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Hotel stock performance and monetary conditions
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Hospitality Management 26 (2007) 588–602 www.elsevier.com/locate/ijhosman
Hotel stock performance and monetary conditions Ming-Hsiang Chen Department of Finance, National Chung Cheng University, Chia-Yi, Taiwan, ROC
Abstract Following the investigation of the link between hotel stock returns and macroeconomic factors in the hospitality finance literature, this study further examines (1) the performance of Taiwanese hotel stocks under two various monetary policy environments, namely expansive and restrictive, and (2) the impact of different monetary stringency on the relationship between hotel stock returns and macro variables in Taiwan. Using changes in the discount rate allows us to effectively measure the monetary policy changes and classify the monetary environment as either restrictive or expansive. Empirical results show that hotel stocks exhibited a higher mean return and reward-to-risk ratio during expansive monetary periods. Moreover, the connection between hotel stock returns and macro variables behaved differently under various monetary conditions. In response to monetary policy developments, the implication for hotel stock investors to reallocate their investment portfolios is provided. r 2006 Elsevier Ltd. All rights reserved. Keywords: Hotel; Stock returns; Monetary conditions; Discount rate; Taiwan
1. Introduction The association between stock returns and macroeconomic (macro hereafter) variables has been well studied in the fields of economics and finance (Chen et al., 1986; Campbell, 1987; Fama and French, 1988; Asprem, 1989; Wasserfallen, 1989; Bulmash and Trivoli, 1991; Booth and Booth, 1997; Nasseh and Strauss, 2000; Chen, 2003). In comparison, within the hospitality literature, there are only a few research papers examining the link between macro factors and hospitality stock returns (Barrows and Naka, 1994; Chen et al., 2005; Chen, 2006a, b; Chen and Kim, 2006). Tel.: +886 5 2720411; fax: +886 5 2720818.
E-mail address: fi[email protected]. 0278-4319/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2006.05.003
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Barrows and Naka (1994) tested whether five selected economic variables, namely growth rates of industrial production, money supply, domestic consumption, expected inflation rate and term structure of the interest rate could influence US hospitality stock returns. They found that, among five economic variables, growth rates of money supply and domestic consumption had a significantly positive impact on the hospitality stock returns, whereas the expected inflation rate affected the hospitality stock returns negatively. Interactions between business conditions and financial performance of tourism firms in both China and Taiwan were examined in Chen (2006a). Chen (2006a) investigated whether the improvement of business conditions (proxied by gross domestic product and industrial production) enhances stock performance of tourism firms and whether financial success of tourism firms matters to business development. Empirical results showed that a long-run equilibrium relationship existed between business conditions and financial performance of tourism firms, and further these two factors reinforced each other in both China and Taiwan. Following Barrows and Naka (1994), Chen et al. (2005) and Chen (2006b) tested a set of macro variables as determinants of hotel stock returns in Taiwan and China, respectively. Chen et al. (2005) detected that money supply growth rates and changes in unemployment rates are two influential macro factors of Taiwanese hotel stock returns, while Chen (2006b) showed that significant macro determinants of Chinese hotel stock returns included changes in discount rates, industrial production growth rates, growth rates of imports and changes in yield spread. Chen (2006b) further reported that among macro forces, the monetary policy variable appeared to be the only macro factor that consistently and significantly explained hotel stock returns in China, Taiwan and US. Chen and Kim (2006) argued that when examining the relationship between macro factors and hospitality stock returns, Barrows and Naka (1994), Chen et al. (2005) and Chen (2006b) used the ordinary least-square (OLS) regression technique, which could fail to capture the long-term effect of economic variables on hospitality stock returns. They applied the cointegration and error-correction model to examine the long-term connection between hospitality stock prices and economic forces in Taiwan. Empirical results still showed that growth rates of money supply served as a significant predictor of tourism stock returns. Singh and Kwansa (1999) pointed out the critical role of monetary policy in financing the lodging industry in the next millennium. They reported that based on the predictions of 39 selected experts from the lodging and financial services industries, the Federal Reserve’s monetary policy in the US would be one of the major forces that significantly influences the lending criteria and terms by financial institutions for hotel mortgages. This implies that the monetary policy would ultimately have a profound impact on the financial performance of hotel companies since the lending criteria and terms determine the ability of hotel companies to access the capital. The purpose of this study, given the above illustration, is to further investigate the impact of monetary policy conducted by the Central Bank of China (CBC hereafter) on hotel stock returns in Taiwan. Specifically, we examine the Taiwanese hotel stock performance under two various monetary policy environments, namely expansive and restrictive, and test whether different monetary stringencies influences the relationship between macro factors and Taiwanese hotel stock returns. In addition, the influences of monetary policy changes on returns of airlines, department store, entertainment
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stocks and the Taiwan stock market as a whole are examined to offer a comparative assessment. Note that Barrows and Naka (1994) and Chen et al. (2005) used growth rates of money supply as the monetary policy variables. Although an increase of money supply (a positive money supply growth rate) is associated with a decrease in the interest rate and hence an expansive monetary policy, money supply has not been generally used as a good indicator of different monetary policy developments because of its frequent changes (Jensen and Johnson, 1995; Jensen et al., 1996; Johnson and Jensen, 1998; Conover et al., 1999; Johnson et al., 2003; Mann et al., 2004; Chen et al., 2006a, b). Different from the monetary policy variables utilized in Barrows and Naka (1994) and Chen et al. (2005), we employed changes in the discount rate as the measure of monetary environment stringency exploited by Jensen et al. (1996) and Johnson and Jensen (1998). This approach enables us to take a close look at how well hotel stocks perform under two explicitly different monetary policy conditions, i.e. expansive and restrictive monetary policy environments. Accordingly, this study not only highlights the important role of monetary policy, but also provides a practical implication for hotel stock investors to reallocate their portfolios in a timely manner based on changes in the monetary policy movements. Section 2 describes the relationship between stock returns and monetary policy. Data description and a preliminary examination of return and risk of hotel stocks during various monetary periods are addressed in Section 3. Section 4 shows the regression analysis and empirical results. Section 5 concludes this study with an investment implication for hotel stock investors.
