# Steps
# Took Indicators
# Subset data with indicators , Calender date and price
# Calucalte return price
# Remove Outliers
# Remove multi collinearity
# Remove NA'S
# Normalize indicator data
# Split data into 75% train and 25 test
# Create Linear model for train data
# Find Coefficients with higher P value
# Build model for train data.
# Predict return price for test data
# Forecast results.
# How do we forecast ? what package , should date be unbroken
#REVENUEUSD Revenues (USD)
#GP Gross Profit
#OPEX Operating Expenses
#EBITUSD Earning Before Interest & Taxes (USD)
#NETINC Net Income
#EPSUSD Earnings per Basic Share (USD)
#NCFO Net Cash Flow from Operations
#NCFI Net Cash Flow from Investing
#NCFF Net Cash Flow from Financing
#NCF Net Cash Flow / Change in Cash & Cash Equivalents
#ASSETS Total Assets
#CASHNEQUSD Cash and Equivalents (USD)
#LIABILITIES Total Liabilities
#INVESTMENTS Investments
#EQUITYUSD hareholders Equity (USD
#DE Debt to Equity Ratio
#EBITDA Earnings Before Interest, Taxes & Depreciation Amortization
#FCF Free Cash Flow
#PE1 Price to Earnings Ratio
#PB Price to Book Value nam
#Defining the Variables(Indicators Selected) from the list
indicator_list<-c(3,7,15,18, 25,28,32,35, 39,78,42,49,57,58, 59, 61,68,70, 86,90,93,94)
#Reading the file into a data frame
stock_data <- read.csv('/Users/jyothi/Downloads/data_file_ARQ.csv', header = T, sep =',')
#initializing the returns vector and loading values into it
return_price<-vector();
### Computing Return price
#log of the returns for the price
for(i in 2:length(stock_data[,1])){
if (identical(stock_data[i,1],stock_data[i-1,1])){
return_price[i] = (stock_data[i,72]/stock_data[i-1,72]);
}else{
return_price[i] = 0;
}
}
return_price[1]=0;
#combining return price to Stock Data
stock_data<-cbind(stock_data,return_price)
#Selecting only the indiactors chosen
stock_factors <- na.omit(stock_data[indicator_list])
#plot(stock_factors$assets)
stock_factors<-subset(stock_factors, stock_factors$assets < 40000000000)
#plot(stock_factors$assets)
stock_factors<-subset(stock_factors, stock_factors$cashnequsd < 6000000000)
#plot(stock_factors$cashnequsd)
stock_factors<-subset(stock_factors, stock_factors$de > -100)
stock_factors<-subset(stock_factors, stock_factors$de < 100)
#plot(stock_factors$de)
#plot(stock_factors$ebitda)
stock_factors<-subset(stock_factors, stock_factors$ebitda > -500000000)
stock_factors<-subset(stock_factors, stock_factors$ebitda < 2000000000)
#plot(stock_factors$ebitda)
#plot(stock_factors$ebitusd)
stock_factors<-subset(stock_factors, stock_factors$ebitusd > -400000000)
stock_factors<-subset(stock_factors, stock_factors$ebitusd < 1500000000)
#plot(stock_factors$ebitusd)
#View(stock_factors)
stock_factors<-subset(stock_factors, stock_factors$epsusd > -10)
#plot(stock_factors$epsusd)
stock_factors<-subset(stock_factors, stock_factors$epsusd < 10)
#plot(stock_factors$epsusd)
stock_factors<-subset(stock_factors, stock_factors$equityusd > -1000000000)
#plot(stock_factors$equityusd)
stock_factors<-subset(stock_factors, stock_factors$equityusd < 20000000000)
#plot(stock_factors$equityusd)
stock_factors_new <- stock_factors
#stock_factors <- stock_factors_new
#plot(stock_factors$fcf)
stock_factors<-subset(stock_factors, stock_factors$fcf < 1500000000)
stock_factors<-subset(stock_factors, stock_factors$fcf > -1000000000)
#plot(stock_factors$fcf)
#plot(stock_factors$revenueusd)
stock_factors<-subset(stock_factors, stock_factors$revenueusd < 8000000000)
#plot(stock_factors$revenueusd)
stock_factors<-subset(stock_factors, stock_factors$revenueusd > -100000)
#plot(stock_factors$revenueusd)
#plot(stock_factors$gp)
stock_factors<-subset(stock_factors, stock_factors$gp < 3000000000)
stock_factors<-subset(stock_factors, stock_factors$gp > -4000000)
#plot(stock_factors$gp)
stock_factors<-subset(stock_factors, stock_factors$liabilities < 25000000000)
stock_factors<-subset(stock_factors, stock_factors$liabilities > -80000)
#plot(stock_factors$liabilities)
stock_factors_new <- stock_factors
#plot(stock_factors$ncff)
stock_factors<-subset(stock_factors, stock_factors$ncff < 2000000000)
#plot(stock_factors$ncff)
stock_factors<-subset(stock_factors, stock_factors$ncff > -1500000000)
#plot(stock_factors$ncff)
#View(stock_factors_new)
stock_factors<-subset(stock_factors, stock_factors$ncfi < 1000000000)
stock_factors<-subset(stock_factors, stock_factors$ncfi < 1000000000)
#plot(stock_factors$ncfi)
stock_factors<-subset(stock_factors, stock_factors$ncfi > - 2000000000)
#plot(stock_factors$ncfi)
stock_factors<-subset(stock_factors, stock_factors$ncfo < 1500000000)
#plot(stock_factors$ncfo)
