1. Price of Gold and US Dollar Index Dwarakamayi Polakam Jennifer Griffeth Ashley Arlotti Rui Feng Ying Fan Qi He Qi Li Group C Presentation

2. Overview 1 US Dollar Index 1.1 Analysis of DOLLARINDEX 1.2 Analysis of DLNDOLLAR 1.3 AR Model 1.4 Forecasting 3 Relationship Between Gold and US Dollar 3.1 The Cross Correlogram 3.2 Analysis of w and resm (Distributed Lag Model) 3.3 Analysis of DLNGOLD and DLNDOLLAR 3.4 Causality Test 3.5 VAR Analysis 2 Price of Gold 2.1 Analysis of GOLD 2.2 Analysis of DLNGOLD 2.3 AR Model 2.4 GARCH Model 2.5 Forecasting

3. Part 1: US Dollar Index The First Model: DLNDOLLAR

4. 1.1 Analysis of DOLLARINDEX (1) Trace

5. 1.1 Analysis of DOLLARINDEX (2) Histogram

6. 1.1 Analysis of DOLLARINDEX (3) Correlogram

7. 1.1 Analysis of DOLLARINDEX (4) Unit Root Test

8. 1.2 Analysis of DLNDOLLAR (1) Trace

9. 1.2 Analysis of DLNDOLLAR (2) Histogram

10. 1.2 Analysis of DLNDOLLAR (3) Correlogram

11. 1.2 Analysis of DLNDOLLAR (4) Unit Root Test

12. 1.3 AR(1), AR(2) Model (1) Add AR(1) and AR(2)

13. 1.3 AR(1), AR(2) Model (2a) Diagnostic - Actual, fitted and residual

14. 1.3 AR(1), AR(2) Model (2b) Diagnostic - Correlogram of residuals

15. 1.3 AR(1), AR(2) Model (2c) Diagnostic - Histogram of residuals

16. 1.3 AR(1), AR(2) Model (2d) Diagnostic - Serial Correlation test on residuals

17. 1.3 AR(1), AR(2) Model (2e) Diagnostic - Correlogram of residual squared

18. 1.3 AR(1), AR(2) Model (2f) Diagnostic - Heteroskedasticity test

19. 1.4 Forecasting (1) Confidence Interval of Two Standard Error

20. 1.4 Forecasting (2) Forecast for Next Eight Months

21. Part 2: Price of Gold The Second Model: DLNGOLD

22. 2.1 Analysis of GOLD (1) Trace

23. 2.1 Analysis of GOLD (2) Histogram

24. 2.1 Analysis of GOLD (3) Correlogram

25. 2.1 Analysis of GOLD (4) Unit Root Test

26. 2.2 Analysis of DLNGOLD (1) Trace

27. 2.2 Analysis of DLNGOLD (2) Histogram

28. 2.2 Analysis of DLNGOLD (3) Correlogram

29. 2.2 Analysis of DLNGOLD (4) Unit Root Test

30. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (1) AIC, SIC, etc for Different Models AICSICHQCDWACPC Serial Correlati on AR(1) AR(2) AR(11)-3.257-3.23-3.2452.000077,8,217,8,14no AR(1) AR(2) AR(7) AR(8) AR(11) AR(18)-3.309-3.254-3.2871.9924195no AR(1) AR(2) AR(7) AR(8) AR(11) AR(18) AR(19)-3.3114-3.2464-3.28581.978217--no AR(1) AR(2) AR(11) MA(7) MA(8) MA(11)-3.228-3.183-3.212.00089829,3535yes AR(1) AR(2) AR(11) MA(7) MA(8) MA(11) MA(29) M,A(35)-3.234-3.17114 - 3.209451.989275--no

31. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (2) Add AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18)

32. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3a) Diagnostic - Actual, fitted and residual

33. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3b) Diagnostic - Correlogram of residuals

34. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3c) Diagnostic - Histogram of residuals

35. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3d) Diagnostic - Serial Correlation test on residuals

36. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3e) Diagnostic - Correlogram of residual squared

37. 2.3 AR(1), AR(2), AR(7), AR(8), AR(11) and AR(18) Model (3f) Diagnostic - Heteroskedasticity test