2. Monetary policy and stock returns 2.1. Links between monetary policy and asset performance It is well known that the central bank, the government authority in charge of monetary policy, is the most important player in financial markets throughout the world (Mishkin and Eakins, 2006). Monetary policies conducted by the central bank can regulate interest rates, which in turn drives the firm’s cost of capital and impacts the real economy. Hence changes in the monetary policy can signal future direction of the economy by providing information about future business conditions and corporate earnings. According to the stock valuation model, the stock price is equal to the present value of all expected future cash flows (dividend payments) received from holding the stock. Consequently, changes in the monetary policy can affect the stock performance through changes in the future corporate earnings and discount rate used in valuing corporate cash flows. For example, the central bank can pursue a restrictive monetary policy by raising interest rates through an open market sale or through bringing up the discount rate. Once interest rates grow, companies are forced to pay more for borrowed funds, and thus lower corporate earnings. Moreover, the discount rate used to value a firm’s cash flow rises, making these cash flows worth less. Through this mechanism, monetary policy can be linked to asset returns. Empirical studies support this connection. Johnson and Jensen (1998) and Conover et al. (1999) found a significant relationship between monetary policy changes and stock returns in the US and several developed countries. Chen et al. (2006a) reported a similar finding in the
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emerging Taiwan stock market. Cook and Hahn (1988) and Johnson et al. (2003) documented influences of monetary policy changes on different debt markets. 2.2. Measures of monetary policy based on discount rate changes To measure changes in the monetary policy, we followed the approach used by Jensen et al. (1996) and Johnson and Jensen (1998). They utilized changes in the discount rate to categorize the monetary environment as either restrictive or expansive. Technically speaking, the central bank can provide reserves to the banking system by making discount loans to its member financial institutions or banks, and the discount rate is the interest rate that banks must pay to the central bank for discount loans (Mishkin and Eakins, 2006). The function of the CBC discount rate in Taiwan is similar to that of the Federal Reserve discount rate in the US. Laurent (1988) indicated three advantages of using changes in the discount rate as the monetary policy indicator. First, changes in the discount rate are perceived to be exogenous signals of the central bank actions and these signals are easy for the public to interpret. Second, discount rate changes are reported regularly and happen relatively infrequently. Third, discount rate changes are regarded as signaling or confirming for future course of monetary policy and possibly economic development. To facilitate the analysis of the linkage between monetary policy and hotel stock returns, we divided the full sample of the monetary policy environment into two sub-samples, e.g. expansive and restrictive monetary periods. An expansive monetary period is associated with experiencing a drop in the discount rate, whereas a restrictive monetary period has a rise in the discount rate. Based on this approach, the level of the discount rate is not the important parameter, instead it is the opposite direction of the rate change that matters. Therefore, a new monetary environment starts when a discount rate change in the opposite direction from the previous change is observed, and consecutive discount rate changes in the same direction are considered a continuation of the same monetary environment (Jensen et al., 1996; Johnson and Jensen, 1998). Jensen et al. (1996) and Booth and Booth (1997) provided convincing evidence that with the use of changes in the discount rate, they could successfully differentiate the monetary policy periods into two various monetary environments (expansive vs. restrictive) in the US. They illustrated that monetary supply measures and reserve aggregate were significantly variable across two monetary regimes. Chen et al. (2006a) further showed that changes in the CBC discount rate also served as an effective indicator of the monetary policy movements in Taiwan. 3. Data and a preliminary examination 3.1. Data and monetary policy Not many hospitality firms are traded in the emerging Taiwan stock market (Chen et al., 2005). The hotel stocks covered in this study include the stocks of Ambassador Hotel, First Hotel, Hotel Holiday Garden, and Leofoo Hotel. The selection of hotel stocks follows the criterion in Chen et al. (2005), which is in consideration of data availability. Monthly hotel stock prices over the period from January 1989 to January 2005 (193 monthly observations) are taken from the Taiwan Economic Journal (TEJ) database. We then
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compute the value-weighted hotel stock price index (HPI) using four hotel stock prices and monthly hotel stock returns (HRt): HRt ¼ ðln HPI t ln HPI t1 Þ100.
(1)
To provide a comparative examination, results of hotel stocks are compared to stocks for airlines, department stores, entertainment, and the Taiwan stock market as a whole. As mentioned, only a small number of hospitality companies are listed in the Taiwan Stock Exchange (TSE). In consideration of the limitation of data availability and the selection criteria of hotel stocks, three stocks of department stores (Far Eastern, Mercuries and Associates and Shin Shin), one stock of airline company (China Airlines) and one stock of entertainment firm (Wan-Hwa Corporation) are selected to construct the corresponding sector price index. The TSE composite index is the Taiwan stock market value-weighted index. Time series price data of department stores, entertainment and the TSE composite include the period from January 1989 to 2005, while the price data of airlines cover the period from January 1993 to 2005. All data are obtained from the TEJ database. Discount rate data were also obtained from the TEJ database. Over the full sample period from January 1989 through 2005, the Central Bank of China changed the discount rate 39 times: 10 increases and 29 decreases. In total, there were 11 rate-change series, 5 decreasing and 6 increasing. Rate change series are considered because it is assumed to be under the same monetary policy until a discount rate change in the opposite direction is observed. Those months during which the first rate change in a series occurred are eliminated from the sample, resulting in a drop of a total number of observations from 193 to 182 months. We omitted those 11 months due to the following reasons. As mentioned, it is our intention to examine (1) the performance of hotel stocks under different monetary periods, and (2) the impact of various monetary policy circumstances on the link between hotel stock returns and macro factors. Thus, it is appropriate to remove months that mark the initiation of a new monetary environment and hence embrace both expansive and restrictive days. Accordingly, we found that of the 182 months retained, 125 follow discount rate decreases and 57 follow discount rate increases. Table 1 provides summary information on the discount rate change series. The time trend of stock prices under different monetary policy environments is plotted in Fig. 1. It is found that prices tended to decline during restrictive monetary conditions, such as periods from June to September 1992, March to June 1995, September 1997 to August 1998, April to November 2000 and November 2004 to January 2005, except that there were several price declines and rises over the period from May 1989 to June 1991. 3.2. Return and risk under various monetary policy environments Table 2 presents mean returns of monthly stocks over the entire sample period and two different monetary periods. Test results for mean return difference between the two monetary periods are also provided in Table 2. In general, the TSE market outperforms four hospitality stocks. The mean return of hotel, airlines, department stores, entertainment and TSE composite over the full sample is .44%, .07%, .36%, .04% and .05%, respectively. All stocks have greater mean return during expansive monetary periods than during restrictive periods. Among them, the difference in the mean return over two different monetary conditions is 4.45% for hotel stocks, 2.19% for department
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Table 1 Discount rate change series: January 1989–2005 Series
Increasing (I) or decreasing (D)
First rate change in series
Rate changes in series
Monthly observations in series
1 2 3 4 5 6 7 8 9 10 11
I D I D I D I D I D I
July 1989 April 1991 May 1992 October 1992 February 1995 July 1995 August 1997 September 1998 March 2000 December 2000 October 2004
2 4 1 2 1 3 1 4 2 14 3
29 9 4 27 4 24 12 17 8 45 3
Note: A series is identified when a sequence of consecutive rate changes is in the same direction. Eleven months in which the direction of a rate change is reversed are dropped.
store stocks and 2% for market stocks, which are all statistically significant difference in their means at the 5% level. These findings illustrate that hotel, department store and market stocks had performed significantly better under an expansive monetary environment. Standard deviations of returns over the full sample and two monetary periods are shown in Table 3. Results indicate that the standard deviation of hotel, department store, entertainment and market returns is higher in restrictive monetary periods than in expansive periods except for the airlines returns. In other words, those four stock returns are more volatile during restrictive periods. However, the difference in standard deviations of hotel and airlines returns between two monetary environments is not statistically significant. Table 4 reports the Sharpe and Treynor ratios (reward-to-risk ratios) for hotel returns over the full sample and both expansive and restrictive periods. Both ratios are given as follows: Sharpe ratio ¼ ð¯r r¯ f Þ=s
(2)
Treynor ratio ¼ ð¯r r¯f Þ=b,
(3)
and
where r¯ is the mean annualized hotel stock return, r¯ f is the mean risk-free rate and s is the standard deviation of the annualized hotel returns, the b value is estimated based on the capital asset pricing model (CAPM) of Lintner (1965) and Sharpe (1964), which is given as rt rf ;t ¼ c þ bðrm;t rf ;t Þ þ et ,
(4)
where r is the annualized hotel stock return, rf is the risk-free rate, and rm is the market return. The monthly series of the 1-month time deposit rate (annual rate) is used as the risk-free rate and the market return is proxied by returns on the TSE composite index. Risk-free rate data are also taken from TEJ database.