stock_factors<-subset(stock_factors, stock_factors$ncfo > -500000000)
#plot(stock_factors$ncfo)
stock_factors_new <- stock_factors
#plot(stock_factors$netinc)
stock_factors<-subset(stock_factors, stock_factors$netinc > -500000000)
#plot(stock_factors$netinc)
#plot(stock_factors$netinc)
stock_factors<-subset(stock_factors, stock_factors$netinc < 1000000000)
#plot(stock_factors$netinc)
#plot(stock_factors$pb)
stock_factors<-subset(stock_factors, stock_factors$pb < 10000)
stock_factors<-subset(stock_factors, stock_factors$pb <200)
stock_factors<-subset(stock_factors, stock_factors$pb > -200)
#plot(stock_factors$pb)
#plot(stock_factors$pe1)
stock_factors<-subset(stock_factors, stock_factors$pe1 > -1000)
stock_factors<-subset(stock_factors, stock_factors$pe1 < 1000)
#plot(stock_factors$pe1)
stock_factors_new <- stock_factors
#plot(stock_factors$sharesbas)
stock_factors<-subset(stock_factors, stock_factors$sharesbas < 800000000)
#plot(stock_factors$sharesbas)
#plot(stock_factors$tangibles)
stock_factors<-subset(stock_factors, stock_factors$tangibles < 20000000000)
#plot(stock_factors$tangibles)
#plot(stock_factors$workingcapital)
stock_factors<-subset(stock_factors, stock_factors$workingcapital > -1500000000)
#plot(stock_factors$workingcapital)
stock_factors<-subset(stock_factors, stock_factors$workingcapital < 6000000000)
#plot(stock_factors$workingcapital)
stock_factors_new <- stock_factors
#View (stock_factors_new)
#####################Multicollinearity Removal#########
stock_factors_new <- stock_factors_new[ ,-c(1,22)]
sink("/Users/jyothi/Desktop/cor.txt")
cor(stock_factors_new)
## assets cashnequsd de ebitda
## assets 1.000000000 0.61421508 0.0782112544 0.83899851
## cashnequsd 0.614215079 1.00000000 0.0365081290 0.60458431
## de 0.078211254 0.03650813 1.0000000000 0.06269383
## ebitda 0.838998510 0.60458431 0.0626938302 1.00000000
## ebitusd 0.742595158 0.58001121 0.0444972107 0.96363758
## epsusd 0.235966783 0.19675398 0.0288497325 0.40764767
## equityusd 0.899765681 0.62279702 0.0275480022 0.78455830
## fcf 0.386186942 0.44547074 0.0294319370 0.48776439
## revenueusd 0.769944853 0.59396030 0.0662162712 0.74379501
## gp 0.806747034 0.63428636 0.0661628765 0.82904399
## liabilities 0.962654770 0.55148906 0.1014117036 0.79623986
## ncff -0.162384874 -0.12605673 0.0066065380 -0.24640434
## ncfi -0.460766693 -0.22590503 -0.0503986453 -0.40006375
## ncfo 0.702608344 0.55144658 0.0575961132 0.76826401
## netinc 0.632897074 0.54753817 0.0253376649 0.89281569
## pb -0.003325166 0.01478398 0.5403373489 0.01669836
## pe1 0.043807234 0.03581321 -0.0008833853 0.06134799
## sharesbas 0.688486571 0.59694030 0.0327751468 0.63941738
## tangibles 0.931149266 0.59337986 0.0808760753 0.79537863
## workingcapital 0.559316932 0.73375250 0.0169005771 0.55067337
## ebitusd epsusd equityusd fcf
## assets 0.74259516 0.23596678 0.899765681 0.38618694
## cashnequsd 0.58001121 0.19675398 0.622797020 0.44547074
## de 0.04449721 0.02884973 0.027548002 0.02943194
## ebitda 0.96363758 0.40764767 0.784558295 0.48776439
## ebitusd 1.00000000 0.45425849 0.714081767 0.51975006
## epsusd 0.45425849 1.00000000 0.257673865 0.21543515
## equityusd 0.71408177 0.25767386 1.000000000 0.38798529
## fcf 0.51975006 0.21543515 0.387985292 1.00000000
## revenueusd 0.70192224 0.27164316 0.688376123 0.41675110
## gp 0.78894894 0.28266526 0.742147423 0.49506087
## liabilities 0.69356867 0.20225501 0.753153852 0.35344194
## ncff -0.26661924 -0.10483488 -0.165869133 -0.41292779
## ncfi -0.32392860 -0.10827465 -0.426020247 -0.03994817
## ncfo 0.71924796 0.27655192 0.671425053 0.78360998
## netinc 0.95404019 0.50739838 0.656816092 0.51211626
## pb 0.02034100 0.02065151 -0.006716599 0.02247697
## pe1 0.06101799 0.07439753 0.051495711 0.03601164
## sharesbas 0.57786280 0.12284752 0.666471898 0.34293056
## tangibles 0.68823342 0.22934215 0.820558567 0.28276013
## workingcapital 0.54578386 0.23358872 0.636742525 0.39013498
## revenueusd gp liabilities ncff
## assets 0.769944853 0.80674703 0.962654770 -0.162384874
## cashnequsd 0.593960298 0.63428636 0.551489056 -0.126056728
## de 0.066216271 0.06616288 0.101411704 0.006606538
## ebitda 0.743795005 0.82904399 0.796239860 -0.246404342
## ebitusd 0.701922242 0.78894894 0.693568667 -0.266619239
## epsusd 0.271643158 0.28266526 0.202255007 -0.104834878
## equityusd 0.688376123 0.74214742 0.753153852 -0.165869133
## fcf 0.416751095 0.49506087 0.353441940 -0.412927790
## revenueusd 1.000000000 0.78376149 0.749847268 -0.220969783
## gp 0.783761493 1.00000000 0.773573679 -0.243806024
## liabilities 0.749847268 0.77357368 1.000000000 -0.148794728
## ncff -0.220969783 -0.24380602 -0.148794728 1.000000000
## ncfi -0.316798948 -0.35392671 -0.435581231 -0.455934980
## ncfo 0.609154717 0.69953337 0.656410785 -0.293864271
## netinc 0.623455697 0.70343212 0.563238166 -0.261607223
## pb 0.002378546 0.02040166 -0.001392047 -0.002440969
## pe1 0.039886615 0.04474907 0.035364463 -0.011452220
## sharesbas 0.571983721 0.66866987 0.637308950 -0.160438083
## tangibles 0.749534746 0.74089207 0.908638572 -0.118267783
## workingcapital 0.616422661 0.58883200 0.465930659 -0.137293039
## ncfi ncfo netinc pb
## assets -0.460766693 0.70260834 0.63289707 -0.003325166
## cashnequsd -0.225905027 0.55144658 0.54753817 0.014783977
## de -0.050398645 0.05759611 0.02533766 0.540337349
## ebitda -0.400063752 0.76826401 0.89281569 0.016698357
## ebitusd -0.323928598 0.71924796 0.95404019 0.020341003
## epsusd -0.108274652 0.27655192 0.50739838 0.020651509
## equityusd -0.426020247 0.67142505 0.65681609 -0.006716599
## fcf -0.039948165 0.78360998 0.51211626 0.022476972
## revenueusd -0.316798948 0.60915472 0.62345570 0.002378546
## gp -0.353926714 0.69953337 0.70343212 0.020401663
## liabilities -0.435581231 0.65641079 0.56323817 -0.001392047
## ncff -0.455934980 -0.29386427 -0.26160722 -0.002440969
## ncfi 1.000000000 -0.40025187 -0.27062287 -0.006801858
## ncfo -0.400251871 1.00000000 0.66058173 0.017157584
## netinc -0.270622865 0.66058173 1.00000000 0.022462637
## pb -0.006801858 0.01715758 0.02246264 1.000000000
## pe1 -0.030509905 0.04865358 0.06394589 -0.009267894
## sharesbas -0.319376831 0.54944951 0.50376558 0.025466026
## tangibles -0.479200211 0.67490590 0.57879543 -0.005176550
## workingcapital -0.206030627 0.44972139 0.52867111 0.004470168
## pe1 sharesbas tangibles workingcapital
## assets 0.0438072338 0.68848657 0.93114927 0.559316932
## cashnequsd 0.0358132116 0.59694030 0.59337986 0.733752498
## de -0.0008833853 0.03277515 0.08087608 0.016900577
## ebitda 0.0613479949 0.63941738 0.79537863 0.550673370
## ebitusd 0.0610179915 0.57786280 0.68823342 0.545783865
## epsusd 0.0743975276 0.12284752 0.22934215 0.233588721
## equityusd 0.0514957106 0.66647190 0.82055857 0.636742525
## fcf 0.0360116375 0.34293056 0.28276013 0.390134985
## revenueusd 0.0398866149 0.57198372 0.74953475 0.616422661
## gp 0.0447490652 0.66866987 0.74089207 0.588832000
## liabilities 0.0353644634 0.63730895 0.90863857 0.465930659
## ncff -0.0114522201 -0.16043808 -0.11826778 -0.137293039
## ncfi -0.0305099051 -0.31937683 -0.47920021 -0.206030627
## ncfo 0.0486535837 0.54944951 0.67490590 0.449721388
## netinc 0.0639458904 0.50376558 0.57879543 0.528671109
## pb -0.0092678945 0.02546603 -0.00517655 0.004470168
## pe1 1.0000000000 0.02520183 0.03836747 0.041335192
## sharesbas 0.0252018287 1.00000000 0.64790893 0.509420427
## tangibles 0.0383674668 0.64790893 1.00000000 0.549589281
## workingcapital 0.0413351919 0.50942043 0.54958928 1.000000000
stock_factors <- stock_factors[ , -c(2,6,20)]
### Unique Dates
## -- Train
#2011-03-31
#2011-06-30
#2011-09-30
#2011-12-31
#2012-03-31
#2012-06-30
#2012-09-30
#2012-12-31
#2013-03-31
#2013-06-30
#2013-09-30
#2013-12-31
#2014-03-31
#2014-06-30
#2014-09-30
# --- Test
#2014-12-31
#2015-03-31
#2015-06-30
#2015-09-30
#2015-12-31
sink()
summary(stock_factors)
## calendardate cashnequsd de
## 2014-12-31: 3049 Min. :0.000e+00 Min. :-98.899
## 2011-03-31: 2989 1st Qu.:8.394e+06 1st Qu.: 0.316
## 2015-03-31: 2971 Median :3.879e+07 Median : 0.782
## 2012-12-31: 2970 Mean :1.603e+08 Mean : 1.163
## 2013-12-31: 2968 3rd Qu.:1.426e+08 3rd Qu.: 1.641
## 2011-06-30: 2963 Max. :5.701e+09 Max. : 99.951
## (Other) :41002
## ebitda epsusd equityusd
## Min. :-379491000 Min. :-9.8000 Min. :-9.950e+08
## 1st Qu.: -193000 1st Qu.:-0.0800 1st Qu.: 3.700e+07
## Median : 9433000 Median : 0.0900 Median : 1.957e+08
## Mean : 56064850 Mean : 0.1434 Mean : 7.256e+08
## 3rd Qu.: 56860250 3rd Qu.: 0.4200 3rd Qu.: 7.548e+08
## Max. :1575000000 Max. : 9.9200 Max. : 1.968e+10
##
## fcf revenueusd gp
## Min. :-969912000 Min. : -87662 Min. : -3979000
## 1st Qu.: -4218648 1st Qu.: 14554400 1st Qu.: 5360750
## Median : 793000 Median : 96138000 Median : 35730000
## Mean : 18702520 Mean : 396538169 Mean : 133685150
## 3rd Qu.: 20045250 3rd Qu.: 393002000 3rd Qu.: 135595500
## Max. :1432000000 Max. :7973107000 Max. :2994000000
##
## liabilities ncff ncfi
## Min. :0.000e+00 Min. :-1.470e+09 Min. :-1.969e+09
## 1st Qu.:2.629e+07 1st Qu.:-1.042e+07 1st Qu.:-2.750e+07
## Median :1.718e+08 Median :-1.263e+05 Median :-4.044e+06
## Mean :1.091e+09 Mean :-4.523e+06 Mean :-3.721e+07
## 3rd Qu.:1.037e+09 