“Forecasting Philippine Stock Market returns with Macroeconomic variables”
Kaine Cornelio R. Gandionco
ECN-4890, Research Methods
Abstract:
The specification and estimation of a model of the Philippine stock market based
on the constant growth model. Monthly data spanning from January 2000 to February
2011 was used. The empirical results showed that Industrial production positively
affected the Philippine Stock market, while exchange devaluations, inflation, real
domestic interest rates, and country risks all negatively impacted Philippine stock
performance.
I. Introduction
The Philippine stock market was one of the best performing stock markets in the year 2010;
it had a total return of 58.10 percent. Such high returns are not surprising for an emerging market
like the Philippines. An investment in the Philippine stock market can provide investors with
both higher returns and the potential for further portfolio diversification, but generally, the level
of risks inherent in the equity investments of an emerging market, such as the Philippines, is
much higher relative to that of comparable equity investments in developed economies. Thus, it
is crucial that the direction of the overall stock market is forecasted in order to avoid investing
during periods with suboptimal conditions.
Research on the modeling of stock returns in the Philippines is quite sparse in comparison to
that of developed countries. Which is quite unfortunate, because a model that would have some
predictive qualities over the direction of the returns of such a stock market would be quite
beneficial for an investor.
A country’s stock market is known as one of the leading indicators of its aggregate economy.
Therefore, the model can also be used to predict the direction of the aggregate economy of the
Philippines based on forecasted stock returns. A model with the ability to forecast future stock
returns allows investors to time the market and determine when to invest, such a model can also
be used in determining the optimal conditions for which to invest in the Philippine stock market.
The Philippine Stock market concentrated in the Philippine stock exchange, which is one of
Asia’s oldest exchanges. It consists of 258 publicly traded companies, and has a total market
capitalization of roughly $130 Billion.
II. Literature Review
Stock Market modeling is usually done through the present value model, which Samuelson had
shown was equivalent to the fair game model. Stock prices a function of expected stream of future
dividends and the discount rate (Samuelson, 1965 and 1975). Therefore, the expected return that
would be realized upon the sale of the stock is already included, since it would be dependent on
the present value of the future dividend streams. Gordon and Shapiro further simplified the
present value model with the assumption of a constant dividend growth, were by, only a single
expected growth rate for the stock would be needed, rather than forecasting the different dividend
streams for each period, thus, the equilibrium price of a stock would now be a function of its
current dividend, expected growth rate, and the discount rate (Gordon and Shapiro, 1956).
Since Stock prices have now been established as a function of Dividends, expected growth
rate, and the discount rate, then any factors that would influences either of these variables would
also have an influence on the stock’s price. The empirical results from the work of Chen et al has
shown that economic variables such as inflation and interest rates have an effect on the discount
rate, while industrial production also had an effect on the growth of future cash flows and
dividend streams (Chen et al, 1986)
The discount rate has three components, a risk free rate (i), an inflation premium (ii), and a
risk premium (iii). Investors want to be compensated for inflation in order to prevent the loss of
their principal investment’s purchasing power over time, and they want to be compensated for
the level of risk that they take, which is what they expect to gain over and above the risk free
rate, which is to compensate them for their opportunity costs. Mankiw and Miron showed in their
expectations theory of the term structure of interest rates, that the long-term interest rates of a
security is the average of all the expected future short-term interest rates that are expected to
prevail over the maturity of that security (Mankiw and Miron, 1986). The long-run interest rate
can be used as a substitute for short-term rates that is assumed to be the risk-free rate in the
present value model, because it would capture the expected short-term interest rates. The Risk
premium is an addition to the discount rate that compensates investors for the asset’s inherent
risks, which would include several uncertainties, such as liquidity risks, exchange rate risks,
interest rate risks, purchasing power risks, financial risks, and country risks.
Andrade showed that the sovereign yield spreads could be proxied as a measure of country
risks, because it carries information such as the likelihood of a negative regime change in an
emerging market. In his model, the discount rate was a function of the sovereign debt yield
spreads (Andrade, 2005)
Exchange rate risk is one of the uncertainties that are built into the discount rate in the form
of a risk premium. Solnik showed that exchange rate fluctuations would affect the factor
loadings and associated risk premiums (Solnik, 1983). Zang showed that stock prices in
emerging markets were greatly influenced by exchange rate fluctuations, He found that currency
devaluations adversely affected stock returns, and led to an increase in market volatility (Zang,
2002).