38. 2.4 GARCH Model (1) Add GARCH

39. 2.4 GARCH Model (2a) Diagnostic - Correlogram of residuals

40. 2.4 GARCH Model (2b) Diagnostic - Histogram of residuals

41. 2.4 GARCH Model (2c) Diagnostic - Correlogram of residual squared

42. 2.4 GARCH Model (2d) Diagnostic - Heteroskedasticity test

43. 2.5 Forecasting (1) Confidence Interval of Two Standard Error

44. 2.5 Forecasting (2) Forecast for Next Eight Months

45. Part 3: Relationship Between Gold and US Dollar

46. 3.1 The Cross Section Correlogram

47. 3.2 Analysis of w and resm (1) Theoretical Analysis LNGOLD(t) = h 0 LNDOLLAR(t) + h 1 LNDOLLAR(t-1) + h 2 LNDOLLAR(t-2) +…+ e(t) = (h 0 + h 1 Z + h 2 Z 2 +…) LNDOLLAR(t) + e(t) = h(z)LNDOLLAR(t) + e(t) First Difference: DLNGOLD(t) = h(z) DLNDOLLAR(t) + e(t) Fit AR(2) model to DLNDOLLAR, B(z)*DLNDOLLAR = WN(t), B(z)* DLNGOLD(t) = h(z)* B(z)*DLNDOLLAR(t) + B(z)* e(t) W(t) = h(z) * resm + error(t)

48. 3.2 Analysis of w and resm (2a) Analysis of w and resm

49. 3.2 Analysis of w and resm (2b) Analysis of w and resm with AR terms

50. 3.2 Analysis of w and resm (3a) Diagnostic - Actual, fitted and residual

51. 3.2 Analysis of w and resm (3b) Diagnostic - Correlogram of residuals

52. 3.2 Analysis of w and resm (3c) Diagnostic - Serial Correlation test on residuals

53. 3.2 Analysis of w and resm (3d) Diagnostic - Heteroskedasticity test

54. 3.3 Analysis of DLNGOLD and DLNDOLLAR (1) Analysis of DLNGOLD and DLNDOLLAR

55. 3.3 Analysis of DLNGOLD and DLNDOLLAR (2a) Diagnostic - Actual, fitted and residual

56. 3.3 Analysis of DLNGOLD and DLNDOLLAR (2b) Diagnostic - Correlogram of residuals

57. 3.3 Analysis of DLNGOLD and DLNDOLLAR (2c) Diagnostic - Serial Correlation test on residuals

58. 3.3 Analysis of DLNGOLD and DLNDOLLAR (2d) Diagnostic - Heteroskedasticity test

59. 3.4 Causality Test Pairwise Granger Causality Tests Date: 05/31/11 Time: 08:00 Sample: 1973:01 2011:12 Lags: 25 Null Hypothesis:ObsF-StatisticProbability DLNDOLLARINDEX does not Granger Cause DLNGOLD4340.912690.58797 DLNGOLD does not Granger Cause DLNDOLLARINDEX1.550180.04616

60. 3.5 VAR Analysis (1a) VAR Analysis DLNGOLDDLNDOLLARINDEX DLNGOLD(-1) 0.185969 0.008348 (0.05448) (0.01922) (3.41364) (0.43432) DLNGOLD(-2) -0.150826 0.025431 (0.05538) (0.01954) (-2.72354) (1.30163) DLNGOLD(-7) 0.112218 0.006677 (0.05538) (0.01954) (2.02625) (0.34176) DLNGOLD(-11) 0.139112-0.022972 (0.05538) (0.01954) (2.51182)(-1.17571) DLNGOLD(-18) -0.111669 0.000383 (0.05360) (0.01891) (-2.08344) (0.02024) DLNGOLD(-19) -0.046602 0.043418 (0.05325) (0.01879) (-0.87519) (2.31119) DLNDOLLARINDEX(-1) -0.156528 0.376342 (0.15434) (0.05445) (-1.01416) (6.91147) DLNDOLLARINDEX(-18) -0.159882 0.120925 (0.16132) (0.05691) (-0.99108) (2.12471)

61. 3.5 VAR Analysis (1a) Impulse Analysis

62. 3.5 VAR Analysis (1b) VAR Analysis

63. Conclusion

64. Thank you!