3rd Qu.: 1.696e+06 3rd Qu.:-1.185e+05
## Max. :2.279e+10 Max. : 1.943e+09 Max. : 9.890e+08
##
## ncfo netinc pb
## Min. :-498613000 Min. :-475000000 Min. :-199.416
## 1st Qu.: -960730 1st Qu.: -2051107 1st Qu.: 1.192
## Median : 5756052 Median : 1997438 Median : 2.143
## Mean : 43404249 Mean : 20474458 Mean : 3.153
## 3rd Qu.: 41940000 3rd Qu.: 20432225 3rd Qu.: 3.932
## Max. :1490000000 Max. : 984000000 Max. : 199.221
##
## pe1 sharesbas workingcapital
## Min. :-998.000 Min. : 45161 Min. :-1.490e+09
## 1st Qu.: -3.821 1st Qu.: 17249770 1st Qu.: 1.047e+07
## Median : 12.553 Median : 38322158 Median : 7.390e+07
## Mean : 10.516 Mean : 69641064 Mean : 2.665e+08
## 3rd Qu.: 22.848 3rd Qu.: 80937901 3rd Qu.: 2.749e+08
## Max. : 993.000 Max. :798026043 Max. : 5.985e+09
##
## return_price
## Min. :0.0000
## 1st Qu.:0.8500
## Median :0.9893
## Mean : Inf
## 3rd Qu.:1.1076
## Max. : Inf
##
#View(stock_factors)
#stock_factors <- na.omit(stock_factors)
#Finding the unique dates
stock_factors<-unique(stock_factors)
#unique(stock_factors$calendardate)
#View(cal_date)
#View(stock_factors)
## remove Calender Return price to normalise rest of the factors.
data_norm<-stock_factors[ , -c(19)]
for (k in 2:18) {
#normalizing each independent var
x<-(data_norm[,k]-mean(data_norm[,k]))/sd(data_norm[,k])
#merging the normalized var to the original dataset
data_norm<-cbind(data_norm,x)
#naming the normalized variable
names(data_norm)[NCOL(data_norm)]<-paste(colnames(data_norm[k]),"_n",sep="")
}
### Select normalised data , calenderdate and Return price.
stock_factors_date <- data_norm[c(1,19:35)]
stock_factors_date["return_price"]<-stock_factors[,19]
### Subset data by calendar Date
stock_factor_2011_06_30 <- subset(stock_factors_date , calendardate =='2011-06-30')
stock_factor_2011_06_30 <- stock_factor_2011_06_30[,-(1)]
stock_factor_2011_09_30 <- subset(stock_factors_date , calendardate =='2011-09-30' )
stock_factor_2011_09_30 <- stock_factor_2011_09_30[,-1]
stock_factor_2011_12_31 <- subset(stock_factors_date , calendardate =='2011-12-31' )
stock_factor_2011_12_31 <- stock_factor_2011_12_31[,-1]
stock_factor_2012_03_31 <- subset(stock_factors_date , calendardate =='2012-03-31' )
stock_factor_2012_03_31 <- stock_factor_2012_03_31[,-1]
stock_factor_2012_06_30 <- subset(stock_factors_date , calendardate =='2012-06-30' )
stock_factor_2012_06_30 <- stock_factor_2012_06_30[,-1]
stock_factor_2012_09_30 <- subset(stock_factors_date , calendardate =='2012-09-30' )
stock_factor_2012_09_30 <- stock_factor_2012_09_30[,-1]
stock_factor_2012_12_31 <- subset(stock_factors_date , calendardate =='2012-12-31' )
stock_factor_2012_12_31 <- stock_factor_2012_12_31[,-1]
stock_factor_2013_03_31 <- subset(stock_factors_date , calendardate =='2013-03-31' )
stock_factor_2013_03_31 <- stock_factor_2013_03_31 [,-1]
stock_factor_2013_06_30 <- subset(stock_factors_date , calendardate =='2013-06-30' )
stock_factor_2013_06_30 <- stock_factor_2013_06_30[,-1]
stock_factor_2013_09_30 <- subset(stock_factors_date , calendardate =='2013-09-30' )
stock_factor_2013_09_30 <- stock_factor_2013_09_30[,-1]
stock_factor_2013_12_31 <- subset(stock_factors_date , calendardate =='2013-12-31' )
stock_factor_2013_12_31 <- stock_factor_2013_12_31[,-1]
stock_factor_2014_03_31 <- subset(stock_factors_date , calendardate =='2014-03-31' )
stock_factor_2014_03_31 <- stock_factor_2014_03_31[,-1]
stock_factor_2014_06_30 <- subset(stock_factors_date , calendardate =='2014-06-30' )
stock_factor_2014_06_30 <- stock_factor_2014_06_30[,-1]
stock_factor_2014_09_30 <- subset(stock_factors_date , calendardate =='2014-09-30' )
stock_factor_2014_09_30 <- stock_factor_2014_09_30[,-1]
# Creates List of 15 stock_factors for each calender date
my.list <- list( stock_factor_2011_06_30, stock_factor_2011_09_30,
stock_factor_2011_12_31,stock_factor_2012_03_31,stock_factor_2012_06_30,stock_factor_2012_09_30,stock_factor_2012_12_31,stock_factor_2013_03_31,
stock_factor_2013_06_30,stock_factor_2013_09_30,stock_factor_2013_12_31,stock_factor_2014_03_31,
stock_factor_2014_06_30,stock_factor_2014_09_30)
#View(my.list[1])
for (i in 1:length(my.list)) {
obj <- as.data.frame(my.list[i])
lm_model <- lm(return_price ~ . , data = obj)
print(summary(lm_model))
#View(my.list[i])
}
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8274 -0.1222 -0.0040 0.1015 7.3536
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.789e-01 4.864e-03 180.689 < 2e-16 ***