According to the efficient market hypothesis, stock prices are constantly automatically
adjusting to new and relevant information. As new information is released, the large number of
investors will automatically act on the information in ways that will make prices fully reflect of
the new information (Fama, 1970).
III. Methods and Procedures
The model of the Philippine stock market is a corollary of the discussions of the influencing
macro-economic variables made in the previous section. The model is based primarily on the
constant growth model. The stock prices are driven by industrial production, the exchange rate,
short-term rates, inflation rate, and country risks.
Figure 1: Model
∆ log PSEi returns = f ( ∆ log Exchange ratet , ∆ log industrial productiont , ∆ log Inflation rate,
∆ log Short-term ratet , ∆ log Country riskst )
Variable Expected SignExchange rate -
Industrial Production +Inflation rate -
Short-term rate -Country risks -
The exogenous variables Inflation rate and Short-term rate are both components of the
discount rate in the present value, and it is known that the discount rate is inversely related to
stock prices. These variables have a negative effect on stock returns. Based on the existing
research on exchange rates and stock returns, the exchange rate and stock returns have a negative
relationship.
Industrial production is proxied for dividends, which would have normally been used in the
constant growth model. Industrial production and stock returns should have a positive
relationship.
Country risks is expected to have a negative relationship with stock returns, because the
changes in a country’s risk factor, such as the as political instability, could negatively affect
stock return.
Data:
The data used in modeling Philippine stock returns was from the period January 2001 to
February 2011.
Variable Description Frequency Measure Source
rPSEi PSEi index returns MonthlyStock Market
Performance
Bangko Sentral ng
Pilipinas Website.
E
Philippine Peso to
U.S dollar exchange
rate.
Monthly
Proxy for
Exchange rate
risks
Bangko Sentral ng
Pilipinas Website.
P
Philippine
Industrial
Production
MonthlyProxy for
Dividends
Banko Sentral ng
Pilipinas Website.
IPhilippine Inflation
rateMonthly
Proxy for
purchasing
power risks
Banko Sentral ng
Pilipinas Website.
S
10 year Philippine
Treasury Note
yields
Monthly Risk-free rateUnion Bank of the
Philippines
K
Yield Spread
between 10 Year
ROP bond and 10
year U.S Treasury
note
MonthlyProxy for
country risks
Union Bank of the
Philippines
-5.0% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Figure 2: PSEi vs Exchange Rate
Exchange Rate
PS
EI
Figure 2 shows that the Exchange rate seems to have a nonlinear negative relationship with
the Philippine stock market.
4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0% Figure 3: PSEI vs 10Y T-note yield
10Y T-note yield
PS
EI
Figure 3 shows that the 10 year treasury note yield has no discernable relationship with the
Philippine stock returns.
1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% 9.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%Figure 4: PSEI vs Inflation Rate
Inflation rate
PS
EI
Figure 4 shows that the inflation rate seems to have a negative effect on the Philippine stock
returns.
-2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0% Figure 5: PSEI vs ROP spread
Sovereign debt yieldspread
PS
EI
Figure 5 shows that the ROP yield spread seems to have a negative effect on the Philippine
stock returns.
-25.0% -20.0% -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0% 25.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%Figure 6: PSEI vs Industrial production
Industrial Production
PSE
I
Figure 6 shows that industrial production seems to have a positive effect on the Philippine
stock returns.
Regression Analysis:
Models that are specified with non-stationary data can result in spurious regressions. This
can cause statistically significant relationships to arise when in fact there are none. It is therefore
vital to utilize only stationary data in specifying a model. Financial and economic time series
data are generally known to be non-stationary. This was resolved by specifying the model with
logarithms in order to eliminate any non-stationarity in the data set. The data was tested for non-
stationarity through the Augmented Dickey fuller test, with the results shown in table 1 in the
appendix.
