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Arguments to pricer function

The function pricer should take three arguments as follows
pricer <- function(infile, outfile, targetsize)

• infile is a string which contain the path to the input file
which is read from the harddrive; the file infile contains the
messages of the limit order book log file
• pricer should write its output to the a file with path specified
the string outfile, which is an argument to pricer
• the final argument is targetsize, which is a natural number,
e.g., 1 or 100, or 250

Test Data

You can download three sample input files here:
https://www2.csc.liv.ac.uk/~rahul/teaching/comp226/assess.html
For these three sample inputs, output for three values of
targetsize are given, so you have 9 examples to use for testing
Your program needs to workwith any value of `
“targetsize

Sample files

Input	Ouput
targetsiz e = 1	targetsize = 250	targetsize = 1000
sample1
sample2
sample3

Input Format

The input file will contain one message per line
Each message is a series of fields separated by spaces, e.g.
28800538 A b S 44.26 100
An Add Order to Book message looks like this:
timestamp ‘A’ order-id side price size
A Reduce Order message looks like this:
timestamp ‘R’ order-id size
The log file messages are sorted by timestamp

Output Format

pricer’s output should be one message per line in this format:
timestamp action total
28800758 S 8832.56

• If pricer encounters an error in an input message, it prints a
warning to the R console and goes to the next message
• Note: the book initially contains no orders, and the
buying expense and selling income start as ‘NA’
• Since pricer only produces output when the income/expense
changes, it does not print anything until the total size of
all bids or asks meets or exceeds targetsize

Standard Input	Standard Output/Notes
28800538 A b S 44.26 100	No output yet because neither the bids nor the asks in the book have a total of 200 shares yet.
28800562 A c B 44.10 100	Still not enough shares on either side of the book.
28800744 R b 100	This reduces order ‘b’ to zero shares, which removes it from the book, so now the book contains no asks. But there’s still no change to the total income or expense on 200 shares.

data.frame

• data.frame is a data structure in R, like a matrix, but
• unlike a matrix, the columns can be of different types

> df <- data.frame(a=1:3,  
b=c("A","B","C"),  
stringsAsFactors=F)  
> df  
a b  
1 1 A  
2 2 B  
3 3 C

部分解答

pricer <- function(infile,outfile,targetsize) {
  #infile<-"E:\\input.txt"
  #outfile<-"E:\\output1.txt"
  #targetsize=250
  
 
  
  Sbook=data.frame(Timestamp=c(NA),Type=c(NA),OrderId=c(NA),Side=c(NA),Price=c(NA),Size=c(NA))
  Bbook=data.frame(Timestamp=c(NA),Type=c(NA),OrderId=c(NA),Side=c(NA),Price=c(NA),Size=c(NA))
  Sbook<- Sbook[-1,]
  Bbook<- Bbook[-1,]
  flag1=0
  flag2=0
  
  
  for (i in 1: nrow(trade)){#type=A
    if(trade[i,"Type"]=="A"){
      if(trade[i,"Side"]=="B") {
        
        Bbook=rbind(Bbook,trade[i,])
        if(is.null(bprice(Bbook,targetsize))==FALSE) {
          cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " S ", format(bprice(Bbook,targetsize),nsmall=2),'\n')
          flag2=1
        }
        else{ if(flag2==1)cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " S NA",'\n')}
      }
      else {
        Sbook=rbind(trade[i,],Sbook)
        if(is.null(price(Sbook,targetsize))==FALSE) {
          cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " B ", format(price(Sbook,targetsize),nsmall=2),'\n')
          flag1=1
        }
        else{ if(flag1==1)cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " B NA",'\n')}
      
      }
    }
    #type=R
    else{
      reduceS=which(Sbook[1:i-1,"Order-Id"]==trade[i,"Order-Id"])
      if(is.null(reduceS)!=TRUE){
        Sbook[reduceS,"Size"]=as.numeric(Sbook[reduceS,"Size"])-as.numeric(trade[i,"Size"])
        if(length(Sbook[reduceS,"Size"])==0)Sbook=Sbook[-reduceS,]
        if(is.null(price(Sbook,targetsize))==FALSE) {
          cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " B ", format(price(Sbook,targetsize),nsmall=2),'\n')
          flag1=1
        }
        else{ if(flag1==1)cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " B NA",'\n')}
        
        
      }else {
        reduceB=which(Bbook[1:i-1,"Order-Id"]==trade[i,"Order-Id"])
        Bbook[reduceB,"Size"]=as.numeric(Bbook[reduceB,"Size"])-as.numeric(trade[i,"Size"])
        if(length(Bbook[reduceB,"Size"])==0)Bbook=Bbook[-reduceB,]
        if(is.null(bprice(Bbook,targetsize))==FALSE) {
          cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " S ", format(bprice(Bbook,targetsize),nsmall=2),'\n')
          flag2=1
        }
        else{ if(flag2==1)cat(file=outfile,append=TRUE,trade[i,"Timestamp"], " S NA",'\n')}
        
        
      }
    }
   
    
    
  }
}

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关于分析师

在此对LE PHUONG对本文所作的贡献表示诚挚感谢，她在山东大学完成了计算机科学与技术专业的硕士学位，专注数据分析、数据可视化、数据采集等。擅长Python、SQL、C/C++、HTML、CSS、VSCode、Linux、Jupyter Notebook。