## cashnequsd_n -4.316e-03 8.321e-03 -0.519 0.60401
## de_n -1.726e-02 6.148e-03 -2.808 0.00502 **
## ebitda_n 2.582e-02 2.598e-02 0.994 0.32038
## epsusd_n 1.908e-02 5.783e-03 3.300 0.00098 ***
## equityusd_n -1.600e-02 1.071e-02 -1.494 0.13532
## fcf_n -3.313e-03 1.074e-02 -0.309 0.75770
## revenueusd_n -5.181e-03 9.546e-03 -0.543 0.58731
## gp_n 2.228e-03 1.018e-02 0.219 0.82684
## liabilities_n -4.700e-03 1.299e-02 -0.362 0.71760
## ncff_n -5.408e-03 7.544e-03 -0.717 0.47356
## ncfi_n 1.938e-03 8.145e-03 0.238 0.81195
## ncfo_n 1.184e-02 1.465e-02 0.808 0.41917
## netinc_n 2.425e-03 1.937e-02 0.125 0.90039
## pb_n 3.821e-02 6.637e-03 5.758 9.4e-09 ***
## pe1_n 1.539e-02 4.830e-03 3.187 0.00145 **
## sharesbas_n -4.728e-05 7.355e-03 -0.006 0.99487
## workingcapital_n -4.700e-03 9.023e-03 -0.521 0.60248
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2592 on 2944 degrees of freedom
## Multiple R-squared: 0.02692, Adjusted R-squared: 0.0213
## F-statistic: 4.791 on 17 and 2944 DF, p-value: 3.069e-10
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.619 -0.230 -0.055 0.145 84.207
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.9458514 0.0321309 29.437 <2e-16 ***
## cashnequsd_n -0.0428069 0.0550956 -0.777 0.4372
## de_n 0.4289061 0.0392490 10.928 <2e-16 ***
## ebitda_n -0.0199314 0.1659624 -0.120 0.9044
## epsusd_n 0.0327520 0.0386259 0.848 0.3965
## equityusd_n 0.0314696 0.0705670 0.446 0.6557
## fcf_n 0.0368658 0.0894578 0.412 0.6803
## revenueusd_n -0.0022733 0.0634233 -0.036 0.9714
## gp_n -0.0196365 0.0652298 -0.301 0.7634
## liabilities_n -0.1275810 0.0844979 -1.510 0.1312
## ncff_n 0.0039441 0.0561670 0.070 0.9440
## ncfi_n -0.0004256 0.0519632 -0.008 0.9935
## ncfo_n -0.0055202 0.1174307 -0.047 0.9625
## netinc_n 0.0274447 0.1124885 0.244 0.8073
## pb_n -0.9197303 0.0415430 -22.139 <2e-16 ***
## pe1_n 0.0308529 0.0318037 0.970 0.3321
## sharesbas_n 0.1047645 0.0498233 2.103 0.0356 *
## workingcapital_n -0.0182780 0.0571972 -0.320 0.7493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.714 on 2907 degrees of freedom
## Multiple R-squared: 0.145, Adjusted R-squared: 0.14
## F-statistic: 29 on 17 and 2907 DF, p-value: < 2.2e-16
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0764 -0.1491 -0.0368 0.1020 12.8273
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.1227447 0.0074348 151.012 < 2e-16 ***
## cashnequsd_n -0.0069652 0.0128768 -0.541 0.588610
## de_n 0.0011991 0.0087808 0.137 0.891387
## ebitda_n -0.0078248 0.0298623 -0.262 0.793316
## epsusd_n 0.0271174 0.0071771 3.778 0.000161 ***
## equityusd_n -0.0103807 0.0161411 -0.643 0.520196
## fcf_n 0.0124862 0.0154970 0.806 0.420474
## revenueusd_n 0.0091391 0.0137329 0.665 0.505788
## gp_n -0.0039288 0.0148905 -0.264 0.791914
## liabilities_n 0.0001761 0.0176696 0.010 0.992047
## ncff_n 0.0046722 0.0116267 0.402 0.687822
## ncfi_n 0.0035367 0.0142612 0.248 0.804159
## ncfo_n -0.0053633 0.0208678 -0.257 0.797188
## netinc_n -0.0114562 0.0201946 -0.567 0.570562
## pb_n 0.0266308 0.0093020 2.863 0.004227 **
## pe1_n -0.0057518 0.0079501 -0.723 0.469435
## sharesbas_n 0.0092518 0.0116017 0.797 0.425255
## workingcapital_n 0.0080115 0.0134800 0.594 0.552343
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3995 on 2939 degrees of freedom
## Multiple R-squared: 0.01049, Adjusted R-squared: 0.004769
## F-statistic: 1.833 on 17 and 2939 DF, p-value: 0.01953
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8490 -0.1118 -0.0141 0.0871 5.0294
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.9826584 0.0045484 216.044 < 2e-16 ***
## cashnequsd_n 0.0024226 0.0077825 0.311 0.755608
## de_n 0.0103135 0.0064033 1.611 0.107366
## ebitda_n -0.0119237 0.0238054 -0.501 0.616492
## epsusd_n 0.0163807 0.0047111 3.477 0.000514 ***
## equityusd_n -0.0128386 0.0094944 -1.352 0.176407
## fcf_n 0.0254931 0.0104018 2.451 0.014311 *
## revenueusd_n -0.0048316 0.0084632 -0.571 0.568109
## gp_n 0.0140563 0.0096445 1.457 0.145103
## liabilities_n 0.0058807 0.0116131 0.506 0.612626
## ncff_n 0.0011044 0.0073055 0.151 0.879852
## ncfi_n -0.0081863 0.0090290 -0.907 0.364656
## ncfo_n -0.0164564 0.0137102 -1.200 0.230118
## netinc_n 0.0101930 0.0159605 0.639 0.523107
## pb_n 0.0010554 0.0063920 0.165 0.868864
## pe1_n 0.0032982 0.0051562 0.640 0.522445
## sharesbas_n -0.0019913 0.0070799 -0.281 0.778525
## workingcapital_n -0.0007458 0.0081809 -0.091 0.927370
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2425 on 2913 degrees of freedom
## Multiple R-squared: 0.01405, Adjusted R-squared: 0.008297
## F-statistic: 2.442 on 17 and 2913 DF, p-value: 0.0008381
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9555 -0.1212 -0.0129 0.0937 4.0153
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.982051 0.004686 209.565 < 2e-16 ***