After ensuring that all the time series data are all stationary, a test for multicollinearity was
performed between the exogenous variables of the model. A correlation matrix was constructed
for all exogenous variables. The matrix shows high correlation between the variables short-term
rates and exchange rate. It also shows a high correlation between the variables country risk and
short-term rates. The high correlation amongst the exogenous variables suggests that
multicollinearity exists.
The estimation of a model with OLS estimation when multicollinearity exists between the
exogenous variable, will result in specifications that are statistically insignificant. A generalized
least square estimation was instead used to specify the model. The generalized least squared
method of regression is used in cases when multicollinearity exists between the variables.
The GLS estimation was used estimate a total of 9 regressions in order to determine the best
specification with the highest explanatory power and statistically significant variables. The initial
specification will be the proposed model.
In order to improve the statistical significance and the explanatory power of the model, lags
were used for the variable short-term rate. A one period lag for specification (II), two period lag
for specification III), and a three period lag for specification (IV).
For specification (V), the variable short-term rate was dropped in an attempt to improve the
model. The possibility of nonlinear relationships amongst the exogenous variables and the
Philippine stock returns were examined in the specifications VI, VII, VIII, and IX.
Results:
All the exogenous variables in the model were found to have exhibited coefficient signs that
were consistent with the expected relationship of these variables and the Philippine stock returns,
this observation was found through out the different regressions. It was found through the initial
specification that the variables Exchange rate, inflation rate, and short-term rates were
statistically insignificant, but the initial specification captures the expected coefficient signs of
these variables.
The variable short-term rate was lagged with varying degrees in specifications II, III, and IV.
The lagging of the variable short-term rates did not produce improvements in the statistical
significance of the variable and the wellness of fit for the model.
The removal of the variable short-term rates had resulted in an improvement of the statistical
significance of all the exogenous variables with the exception of the variable exchange rate.
Table 1: Linear Regression
I II III IV V
R2 24.40% 22.81% 24.79% 25.78% 23.48%
Adjusted R2 20.80% 19.48% 21.52% 22.22% 20.88%
Standard Error 0.0576281 0.0575991 0.05694 0.056 0.05759
ValueP
value ValueP
value ValueP
Value ValueP
Value ValueP
Value
Intercept 0.00309 0.557 0.00387 0.466 0.00513 0.33 0.00555 0.288 0.00335 0.524
Exchange rate-
0.56743 0.122 -0.60729 0.09 -0.59804 0.094 -0.51328 0.146 -0.66801 0.057Industrial production 0.10689 0.043 0.09873 0.064 0.10383 0.05 0.12989 0.018 0.10833 0.04
Inflation rate-
2.28506 0.08 -2.13688 0.102 -2.38873 0.066 -2.04859 0.108 -2.55714 0.045
Short-term rate-
0.96025 0.352 0.25765 0.75 1.07101 0.181 0.1736 0.833 N/A N/A
Country risks-
3.19454 0.001 -4.87776 0 -4.87082 0 -5.22441 0 -3.66211 0
Specifications VI, VII, VIII, and IX were specified as nonlinear models in order to determine
if there were any nonlinear relationships between the Philippine stock market, and the exogenous
variables.
As shown in specification IX, the exchange rate was the only variable that had a statistically
significant nonlinear term. The introduction of the nonlinear variable for exchange rate also
resulted in a specification that had statistically significance in all variables and the highest
explanatory power.
Table 2: Nonlinear Regression
VI VII VIII IXR2 23.48% 23.63% 24.48% 28.34%Adjusted R2 20.21% 20.37% 21.25% 25.28%Standard Error 0.05784 0.05783 0.05746 0.05597 Value P value Value P value Value P Value Value P ValueIntercept 0.0033 0.613 0.00395 0.466 0.0044 0.41 0.0134 0.034
Exchange rate
-0.6684
1 0.059 -0.68783 0.052 -0.5891 0.097 -0.749 0.029Industrial Production
0.10836 0.041 0.10536 0.048 0.0993 0.062 0.1146 0.026
Inflation rate
-2.5582
1 0.046 -2.60695 0.042 -2.256 0.081 -2.5164 0.042-
IV. Summary and Conclusions
Based on the proposed model, It was found that only industrial production and country
risk were significant in predicting Philippine stock returns, while the exchange rate, inflation
rate, and the short-term rate were found to be insignificant, but despite that, all these variables
had the expected relationships with the Philippine stock returns. The most significant variable
was country risks. The lack of statistical significance does not discount the theoretical
relationship between these variables and the stock returns. But, the proposed model in its
unaltered form cannot be used to predict with confidence the future returns of the Philippine
stock market.
