US Dollar Index (DXY): Modeling against Domestic and Global Macro-Economic Factors
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Transcript of US Dollar Index (DXY): Modeling against Domestic and Global Macro-Economic Factors
US Dollar Index – DXYModeling against Domestic and Global Macro-
Economic Factors
3/9/2013Rama KappagantulaKiran Sankuru Global Equity Fund
Kiran Sankuru | Rama Kappagantula
2
Goal US Dollar Index – DXY Domestic & Global Macroeconomic Factors
o Euroo Yeno VIXo S&Po Goldo BDIo Unemploymento Inflationo LEIo GDPo Money Supplyo Current Acct
3/9/2013
Kiran Sankuru | Rama Kappagantula
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Dollar Index
US Dollar Index – DXYo Started in 1973o Proxy for US $o Strength against world currencies
Euro, Yen, GDP, Canadian $, Swedish Krona, Swiss Franc
3/9/2013
History & Performance
1/3/
1994
8/3/
1994
3/3/
1995
10/3
/199
5
5/3/
1996
12/3
/199
6
7/3/
1997
2/3/
1998
9/3/
1998
4/3/
1999
11/3
/199
9
6/3/
2000
1/3/
2001
8/3/
2001
3/3/
2002
10/3
/200
2
5/3/
2003
12/3
/200
3
7/3/
2004
2/3/
2005
9/3/
2005
4/3/
2006
11/3
/200
6
6/3/
2007
1/3/
2008
8/3/
2008
3/3/
2009
10/3
/200
9
5/3/
2010
12/3
/201
0
7/3/
2011
2/3/
2012
9/3/
2012
50
60
70
80
90
100
110
120
130
DXY
Kiran Sankuru | Rama Kappagantula
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Process Data Exploration Analysis DM Methods Apply & Evaluate Interpretation & Performance Conclusion
3/9/2013
Kiran Sankuru | Rama Kappagantula
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Data
CIA.gov Dept. of Labor US Dept. of Treasury Conference Board
3/9/2013
Collection
Kiran Sankuru | Rama Kappagantula
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Data
Timeline Frequency Missing values
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Exploration
Predictor(s) Frequency Adjusted Frequency
VIX, S&P,OIL, Gold, 10YrTres,Euro, UKSterling, BDI, DXY and JPYen
Daily Daily
UnEmployment, PMI, Inflation, LEI, Debt, MoneySupply, TradeBalance
Monthly Daily
GDP, CurrentAccount Quarterly Daily
Kiran Sankuru | Rama Kappagantula
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Data
Scatterplot matrix Normalization Summary Statistics Correlation Matrix PCA Analysis Regression Trees
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Analysis & Cleanup
Kiran Sankuru | Rama Kappagantula
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Data
Normalizationo Xnorm = (X – Min)/(Max - Min)
Summary Stats
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Analysis & Cleanup
Kiran Sankuru | Rama Kappagantula
9
Data
Correlation Matrix
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Analysis & Cleanup
Kiran Sankuru | Rama Kappagantula
10
Data
PCA Analysis
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Analysis & Cleanup
Kiran Sankuru | Rama Kappagantula
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Data
Regression Tree
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Analysis & Cleanup
Kiran Sankuru | Rama Kappagantula
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Data Mining Predictors
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Dependent Variable DXY
Predictors
Euro JPYen VIX S&P Gold BDI Unemployment Inflation LEI Money Supply GDP Current Acct
Kiran Sankuru | Rama Kappagantula
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Data Mining
Neural Networks
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Methodology
Kiran Sankuru | Rama Kappagantula
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Data Mining Methodology
Network Diagram
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Neural Networks
1
2
4
5
3
6
Input Layer Hidden Layer Output Layer
S&P
GDP
DXY
W13
O3
O4
O5
O6W14
W15
W23
W24
W25
W36
W46
W56
Outputj = 1 / (1 + e-(Oj + ∑ Wij * Xi ))
Kiran Sankuru | Rama Kappagantula
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Data Mining Methodology