## cashnequsd_n -0.005774 0.008141 -0.709 0.478169
## de_n -0.012214 0.006314 -1.935 0.053143 .
## ebitda_n -0.025171 0.024123 -1.043 0.296823
## epsusd_n 0.017216 0.005181 3.323 0.000902 ***
## equityusd_n 0.001750 0.009438 0.185 0.852902
## fcf_n 0.009459 0.010772 0.878 0.379928
## revenueusd_n -0.002536 0.009133 -0.278 0.781296
## gp_n 0.003708 0.009794 0.379 0.705010
## liabilities_n 0.006911 0.011602 0.596 0.551455
## ncff_n 0.003741 0.006748 0.554 0.579282
## ncfi_n 0.006779 0.007311 0.927 0.353842
## ncfo_n 0.002547 0.015315 0.166 0.867909
## netinc_n 0.020285 0.016910 1.200 0.230409
## pb_n 0.029101 0.006137 4.742 2.22e-06 ***
## pe1_n 0.002635 0.004996 0.528 0.597868
## sharesbas_n 0.002990 0.007322 0.408 0.683011
## workingcapital_n -0.016146 0.008263 -1.954 0.050785 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2519 on 2924 degrees of freedom
## Multiple R-squared: 0.01799, Adjusted R-squared: 0.01228
## F-statistic: 3.151 on 17 and 2924 DF, p-value: 1.318e-05
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8527 -0.1156 -0.0197 0.0795 6.1698
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.022617 0.005299 192.999 < 2e-16 ***
## cashnequsd_n -0.007348 0.009727 -0.755 0.450
## de_n -0.009464 0.006908 -1.370 0.171
## ebitda_n 0.019480 0.026685 0.730 0.465
## epsusd_n 0.025992 0.006210 4.186 2.93e-05 ***
## equityusd_n -0.005062 0.010793 -0.469 0.639
## fcf_n 0.008357 0.011967 0.698 0.485
## revenueusd_n 0.013492 0.010286 1.312 0.190
## gp_n 0.001523 0.010639 0.143 0.886
## liabilities_n 0.006293 0.013217 0.476 0.634
## ncff_n 0.001830 0.007971 0.230 0.818
## ncfi_n 0.009576 0.009357 1.023 0.306
## ncfo_n -0.001971 0.016146 -0.122 0.903
## netinc_n -0.021116 0.018935 -1.115 0.265
## pb_n 0.032653 0.007389 4.419 1.03e-05 ***
## pe1_n 0.001781 0.005648 0.315 0.753
## sharesbas_n -0.006783 0.008113 -0.836 0.403
## workingcapital_n 0.004098 0.009168 0.447 0.655
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2833 on 2878 degrees of freedom
## Multiple R-squared: 0.0197, Adjusted R-squared: 0.01391
## F-statistic: 3.402 on 17 and 2878 DF, p-value: 2.792e-06
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0885 -0.1503 -0.0320 0.1001 5.7394
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.1326587 0.0062233 182.004 < 2e-16 ***
