De Bondt, 1987). One measure of the interest in a stock is measured by turnover. High turnover stocks are popular, and the literature indicates that institutional investors are interested in these popular stocks (Eakins et al., 1998; Hu, 1997). Risky stocks, however, do not show particular favor with institutional investors, particularly mutual funds (Del Guercio, 1996). Previous research measures this risk (volatility) as the variance of monthly returns (Falkenstein, 1996).
Table 1 Variables used in the hypothesis tests and expected signs Independent variables
Dependent variable (log of institutional holdings) Predicted sign
Size BVA/MVA CAP EXP/AS DR ROAa Price Momentuma Turnover Volatility
Hotel industry
Other industries
+ + + ? + ? +
+ + ? + ? +
Note: The dependent variable is calculated as the log of the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, institutional holding of the firm becomes zero. Size is the natural log of market value of a firm’s equity in millions of dollars at the end of year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year; DR is the ratio of total debt to total assets at the end of the year. ROA is net income divided by total assets at the end of the year. Price is price per share (closing price at the end of the year). Momentum is previous period’s net returns. Turnover is computed by volume dividend by share outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for a 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability. a Institutional investor preference is indeterminate.
uncertain what the signs will be for these variables for this study. Other variables are expected to have the same sign for both lodging and other industries.
3. Models and expected signs of the coefficients
4. Data and methodology
Based upon our review of the literature, we will assess whether there is difference in investment determinants of institutional investors between the lodging industry and other industries. The following model is the full model for the regression analysis: Institutional holdings ¼ intercept+b1size+b2book-tomarket ratio+b3capital expenditure to assets+b4debt ratio+b5ROA+b6Price+b7momentum+b8turnover+b9volatility+error term of the regression. The variables for investment determinants and the expected relationships with the dependent variable are shown in Table 1. The signs of the coefficients for the variables for other industries were derived from the literature. When institutional holdings of lodging industry are compared with holdings in other industries, only bookto-market values are expected to show a different sign. Since the momentum strategy and ROA variable have proven to be indeterminate in previous studies, it is
Data for institutional holdings are from the Thompson Financial Spectrum database. SEC regulations state that all institutions with over $100 million in discretionary funds under management and all positions in individual stocks greater than $200,000 or 10,000 shares need to file form 13(f) within 45 days after the last day of each quarter. These forms are available in electronic form dating back to 1980 in the CDA/Spectrum 13(f) Institutional Stock Holdings (Spectrum). Quarterly institutional ownership in Spectrum is categorized into five groups: banks, insurance companies, mutual funds, brokerage firms and pension fund. We compile a lodging sample by using either firm CUSIP numbers or stock symbols for the years 1981–2003. We restrict our study to the common stock of lodging firms found in the annual Compustat files in order to match firm characteristics. Data from the Compustat and Spectrum databases are subsequently merged using the respective stock symbols or CUSIP numbers.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
We use pooled regression models to test the expected relationships found in Table 1. The dependent variable is the natural log of institutional holdings. The log of institutional holdings for a specific stock in the given quarter represents the log of the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, the institutional holding for that firm is determined by zero. The independent variables for this study are the firm’s characteristics: size (log of market value of equity in millions), book-to-market value, the ratio of capital expenditure-to-assets, total debt ratio, ROA, price, momentum, turnover and volatility. Since the dependent variable uses institutional holdings at the end of the quarter, the independent variables are size, book-to-market value, the ratio of capital expenditure-toassets, total debt ratio, ROA and price at the end of year. Momentum, turnover and volatility use previous periods. A full description of the variables can be found in Table 2. Regression models are selected based on the stepwise regression method. 5. Results Table 2 shows the descriptive statistics for the variables. The mean of institutional holdings in lodging firms is 30.7%. This means that nearly a third of lodging company stock is held by institutional investors. The total debt ratio
7