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Department store
Hotel 200
200
160
160
120
120
80
80
40
40
0
0 1990 1992 1994 1996 1998 2000 2002 2004
1990 1992 1994 1996 1998 2000 2002 2004 Entertainment
Airlines 200
200
160
160
120
120
80
80
40
40
0
0 1990 1992 1994 1996 1998 2000 2002 2004
1990 1992 1994 1996 1998 2000 2002 2004
TSE composite 14000 12000 10000 8000 6000 4000 2000 1990 1992 1994 1996 1998 2000 2002 2004
Fig. 1. The time trends of stock prices under different monetary conditions. Note: The shaded areas indicate the restrictive monetary periods (August 1989–March 1991, June–September 1992, March–June 1995, September 1997–August 1998, April–November 2000 and November 2004–January 2005).
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Table 2 Mean returns of monthly stocks Company
Full sample
Expansive period
Restrictive period
Difference in means
t-statistics (p-value) for difference in means
Hotel Airlines Department store Entertainment TSE composite
0.44 0.07 0.36 0.04 0.05
0.95 0.30 0.24 0.86 0.69
3.50 1.93 1.95 2.45 1.31
4.45 2.23 2.19 3.31 2.00
1.95 0.90 2.38 1.38 2.73
(.05)** (.37) (.02)** (.17) (.01)***
Note: The data excludes months of changes in the monetary policy. **Significant at the 5% level. ***Significant at the 1% level.
Table 3 Standard deviation of monthly returns of hotel stocks Company
Full sample
Expansive period
Restrictive period
Difference in standard deviations
F-statistics (p-value) for difference in standard deviations
Hotel Airlines Department store Entertainment TSE composite
14.30 11.44 5.80 15.16 4.56
13.87 11.90 4.51 12.36 3.85
15.22 10.15 7.89 19.61 5.86
1.35 1.75 3.38 7.25 2.01
1.21 1.37 3.06 2.52 2.31
(.44) (.26) (.00)*** (.00)*** (.00)***
Note: The data excludes months of changes in the monetary policy. **Significant at the 5% level. ***Significant at the 1% level. Table 4 Sharpe and Treynor ratios of hotel stock returns Full sample
Expansive periods
Restrictive periods
Difference in reward ratios
Hotel Sharpe ratio Treynor ratio
0.07 2.01
0.04 1.90
0.30 23.76
0.34 25.66
Airlines Sharpe ratio Treynor ratio
0.53 3.85
0.06 1.91
1.59 95.97
1.53 97.88
Department store Sharpe ratio 1.64 Treynor ratio 15.88
0.33 1.79
3.85 65.62
3.52 63.83
Entertainment Sharpe ratio Treynor ratio
0.31 1.97
0.48 2.72
1.14 14.05
1.62 16.77
TSE composite Sharpe ratio Treynor ratio
1.03 4.71
1.02 3.93
3.88 22.71
4.90 26.64
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As shown in Table 4, the Sharpe ratio of hotel stock returns is 0.07 over the entire sample period, 0.30 during restrictive periods and 0.04 during expansive periods. Similarly, the Treynor ratio of hotel stock returns is 2.01 over the entire sample period, 23.76 during restrictive periods and 1.90 during expansive periods. Both Sharpe and Treynor ratios are positive only in the expansive monetary environment, implying that hotel stocks offer a better reward per unit of risk in expansive periods. Further, negative Sharpe and Treynor ratios of hotel returns in restrictive periods imply that hotel stock investors would have achieved better investment performance simply by holding risk-free assets instead of hotel stocks during restrictive monetary periods. Similar results are detected for the airlines, department stores, entertainment stocks, and market composite. 4. Regression analysis and empirical results 4.1. Regressions of hotel returns on the monetary policy dummy variable In this section, we followed Johnson and Jensen (1998) formally examining the connection between stock returns and changes in the monetary policy based on Eq. (5): HRt ¼ a0 þ a1 DR_dummy þ vt ,
(5)
where HRt is the monthly hospitality or market returns and DR_dummy is the dummy variable for changes in the discount rate, which takes a value of one during restrictive monetary periods and zero during expansive monetary periods. To obtain consistent estimates in regression coefficients, standard errors, and associated t-statistics by correcting the possible presence of autocorrelation and heteroscedasticity, the approach proposed by Newey and West (1987) is used. Additionally, to control for the possible impact of other variables on the relationship between monetary policy dummy variable and stock returns, we added five economic factors tested in Chen et al. (2005) and the total number of foreign tourist arrivals (TA) used in Chen (2006b) as another explanatory factors. Chen (2006b) argued that the total number of foreign TA could be another factor that could have a direct impact on the hospitality sector since TA is widely used as a proxy for tourism development or expansion (Wang and Godbey, 1994; Shan and Wilson, 2001; Kim et al., 2006). Accordingly, the following regression is performed: HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DTAt þ a7 DR_dummy þ t ,
ð6Þ
where MSt , DUEPt , IPt , EINF t , SPDt , TAt and et denote growth rates of money supply (M2), changes in unemployment rates, industrial production growth rates, expected inflation rates, changes in yield spread, TA growth rates and residuals, respectively. Before running multiple regression based on Eq. (6), we checked correlations between DR_dummy and other macro variables over the full sample period (see Table 5). Among six variables, only EINF t was highly correlated with the DR_dummy. To avoid the possible existence of multicollinearity, we carried out two separate multiple regressions with and without the EINF t factor. The regression results are shown in Tables 6 and 7. Over the full sample period from February 1989 to January 2005, the dummy variable of changes in the discount rate DR_dummy has a significantly negative impact on hotel, department store and maket returns (see Table 6). The negative coefficient of the
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Table 5 Correlations between monetary policy dummy variable and macro factors Variable
DMS
DUEP
DIP
EINF
SPD
DTA
DR_dummy
0.06
0.01
0.01
0.37
0.08
0.02
Table 6 Regression results of returns on the dummy variable of changes in discount rate HRt ¼ a0 þ a1 DR_dummy þ vt Company
Sample period
Constant
DR_dummy
¯2 R
Hotel
February 1989–January 2005
0.95 (0.86)
4.48 (1.76)*
0.021
Airlines
February 1993–January 2005
0.30 (0.36)
2.23 (1.13)
0.006
Department store
February 1989–January 2005
0.24 (0.68)
2.20 (2.62)***
0.031
Entertainment
February 1989–January 2005
0.86 (0.88)
3.31 (1.21)
0.010
2.00 (2.08)**
0.031
TSE composite
February 1989–January 2005
**
0.69 (2.07)
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2. changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
DR_dummy dummy variable indicates that restrictive monetary conditions were significantly associated with lower hotel (department store or market) stock returns, whereas hotel (department store or market) stocks experienced higher returns in expansive monetary periods. Empirical results in Table 6 further illustrate that monetary policy changes had a bigger impact on hotel returns (4.48) than on department store returns (2.20) and market returns (2.00). This negative influence remains significant after controlling macro variables are added to the regressions (see Table 7). Moreover, hotel returns, among three (hotel, department store and market) returns, are still the most influenced by changes in the discount rate. For the purpose of providing a comparative examination, we also add the DR_dummy variable into the multiple regressions of hotel stock returns on five macro factors over the same period (from February 1989 to August 2003) as in Chen et al. (2005). Similar results are still detected (see Table 8). In sum, the significantly negative reactions of hotel stock returns to the dummy variable DR_dummy are consistent with results of the preliminary examination presented in Table 2. 4.2. Links between macro factors and hotel returns under different monetary stringency To further investigate the impact of different monetary environments on the connection between macro factors and hotel returns, we separated all sample data into expansive and restrictive periods, which includes 125 and 57 monthly observations, respectively. We then