## cashnequsd_n 0.0074541 0.0110192 0.676 0.498800
## de_n -0.0015371 0.0074738 -0.206 0.837070
## ebitda_n -0.0004743 0.0218394 -0.022 0.982676
## epsusd_n 0.0126662 0.0065592 1.931 0.053571 .
## equityusd_n -0.0090622 0.0126587 -0.716 0.474119
## fcf_n 0.0100693 0.0106710 0.944 0.345444
## revenueusd_n 0.0071351 0.0125762 0.567 0.570521
## gp_n -0.0134158 0.0134931 -0.994 0.320171
## liabilities_n 0.0045670 0.0143595 0.318 0.750469
## ncff_n 0.0036882 0.0091375 0.404 0.686512
## ncfi_n 0.0041310 0.0096371 0.429 0.668208
## ncfo_n 0.0031214 0.0149802 0.208 0.834955
## netinc_n -0.0166468 0.0147950 -1.125 0.260611
## pb_n 0.0282163 0.0072536 3.890 0.000102 ***
## pe1_n 0.0028903 0.0066017 0.438 0.661550
## sharesbas_n 0.0011165 0.0093887 0.119 0.905350
## workingcapital_n 0.0021682 0.0109243 0.198 0.842688
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3342 on 2952 degrees of freedom
## Multiple R-squared: 0.01084, Adjusted R-squared: 0.005139
## F-statistic: 1.902 on 17 and 2952 DF, p-value: 0.01403
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.00894 -0.10829 -0.01991 0.07728 2.71410
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.0473682 0.0041885 250.059 < 2e-16 ***
## cashnequsd_n 0.0020662 0.0073209 0.282 0.7778
## de_n 0.0044940 0.0050904 0.883 0.3774
## ebitda_n 0.0035653 0.0214684 0.166 0.8681
## epsusd_n 0.0219432 0.0050417 4.352 1.39e-05 ***
## equityusd_n -0.0166247 0.0082982 -2.003 0.0452 *
## fcf_n 0.0043540 0.0105216 0.414 0.6790
## revenueusd_n -0.0073925 0.0082021 -0.901 0.3675
## gp_n 0.0117395 0.0091282 1.286 0.1985
## liabilities_n 0.0085783 0.0099462 0.862 0.3885
## ncff_n 0.0050784 0.0064014 0.793 0.4277
## ncfi_n 0.0061016 0.0075657 0.806 0.4200
## ncfo_n 0.0010323 0.0135273 0.076 0.9392
## netinc_n -0.0046105 0.0148737 -0.310 0.7566
## pb_n 0.0041753 0.0048529 0.860 0.3897
## pe1_n -0.0007045 0.0041587 -0.169 0.8655
## sharesbas_n 0.0081148 0.0062854 1.291 0.1968
## workingcapital_n -0.0032877 0.0068956 -0.477 0.6336
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2239 on 2913 degrees of freedom
## Multiple R-squared: 0.0131, Adjusted R-squared: 0.007343
## F-statistic: 2.275 on 17 and 2913 DF, p-value: 0.002085
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.06313 -0.12764 -0.02717 0.09270 2.34458
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.099e+00 4.841e-03 226.964 < 2e-16 ***
## cashnequsd_n 7.019e-03 8.397e-03 0.836 0.4033
## de_n -6.093e-03 5.835e-03 -1.044 0.2965
## ebitda_n -1.007e-02 2.277e-02 -0.442 0.6583
## epsusd_n 2.581e-02 5.797e-03 4.452 8.83e-06 ***
## equityusd_n -2.357e-02 9.963e-03 -2.366 0.0180 *
## fcf_n 1.779e-03 1.019e-02 0.175 0.8615
## revenueusd_n 9.467e-03 9.298e-03 1.018 0.3087
## gp_n 9.054e-03 1.039e-02 0.871 0.3836
## liabilities_n -2.865e-03 1.104e-02 -0.259 0.7953
## ncff_n 8.489e-03 6.536e-03 1.299 0.1941
## ncfi_n 2.998e-03 7.395e-03 0.405 0.6853
## ncfo_n 2.330e-04 1.464e-02 0.016 0.9873
## netinc_n -8.919e-03 1.633e-02 -0.546 0.5849
## pb_n 1.303e-02 5.478e-03 2.378 0.0175 *
## pe1_n -3.913e-05 4.484e-03 -0.009 0.9930
## sharesbas_n 6.324e-03 7.407e-03 0.854 0.3933
## workingcapital_n -1.227e-03 8.338e-03 -0.147 0.8830
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2614 on 2912 degrees of freedom
## Multiple R-squared: 0.01445, Adjusted R-squared: 0.008699
## F-statistic: 2.512 on 17 and 2912 DF, p-value: 0.0005675
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.024 -0.148 -0.039 0.076 38.892
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.0779549 0.0146846 73.407 <2e-16 ***
## cashnequsd_n -0.0001760 0.0241166 -0.007 0.994
## de_n 0.0060271 0.0180973 0.333 0.739
## ebitda_n 0.0102945 0.0630789 0.163 0.870
## epsusd_n 0.0197100 0.0186922 1.054 0.292
## equityusd_n -0.0090325 0.0297634 -0.303 0.762
## fcf_n 0.0053644 0.0309037 0.174 0.862
## revenueusd_n -0.0078120 0.0277820 -0.281 0.779
## gp_n 0.0001712 0.0300626 0.006 0.995
## liabilities_n -0.0018660 0.0341445 -0.055 0.956
## ncff_n 0.0065067 0.0217269 0.299 0.765
## ncfi_n 0.0012456 0.0227850 0.055 0.956
## ncfo_n 0.0042575 0.0431728 0.099 0.921
## netinc_n -0.0058064 0.0462327 -0.126 0.900
## pb_n 0.0213426 0.0172070 1.240 0.215
## pe1_n 0.0012915 0.0147944 0.087 0.930
## sharesbas_n -0.0128522 0.0216726 -0.593 0.553
## workingcapital_n -0.0030277 0.0246248 -0.123 0.902
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7877 on 2881 degrees of freedom
## Multiple R-squared: 0.002126, Adjusted R-squared: -0.003763
## F-statistic: 0.361 on 17 and 2881 DF, p-value: 0.9921
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.1789 -0.1740 -0.0577 0.0861 9.7723
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.1244176 0.0080601 139.505 < 2e-16 ***
