There are some limitations in this study.
The occupancy rate of all hotels in Hong Kong is used as a proxy for the occupancy rate factor as only half yearly data of the Regal Hotels International Holdings Limited is available.
The data used for the visitor arrivals is the total visitor arrivals each month. It is suggested that the number of overnight visitors or the number of visitors multiplied by the relative length of stay (weighted visitor arrivals) each month would be more appropriate in determining the actual demand. However, the data for number of overnight visitors was just available since 2002 and the monthly data for the length of stay are available until 2001.
The methodology used in this study to develop the factor model is the time series multiple regression analysis. Other methodology like the auto regressive method can be attempted to construct a time series time model which might have work better.
As suggested in Chapter 6, it is found that there are some missing factors which the model failed to include. This can be an area for further study. One suggestion is that as this study focus on economic variables, fundamental variables can also be added into the model. It should be noted that the concept of multifactor model and its advantage for risk analysis can be appreciated, but for practical issue which is to build it step by step, where the workload is huge and it will suffer from many thorny problems as well as challenges such as descriptors definitions and factors formulating (Shyu et al., 2006).
Appendices
Appendix 1 A Zero Order Correlation Matrix for the Independent Variables
R INT DEXC DOCC(-1) DHS DVIS RHSI SARS
R 1.000000 -0.248080 -0.067570 0.539971 -0.080322 0.249114 0.348737 -0.064757 INT -0.248080 1.000000 0.265639 -0.049717 -0.109183 -0.057931 -0.197087 -0.114568 DEXC -0.067570 0.265639 1.000000 0.089241 -0.135977 0.000792 -0.300001 0.025178 DOCC(-1) 0.539971 -0.049717 0.089241 1.000000 0.033786 0.357461 0.038241 -0.028282 DHS -0.080322 -0.109183 -0.135977 0.033786 1.000000 0.140786 0.014801 -0.129254 DVIS 0.249114 -0.057931 0.000792 0.357461 0.140786 1.000000 0.035093 -0.311411 RHSI 0.348737 -0.197087 -0.300001 0.038241 0.014801 0.035093 1.000000 -0.048462 SARS -0.064757 -0.114568 0.025178 -0.028282 -0.129254 -0.311411 -0.048462 1.000000
Appendix 2 Comparison between the actual returns and the estimated returns from the model (in the period 2007 - 2008)
Actual Model
Feb-07 0.0580 -0.0746 -0.0741 228.57% 227.68%
Mar-07 -0.0548 -0.0403 -0.0386 26.42% 29.49%
Apr-07 -0.0145 0.0789 0.0803 644.10% 653.70%
May-07 0.0441 -0.0485 -0.0476 209.98% 207.99%
Jun-07 -0.0704 -0.0589 -0.0568 16.32% 19.27%
Jul-07 -0.0152 0.0626 0.0634 511.57% 517.18%
Aug-07 -0.0769 0.0875 0.0870 213.85% 213.10%
Sep-07 -0.0167 0.1003 0.0964 700.75% 676.97%
Jul-08 -0.0132 0.0563 0.0507 526.38% 483.92%
Aug-08 -0.1979 0.0400 0.0346 120.19% 117.49%
Sep-08 -0.2700 -0.1859 -0.1894 31.15% 29.87%
Oct-08 -0.3425 -0.2314 -0.2406 32.45% 29.75%
Nov-08 0.2431 0.0941 0.0805 61.30% 66.90%
Dec-08 0.1544 0.0819 0.0722 46.96% 53.27%
Mean 186.34% 184.03%
Appendix 3 Beta Coefficients of the Stock of Regal Hotels International Holdings Limited estimated by the Regression Analysis
Beta Coefficients
Appendix 4 Comparison between the Actual Returns and the Estimated Returns by the CAPM (in the period 2007-2008)
Actual CAPM
Appendix 5 Comparison between the Absolute Percentage Error of Estimated Returns by the Model and CAPM (in the period 2007-2008
Actual Model CAPM Abs. % error (Model) (A) Abs. % error (CAPM) (B) B - A
Jan-07 0.0000 -0.0380 -0.0265 NA NA NA
Feb-07 0.0580 -0.0754 -0.0895 228.57% 254.33% 25.76%
Mar-07 -0.0548 -0.0383 -0.0214 26.42% 60.90% 34.48%
Apr-07 -0.0145 0.0814 0.0138 644.10% 195.15% -448.95%
May-07 0.0441 -0.0416 -0.0108 209.98% 124.45% -85.52%
Jun-07 -0.0704 -0.0574 0.0764 16.32% 208.52% 192.20%
Jul-07 -0.0152 0.0664 0.0979 511.57% 746.06% 234.49%
Aug-07 -0.0769 0.1009 0.0278 213.85% 136.17% -77.67%
Sep-07 -0.0167 0.1233 0.2548 700.75% 1628.53% 927.78%
Oct-07 0.1186 0.0510 0.3127 61.37% 163.60% 102.23%
Nov-07 -0.1515 -0.0295 -0.1828 98.30% 20.66% -77.64%
Dec-07 0.1429 0.0225 -0.0823 77.43% 157.59% 80.16%
Jan-08 -0.1594 -0.1366 -0.3480 35.05% 118.33% 83.27%
Feb-08 -0.0372 0.0305 0.0705 133.77% 289.55% 155.78%
Mar-08 -0.1158 -0.1203 -0.1379 12.54% 19.02% 6.48%
Apr-08 -0.0546 0.2072 0.2612 437.21% 578.61% 141.40%
May-08 -0.0208 -0.0114 -0.1098 39.25% 428.48% 389.23%
Jun-08 -0.1061 -0.0862 -0.2217 20.97% 108.92% 87.95%
Jul-08 -0.0132 0.0671 0.0469 526.38% 455.64% -70.74%
Aug-08 -0.1979 0.0367 -0.1498 120.19% 24.31% -95.88%
Sep-08 -0.2700 -0.1640 -0.3217 31.15% 19.13% -12.02%
Oct-08 -0.3425 -0.2942 -0.4783 32.45% 39.67% 7.21%
Nov-08 0.2431 0.0846 -0.0128 61.30% 105.26% 43.96%
Dec-08 0.1544 0.0832 0.0760 46.96% 50.76% 3.81%
Mean 186.34% 257.98% 74.73%
Appendix 6 Comparison between the Absolute Percentage error of the Estimated Returns by the Model and CAPM (using updated data)
Actual Model CAPM Abs% error (Model) (C)
Sep-07 -0.0167 0.1194 0.2308 676.97% 1484.99% 808.02%
Oct-07 0.1186 0.0432 0.2505 67.41% 111.14% 43.72%
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