and long-term debt ratio are not significantly different in terms of mean and standard deviation. Accordingly, to help alleviate any problems with multicollinearity the total debt ratio was used in the regression models. The mean of the book-to-market value ratio is 1.17, which is greater than 1. This may be due to the notion that pension funds tend to hold high book-to-market stocks. Regression model 7 in Table 3 shows all other institutions prefer stocks with low book-to-market values. Thus, institutional investors except pension funds prefer glamour stocks (those with a low book-to-market value ratio). The results of the regression models are shown in Table 3. The dependent variable in the regressions is the natural log of the institutional holdings in the lodging industry. Log of institutional holdings is the log of the percentage of shares owned by the institutional investor divided by the number of total outstanding shares. The regression models were first checked for multicollinearity by examining variance inflation factors (VIF). Since all the VIF’s are lower than 2, multicollinearity is not considered to be a problem. When observations from all types of institutions are included, institutions increase their holdings in large lodging firms with high capital expenditures relative to assets and high total debt (regression model 1 in Table 3). Moreover, institutions prefer lodging firms with high stock prices. Accordingly, institutional holdings have a significantly positive relationship with firm size, capital expenditure-to-assets, debt ratio and price. While studies on other industries indicate a negative relationship between institu-
Table 2 Descriptive statistics for the samplea Variable
N
Mean
Standard deviation
Median
Institutional holdings Log of institutional holdings Size BVA/MVA CAP EXP/AS DR LTDR ROA Price Momentum3,0 Momentum12,3 Turnover Volatility
1981 1932 1875 1875 1791 1888 1888 1882 1981 1648 1484 1575 363
0.307 1.930 4.804 1.165 0.090 0.479 0.423 0.406 17.691 0.034 0.069 0.565 0.016
0.261 1.767 2.172 1.198 0.121 0.794 0.794 19.771 16.287 0.336 0.525 1.078 0.015
0.249 1.338 4.596 1.024 0.055 0.450 0.407 0.022 13.500 0.012 0.020 0.337 0.011
Note: Institutional holdings for a specific stock in the given quarter are determined by the percentage of institutional ownership (the share holdings of all reporting institutions divided by the total shares outstanding for the firm). If a lodging firm in the Compustat database is not held by any institution, institutional holding of the firm becomes zero. Size is the natural log of the market value of a firm’s equity in millions of dollars at the end of the year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year. DR is the ratio of total debt to total assets at the end of the year. Institutional holdings are the ratio of the holdings of all reporting institutions to the outstanding shares for the firm; LTDR is the ratio of long-term debt to total assets at the end of the year. ROA is net income dividend by total assets at the end of the year. Price is price per share at the end of the year; Momentum 3,0 is past 3-month gross return. This is the percentage return earned in the current quarter (i.e. 31 March–30 June return for 30 June 13F filing). Momentum12,3 is the 9-month gross return preceding the quarter of filing (i.e. 30 June–31 March, return for 30 June 13F filing in the following year). Turnover is computed by volume dividend by shares outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability. a Please note that the sample size is different because Spectrum, Compustat and CRSP data have a different number of observations.
8
No. of observations R2 (%) Adjusted R2 (%)
Model 2
Model 3
Model 4
Model 5
Model 6
Model 7
All Institutions
Banks
Insurance
Mutual fund
Brokerage firms
Pension fund
Institutions except pension fund
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
5.12 0.16*** 0.27 2.44*** 0.95*** 0.05 0.01** 0.24 0.06 0.12 7.84
0.00 0.00 0.16 0.00 0.00 0.96 0.04 0.40 0.48 0.14 0.13
4.66 0.154** 0.52** 0.62 0.04 1.70 0.02*** 0.76* 0.05 0.21 7.50
0.00 0.02 0.07 0.52 0.93 0.20 0.00 0.09 0.72 0.11 0.24
6.97 0.27*** 0.74 5.08*** 1.43* 1.26 0.01 0.11 0.03 0.20 9.53
0.00 0.01 0.12 0.00 0.06 0.69 0.46 0.90 0.89 0.28 0.54
3.10 0.08 1.74*** 4.88*** 2.31*** 2.25 0.01 0.24 0.41** 0.10 31.28
0.01 0.41 0.00 0.00 0.00 0.29 0.45 0.76 0.03 0.59 0.05
3.83 0.10 0.71** 4.48*** 0.9* 0.28 0.02** 0.96*** 0.05 0.18 13.7*
0.00 0.13 0.03 0.00 0.10 0.87 0.02 0.01 0.76 0.22 0.10
8.35 0.55*** 1.90*** 2.51* 0.45 0.23 0.01 1.81*** 0.24 0.51*** 6.02
0.00 0.00 0.00 0.08 0.54 0.93 0.32 0.01 0.19 0.01 0.64
4.23 0.07 0.88*** 3.56*** 0.96*** 0.11 0.01*** 0.65** 0.13 0.02 10.46**
0.00 0.11 0.00 0.00 0.00 0.91 0.00 0.03 0.14 0.78 0.05
1209 9.20 8.40
301 26.20 23.60
190 18.30 13.80
191 29.70 25.70
294 27.50 23.10
233 31.50 28.40
976 15.10 14.20
Dependent variable ¼ log of the percentage of institutional holdings.Note: Size is the natural log of the market value of a firm’s equity in millions of dollars at the end of the year. BVA/MVA is the ratio of book value of assets to market value of assets at the end of the year. CAP EXP/AS is the ratio of capital expenditures to total assets at the end of the year. DR is the ratio of total debt to total assets. Institutional holdings are the ratio of the holdings of all reporting institutions to the outstanding shares for the firm at the end of the year. ROA is net income dividend by total assets at the end of the year. Price is price per share at the end of the year. Momentum3,0 is the past 3-month gross return. This is the percentage return earned in the current quarter (i.e. 31 March–30 June return for 30 June 13F filing). Momentum12,3 is the 9-month gross return preceding the quarter of filing (i.e. 30 June–31 March, return for 30 June 13F filing in the following year). Turnover is computed by volume dividend by share outstanding measured for the month prior to the beginning of the quarter (for example, March turnover for 30 June 13F filing). Volatility is the variance of monthly returns over the previous 24–60 months depending on availability.*Significant at 10%.**Significant at 5%.***Significant at 1% level.