Allowing for modifications of the proposed model, it was found that the removal of the
short-term rates in the specification resulted in an improvement of the p values of the exchange
rate and inflation rate, which was quite surprising. It seems that this may have been due to the
short-term rate being somewhat of a determinant of the exchange rate and inflation rate, which
would explain the multicollinearity amongst the exogenous variables. But then, the measure for
country risk also showed a high correlation with the short-term rate and that had significance
all through out. It would appear that the better explanation would be that exchange rate risks is
already inherent in the Philippine treasury note yield, because it is denominated in Philippine
pesos. While, the sovereign debt does not have any exchange rate risks as it is denominated in
U.S dollars. A risk premium that accounts for exchange rate risks is already built into the
Philippine Treasury note yield; the inclusion of the variables exchange rate and short-term rate
in the model may have had the effect of double counting.
In the final specification, as shown below in Figure 7, the addition of a nonlinear
relationship between the exchange rate and the Philippine stock returns into the model, had
vastly improved the model’s predictive powers. It would appear that the final specification
could be used with confidence to forecast the Philippine stock market returns.
Figure 7: nonlinear Specification (Equation IX)
Philippine Stock returns = 0.0133604 - 0.749011 Exchange rate + 0.114586 Industrial
production - 2.51636 Inflation rate - 3.4899 Country risks - 41.2279 (Exchange rate)2
Variable T statisticExchange rate 2.21110
Industrial production 2.25267Inflation rate -2.05200Country risks 4.55745
(Exchange rate)2 -2.81812
Industrial production was estimated to have a positive effect on the stock returns in the
Philippines. Periods of high levels of industrial production should lead to higher stock prices in
the Philippines.
The exchange rate was estimated to have a nonlinear negative influence on the Philippine
stock returns. Since the Philippines is a net importer of goods and raw materials, a strong
Philippine peso relative to the U.S dollar is beneficial, because it makes these imports cheaper,
but the nonlinear relationship shows that the benefits derived from the exchange rate
appreciation seems to exhibit diminishing marginal returns. The cheaper costs of raw materials
for Philippine business results in an increase in their profit margins. This would generate an
optimistic outlook on Philippine businesses that would increase Philippine stock prices.
The inflation rate was estimated to have a negative effect on the stock returns. This is
consistent with the theoretical relationship between the inflation rate and stock prices. Investors
should be wary of periods of high inflation rates in the Philippines, as this will tend to depress
stock prices.
Country risk was estimated to be negative and very significant. It poses a serious threat for
investors in the Philippine stock market, because any adverse changes in the political and
social situation of the Philippines could result in dramatic changes in the stock market.