## cashnequsd_n 0.0101455 0.0127910 0.793 0.4277
## de_n -0.0463170 0.0093210 -4.969 7.11e-07 ***
## ebitda_n -0.0228807 0.0271396 -0.843 0.3993
## epsusd_n -0.0002878 0.0090627 -0.032 0.9747
## equityusd_n -0.0297569 0.0158895 -1.873 0.0612 .
## fcf_n 0.0237160 0.0151671 1.564 0.1180
## revenueusd_n -0.0159993 0.0141274 -1.133 0.2575
## gp_n -0.0206879 0.0175935 -1.176 0.2397
## liabilities_n 0.0313528 0.0176401 1.777 0.0756 .
## ncff_n 0.0028819 0.0114682 0.251 0.8016
## ncfi_n 0.0021917 0.0124281 0.176 0.8600
## ncfo_n -0.0174223 0.0209238 -0.833 0.4051
## netinc_n 0.0116724 0.0190718 0.612 0.5406
## pb_n 0.0725291 0.0084498 8.584 < 2e-16 ***
## pe1_n -0.0099871 0.0068224 -1.464 0.1433
## sharesbas_n 0.0150355 0.0119903 1.254 0.2099
## workingcapital_n -0.0018128 0.0130437 -0.139 0.8895
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4343 on 2949 degrees of freedom
## Multiple R-squared: 0.03533, Adjusted R-squared: 0.02977
## F-statistic: 6.352 on 17 and 2949 DF, p-value: 5.891e-15
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8593 -0.1027 -0.0067 0.0775 4.1164
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.9657672 0.0044754 215.794 < 2e-16 ***
## cashnequsd_n -0.0062570 0.0071805 -0.871 0.3836
## de_n -0.0014130 0.0055192 -0.256 0.7980
## ebitda_n -0.0015179 0.0209664 -0.072 0.9423
## epsusd_n 0.0363460 0.0057450 6.327 2.89e-10 ***
## equityusd_n -0.0016980 0.0085154 -0.199 0.8420
## fcf_n -0.0154614 0.0089293 -1.732 0.0835 .
## revenueusd_n 0.0159357 0.0079413 2.007 0.0449 *
## gp_n -0.0066066 0.0107065 -0.617 0.5372
## liabilities_n 0.0091190 0.0104270 0.875 0.3819
## ncff_n 0.0010090 0.0063998 0.158 0.8747
## ncfi_n -0.0009621 0.0073953 -0.130 0.8965
## ncfo_n 0.0256372 0.0119958 2.137 0.0327 *
## netinc_n -0.0042161 0.0158853 -0.265 0.7907
## pb_n 0.0008507 0.0053369 0.159 0.8734
## pe1_n 0.0073280 0.0039621 1.850 0.0645 .
## sharesbas_n -0.0024332 0.0066236 -0.367 0.7134
## workingcapital_n 0.0038923 0.0072523 0.537 0.5915
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.239 on 2906 degrees of freedom
## Multiple R-squared: 0.03725, Adjusted R-squared: 0.03162
## F-statistic: 6.614 on 17 and 2906 DF, p-value: 9.298e-16
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97444 -0.10145 -0.01377 0.08218 2.48002
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.0100803 0.0038945 259.359 < 2e-16 ***
## cashnequsd_n 0.0118107 0.0062035 1.904 0.057 .
## de_n -0.0025228 0.0045515 -0.554 0.579
## ebitda_n -0.0174550 0.0180692 -0.966 0.334
## epsusd_n 0.0266494 0.0052449 5.081 3.99e-07 ***
## equityusd_n -0.0088718 0.0074246 -1.195 0.232
## fcf_n -0.0008175 0.0080334 -0.102 0.919
## revenueusd_n 0.0003193 0.0067595 0.047 0.962
## gp_n -0.0023617 0.0091825 -0.257 0.797
## liabilities_n 0.0049472 0.0090634 0.546 0.585
## ncff_n 0.0038283 0.0059145 0.647 0.518
## ncfi_n 0.0031718 0.0065314 0.486 0.627
## ncfo_n 0.0179212 0.0112461 1.594 0.111
## netinc_n -0.0018691 0.0127154 -0.147 0.883
## pb_n 0.0057576 0.0047160 1.221 0.222
## pe1_n -0.0006006 0.0036653 -0.164 0.870
## sharesbas_n 0.0066495 0.0059041 1.126 0.260
## workingcapital_n -0.0023348 0.0060591 -0.385 0.700
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2105 on 2919 degrees of freedom
## Multiple R-squared: 0.01439, Adjusted R-squared: 0.008646
## F-statistic: 2.506 on 17 and 2919 DF, p-value: 0.0005855
##
##
## Call:
## lm(formula = return_price ~ ., data = obj)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9287 -0.1288 -0.0059 0.1081 9.3448
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.878e-01 5.743e-03 172.003 < 2e-16 ***
## cashnequsd_n 8.820e-03 8.978e-03 0.982 0.325990
## de_n -7.630e-03 6.549e-03 -1.165 0.244084
## ebitda_n -4.369e-02 2.207e-02 -1.980 0.047778 *
## epsusd_n 3.159e-02 7.733e-03 4.085 4.53e-05 ***
## equityusd_n 7.666e-03 1.071e-02 0.716 0.474017
## fcf_n 2.413e-02 1.047e-02 2.304 0.021266 *
## revenueusd_n -5.240e-07 9.758e-03 0.000 0.999957
## gp_n 3.132e-02 1.252e-02 2.502 0.012416 *
## liabilities_n 1.179e-02 1.236e-02 0.954 0.340142
## ncff_n 6.082e-03 7.400e-03 0.822 0.411192
## ncfi_n 2.127e-03 8.770e-03 0.243 0.808354
## ncfo_n -1.660e-02 1.636e-02 -1.014 0.310445
## netinc_n 4.356e-03 1.571e-02 0.277 0.781664
## pb_n 2.339e-02 6.337e-03 3.690 0.000228 ***
## pe1_n 1.062e-03 5.858e-03 0.181 0.856109
## sharesbas_n -1.677e-02 8.632e-03 -1.942 0.052188 .
## workingcapital_n -4.168e-03 9.245e-03 -0.451 0.652169
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3084 on 2892 degrees of freedom
## Multiple R-squared: 0.02131, Adjusted R-squared: 0.01556
## F-statistic: 3.704 on 17 and 2892 DF, p-value: 4.103e-07