ARTICLE IN PRESS
Constant Size BVA/MVA CAP EXP/AS DR ROA Price Momentum3,0 Momentum12,3 Turnover Volatility
Model 1
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
Table 3 Institutional holdings by institution type
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
tional holdings and the total debt ratio, the lodging industry shows a positive relationship. On the other hand, institutional holdings have no significant relationship with book-to-market value ratios, ROA, momentum, turnover or volatility. The institutional preference for stock of large firms is consistent with previous studies since institutions expect high liquidity and less information asymmetry (Gompers and Metrick, 2001). While previous research finds institutional preferences for firms with low book-to-market value ratios (Del Guercio, 1996), our study shows institutional investors with all the observations have no preference for lodging firms with low book-to-market value ratios. However, when the regressions are run for specific institutional investors, they show that banks, mutual funds and brokerage firms have a negatively significant sign for book-to-market value ratios. Insurance company holdings indicate an insignificant coefficient with a negative sign for book-to-market value ratios. Upon examination of the regression model that includes all institutions except pension funds, the book-to-market value coefficient has a negative sign (regression model 7 in Table 3). Thus, institutional investors prefer firms with a low book-tomarket value ratio. Additionally, lodging firms with high debt ratios may have less information asymmetry since lenders can act as monitoring agents of the firm. Banks tend to prefer larger lodging firms with low bookto-market value ratios (regression model 2 in Table 3). They prefer firms with high liquidity and high growth opportunities. Since banks are restricted by the prudentman law, they may have a preference for lodging firms with growth opportunities. In addition, banks prefer stocks with high prices and low prior returns. Banks can save on transaction costs by choosing high-price stocks since low price stocks have larger percentage bid-ask spreads. Banks apparently do not make investment decisions based on a momentum strategy. The findings support the notion that they buy past losers and sell past winners. Insurance companies prefer large lodging firms with high capital expenditure-to-asset and high debt ratios (regression model 3 in Table 3). This means that institutional investors prefer lodging companies with high growth opportunities that are financed with debt. Firms with high debt ratios have less information asymmetry. Also previous research supports the notion that lodging firms with growth opportunities tend to be financed with debt (Dalbor and Upneja, 2004). Mutual funds prefer lodging stocks with low book-tomarket value ratios and high capital expenditures-to-sales as well as those with high debt ratios (regression model 4 in Table 3). Once again, this finding supports the idea that institutional investors look for lodging firms with high growth opportunities financed with debt. Additionally, stocks with high returns for the previous 9 months are preferred by mutual funds. Since mutual fund managers are thought to chase highly liquid stocks (Shyam-Sunder and Myers, 1999), our results showing the size variable to
9
be insignificant is inconsistent with previous studies. It could be that growth opportunities are a greater consideration when choosing lodging stocks for these fund managers. Mutual funds tend to use momentum strategies that buy past winners and sell past losers. The regression results indicate that brokerage firms tend to prefer lodging firms with low book-to-market value ratios, high capital expenditures-to-assets, high debt ratios, high price and low past returns (regression model 5 in Table 3). This result implies that they prefer lodging firms with high growth opportunities. Lodging firms with high growth opportunities are likely to be financed by debt (Dalbor and Upneja, 2004). Moreover, brokerage firms prefer high-priced stocks in order to avoid transaction costs due to large bid-ask spreads. Finally, brokerage firms appear to not use a momentum strategy, tending to prefer lodging stocks with lower total risk (volatility). Pension funds prefer larger lodging firms and those with high book-to-market value and low capital expenditure-toasset ratios, high past 3 months returns and high turnover (regression model 6 in Table 3). The debt ratio coefficient is insignificant for pension funds. This implies that these institutions look for lodging firms with high liquidity and are not as concerned about growth opportunities. Since pension funds have a long-term investment horizon rather than a short-term active investment strategy, they may choose value stocks (high book-to-market value ratio). Also since pension funds tend to hold their assets longer than other types of institutions, assets in their portfolio have increased over time and they became value stocks after a certain period. It appears that pension fund managers use a momentum strategy that involves buying past winners and selling past losers. 