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Appendix:
Table 1: Augmented Dickey Fuller Test
Dickey Fuller Test Statistic p-value
rpsei -4.632313739 0.01
Exchange Rate -4.462884906 0.01
Inflation rate -4.547599323 0.01
Industrial Production -6.933930658 0.01
10 Year T-note -6.121390944 0.01
Sovereign debt yield spread -6.527660801 0.01
Critical Value 1% -3.5682
Critical Value 5% -2.9215
Critical Value 10% -2.5983
Table 2: Correlation Matrix
r E I P S Kr 1E 0.113039 1I -0.13523 0.294334 1P 0.105066 0.000253 -0.01955 1S -0.08332 0.689187 0.361363 -0.01888 1K -0.06311 0.56471 0.329255 -0.05099 0.897988 1
Table 3: Data
Date rpsei E I3/1/11 1.94% 43.66 4.30%2/1/11 -2.96% 43.7 3.50%1/3/11 -7.61% 44.17 3.30%12/1/10 6.26% 43.95 3.40%11/2/10 -7.38% 43.49 3.50%10/1/10 4.11% 43.44 3.30%9/1/10 14.97% 44.31 3.80%8/2/10 4.06% 45.18 4.20%7/1/10 1.61% 46.32 3.90%6/1/10 3.05% 46.3 3.80%5/4/10 -0.53% 45.6 3.90%4/5/10 4.06% 44.63 4.00%3/1/10 3.84% 45.74 3.80%2/1/10 3.11% 46.31 3.60%1/4/10 -3.26% 46.03 3.00%12/1/09 0.25% 46.421 3.20%11/3/09 4.69% 47.032 2.70%10/1/09 3.84% 46.851 2.71%9/1/09 -2.89% 48.139 2.80%
8/3/09 3.07% 48.161 2.90%7/1/09 14.78% 48.146 3.60%6/1/09 2.04% 47.905 3.90%5/4/09 13.59% 47.524 4.40%4/1/09 5.90% 48.217 5.00%3/2/09 6.09% 48.458 5.60%2/2/09 2.58% 47.585 6.40%1/5/09 -2.55% 47.207 6.90%12/2/08 -5.01% 48.094 7.30%11/3/08 1.05% 49.186 7.90%10/2/08 -24.07% 48.025 7.80%9/1/08 -4.41% 46.692 7.50%8/1/08 4.31% 44.877 7.00%7/1/08 4.76% 44.956 6.30%6/2/08 -13.00% 44.281 6.60%5/2/08 2.82% 42.902 6.20%4/1/08 -7.87% 41.82 5.90%3/3/08 -4.64% 41.252 4.80%2/1/08 -4.16% 40.671 4.00%1/2/08 -9.82% 40.938 3.40%
rpsei E I12/3/07 1.20% 41.743 2.60%11/5/07 -4.80% 43.218 2.30%10/1/07 5.21% 44.38 2.40%9/3/07 6.17% 46.131 2.70%8/1/07 -3.88% 46.074 2.90%7/2/07 -4.48% 45.625 3.00%6/4/07 5.48% 46.16 2.50%5/2/07 6.24% 46.814 2.60%4/2/07 2.10% 47.822 2.60%3/1/07 4.44% 48.517 2.60%2/1/07 -5.30% 48.381 3.00%1/2/07 8.61% 48.914 3.90%12/4/06 6.96% 49.467 4.60%11/2/06 2.95% 49.843 4.70%10/2/06 5.94% 50.004 5.10%9/1/06 10.57% 50.401 5.00%8/1/06 -3.29% 51.362 5.30%7/3/06 9.73% 52.398 5.40%6/1/06 -5.11% 53.157 5.80%5/2/06 1.13% 52.127 6.10%4/3/06 3.40% 51.36 6.30%
