### Table 2a Return and Higher Moments Predictability

"... In PAGE 19: ...Table2 a presents the estimates of parameters ^ a, ^b, and using the full sample period. The linear regression results show that the lagged return has signi cant predictive power for both Mexico and Thailand, particularly so for the Mexico index; but it is not signi cant for the Dow Jones Industrials.... In PAGE 20: ...make 4 periods forecasts. The volatility forecast for the stock return over the next four weeks would be Et h 4w 2t+1i = 4 X q=1 Et h w 2t+qi : Table2 b presents the GARCH(1,1) estimation results on the weekly data. Note that the kurtosis in the weekly innovation is enormous.... In PAGE 21: ...Table2 a while the conditional higher moments are replaced by the unconditional moments of the residual because we are hesitant to use the non-stationary estimates of the GARCH(1,1) model in Table 2. In all cases, compared to the benchmark case where only the unconditional mean and variance of the excess return are used, taking into the conditional information in the excess return greatly improves the portfolio performance both from the standard of cumulative return and from that of the Sharpe ratio, de ned as the mean excess return divided by the standard deviation of the portfolio.... In PAGE 21: ... However, the dynamic strategy yields no improvement over the static strategy in portfolio performance when investing in the Dow Jones. Corresponding to this result is the magnitudes of the R2 in the linear regression in Table2 : while the lagged re- turn has signi cant predictive powers in the cases of both Thailand and Mexico, the regression is not signi cant for the Dow Jones case. As analyzed in the previous sec- tion, the dynamic model reduces to the static model when there is no predictability.... ..."

### Table 3: Predicted moments of inertia

in GROUP #2

2007

"... In PAGE 4: ...able 2: Physical parameters used in MATLAB analysis............................................................ 18 Table3 : Predicted moments of inertia.... In PAGE 19: ... Table 2 summarizes the parameters used in these calculations. Table3 summarizes the predicted moments of inertia. Table 2: Physical parameters used in MATLAB analysis Parameter Value Description W [m] 0.... ..."

### Table 2b Return and Higher Moments Predictability in Weekly Data

"... In PAGE 19: ...Table2 a presents the estimates of parameters ^ a, ^b, and using the full sample period. The linear regression results show that the lagged return has signi cant predictive power for both Mexico and Thailand, particularly so for the Mexico index; but it is not signi cant for the Dow Jones Industrials.... In PAGE 20: ...make 4 periods forecasts. The volatility forecast for the stock return over the next four weeks would be Et h 4w 2t+1i = 4 X q=1 Et h w 2t+qi : Table2 b presents the GARCH(1,1) estimation results on the weekly data. Note that the kurtosis in the weekly innovation is enormous.... In PAGE 21: ...Table2 a while the conditional higher moments are replaced by the unconditional moments of the residual because we are hesitant to use the non-stationary estimates of the GARCH(1,1) model in Table 2. In all cases, compared to the benchmark case where only the unconditional mean and variance of the excess return are used, taking into the conditional information in the excess return greatly improves the portfolio performance both from the standard of cumulative return and from that of the Sharpe ratio, de ned as the mean excess return divided by the standard deviation of the portfolio.... In PAGE 21: ... However, the dynamic strategy yields no improvement over the static strategy in portfolio performance when investing in the Dow Jones. Corresponding to this result is the magnitudes of the R2 in the linear regression in Table2 : while the lagged re- turn has signi cant predictive powers in the cases of both Thailand and Mexico, the regression is not signi cant for the Dow Jones case. As analyzed in the previous sec- tion, the dynamic model reduces to the static model when there is no predictability.... ..."

### Table 3 Portfolio Performance Comparisons (Investing In Thailand): E ects of Higher Moments and Predictability

"... In PAGE 20: ...he second half. We also vary the spliting point. The results are qualitatively the same, but the predictability tends to be smaller and the e ects of higher moments smaller. Table3 -5 presents the performance results where the risky asset is proxyed by the Thailand stock index, the Mexico stock index, and the Dow Jones Industrials, respectively. The expected excess return is forecasted by the linear regression in... ..."

### Table 4 Portfolio Performance Comparisons (Investing In Mexico): E ects of Higher Moments and Predictability

### Table 5 Portfolio Performance Comparisons (Investing In The Dow): E ects of Higher Moments and Predictability

### Table 5 Predicted NSC moments by various methods for pipe in experiment 2$

### Table 5. Product Moment Correlation Coefficients for the Prediction of MR Using the Optimal Number of Clusters (k) and Using the Optimal m Values for the Fuzzy Clustering Runsa

2003

"... In PAGE 5: ... Further, analogous experiments were carried out in which the SYBYL package was used to calculate molar refractivity values for each of the Starlist molecules. The results of these experiments are shown in Table5 , where it will be seen that the fuzzy correlations are often higher than the crisp correlations. However, the differences here are noticeably less than in Table 3, with none of these being significant at the 0.... ..."

### Table 1.1: The baryon spin- avor SU(6) wavefunctions. quark moments, obtained by measuring the magnetic moments of any three baryons such as the proton, neutron, and magnetic moments, it is possible to nd numerical values for the baryon magnetic moments under SQM. Table 1.2 gives these predictions and previous experimental values of hyperon. The 0 - is a transition moment which can be predicted by the overlap of the 0 and wavefunctions from ? = h j Xi ~ ij i:

1995