4.49 (1.57)
4.74 (1.67)*
Regression II
Regression III
1.74 (1.74)* 1.94 (1.78)* 2.08 (1.98)**
2.47 (1.05) 1.46 (0.62) 0.13 (.07)
1.29 (0.40) 2.68 (0.43) 1.40 (0.54)
18.86 (2.84)*** 17.14 (2.72)*** 14.64 (2.40)**
DUEP
0.02 (0.46) 0.01 (0.11) 0.03 (0.89)
0.05 (0.65) 0.07 (1.03) 0.04 (0.81)
0.05 (0.45)
0.12 (0.89)
0.18 (1.34)
DIP
1.14 (1.44) 0.91 (1.20) —
0.44 (0.44) 0.89 (0.82) —
—
1.71 (1.12)
2.06 (1.25)
EINF
0.16 (0.30) 0.24 (0.40) 0.16 (0.28)
0.98 (1.74)* 0.87 (1.80)* 0.80 (1.80)*
1.00 (0.88)
1.14 (1.01)
0.68 (0.66)
SPD
0.20 (0.13) 0.06 (0.04) 0.09 (0.06)
2.04 (1.09) 1.83 (1.02) 1.69 (0.36)
1.77 (0.30)
1.49 (0.25)
1.03 (0.18)
DTA
— 1.93 (2.27)** 2.08 (2.31)**
— 2.37 (3.13)*** 2.23 (2.75)***
4.69 (2.18)**
4.41 (2.08)**
—
DR_dummy
0.050 0.086 0.076
0.057 0.085 0.079
0.083
0.087
0.075
¯2 R
¯ 2 is the adjusted R2. Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
TSE composite Regression I Regression II Regression III
Department store Regression I 3.77 (2.75)*** Regression II 3.68 (2.52)*** Regression III 3.55 (2.60)***
4.88 (1.78)*
Hotel Regression I
DMS
HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DTAt þ a7 DR_dummy þ t
Table 7 Multiple regression results of stock returns on macro factors: February 1989–January 2005
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Table 8 Multiple regression results of hotel stock returns on macro factors: February 1989–August 2003 HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DR_dummy þ t Hotel
DMS
DUEP
EINF
DIP
SPD
DR_dummy
¯2 R
Regression I 3.60 (2.70)*** 12.51 (1.81)* 0.05 (0.44) 0.43 (0.28) 0.32 (0.29) — 0.076 Regression II 4.48 (1.51) 14.33 (2.25)** 0.05 (0.39) 1.18 (0.47) 1.08 (0.92) 4.56 (2.04)** 0.078 Regression III 5.05 (1.69)*** 12.88 (2.06)* 0.01 (0.11) — 0.88 (0.73) 4.56 (2.04)** 0.080
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2. changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
Table 9 Multiple regression results over restrictive monetary policy periods HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et Constant
DMS
DUEP
DIP
EINF
SPD
¯2 R
6.72 (1.61)
4.09 (1.00)
22.11 (1.73)*
0.00 (1.08)
0.02 (0.83)
0.80 (0.45)
0.136
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2 . changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
executed two separate regressions according to Eq. (7), which is the same regression equation as in Chen et al. (2005): HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et .
(7)
The regression results are reported in Tables 9 and 10. Note that among all macro factors, only growth rates of money supply (DMSt ) and changes in unemployment rates (DUEPt ) can significantly explain the hotel returns over the full sample period (see the regression I for hotel stocks in Table 7). However, the explanatory ability of DMS t on hotel returns disappeared during restrictive monetary periods (see Table 9). Moreover, the explanatory ability of both DMSt and DUEPt vanished during expansive monetary periods (see Table 10). These evidences indicate that the monetary policy stringency does affect the association between hotel stock returns and macro variables. 5. Conclusion and managerial implication Within the hospitality finance literature, a few research papers that investigated the connection between macro forces and hospitality stock returns (Barrows and Naka, 1994;
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Table 10 Multiple regression results over expansive monetary policy periods HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et Constant
DMS
DUEP
DIP
EINF
SPD
¯2 R
2.02 (1.05)
5.46 (1.45)
13.54 (1.62)
0.00 (0.41)
0.03 (1.37)
1.07 (0.77)
0.058
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2 . changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
Chen et al., 2005; Chen, 2006a, b; Chen and Kim, 2006) have pointed out the crucial role of the monetary policy variable in explaining hotel stock returns. Following this issue, this study examines the Taiwanese hotel stock performance under expansive and restrictive monetary environments, and the influence of various monetary conditions on the relationship between macro factors and Taiwanese hotel stock returns. Different from the previous work (Barrows and Naka, 1994; Chen et al., 2005), which used money supply growth rates as the monetary policy variable, we employed changes in the discount rate to measure the monetary policy changes and classify the monetary environment as either restrictive or expansive. Under these two different monetary policy regimes, we found that hotel stocks exhibited a higher mean return and lower standard deviation in an expansive monetary environment. The Sharpe and Treynor ratios of hotel stocks are positive and relatively high during expansive monetary periods, but negative during restrictive monetary periods, showing that even the risk-free asset outperformed the hotel stocks in a restrictive monetary environment. These evidences suggest that in response to monetary policy developments, hotel stock investors can reallocate their portfolios in a timely manner, i.e. rebalancing their investment portfolios between hotel stocks and risk-free asset according to the monetary policy changes. For example, hotel stock investors should increase their investment holdings in hotel stocks during expansive monetary periods, but invest more in risk-free assets during restrictive monetary periods. The results of regression analyses also support the empirical finding that hotel stocks had higher mean return in expansive periods because of the significantly negative coefficient of the dummy variable of changes in the discount rate, which takes one and zero during restrictive and expansive monetary periods, respectively. This finding remains robust after the regressions were carried out by controlling other macro factors. Finally, different behaviors of the link between hotel stock returns and macro variables under two various monetary conditions were detected. Among five macro forces, only the macro factor of changes in unemployment rate was significantly correlated with hotel stock returns in restrictive monetary periods. Furthermore, all five macro factors failed to explain hotel stock returns in expansive monetary periods. This study consequently highlights the critical role of monetary policy stringency proxied by changes in the discount rate, and makes a contribution by allowing us to capture variation in hotel stock returns associated with hotel stock-pricing variables.
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Sharpe, W.F., 1964. Capital asset prices: a theory of market equilibrium under conditions of risk. Journal of Finance 19, 425–442. Singh, A.J., Kwansa, F.A., 1999. Financing the lodging industry in the next millennium. International Journal of Hospitality Management 18, 415–425. Wang, P., Godbey, G., 1994. A normative approach to tourism growth to the year 2000. Journal of Travel Research 2, 32–37. Wasserfallen, W., 1989. Macroeconomic news and the stock market. Journal of Banking and Finance 13, 613–626.