3/1/06 3.44% 51.219 6.50%2/1/06 -1.05% 51.817 6.30%1/2/06 2.35% 52.617 5.70%12/1/05 -0.18% 53.612 5.90%11/2/05 7.12% 54.561 6.10%10/3/05 0.93% 55.708 6.30%9/1/05 0.27% 56.156 6.50%8/1/05 -3.17% 55.952 6.60%7/1/05 3.95% 56.006 6.80%6/1/05 -0.27% 55.179 7.10%5/3/05 4.03% 54.341 7.60%4/1/05 -5.12% 54.492 7.80%3/1/05 -6.02% 54.44 8.00%2/1/05 2.99% 54.813 8.10%1/3/05 10.79% 55.766 7.90%12/1/04 -0.44% 56.267 7.80%11/1/04 0.66% 56.231 7.60%10/1/04 3.26% 56.351 6.90%9/1/04 11.50% 56.336 6.60%
rpsei E I
8/2/04 -0.31% 56.216 6.40%
7/1/04 0.34% 56.009 6.20%
6/1/04 4.50% 56.181 5.30%
5/3/04 -2.81% 55.837 4.70%
4/1/04 9.17% 55.858 4.30%
3/1/04 -3.97% 56.357 4.30%
2/2/04 -1.67% 56.275 4.10%
1/1/04 4.57% 56.085 4.10%
12/1/03 9.78% 55.569 3.80%
11/3/03 -6.09% 55.767 3.90%
10/1/03 7.83% 55.245 3.80%
9/1/03 8.77% 54.942 3.90%
8/1/03 -3.84% 55.113 3.70%
7/1/03 1.44% 54.689 3.60%
6/2/03 13.89% 53.706 3.20%
5/1/03 0.52% 53.282 2.50%
4/1/03 2.74% 52.817 2.60%
3/3/03 2.00% 53.532 2.40%
2/3/03 -3.54% 54.345 2.90%
1/1/03 3.76% 53.799 2.90%
12/2/02 -2.75% 53.096 2.50%
11/1/02 -0.12% 53.589 2.40%
10/1/02 -7.16% 53.017 2.60%
9/2/02 2.35% 52.447 2.70%
8/1/02 -1.77% 51.809 3.00%
7/1/02 -2.86% 51.287 2.60%
6/3/02 -12.06% 50.418 2.90%
5/1/02 -2.31% 49.966 3.50%
4/1/02 -4.10% 50.744 3.50%
3/1/02 -0.18% 51.148 3.50%
2/1/02 7.58% 51.354 3.20%
1/1/02 11.90% 51.201 3.70%
12/3/01 3.51% 51.404 4.50%
11/1/01 13.60% 52.024 5.00%
10/1/01 -12.99% 51.935 6.10%
9/3/01 -9.79% 51.355 6.80%
8/1/01 -7.15% 51.21 7.00%
7/2/01 -3.35% 53.562 7.40%
6/1/01 0.55% 52.366 7.20%
5/1/01 1.70% 50.584 7.40%
4/2/01 -4.67% 51.218 7.40%
3/1/01 -10.36% 49.378 7.60%
2/1/01 -4.36% 48.263 7.40%
1/1/01 12.88% 49.412 7.50%
Date P T S3/1/11 0.60% 7.59% 1.28%2/1/11 0.36% 7.32% 0.97%1/3/11 0.48% 7.20% 0.90%12/1/10 0.98% 6.10% 0.36%11/2/10 1.43% 6.00% 0.79%10/1/10 4.54% 5.96% 0.94%9/1/10 0.52% 6.94% 1.63%8/2/10 -1.29% 7.60% 2.09%7/1/10 0.91% 7.60% 1.62%6/1/10 1.65% 7.66% 1.62%5/4/10 6.02% 7.93% 1.45%4/5/10 0.28% 8.00% 1.11%3/1/10 5.87% 8.11% 1.03%2/1/10 0.30% 8.04% 1.21%1/4/10 -13.15% 7.98% 1.16%12/1/09 2.39% 8.09% 1.00%11/3/09 1.75% 7.93% 1.55%10/1/09 4.51% 7.95% 1.36%9/1/09 6.30% 8.03% 1.51%8/3/09 0.60% 7.98% 1.39%7/1/09 2.71% 8.01% 1.29%6/1/09 2.22% 8.11% 1.34%
5/4/09 10.11% 7.95% 1.30%4/1/09 -1.29% 8.13% 1.72%3/2/09 19.67% 8.16% 2.18%2/2/09 0.00% 8.08% 1.83%1/5/09 -31.72% 7.49% 1.63%12/2/08 -3.53% 7.44% 2.21%11/3/08 -9.74% 9.45% 2.74%10/2/08 0.80% 9.48% 1.68%9/1/08 5.19% 8.14% 1.03%8/1/08 0.26% 8.06% 1.01%7/1/08 -4.30% 9.66% 1.81%6/2/08 7.36% 9.43% 1.67%5/2/08 3.39% 8.93% 1.30%4/1/08 6.32% 8.58% 1.38%3/3/08 1.64% 7.27% 0.91%2/1/08 0.38% 7.07% 0.71%