6. Conclusions and implications for further research The results show that there are some differences in institutional investor preferences for stock of lodging firms and stock of firms in other industries. This research utilizes a number of key accounting and financial indicators found in the empirical literature to assess any potential differences. While institutions prefer lodging industry stocks with high debt ratios, they prefer stocks of companies in other industries with low debt ratios. We believe that this is because of the fixed asset nature of most lodging firms. Unlike other industries, the institutional preference for lodging stocks does not have any significant relationship with turnover or volatility. Moreover, the results of this research indicate that there may be different preferences for the stock of lodging firms based on the type of institutional investor. For example, while banks, insurance companies and pension funds tend to prefer large lodging companies, mutual funds and brokerage firms do not. In terms of the book-to-market value ratio, pension funds tend to choose firms with high ratios, but other institutions (banks, mutual funds and brokerage firms) prefer low ratios. This ratio does not
ARTICLE IN PRESS 10
S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11
appear to a significant differentiating factor for insurance companies. As previously discussed, lodging firms rely heavily on capital expenditures. The results indicate that pension funds tend to choose lodging firms with low capital expenditure-to-asset ratio, while other institutions (insurance, mutual fund and brokerage firms) choose the opposite. The lodging industry also relies upon debt financing. While debt ratios appear to be important to insurance companies, mutual funds and brokerage firms, they do not appear to be important to banks. This important difference between these institutions could be a potential topic for additional research. As discussed in the literature, some institutions make use of a momentum investment strategy that focuses on past returns. Our results indicate a positive relationship between this momentum strategy and holdings for pension funds, but a negative relationship for banks and brokerage firms. Institutions often use a momentum strategy when they enter and purchase stocks but they use a contrarian strategy at both exit and adjustment (Badrinath and Wahal, 2002). Thus, pension funds with long-term holding periods use a momentum strategy and banks and brokerage firms with shorter holding periods show contrarian strategies during adjustment and selling periods. Turnover is followed by institutional fund managers as an indication of the interest in a particular stock. Our results indicate a positive relationship between institutional holdings and turnover for pension funds. This is because pension funds are under more pressure to make prudent investment choices. The price of the stock may also be an indicator of a successful firm. Our findings indicate that these higherpriced stocks are preferred by banks and brokerage firms. The last variable we examine is volatility of return, and this appears to not be important to most institutions. There is only modest support for the notion of brokerage firms avoiding firms with high total risk (volatility). Further research should be conducted into the preferences of two specific institutions. First, it appears that pension funds prefer lodging stocks with high book-tomarket value ratios. On the other hand, mutual funds and brokerage firms prefer the opposite. This would imply that, unlike other institutions, pension funds may prefer lodging firms with fewer growth opportunities. This could mean that pension funds prefer firms with stable dividend payout policies. While lodging REITs tend to distribute 90% of earnings as dividends, lodging corporations (on average) have a dividend payout ratio of approximately 7%. Examining the institutional holdings in lodging REITs and lodging corporations could provide some insight into the relationship between institutional preferences and dividend payout policies. Another key difference between major institutions is the behavior of pension funds and brokerage firms in terms of the momentum strategy. Our results indicate that these two institutions have opposite preferences when investments in