Hospitality Management 26 (2007) 588–602 www.elsevier.com/locate/ijhosman
Hotel stock performance and monetary conditions Ming-Hsiang Chen Department of Finance, National Chung Cheng University, Chia-Yi, Taiwan, ROC
Abstract Following the investigation of the link between hotel stock returns and macroeconomic factors in the hospitality finance literature, this study further examines (1) the performance of Taiwanese hotel stocks under two various monetary policy environments, namely expansive and restrictive, and (2) the impact of different monetary stringency on the relationship between hotel stock returns and macro variables in Taiwan. Using changes in the discount rate allows us to effectively measure the monetary policy changes and classify the monetary environment as either restrictive or expansive. Empirical results show that hotel stocks exhibited a higher mean return and reward-to-risk ratio during expansive monetary periods. Moreover, the connection between hotel stock returns and macro variables behaved differently under various monetary conditions. In response to monetary policy developments, the implication for hotel stock investors to reallocate their investment portfolios is provided. r 2006 Elsevier Ltd. All rights reserved. Keywords: Hotel; Stock returns; Monetary conditions; Discount rate; Taiwan
1. Introduction The association between stock returns and macroeconomic (macro hereafter) variables has been well studied in the fields of economics and finance (Chen et al., 1986; Campbell, 1987; Fama and French, 1988; Asprem, 1989; Wasserfallen, 1989; Bulmash and Trivoli, 1991; Booth and Booth, 1997; Nasseh and Strauss, 2000; Chen, 2003). In comparison, within the hospitality literature, there are only a few research papers examining the link between macro factors and hospitality stock returns (Barrows and Naka, 1994; Chen et al., 2005; Chen, 2006a, b; Chen and Kim, 2006). Tel.: +886 5 2720411; fax: +886 5 2720818.
E-mail address: fi[email protected]. 0278-4319/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhm.2006.05.003
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Barrows and Naka (1994) tested whether five selected economic variables, namely growth rates of industrial production, money supply, domestic consumption, expected inflation rate and term structure of the interest rate could influence US hospitality stock returns. They found that, among five economic variables, growth rates of money supply and domestic consumption had a significantly positive impact on the hospitality stock returns, whereas the expected inflation rate affected the hospitality stock returns negatively. Interactions between business conditions and financial performance of tourism firms in both China and Taiwan were examined in Chen (2006a). Chen (2006a) investigated whether the improvement of business conditions (proxied by gross domestic product and industrial production) enhances stock performance of tourism firms and whether financial success of tourism firms matters to business development. Empirical results showed that a long-run equilibrium relationship existed between business conditions and financial performance of tourism firms, and further these two factors reinforced each other in both China and Taiwan. Following Barrows and Naka (1994), Chen et al. (2005) and Chen (2006b) tested a set of macro variables as determinants of hotel stock returns in Taiwan and China, respectively. Chen et al. (2005) detected that money supply growth rates and changes in unemployment rates are two influential macro factors of Taiwanese hotel stock returns, while Chen (2006b) showed that significant macro determinants of Chinese hotel stock returns included changes in discount rates, industrial production growth rates, growth rates of imports and changes in yield spread. Chen (2006b) further reported that among macro forces, the monetary policy variable appeared to be the only macro factor that consistently and significantly explained hotel stock returns in China, Taiwan and US. Chen and Kim (2006) argued that when examining the relationship between macro factors and hospitality stock returns, Barrows and Naka (1994), Chen et al. (2005) and Chen (2006b) used the ordinary least-square (OLS) regression technique, which could fail to capture the long-term effect of economic variables on hospitality stock returns. They applied the cointegration and error-correction model to examine the long-term connection between hospitality stock prices and economic forces in Taiwan. Empirical results still showed that growth rates of money supply served as a significant predictor of tourism stock returns. Singh and Kwansa (1999) pointed out the critical role of monetary policy in financing the lodging industry in the next millennium. They reported that based on the predictions of 39 selected experts from the lodging and financial services industries, the Federal Reserve’s monetary policy in the US would be one of the major forces that significantly influences the lending criteria and terms by financial institutions for hotel mortgages. This implies that the monetary policy would ultimately have a profound impact on the financial performance of hotel companies since the lending criteria and terms determine the ability of hotel companies to access the capital. The purpose of this study, given the above illustration, is to further investigate the impact of monetary policy conducted by the Central Bank of China (CBC hereafter) on hotel stock returns in Taiwan. Specifically, we examine the Taiwanese hotel stock performance under two various monetary policy environments, namely expansive and restrictive, and test whether different monetary stringencies influences the relationship between macro factors and Taiwanese hotel stock returns. In addition, the influences of monetary policy changes on returns of airlines, department store, entertainment
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stocks and the Taiwan stock market as a whole are examined to offer a comparative assessment. Note that Barrows and Naka (1994) and Chen et al. (2005) used growth rates of money supply as the monetary policy variables. Although an increase of money supply (a positive money supply growth rate) is associated with a decrease in the interest rate and hence an expansive monetary policy, money supply has not been generally used as a good indicator of different monetary policy developments because of its frequent changes (Jensen and Johnson, 1995; Jensen et al., 1996; Johnson and Jensen, 1998; Conover et al., 1999; Johnson et al., 2003; Mann et al., 2004; Chen et al., 2006a, b). Different from the monetary policy variables utilized in Barrows and Naka (1994) and Chen et al. (2005), we employed changes in the discount rate as the measure of monetary environment stringency exploited by Jensen et al. (1996) and Johnson and Jensen (1998). This approach enables us to take a close look at how well hotel stocks perform under two explicitly different monetary policy conditions, i.e. expansive and restrictive monetary policy environments. Accordingly, this study not only highlights the important role of monetary policy, but also provides a practical implication for hotel stock investors to reallocate their portfolios in a timely manner based on changes in the monetary policy movements. Section 2 describes the relationship between stock returns and monetary policy. Data description and a preliminary examination of return and risk of hotel stocks during various monetary periods are addressed in Section 3. Section 4 shows the regression analysis and empirical results. Section 5 concludes this study with an investment implication for hotel stock investors.
