Commitment of Traders as features of a model

cot.jl

julia> using Quandl, TimeSeries

julia> rut = quandl("YAHOO/INDEX_RUT");

julia> cot_rut = quandl("OFDP/FUTURE_COT_38");

julia> r = merge(rut, cot_rut, "Date");

julia> simple_return!(r, "Close");

julia> colnames(r)
17-element Union(UTF8String,ASCIIString) Array:
 "Date"                           
 "Open"                           
 "High"                           
 "Low"                            
 "Close"                          
 "Volume"                         
 "Adjusted Close\n"               
 "Non-Commercial Long"            
 "Non-Commercial Short"           
 "Non-Commercial Spreads"         
 "Commercial Long"                
 "Commercial Short"               
 "Total Long"                     
 "Total Short"                    
 "Nonreportable Positions Long"   
 "Nonreportable Positions Short\n"
 "Close_RET"                      

julia> within!(r, :(y = $lead($r["Close_RET"])));


julia> head(r[:,["Close_RET", "y"]])
6x2 DataFrame:
         Close_RET          y
[1,]           0.0  0.0129526
[2,]     0.0129526 -0.0397666
[3,]    -0.0397666 -0.0270627
[4,]    -0.0270627  0.0218141
[5,]     0.0218141 -0.0293981
[6,]    -0.0293981  0.0356801

julia> rfit = r[:,[8:16, 18]];

julia> rX = [ones(nrow(rfit))];

julia> for i in 2:ncol(rfit)-1
       rX = [rX rfit[i]]
       end

julia> rX = rX[1:end-1,:]; # taking out the last observation since it's prediction is missing

julia> ry = [float(rfit[1:end-1,ncol(rfit)])]; # matches what we just did with feature matrix

# theta = pinv(X'X) * X'* y

julia> rtheta = pinv(rX'rX) * rX'* ry # regression parameters

julia> rtheta' * rXnext'
1x1 Float64 Array:
 -0.00167277