lodging firms are considered. Further research could provide insight as to this result. References Andrew, W., Schmidgall, R., 1993. Financial Management for the Hospitality Industry. American Hotel & Lodging Association. Badrinath, S., Wahal, S., 2002. Momentum trading by institution. Journal of Finance 57 (6), 2449–2478. Chaganti, R., Damanpour, F., 1991. Institutional ownership, capital structure, and firm performance. Strategic Management Journal 12, 479–491. Ciochetti, B., Craft, T., Shilling, J., 2002. Institutional investor’s preferences for REIT stocks. Real Estate Economics 30, 567–593. Conrad, J., Kaul, G., 1993. Long-term market overaction or biases in computed returns. Journal of Finance 48, 39–64. Corgel, J., DeRoos, J., 1994. Buying high and selling low in the lodgingproperty market. Cornell Hotel and Restaurant Administration Quarterly 35, 33–39. Corgel, J., DeRoos, J., 2003. Buying high and selling low revisited: the quiet industry. Cornell Hotel and Restaurant Administration Quarterly 44, 76–80. Coval, J., Moskowitz, T., 1999. Home bias at home: local equity preference in domestic portfolio. Journal of Finance 54, 2045–2073. Dalbor, M., Upneja, A., 2002. Factors affecting the long-term debt decision of restaurant firms. Journal of Hospitality and Tourism Research 26, 422–434. Dalbor, M., Upneja, A., 2004. The investment opportunity set and the long-term debt decision of U.S. lodging firms. Journal of Hospitality and Tourism Research 28, 346–355. De Bondt, W, Werner, W., Thaler, R., 1985. Does the stock market overreact? Journal of Finance 40, 793–805. Thaler, R., De Bondt, W., 1987. Further evidence of investor overreaction and stock market seasonality. Journal of Finance 42, 557–581. Del Guercio, D., 1996. The distorting effect of the prudent-man laws on institutional equity investments. Journal of Financial Economics 40, 31–62. Eakins, S., Stansell, S., Wertheim, P., 1998. Institutional portfolio composition: an examination of the prudent investment hypothesis. Quarterly Review of Economics and Finance 38, 93–109. Falkenstein, E., 1996. Preference for stock characteristics as revealed by mutual fund portfolio holdings. Journal of Finance 51 (1), 111–135. Fama, E., French, K., 1998. Value versus growth: the international evidence. Journal of Finance 53 (6), 1975–1999. Gaver, J., Gaver, K., 1993. Additional evidence on the association between the investment opportunity set and corporate financing, dividend, and compensation policies. Journal of Accounting and Economics 16, 125–160. Gompers, P., Metrick, A., 2001. Institutional investors and equity price. Quarterly Journal of Economics 116 (1), 229–259. Hovakimian, A., Hovakimian, G., Tehranian, H., 2004. Determinants of target capital structure: the case of dual debt and equity issues. Journal of Financial Economics 71, 517–540. Hu, S., 1997. Trading turnover and expected stock returns: the trading frequency hypothesis and evidence from the Tokyo stock exchange. Working Paper, National Taiwan University and University of Chicago. Jegadeesh, N., Titman, S., 1993. Returns to buying winners and selling losers: implications for stock market efficiency. Journal of Finance 48, 65–92. Kang, J., Stulz, R., 1997. Why is there a home bias? An analysis of foreign portfolio equity ownership in Japan. Journal of Financial Economics 46, 3–28. Kothari, S., Shanken, J., Sloan, R., 1995. Another look at expected stock returns. Journal of Finance 50, 185–224. Lakonishock, J., Shleifer, A., Vishny, R., 1994. Contrarian investment, extrapolation, and risk. Journal of Finance 49, 1541–1578.
ARTICLE IN PRESS S. Oak, M.C. Dalbor / International Journal of Hospitality Management 27 (2008) 3–11 Leung, W., Lee, T., 2005. Institutional investors and the Monday effect on tourism stocks. International Journal of Hospitality Management 25 (3), 348–372. Myers, S., 2001. Capital structure. Journal of Economic Perspectives 15, 81–102. Rouwenhorst, K., 1999. Local return factors and turnover in emerging markets. Journal of Finance 54, 1439–1464. Schwartz, R., Shapiro, J., 1992. The challenge of institutionalization of the equity market. In: Saunders, A. (Ed.), Recent Developments in Finance. Salomon Center, New York, pp. 31–45.
11
Shyam-Sunder, L., Myers, S., 1999. Testing static tradeoff theory against pecking order models of capital structure. Journal of Financial Economics 51, 219–244. Singh, A., Schmidgall, R., 2000. Financing lodging properties. Cornell Hotel and Restaurant Administration Quarterly 41, 39–47. Smith Jr., C., Watts, R., 1992. The investment opportunity set and corporate financing, dividend, and compensation policies. Journal of Financial Economics 32, 263–292. Tong, S., Ning, Y., 2004. Does capital structure affect institutional investor choices? Journal of Investing 13, 53–66.