COMP226 Assignment 1: Limit Order
Book Pricer
Continuous
Assessment Number
1 (of 2)
Weighting 10%
Assignment Circulated 10:00 Tuesday 19 February 2019
Deadline 12:00 Thursday 7 March 2019
Submission Mode Electronic only
http://www.csc.liv.ac.uk/cgi-…
Learning Outcomes
Assessed
This assignment will address the following learning outcomes:
Have an understanding of market microstructure and its
impact on trading.
Understand the spectrum of computer-based trading
applications and techniques, from profit-seeking trading
strategies to execution algorithms.
Understand the benchmarks used to evaluate execution
algorithms.
Purpose of Assessment The goal of this assignment is to implement a limit order book
pricer
Marking Criteria Correctness (80%); Readability (20%). See the end of this
document.
Submission necessary
in order to satisfy
module requirements
No
Late Submission
Penalty
Standard UoL policy; note that no resubmissions after the
deadline will be considered.
Expected time taken Roughly 8-12 hours
Please submit a single file called MWS-username.R, where MWS-username is your MWS
username (which you use to log on to the submission system)
This file must contain a function called pricer, whose form and functionality is described
below. The file may also contain other functions used by pricer, but the function pricer
should not be called within the file.
Warning
Your code will be put through the department’s automatic plagiarism and collusion
detection system. Student’s found to have plagiarized or colluded will likely receive a
mark of zero. Do not discuss or show your work to other students. Several students
were found to have plagiarised in previous years and this had serious consequences
for their studies (two students had their studies terminated and left without a degree).
To aid with marking, your code will be put through a number of automatic tests, so you
must ensure that it is written as specified below.
Learning Outcomes
The syllabus for COMP226 can be found here:
http://intranet.csc.liv.ac.uk…
This assignment will address the following two learning outcomes:
Have an understanding of market microstructure and its impact on trading.
Understand the spectrum of computer-based trading applications and techniques, from
profit-seeking trading strategies to execution algorithms.
Understand the benchmarks used to evaluate execution algorithms.
Marking
The marking will be as follows:
80% for correctness; this will be determined primarily by automatic tests. If your code
fails many of these then a mark will be decided via manual testing of your code.
20% for readability of your code; first and foremost you should ensure that your code
so is correct. The next most important thing is that it can be understood by others; to
aid its readability your are encouraged to include clear informative comments.
Background
In this exercise you will write an R program to analyse the log file of a limit order book
market.
The log file contains messages that describe changes to the book. Each message either
adds an order to the book, or
reduces the size of an order in the book (possibly removing the order entirely).
Problem
The function pricer should take three arguments as follows
pricer <- function(infile, outfile, targetsize)
pricer should write its output to the file outfile. The file infile contains the messages of
the limit order book log file, as described in more detail below.
As the book is modified (according to the messages, which should be processed in order),
pricer calculates the
total expense you would incur if you bought targetsize shares (by taking as many asks
as necessary, lowest first), and
the total income you would receive if you sold targetsize shares (by hitting as many
bids as necessary, highest first).
Each time the income or expense changes, it prints the changed value to outfile in
the format described below.
Input Format
The market data log contains one message per line (terminated by a single linefeed
character, ‘\n’), and each message is a series of fields separated by spaces.
An “Add Order to Book” message looks like this:
timestamp ‘A’ order-id side price size
Where all fields are variables except ‘A’, which is a constant (examples below).
Field Meaning
timestam
p
The time when this message was generated by the market, as milliseconds
since midnight.
A A literal string identifying this as an “Add Order to Book” message.
order-id A unique string that subsequent “Reduce Order” messages will use to modify
this order.
side A ‘B’ if this is a buy order (a bid), and a ‘S’ if this is a sell order (an ask).
price The limit price of this order.
size The size in shares of this order, when it was initially sent to the market by
some stock trader.
A “Reduce Order” message looks like this:
timestamp ‘R’ order-id size
Where all fields are variables except ‘R’, which is a constant (examples below).
Field Meaning
timestam
p
The time when this message was generated by the market, as milliseconds
since midnight.
R A literal string identifying this as an “Reduce Order” message.
order-id The unique string that identifies the order to be reduced.
size The amount by which to reduce the size of the order. This is not the new size
of the order. If size is equal to or greater than the existing size of the order,
the order is removed from the book.
The log file messages are sorted by timestamp.
Output Format
pricer’s output consists of one message per line in this format:
timestamp action total
Field Meaning
timestam
p
The timestamp from the input message that caused this output message to
be generated.
action A string: ‘B’ if this message contains the new expense to buy targetsize
shares, and ‘S’ if this message contains the new income for selling
targetsize shares.
total The total expense (if action is ‘B’) to buy targetsize shares, or the total
income (if action is ‘S’) for selling targetsize shares. If the book does not
contain targetsize shares in the appropriate type of order (asks for
expense; bids for income), the total field contains the string ‘NA’.
If pricer encounters an error in an input message, it prints a warning to the R console and
goes to the next message.
Example Input and Output
Here is an example run of pricer with a targetsize of 200. Input messages are in the left
column. Notes and output messages are in the right column.
