资源描述
Click to edit Master title style,*,Click to edit Master text styles,Second level,Third level,Fourth level,Fifth level,Forecasting Fed Funds Rate,Group 4,Neelima Akkannapragada,Chayaporn Lertrattanapaiboon,Anthony Mak,Joseph Singh,Corinna Traumueller,Hyo Joon You,Background,Fed funds rate(FFR)as an instrument of control.,FFR as sign of economic strength/weakness.,FFR is at 1.25%,the lowest since 1961.,Greenspan intimates at possibility of deflation(last week).,Japanese Deflation and the Great Depression.,Objectives,What will happen to the FFR given indicators such as GDP,CPI,stock market price levels,etc?,Create a distributed lag model with FFR as the dependent variable.,Provide one period ahead forecast of FFR.,And what does this forecast mean to us?,Provide economic context for the forecast.,The Idea,Supposing that the Fed made its decision solely on previous FFR would be naive.,Feds decision on future FFR depends on existing information.,We focus on these existing information to explain FFR.,GDP,CPI,SP500,Data Standardization,All data from Fred II.,Different time range and frequencies,But same time range and frequencies necessary for DL model,Lower bound set by data with the latest start(SP5000 Jan 1970),Upper bound set by data with the earliest end(GDP Jan 2003),Frequency set by data with lowest frequency(GDP quarterly).,Result is a shorter and less frequent data set(120 obs).,Still enough data.,Trace of Variables,Trace of Stationary Variables,Pairwise Granger Causality Tests,Date:05/27/03 Time:14:23,Sample:1970:1 2003:2,Lags:2,Null Hypothesis:ObsF-StatisticProbability,DLGDP does not Granger Cause DLFFR130 12.8145 8.7E-06,DLFFR does not Granger Cause DLGDP 1.75070 0.17788,DLSP does not Granger Cause DLFFR130 7.35499 0.00096,DLFFR does not Granger Cause DLSP 2.07473 0.12989,DDLCPI does not Granger Cause DLFFR129 0.61862 0.54034,DLFFR does not Granger Cause DDLCPI,7.36316 0.00095,DLSP does not Granger Cause DLGDP,130 1.16482 0.31534,DLGDP does not Granger Cause DLSP,0.54295 0.58240,DDLCPI does not Granger Cause DLGDP129 3.40096 0.03648,DLGDP does not Granger Cause DDLCPI 2.80740 0.06420,DDLCPI does not Granger Cause DLSP129 1.48890 0.22963,DLSP does not Granger Cause DDLCPI 0.48034 0.61972,Time Causality,Cross Correlogram 1,Cross Correlogram 2,Dependent Variable:DLFFR,Method:Least Squares,Sample(adjusted):1972:2 2003:1,Included observations:124 after adjusting endpoints,Convergence achieved after 8 iterations,Variable Coefficient Std.Error t-Statistic Prob.,4.6565699798e-07,DLGDP(-1)5.742530598661.3480009163 4.26003464036,AR(5)0.2469531144840.0878659566173 2.8105665037,0.00578442215627,R-squared0.27792384769 Mean dependent var -0.00836815797483,Sum squared resid2.07114473911 Schwarz criterion -1.05993683855,Log likelihood 77.766787904,F-statistic 11.4506405485,Durbin-Watson stat1.79038035224,Prob(F-statistic)6.75508422109e-08,Inverted AR Roots .76 .23+.72i .23-.72i -.61-.44i,-.61+.44i,Estimation Output DL Model,Residual Correlogram of the DL Model,Residual Diagnostics,Forecast,Summary,Standardization of data for DL modeling causes results in fewer observations.,Granger test is useful in isolating independent variables.,dlSP500 did not have AR structure.Creating the transformed dependent variable may have been more difficult.,Result is more plausible than ARMA model.,Fed funds rate will go down next quarter.,What Now?,Assuming that fed funds will continue to go down,one can,buy treasury bonds now and sell them later at a higher price when interest rate drops,simply try harder to find a job in the sluggish economy,start a business now in anticipation of next boom,Dependent Variable:DLFFR,Method:Least Squares,Sample(adjusted):1970:3 2003:1,Included observations:131 after adjusting endpoints,Convergence achieved after 3 iterations,VariableCoefficient Std.Error t-Statistic Prob.,C-0.014695 0.016465 -0.892533 0.3738,AR(1)0.166843 0.088232 1.890959 0.0609,R-squared 0.026971 Mean dependent var-0.014326,Adjusted R-squared 0.019428 S.D.dependent var 0.158538,S.E.of regression 0.156991 Akaike info criterion0.850112,Sum squared resid 3.179341 Schwarz criterion-0.806216,Log likelihood 57.68233 F-statistic 3.575725,Durbin-Watson stat 1.961340 Prob(F-statistic)0.060873,Estimation Output AR Model,Residual Correlogram AR Model,Residual of the AR Model,
展开阅读全文