HenryB-A5-0329-6EdwardB-A6-0019-9VeasnaB-A6-0047-1Marco B-A6-0193-3

• Why we choose this topic• Data Description• Data analysis• Conclusion

Findings of Eric J Levin and Robert E Wright

Gold price and Inflation go simultaneously: Gold can be a inflation hedge in the long-run

• Monthly gold price From 1973.Jan to 2008.Nov 431 data points

• London pm fix ,quoted in us dollars . The market-clearing price of gold set twice a day in

London is commonly referred to as the London fixing price (am or pm).

The price is also the international benchmark price.

• Multi-linear regression

Forecast gold price by some determinates, such as CPI, exchange rate, DJ index etc. (Source from U.S department of labor and Federal Reserve)

• ARIMA

Forecast gold price only by previous prices, regardless of other factors.

Regression Model- Determinants

• CPI of America

- General inflation of all goods

•Exchange rate of USD against world currencies

- Gold price is in USD

- Exchange rate and the economy condition

•Dow-Jones index

- Less risk investment tool when stock market performance is bad

Oil price Gold price and Oil price are closely related Oil price indicates inflation

Real interest rate Higher interest rate, lower gold price Depositing in bank versus investing in gold

Regression Model- Determinants (continued)

Gold price= 115.5702+2.5385CPI-0.0198DOWindex-2.2859exchange rate +4.849Oil price+14.90248real interest rate+95.276Dummy

Regression Model- Result

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Residual Actual Fitted

Dependent Variable: GOLD_PRICEMethod: Least SquaresDate: 12/12/08 Time: 16:44Sample: 1 431Included observations: 431

Variable Coefficient Std. Error t-Statistic Prob.  

C 115.5702 27.72153 4.168968 0.0000CPI 2.538530 0.129165 19.65334 0.0000

DOW_INDEX -0.019855 0.001615 -12.29644 0.0000EXCHANGE_RATE -2.285975 0.231132 -9.890334 0.0000

OIL 4.844002 0.181572 26.67817 0.0000REAL_INTEREST_RATE 14.90248 1.238273 12.03489 0.0000

DUMMY 95.27625 9.008833 10.57587 0.0000

R-squared 0.886812     Mean dependent var 362.1076Adjusted R-squared 0.885211     S.D. dependent var 154.4284S.E. of regression 52.32121     Akaike info criterion 10.76879Sum squared resid 1160704.     Schwarz criterion 10.83483Log likelihood -2313.674     F-statistic 553.6656Durbin-Watson stat 0.266398     Prob(F-statistic) 0.000000

Statistical result

Regression Model- Special event and Dummy variable

• Stock collapse will happen once about every 10 years, and investors will invest more in gold, hence the gold price will increase in this period.

• Although gold price changes in these stock collapses can be reflected by the fluctuation of some factors such as stock market, oil price and exchange rate etc, investors’ risk inverse affects gold price more significant.

A dummy variable should be added when there is a market crash in order to increase the impact on gold price forecasting.

Special event and Dummy variable- continued

Huge Fluctuation of gold price from 1979-1983

•Gold price soared during 1979-1980• Irrational investment in gold caused by bad expectation to future• War in 1980

•Gold price fell down sharply in 1982•Bubble explosion

•Gold price increased during 1982-1983•Economy recovery•Investors’ confidence back

Huge Fluctuation of gold price from 1979-1983 is due to war and bubble explosion happened simultaneously, which is very rare. And this kind event can not be predicted at all. Therefore, we can ignore it, that's why there is a big residual in our result.

Forecasting the gold price of 2007-2008 MAPE=0.10

Regression model can not account for significant fluctuation in SHORT PERIOD caused by irrational investing behavior, gold future speculation etc. Such as the Global Financial crisis 2008.

Regression Model- Accuracy and implication

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Autocorrelation Function for US$(with 5% significance limits for the autocorrelations)

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MAPE 42.7MAD 99.1MSD 16824.6

Accuracy Measures

ActualFits

Variable

Trend Analysis Plot for US$Linear Trend Model

Yt = 168.5 + 0.781*t

ARIMA method- Pattern of gold price

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GOLDPRICE1

ARIMA method- First difference

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Partial Autocorrelation Function for first d(with 5% significance limits for the partial autocorrelations)

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Autocorrelation Function for first d(with 5% significance limits for the autocorrelations)

ARIMA method- Autocorrelation and Partial Autocorrelation

ARIMA Coefficient

Significant P-value of LBQ at

lag12 ,24,36,48 AIC BIC

(1,1,0) Lag12,24,36,48 6.131482 12.26

(2.1.0) Do not have 6.117008 12.2511

(0,1,1) Lag12,24,36,48 6.123105 12.2481

(0,1,2)One

insignificant 0.0656.1197

12.2538

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insignificant Lag24,36,486.122717

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Insignificant AR(1) and

MA(1) -6.115005

12.2672

(1,1,2) All insignificant - 6.123772 12.2669

ARIMA method- Results of different ARIMA models

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ARIMA method- Graphical Result

Forecasting of gold price from 2007 January to June by using previous data:

ARIMA model can only forecast next several period

Period Forecasts

Lower bound

Upper bound

Actual

January 637.221 594.473 679.97 629.418

February 633.175 566.945 699.405 631.166

March 631.144 550.416 711.872 664.745

April 631.327 539.256 723.398 654.895

May 631.639 529.364 733.914 679.368

June 631.671 519.998 743.344 666.919

ARIMA method- Forecasting and Implication

Conclusion- Comparison of ARIMA and Regression for gold price forecasting

ARIMA

• More accurate in short period forecasting

• Only requires historical gold price data

Regression

• Appropriate for predicting long-run trend

• More difficult in choosing indicators

Q&A