Financial Trading Techniques - Coursework Example

of Greenwich Registration Number: Financial Trading Techniques – FINA 1070 Leader: Dr. Cesario MateusQn.3 Probit and logit models are among the most popular models.  The dependent variable is a binary response, commonly coded as a 0 or 1 variable.  The decision/choice is whether or not to have, do, use, or adopt.  Examples include whether a consumer makes a purchase or not, and whether an individual participates in the labour market or not. According to the question presented, we are required to find out through probit and logit whether lagged variables (such as other currency pairs, stock indices or other financial instruments) in the stock market or financial markets have an effect on the daily closing price of a given currency pair or whether these lagged variables have no effect whatsoever in the daily closing price of a given currency pair over the period of February 2013 to 2015 February. My data set included currency pairs GBP/USD and EUR/USD as a lagged variable from January 2013 to January 2015 .This since the historical data I found for these currency pairs over the previous years were only available up to January of 2015.I had to modify the data availed so as to work out the probit and logit models on it to provided the required results as shown below. For solving probit and logit one can use excel or programming language R. Since probit equals logit solving probit will give us the logit as well. By use of R programming method we have our in and out logit for the data sample in excel as: # importing excel files. Mydata < - read.csv ("C:\\ Users \\ Lwanga \\ Desktop \\ GBPUSD_day.csv", header = TRUE) # applying Logit/probit on data # convert Rank to a factor (categorical variable) Mydata$Rank < - factor (mydata$Rank) # view first few rows head (mydata) DATE Affect GBPUSD EURUSD Rank 1 20130102 0 1.6250 1.3187 1 2 20130103 0 1.6084 1.3035 1 3 20130104 1 1.6075 1.3078 1 4 20130107 1 1.6125 1.3124 2 5 20130108 0 1.6056 1.3078 2 6 20130109 1 1.6015 1.3053 1 summary (mydata) DATE Affect GBPUSD EURUSD Rank Min. :20130102 Min. :0.0000 Min. :1.486 Min. :1.121 1:256 1st Qu.:20130708 1st Qu.:0.0000 1st Qu.:1.552 1st Qu.:1.298 2:101 Median: 20140114 Median: 0.0000 Median: 1.606 Median: 1.335 3:117 Mean : 20136101 Mean : 0.4026 Mean :1.603 Mean :1.324 4: 60 3rd Qu.:20140718 3rd Qu.:1.0000 3rd Qu.:1.658 3rd Qu.:1.361 Max. :20150123 Max. :1.0000 Max. :1.716 Max. :1.393 new data Read More