P T S12/3/07 7.18% 6.58% -0.09%11/5/07 0.54% 6.97% 0.21%10/1/07 0.34% 7.08% -0.23%9/3/07 0.97% 7.15% -0.30%8/1/07 1.26% 7.88% 0.18%7/2/07 0.35% 7.47% -0.30%6/4/07 3.71% 7.42% -0.58%5/2/07 1.85% 7.04% -0.68%4/2/07 -5.66% 7.25% -0.28%3/1/07 15.02% 7.42% -0.20%2/1/07 -9.39% 6.83% -0.47%1/2/07 1.11% 6.95% -0.66%12/4/06 5.14% 6.38% -0.88%11/2/06 -2.04% 6.70% -0.44%10/2/06 0.74% 7.68% 0.00%9/1/06 74.65% 8.26% 0.32%8/1/06 -42.90% 9.10% 0.72%7/3/06 -2.12% 9.87% 0.93%6/1/06 3.44% 10.30% 1.03%5/2/06 3.86% 10.06% 0.91%4/3/06 -0.57% 7.44% -0.60%3/1/06 4.65% 7.84% -0.16%2/1/06 -1.21% 9.10% 0.91%1/2/06 -14.12% 9.83% 1.37%12/1/05 0.58% 10.88% 2.14%11/2/05 -2.84% 10.88% 2.04%
10/3/05 9.35% 11.91% 2.57%9/1/05 3.24% 11.96% 2.83%8/1/05 0.24% 12.02% 3.19%7/1/05 2.52% 12.24% 3.06%6/1/05 -0.08% 12.03% 3.28%5/3/05 2.33% 12.00% 3.20%4/1/05 8.67% 12.11% 3.06%3/1/05 -0.85% 12.28% 2.86%2/1/05 1.09% 12.46% 3.12%1/3/05 -10.24% 12.49% 3.36%12/1/04 3.14% 13.87% 4.08%11/1/04 -1.49% 13.69% 3.85%10/1/04 3.24% 13.59% 4.10%
P T S
8/2/04 -4.71% 13.44% 3.94%
7/1/04 -0.79% 12.68% 3.11%
6/1/04 5.04% 12.93% 3.14%
5/3/04 2.95% 12.64% 2.93%
4/1/04 2.19% 12.04% 2.70%
3/1/04 1.78% 12.63% 3.72%
2/2/04 1.25% 13.13% 3.89%
1/1/04 -1.04% 11.64% 2.82%
12/1/03 0.45% 11.79% 2.80%
11/3/03 -4.89% 11.72% 2.69%
10/1/03 1.84% 11.27% 2.43%
9/1/03 -0.05% 11.56% 2.97%
8/1/03 -1.19% 11.92% 2.70%
7/1/03 1.30% 11.58% 2.46%
6/2/03 -0.39% 11.69% 3.47%
5/1/03 4.16% 11.54% 3.55%
4/1/03 -7.47% 12.99% 3.90%
3/3/03 10.80% 12.93% 3.93%
2/3/03 -2.99% 12.99% 4.08%
1/1/03 3.51% 12.30% 3.38%
12/2/02 -3.87% 12.57% 3.71%
11/1/02 -0.49% 12.43% 3.24%
10/1/02 3.11% 12.48% 3.56%
9/2/02 4.97% 12.43% 3.83%
8/1/02 1.24% 12.75% 3.51%
7/1/02 -12.99% 12.59% 3.05%
6/3/02 2.66% 13.08% 2.99%
5/1/02 4.28% 13.36% 2.94%
4/1/02 -2.36% 13.07% 2.73%
3/1/02 6.22% 14.41% 3.22%
2/1/02 4.65% 14.50% 3.82%
1/1/02 -7.02% 14.44% 3.59%
12/3/01 1.29% 15.53% 4.25%
11/1/01 -5.09% 15.73% 4.66%
10/1/01 2.15% 17.62% 6.27%
9/3/01 -6.14% 15.92% 4.95%
8/1/01 8.99% 15.77% 4.61%
7/2/01 0.30% 15.75% 4.38%
6/1/01 14.74% 15.18% 3.68%
5/1/01 8.73% 15.02% 3.58%
4/2/01 -15.17% 15.38% 3.88%
3/1/01 20.94% 14.66% 3.87%
2/1/01 8.96% 14.89% 4.38%
1/1/01 -19.51% 16.29% 4.49%