Training the Modelo Input nodes: 12 predictorso # of Hidden layers: 1o # of Hidden layer nodes: 12o # of Epochs: 30o Output nodes: 1
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Neural Networks
Kiran Sankuru | Rama Kappagantula
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Data Mining Methodology
Data Partition: Training – 80%, Validation – 20%
Runs
3/9/2013
Neural Networks - Implementation
#Run#Hidden layer
#Hidden Layer Nodes
#No of epochs/iterations
RMSE - Training
RMSE – Validation
RMSE Chg Return
1 1 12 30 0.107477474 0.111156007 3.423%
2 1 24 30 0.121486949 0.126022016 3.733%
3 1 6 30 0.099382581 0.102438743 3.075%
4 1 4 30 0.103504299 0.107414073 3.777%
5 1 6 45 0.066935626 0.067200881 0.396%
6 1 6 150 0.019869902 0.019022021 -4.267%
7 1 6 300 0.01733016 0.01701691 -1.808%
12:30 24:30 6:30 4:30 6:45 6:150 6:3000
0.02
0.04
0.06
0.08
0.1
0.12
0.14
-5.000%
-4.000%
-3.000%
-2.000%
-1.000%
0.000%
1.000%
2.000%
3.000%
4.000%
5.000%
RMSE
RMSE - Training RMSE - Validation RMSE Chg Rt
Kiran Sankuru | Rama Kappagantula
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Data Mining Methodology
Final Designo Input nodes: 12 predictorso # of Hidden layers: 1o # of Hidden layer nodes: 6o Output nodes: 1
Xactual = (Xnorm)*(b - a) + a for each predicted periodNote: a – minimum in the original range & b – maximum in the original range
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Neural Networks
Kiran Sankuru | Rama Kappagantula
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Model
3/9/2013
Results
1/3/
1994
6/3/
1994
11/3
/199
44/
3/19
959/
3/19
952/
3/19
967/
3/19
9612
/3/1
996
5/3/
1997
10/3
/199
73/
3/19
988/
3/19
981/
3/19
996/
3/19
9911
/3/1
999
4/3/
2000
9/3/
2000
2/3/
2001
7/3/
2001
12/3
/200
15/
3/20
0210
/3/2
002
3/3/
2003
8/3/
2003
1/3/
2004
6/3/
2004
11/3
/200
44/
3/20
059/
3/20
052/
3/20
067/
3/20
0612
/3/2
006
5/3/
2007
10/3
/200
73/
3/20
088/
3/20
081/
3/20
096/
3/20
0911
/3/2
009
4/3/
2010
9/3/
2010
2/3/
2011
7/3/
2011
12/3
/201
15/
3/20
1210
/3/2
012
0
20
40
60
80
100
120
140
-5.000%
-4.000%
-3.000%
-2.000%
-1.000%
0.000%
1.000%
2.000%
3.000%
4.000%
5.000%
Training Data
Regular Value - Predicted Regular Value - Actual % Prediction Error
8eoQSyDyMCjQVwoNGtOKpp
1/7/
1994
6/7/
1994
11/7
/199
44/
7/19
959/
7/19
952/
7/19
967/
7/19
9612
/7/1
996
5/7/
1997
10/7
/199
73/
7/19
988/
7/19
981/
7/19
996/
7/19
9911
/7/1
999
4/7/
2000
9/7/
2000
2/7/
2001
7/7/
2001
12/7
/200
15/
7/20
0210
/7/2
002
3/7/
2003
8/7/
2003
1/7/
2004
6/7/
2004
11/7
/200
44/
7/20
059/
7/20
052/
7/20
067/
7/20
0612
/7/2
006
5/7/
2007
10/7
/200
73/
7/20
088/
7/20
081/
7/20
096/
7/20
0911
/7/2
009
4/7/
2010
9/7/
2010
2/7/
2011
7/7/
2011
12/7
/201
15/
7/20
1210
/7/2
012
0
20
40
60
80
100
120
140
-4.000%
-3.000%
-2.000%
-1.000%
0.000%
1.000%
2.000%
3.000%
4.000%
Validation Data
Regular Value - Predicted Regular Value - Actual % Prediction Error9fGpnYAGToIf8cclCaKZh8
Kiran Sankuru | Rama Kappagantula
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Model
Model Performance
3/9/2013
Validation
1/1/
2013
1/2/
2013
1/3/
2013
1/4/
2013
1/5/
2013
1/6/
2013
1/7/
2013
1/8/
2013
1/9/
2013
1/10
/201
3
1/11
/201
3
1/12
/201
3
1/13
/201
3
1/14
/201
3
1/15
/201
3
1/16
/201
3
1/17
/201
3
1/18
/201
3
1/19
/201
3
1/20
/201
3
1/21
/201
3
1/22
/201
3
1/23
/201
3
1/24
/201
3
1/25
/201
3
1/26
/201
3
1/27
/201
3
1/28
/201
3
1/29
/201
3
1/30
/201
3
1/31
/201
377.5
78
78.5
79
79.5
80
80.5
81
-1.200%
-1.000%
-0.800%
-0.600%
-0.400%
-0.200%
0.000%
0.200%
0.400%
DXY - Test Data 01/01/2013 - 01/31/2013
DXY - Actual DXY - Predicted % Prediction Error
Kiran Sankuru | Rama Kappagantula
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Model
Q1 2013 & Q2 2013
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Prediction
Date DXY_Norm ActualDXY_Norm Predicted
DXY Actual
Time SeriesDXY
Predicted
Q1 2013 0.175558586 0.174875784 79.765 79.731
Q2 2013 0.187186009 0.234279779 80.345 82.693