2. Monetary policy and stock returns 2.1. Links between monetary policy and asset performance It is well known that the central bank, the government authority in charge of monetary policy, is the most important player in financial markets throughout the world (Mishkin and Eakins, 2006). Monetary policies conducted by the central bank can regulate interest rates, which in turn drives the firm’s cost of capital and impacts the real economy. Hence changes in the monetary policy can signal future direction of the economy by providing information about future business conditions and corporate earnings. According to the stock valuation model, the stock price is equal to the present value of all expected future cash flows (dividend payments) received from holding the stock. Consequently, changes in the monetary policy can affect the stock performance through changes in the future corporate earnings and discount rate used in valuing corporate cash flows. For example, the central bank can pursue a restrictive monetary policy by raising interest rates through an open market sale or through bringing up the discount rate. Once interest rates grow, companies are forced to pay more for borrowed funds, and thus lower corporate earnings. Moreover, the discount rate used to value a firm’s cash flow rises, making these cash flows worth less. Through this mechanism, monetary policy can be linked to asset returns. Empirical studies support this connection. Johnson and Jensen (1998) and Conover et al. (1999) found a significant relationship between monetary policy changes and stock returns in the US and several developed countries. Chen et al. (2006a) reported a similar finding in the
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emerging Taiwan stock market. Cook and Hahn (1988) and Johnson et al. (2003) documented influences of monetary policy changes on different debt markets. 2.2. Measures of monetary policy based on discount rate changes To measure changes in the monetary policy, we followed the approach used by Jensen et al. (1996) and Johnson and Jensen (1998). They utilized changes in the discount rate to categorize the monetary environment as either restrictive or expansive. Technically speaking, the central bank can provide reserves to the banking system by making discount loans to its member financial institutions or banks, and the discount rate is the interest rate that banks must pay to the central bank for discount loans (Mishkin and Eakins, 2006). The function of the CBC discount rate in Taiwan is similar to that of the Federal Reserve discount rate in the US. Laurent (1988) indicated three advantages of using changes in the discount rate as the monetary policy indicator. First, changes in the discount rate are perceived to be exogenous signals of the central bank actions and these signals are easy for the public to interpret. Second, discount rate changes are reported regularly and happen relatively infrequently. Third, discount rate changes are regarded as signaling or confirming for future course of monetary policy and possibly economic development. To facilitate the analysis of the linkage between monetary policy and hotel stock returns, we divided the full sample of the monetary policy environment into two sub-samples, e.g. expansive and restrictive monetary periods. An expansive monetary period is associated with experiencing a drop in the discount rate, whereas a restrictive monetary period has a rise in the discount rate. Based on this approach, the level of the discount rate is not the important parameter, instead it is the opposite direction of the rate change that matters. Therefore, a new monetary environment starts when a discount rate change in the opposite direction from the previous change is observed, and consecutive discount rate changes in the same direction are considered a continuation of the same monetary environment (Jensen et al., 1996; Johnson and Jensen, 1998). Jensen et al. (1996) and Booth and Booth (1997) provided convincing evidence that with the use of changes in the discount rate, they could successfully differentiate the monetary policy periods into two various monetary environments (expansive vs. restrictive) in the US. They illustrated that monetary supply measures and reserve aggregate were significantly variable across two monetary regimes. Chen et al. (2006a) further showed that changes in the CBC discount rate also served as an effective indicator of the monetary policy movements in Taiwan. 3. Data and a preliminary examination 3.1. Data and monetary policy Not many hospitality firms are traded in the emerging Taiwan stock market (Chen et al., 2005). The hotel stocks covered in this study include the stocks of Ambassador Hotel, First Hotel, Hotel Holiday Garden, and Leofoo Hotel. The selection of hotel stocks follows the criterion in Chen et al. (2005), which is in consideration of data availability. Monthly hotel stock prices over the period from January 1989 to January 2005 (193 monthly observations) are taken from the Taiwan Economic Journal (TEJ) database. We then
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compute the value-weighted hotel stock price index (HPI) using four hotel stock prices and monthly hotel stock returns (HRt): HRt ¼ ðln HPI t ln HPI t1 Þ100.
(1)
To provide a comparative examination, results of hotel stocks are compared to stocks for airlines, department stores, entertainment, and the Taiwan stock market as a whole. As mentioned, only a small number of hospitality companies are listed in the Taiwan Stock Exchange (TSE). In consideration of the limitation of data availability and the selection criteria of hotel stocks, three stocks of department stores (Far Eastern, Mercuries and Associates and Shin Shin), one stock of airline company (China Airlines) and one stock of entertainment firm (Wan-Hwa Corporation) are selected to construct the corresponding sector price index. The TSE composite index is the Taiwan stock market value-weighted index. Time series price data of department stores, entertainment and the TSE composite include the period from January 1989 to 2005, while the price data of airlines cover the period from January 1993 to 2005. All data are obtained from the TEJ database. Discount rate data were also obtained from the TEJ database. Over the full sample period from January 1989 through 2005, the Central Bank of China changed the discount rate 39 times: 10 increases and 29 decreases. In total, there were 11 rate-change series, 5 decreasing and 6 increasing. Rate change series are considered because it is assumed to be under the same monetary policy until a discount rate change in the opposite direction is observed. Those months during which the first rate change in a series occurred are eliminated from the sample, resulting in a drop of a total number of observations from 193 to 182 months. We omitted those 11 months due to the following reasons. As mentioned, it is our intention to examine (1) the performance of hotel stocks under different monetary periods, and (2) the impact of various monetary policy circumstances on the link between hotel stock returns and macro factors. Thus, it is appropriate to remove months that mark the initiation of a new monetary environment and hence embrace both expansive and restrictive days. Accordingly, we found that of the 182 months retained, 125 follow discount rate decreases and 57 follow discount rate increases. Table 1 provides summary information on the discount rate change series. The time trend of stock prices under different monetary policy environments is plotted in Fig. 1. It is found that prices tended to decline during restrictive monetary conditions, such as periods from June to September 1992, March to June 1995, September 1997 to August 1998, April to November 2000 and November 2004 to January 2005, except that there were several price declines and rises over the period from May 1989 to June 1991. 3.2. Return and risk under various monetary policy environments Table 2 presents mean returns of monthly stocks over the entire sample period and two different monetary periods. Test results for mean return difference between the two monetary periods are also provided in Table 2. In general, the TSE market outperforms four hospitality stocks. The mean return of hotel, airlines, department stores, entertainment and TSE composite over the full sample is .44%, .07%, .36%, .04% and .05%, respectively. All stocks have greater mean return during expansive monetary periods than during restrictive periods. Among them, the difference in the mean return over two different monetary conditions is 4.45% for hotel stocks, 2.19% for department
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Table 1 Discount rate change series: January 1989–2005 Series
Increasing (I) or decreasing (D)
First rate change in series
Rate changes in series
Monthly observations in series
1 2 3 4 5 6 7 8 9 10 11
I D I D I D I D I D I
July 1989 April 1991 May 1992 October 1992 February 1995 July 1995 August 1997 September 1998 March 2000 December 2000 October 2004
2 4 1 2 1 3 1 4 2 14 3
29 9 4 27 4 24 12 17 8 45 3
Note: A series is identified when a sequence of consecutive rate changes is in the same direction. Eleven months in which the direction of a rate change is reversed are dropped.
store stocks and 2% for market stocks, which are all statistically significant difference in their means at the 5% level. These findings illustrate that hotel, department store and market stocks had performed significantly better under an expansive monetary environment. Standard deviations of returns over the full sample and two monetary periods are shown in Table 3. Results indicate that the standard deviation of hotel, department store, entertainment and market returns is higher in restrictive monetary periods than in expansive periods except for the airlines returns. In other words, those four stock returns are more volatile during restrictive periods. However, the difference in standard deviations of hotel and airlines returns between two monetary environments is not statistically significant. Table 4 reports the Sharpe and Treynor ratios (reward-to-risk ratios) for hotel returns over the full sample and both expansive and restrictive periods. Both ratios are given as follows: Sharpe ratio ¼ ð¯r r¯ f Þ=s
(2)
Treynor ratio ¼ ð¯r r¯f Þ=b,
(3)
and
where r¯ is the mean annualized hotel stock return, r¯ f is the mean risk-free rate and s is the standard deviation of the annualized hotel returns, the b value is estimated based on the capital asset pricing model (CAPM) of Lintner (1965) and Sharpe (1964), which is given as rt rf ;t ¼ c þ bðrm;t rf ;t Þ þ et ,
(4)
where r is the annualized hotel stock return, rf is the risk-free rate, and rm is the market return. The monthly series of the 1-month time deposit rate (annual rate) is used as the risk-free rate and the market return is proxied by returns on the TSE composite index. Risk-free rate data are also taken from TEJ database.
