creative-quant

library(IBrokers)
library(twsInstrument)

tws <- twsConnect(host='127.0.0.1', port=4001)
contract <- getContract("EUR.USD")
reqHistoricalData( tws, contract, verbose=T, whatToShow="BID" )
reqHistoricalData( tws, contract, verbose=T, whatToShow="ASK" )
twsDisconnect(tws)

creative-quant

#sources
#https://www.quandl.com/CURRFX/USDCAD-Currency-Exchange-Rates-USD-vs-CAD
#curl https://www.quandl.com/api/v1/datasets/CURRFX/USDCAD.csv -o /tmp/USDCAD.csv
#https://www.quandl.com/DOE/RWTC-WTI-Crude-Oil-Spot-Price-Cushing-OK-FOB
#curl https://www.quandl.com/api/v1/datasets/DOE/RWTC.csv -o /tmp/RWTC.csv

library(xts)
library(ggplot2)

usd.cad <- read.csv("/tmp/USDCAD.csv")

creative-quant

############################################################
## Content of the Traders in Financial Futures (TFF) Report
## http://www.cftc.gov/ucm/groups/public/@commitmentsoftraders/documents/file/tfmexplanatorynotes.pdf
############################################################
#  Dealer/Intermediary
# These participants are what are typically described as the "sell side” of the market. Though they
# may not predominately sell futures, they do design and sell various financial assets to clients.
# They tend to have matched books or offset their risk across markets and clients. Futures
# contracts are part of the pricing and balancing of risk associated with the products they sell and 
# their activities. These include large banks (U.S. and non-U.S.) and dealers in securities, swaps

creative-quant

#curl http://www.dailyfx.com/files/Calendar-02-01-2015.csv -o /tmp/Calendar-02-01-2015.csv
cal <- read.csv("/tmp/Calendar-02-01-2015.csv")

creative-quant

library(ggplot2)

#curl 'http://research.stlouisfed.org/fred2/series/PAYEMS/downloaddata' --data 'form%5Bnative_frequency%5D=Monthly&form%5Bunits%5D=lin&form%5Bfrequency%5D=Monthly&form%5Baggregation%5D=Average&form%5Bobs_start_date%5D=1939-01-01&form%5Bobs_end_date%5D=2015-01-01&form%5Bfile_format%5D=csv&form%5Bdownload_data_2%5D=' -o /tmp/PAYEMS.csv
nfp <- read.csv("/tmp/PAYEMS.csv")
nfp$DATE <- as.Date( nfp$DATE, "%Y-%m-%d" )
df <- data.frame( change=diff(nfp$VALUE), date=tail(nfp$DATE,-1) )
plot <- ggplot(df,aes(x=date,y=change)) + 
  geom_area()
plot

creative-quant

#http://www20.statcan.gc.ca/tables-tableaux/cansim/csv/02820087-eng.zip

creative-quant

/*
 * AlmostEqual.h
 *
 */

#ifndef ALMOSTEQUAL_H_
#define ALMOSTEQUAL_H_

// Usable AlmostEqual function - http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm
bool AlmostEqual(float A, float B) {

creative-quant

[alias]
    sstash = "!f() { git stash save $1; }; f"
    sshow = "!f() { echo $@; git stash show stash^{/$*} -p; }; f"
    sapply = "!f() { git stash apply stash^{/$*}; }; f"

creative-quant

#$ curl -o /tmp/cad.cpi.csv  http://www.statcan.gc.ca/daily-quotidien/160122/cg160122a001-eng.csv
# "The 12-month change in the Consumer Price Index (CPI) and the CPI excluding gasoline, 12-month % change"
# ,"CPI","CPI excluding gasoline"

library(ggplot2)

cad.cpi <- read.table( "/tmp/cad.cpi.csv", sep = ",", col.names=c("date", "cpi", "exgas"), skip=2, fill=T )
cad.cpi <- cad.cpi[1:(nrow( cad.cpi ) - 1),]
cad.cpi$date = as.Date( paste( cad.cpi$date, '01' ), "%B %Y %d" )
df <- data.frame(cad.cpi)

creative-quant

library(xts)
library(ggplot2)

#cad gdp
#curl http://www20.statcan.gc.ca/tables-tableaux/cansim/csv/03790031-eng.zip -o /tmp/ca.gpd.zip && unzip /tmp/ca.gpd.zip -d /tmp
#curl http://www.statcan.gc.ca/cgi-bin/sum-som/fl/cstsaveascsv.cgi?filename=gdps04a-eng.htm&lan=eng -o 
#http://www20.statcan.gc.ca/tables-tableaux/cansim/csv/03790031-eng.zip
#Ref_Date,GEO,SEAS,PRICES,NAICS,Vector,Coordinate,Value
if( !exists( "ca.gdp" ) ) {
  ca.gdp <- read.csv("/tmp/03790031-eng.csv")