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Department store
Hotel 200
200
160
160
120
120
80
80
40
40
0
0 1990 1992 1994 1996 1998 2000 2002 2004
1990 1992 1994 1996 1998 2000 2002 2004 Entertainment
Airlines 200
200
160
160
120
120
80
80
40
40
0
0 1990 1992 1994 1996 1998 2000 2002 2004
1990 1992 1994 1996 1998 2000 2002 2004
TSE composite 14000 12000 10000 8000 6000 4000 2000 1990 1992 1994 1996 1998 2000 2002 2004
Fig. 1. The time trends of stock prices under different monetary conditions. Note: The shaded areas indicate the restrictive monetary periods (August 1989–March 1991, June–September 1992, March–June 1995, September 1997–August 1998, April–November 2000 and November 2004–January 2005).
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Table 2 Mean returns of monthly stocks Company
Full sample
Expansive period
Restrictive period
Difference in means
t-statistics (p-value) for difference in means
Hotel Airlines Department store Entertainment TSE composite
0.44 0.07 0.36 0.04 0.05
0.95 0.30 0.24 0.86 0.69
3.50 1.93 1.95 2.45 1.31
4.45 2.23 2.19 3.31 2.00
1.95 0.90 2.38 1.38 2.73
(.05)** (.37) (.02)** (.17) (.01)***
Note: The data excludes months of changes in the monetary policy. **Significant at the 5% level. ***Significant at the 1% level.
Table 3 Standard deviation of monthly returns of hotel stocks Company
Full sample
Expansive period
Restrictive period
Difference in standard deviations
F-statistics (p-value) for difference in standard deviations
Hotel Airlines Department store Entertainment TSE composite
14.30 11.44 5.80 15.16 4.56
13.87 11.90 4.51 12.36 3.85
15.22 10.15 7.89 19.61 5.86
1.35 1.75 3.38 7.25 2.01
1.21 1.37 3.06 2.52 2.31
(.44) (.26) (.00)*** (.00)*** (.00)***
Note: The data excludes months of changes in the monetary policy. **Significant at the 5% level. ***Significant at the 1% level. Table 4 Sharpe and Treynor ratios of hotel stock returns Full sample
Expansive periods
Restrictive periods
Difference in reward ratios
Hotel Sharpe ratio Treynor ratio
0.07 2.01
0.04 1.90
0.30 23.76
0.34 25.66
Airlines Sharpe ratio Treynor ratio
0.53 3.85
0.06 1.91
1.59 95.97
1.53 97.88
Department store Sharpe ratio 1.64 Treynor ratio 15.88
0.33 1.79
3.85 65.62
3.52 63.83
Entertainment Sharpe ratio Treynor ratio
0.31 1.97
0.48 2.72
1.14 14.05
1.62 16.77
TSE composite Sharpe ratio Treynor ratio
1.03 4.71
1.02 3.93
3.88 22.71
4.90 26.64
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As shown in Table 4, the Sharpe ratio of hotel stock returns is 0.07 over the entire sample period, 0.30 during restrictive periods and 0.04 during expansive periods. Similarly, the Treynor ratio of hotel stock returns is 2.01 over the entire sample period, 23.76 during restrictive periods and 1.90 during expansive periods. Both Sharpe and Treynor ratios are positive only in the expansive monetary environment, implying that hotel stocks offer a better reward per unit of risk in expansive periods. Further, negative Sharpe and Treynor ratios of hotel returns in restrictive periods imply that hotel stock investors would have achieved better investment performance simply by holding risk-free assets instead of hotel stocks during restrictive monetary periods. Similar results are detected for the airlines, department stores, entertainment stocks, and market composite. 4. Regression analysis and empirical results 4.1. Regressions of hotel returns on the monetary policy dummy variable In this section, we followed Johnson and Jensen (1998) formally examining the connection between stock returns and changes in the monetary policy based on Eq. (5): HRt ¼ a0 þ a1 DR_dummy þ vt ,
(5)
where HRt is the monthly hospitality or market returns and DR_dummy is the dummy variable for changes in the discount rate, which takes a value of one during restrictive monetary periods and zero during expansive monetary periods. To obtain consistent estimates in regression coefficients, standard errors, and associated t-statistics by correcting the possible presence of autocorrelation and heteroscedasticity, the approach proposed by Newey and West (1987) is used. Additionally, to control for the possible impact of other variables on the relationship between monetary policy dummy variable and stock returns, we added five economic factors tested in Chen et al. (2005) and the total number of foreign tourist arrivals (TA) used in Chen (2006b) as another explanatory factors. Chen (2006b) argued that the total number of foreign TA could be another factor that could have a direct impact on the hospitality sector since TA is widely used as a proxy for tourism development or expansion (Wang and Godbey, 1994; Shan and Wilson, 2001; Kim et al., 2006). Accordingly, the following regression is performed: HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DTAt þ a7 DR_dummy þ t ,
ð6Þ
where MSt , DUEPt , IPt , EINF t , SPDt , TAt and et denote growth rates of money supply (M2), changes in unemployment rates, industrial production growth rates, expected inflation rates, changes in yield spread, TA growth rates and residuals, respectively. Before running multiple regression based on Eq. (6), we checked correlations between DR_dummy and other macro variables over the full sample period (see Table 5). Among six variables, only EINF t was highly correlated with the DR_dummy. To avoid the possible existence of multicollinearity, we carried out two separate multiple regressions with and without the EINF t factor. The regression results are shown in Tables 6 and 7. Over the full sample period from February 1989 to January 2005, the dummy variable of changes in the discount rate DR_dummy has a significantly negative impact on hotel, department store and maket returns (see Table 6). The negative coefficient of the
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Table 5 Correlations between monetary policy dummy variable and macro factors Variable
DMS
DUEP
DIP
EINF
SPD
DTA
DR_dummy
0.06
0.01
0.01
0.37
0.08
0.02
Table 6 Regression results of returns on the dummy variable of changes in discount rate HRt ¼ a0 þ a1 DR_dummy þ vt Company
Sample period
Constant
DR_dummy
¯2 R
Hotel
February 1989–January 2005
0.95 (0.86)
4.48 (1.76)*
0.021
Airlines
February 1993–January 2005
0.30 (0.36)
2.23 (1.13)
0.006
Department store
February 1989–January 2005
0.24 (0.68)
2.20 (2.62)***
0.031
Entertainment
February 1989–January 2005
0.86 (0.88)
3.31 (1.21)
0.010
2.00 (2.08)**
0.031
TSE composite
February 1989–January 2005
**
0.69 (2.07)
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2. changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
DR_dummy dummy variable indicates that restrictive monetary conditions were significantly associated with lower hotel (department store or market) stock returns, whereas hotel (department store or market) stocks experienced higher returns in expansive monetary periods. Empirical results in Table 6 further illustrate that monetary policy changes had a bigger impact on hotel returns (4.48) than on department store returns (2.20) and market returns (2.00). This negative influence remains significant after controlling macro variables are added to the regressions (see Table 7). Moreover, hotel returns, among three (hotel, department store and market) returns, are still the most influenced by changes in the discount rate. For the purpose of providing a comparative examination, we also add the DR_dummy variable into the multiple regressions of hotel stock returns on five macro factors over the same period (from February 1989 to August 2003) as in Chen et al. (2005). Similar results are still detected (see Table 8). In sum, the significantly negative reactions of hotel stock returns to the dummy variable DR_dummy are consistent with results of the preliminary examination presented in Table 2. 4.2. Links between macro factors and hotel returns under different monetary stringency To further investigate the impact of different monetary environments on the connection between macro factors and hotel returns, we separated all sample data into expansive and restrictive periods, which includes 125 and 57 monthly observations, respectively. We then
4.49 (1.57)
4.74 (1.67)*
Regression II
Regression III
1.74 (1.74)* 1.94 (1.78)* 2.08 (1.98)**
2.47 (1.05) 1.46 (0.62) 0.13 (.07)
1.29 (0.40) 2.68 (0.43) 1.40 (0.54)
18.86 (2.84)*** 17.14 (2.72)*** 14.64 (2.40)**
DUEP
0.02 (0.46) 0.01 (0.11) 0.03 (0.89)
0.05 (0.65) 0.07 (1.03) 0.04 (0.81)
0.05 (0.45)
0.12 (0.89)
0.18 (1.34)
DIP
1.14 (1.44) 0.91 (1.20) —
0.44 (0.44) 0.89 (0.82) —
—
1.71 (1.12)
2.06 (1.25)
EINF
0.16 (0.30) 0.24 (0.40) 0.16 (0.28)
0.98 (1.74)* 0.87 (1.80)* 0.80 (1.80)*
1.00 (0.88)
1.14 (1.01)
0.68 (0.66)
SPD
0.20 (0.13) 0.06 (0.04) 0.09 (0.06)
2.04 (1.09) 1.83 (1.02) 1.69 (0.36)
1.77 (0.30)
1.49 (0.25)
1.03 (0.18)
DTA
— 1.93 (2.27)** 2.08 (2.31)**
— 2.37 (3.13)*** 2.23 (2.75)***
4.69 (2.18)**
4.41 (2.08)**
—
DR_dummy
0.050 0.086 0.076
0.057 0.085 0.079
0.083
0.087
0.075
¯2 R
¯ 2 is the adjusted R2. Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
TSE composite Regression I Regression II Regression III
Department store Regression I 3.77 (2.75)*** Regression II 3.68 (2.52)*** Regression III 3.55 (2.60)***
4.88 (1.78)*
Hotel Regression I
DMS
HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DTAt þ a7 DR_dummy þ t
Table 7 Multiple regression results of stock returns on macro factors: February 1989–January 2005
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Table 8 Multiple regression results of hotel stock returns on macro factors: February 1989–August 2003 HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ a6 DR_dummy þ t Hotel
DMS
DUEP
EINF
DIP
SPD
DR_dummy
¯2 R
Regression I 3.60 (2.70)*** 12.51 (1.81)* 0.05 (0.44) 0.43 (0.28) 0.32 (0.29) — 0.076 Regression II 4.48 (1.51) 14.33 (2.25)** 0.05 (0.39) 1.18 (0.47) 1.08 (0.92) 4.56 (2.04)** 0.078 Regression III 5.05 (1.69)*** 12.88 (2.06)* 0.01 (0.11) — 0.88 (0.73) 4.56 (2.04)** 0.080
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2. changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
Table 9 Multiple regression results over restrictive monetary policy periods HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et Constant
DMS
DUEP
DIP
EINF
SPD
¯2 R
6.72 (1.61)
4.09 (1.00)
22.11 (1.73)*
0.00 (1.08)
0.02 (0.83)
0.80 (0.45)
0.136
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2 . changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
executed two separate regressions according to Eq. (7), which is the same regression equation as in Chen et al. (2005): HRt ¼ a0 þ a1 DMS t þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et .
(7)
The regression results are reported in Tables 9 and 10. Note that among all macro factors, only growth rates of money supply (DMSt ) and changes in unemployment rates (DUEPt ) can significantly explain the hotel returns over the full sample period (see the regression I for hotel stocks in Table 7). However, the explanatory ability of DMS t on hotel returns disappeared during restrictive monetary periods (see Table 9). Moreover, the explanatory ability of both DMSt and DUEPt vanished during expansive monetary periods (see Table 10). These evidences indicate that the monetary policy stringency does affect the association between hotel stock returns and macro variables. 5. Conclusion and managerial implication Within the hospitality finance literature, a few research papers that investigated the connection between macro forces and hospitality stock returns (Barrows and Naka, 1994;
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Table 10 Multiple regression results over expansive monetary policy periods HRt ¼ a0 þ a1 DMSt þ a2 DUEPt þ a3 DIPt þ a4 EINF t þ a5 SPDt þ et Constant
DMS
DUEP
DIP
EINF
SPD
¯2 R
2.02 (1.05)
5.46 (1.45)
13.54 (1.62)
0.00 (0.41)
0.03 (1.37)
1.07 (0.77)
0.058
Note: Figures in parentheses are Newey and West (1987) corrected t-statistics. The data excludes months of ¯ 2 is the adjusted R2 . changes in the monetary policy. R *Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.
Chen et al., 2005; Chen, 2006a, b; Chen and Kim, 2006) have pointed out the crucial role of the monetary policy variable in explaining hotel stock returns. Following this issue, this study examines the Taiwanese hotel stock performance under expansive and restrictive monetary environments, and the influence of various monetary conditions on the relationship between macro factors and Taiwanese hotel stock returns. Different from the previous work (Barrows and Naka, 1994; Chen et al., 2005), which used money supply growth rates as the monetary policy variable, we employed changes in the discount rate to measure the monetary policy changes and classify the monetary environment as either restrictive or expansive. Under these two different monetary policy regimes, we found that hotel stocks exhibited a higher mean return and lower standard deviation in an expansive monetary environment. The Sharpe and Treynor ratios of hotel stocks are positive and relatively high during expansive monetary periods, but negative during restrictive monetary periods, showing that even the risk-free asset outperformed the hotel stocks in a restrictive monetary environment. These evidences suggest that in response to monetary policy developments, hotel stock investors can reallocate their portfolios in a timely manner, i.e. rebalancing their investment portfolios between hotel stocks and risk-free asset according to the monetary policy changes. For example, hotel stock investors should increase their investment holdings in hotel stocks during expansive monetary periods, but invest more in risk-free assets during restrictive monetary periods. The results of regression analyses also support the empirical finding that hotel stocks had higher mean return in expansive periods because of the significantly negative coefficient of the dummy variable of changes in the discount rate, which takes one and zero during restrictive and expansive monetary periods, respectively. This finding remains robust after the regressions were carried out by controlling other macro factors. Finally, different behaviors of the link between hotel stock returns and macro variables under two various monetary conditions were detected. Among five macro forces, only the macro factor of changes in unemployment rate was significantly correlated with hotel stock returns in restrictive monetary periods. Furthermore, all five macro factors failed to explain hotel stock returns in expansive monetary periods. This study consequently highlights the critical role of monetary policy stringency proxied by changes in the discount rate, and makes a contribution by allowing us to capture variation in hotel stock returns associated with hotel stock-pricing variables.
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