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.
28800758 A d B 44.18 157 The bid sizes now total 257, which is more than the
target size of 200. To sell 200 shares, you would first
hit the bid at 44.18 for 157 shares, spending
$6936.26. Then you would hit the bid at 44.10 for
the remaining 43 shares, spending another
$1896.30. Your total income would be $8832.56, so
pricer emits this message:
28800758 S 8832.56
28800773 A e S 44.38 100 The book now contains a single ask of size 100,
which is still not enough to change the target size
expense from ‘NA’.
28800796 R d 157 This removes bid ‘d’ from the book, leaving just one
bid with a size of 100 on the book, so the income
from selling changes to ‘NA’:
28800796 S NA
28800812 A f B 44.18 157 This new bid brings the total bid size back over 200,
so the selling income is no longer ‘NA’:
28800812 S 8832.56
28800974 A g S 44.27 100 This ask brings the total ask size up to 200, exactly
the target size. The total expense for buying 200
shares would be 100 * $44.27 + 100 * $44.38:
28800974 B 8865.00
28800975 R e 100 Removing ask ‘e’ from the book leaves less than 200
shares on the ask side, so the buying expense
changes back to ‘NA’:
28800975 B NA
28812071 R f 100 Reducing bid ‘f’ by 100 shares leaves only 157
shares on the bid side, so the selling income changes
to ‘NA’:
28812071 S NA
28813129 A h B 43.68 50 This new bid makes it possible to sell 200 shares: 57
at $44.18, 100 at $44.10, and the last 43 at $43.68.
28813129 S 8806.50
28813300 R f 57 This removes bid ‘f’ from the book, so it is no longer
possible to sell 200 shares:
28813300 S NA
28813830 A i S 44.18 100 This ask makes it possible to buy 200 shares again:
100 at $44.18 and 100 at $44.27.
28813830 B 8845.00
28814087 A j S 44.18 1000 This ask has the same price as an existing ask, and
these two asks are tied for the best asking price.
This means you could now buy all 200 shares at
$44.18 instead of buying half of them at $44.27, so
the buying expense decreases:
28814087 B 8836.00
28814834 R c 100 This leaves only 50 shares on the bid side (all in
order ‘h’), so it is still not possible to sell 200 shares.
The selling income is therefore unchanged from ‘NA’
and pricer prints no output message.
28814864 A k B 44.09 100 Only 150 shares on the bid side, so no output
needed.
28815774 R k 100 Back to 50 shares on the bid side; still no output
needed.
28815804 A l B 44.07 175 There are now more than 200 shares on the bid side.
You could sell 175 shares at $44.07 each, and the
remaining 25 shares at $43.68 each:
28815804 S 8804.25
28815937 R j 1000 After ask ‘j’ is removed from the book, you can still
buy 200 shares: 100 at $44.18 each, and 100 at the
worse price of $44.27.
28815937 B 8845.00
28816245 A m S 44.22 100 Since $44.22 is a better price than $44.27, the
buying expense decreases:
28816245 B 8840.00
Note that the book initially contains no orders, and that the buying expense and selling
income are both considered to start at ‘NA’. Since pricer only produces output when the
income or expense changes, it does not print anything until the total size of all bids or the
total size of all asks meets or exceeds targetsize.
Test Data
You can download three sample input files here:
https://www2.csc.liv.ac.uk/~r…
Your program needs to work with any targetsize.
In case you want to test your implementation on the example input data from above, here it
is in an easy-to-cut-and-paste format:
28800538 A b S 44.26 100
28800562 A c B 44.10 100
28800744 R b 100
28800758 A d B 44.18 157
28800773 A e S 44.38 100
28800796 R d 157
28800812 A f B 44.18 157
28800974 A g S 44.27 100
28800975 R e 100
28812071 R f 100
28813129 A h B 43.68 50
28813300 R f 57
28813830 A i S 44.18 100
28814087 A j S 44.18 1000
28814834 R c 100
28814864 A k B 44.09 100
28815774 R k 100
28815804 A l B 44.07 175
28815937 R j 1000
28816245 A m S 44.22 100
And here is the corresponding output:
28800758 S 8832.56
28800796 S NA
28800812 S 8832.56
28800974 B 8865.00
28800975 B NA
28812071 S NA
28813129 S 8806.50
28813300 S NA
28813830 B 8845.00
28814087 B 8836.00
28815804 S 8804.25
28815937 B 8845.00
28816245 B 8840.00
Hints
We did some relevant things in the Worksheet 02. For example, we computed the
average price of a market order; the total price was obviously part of that calculation.
Some further guidance follows.
Data Input
There are many ways to read and write data in R.
read.table reads in a file and returns a data.frame. If you are reading in strings and want
them to stay as strings (rather than become factors) you should add to the arguments
stringsAsFactors=FALSE. There are variants of read.table that you may want to check
out, like read.csv and read.csv2.
Also the data in the assignment does not all have the same number of fields per line. Thus
you want to use the fill=TRUE argument.
An alternative to reading in the whole input file is to read it line by line. For that open a
connection using file. For example,
con <- file(“FILENAME”, open = “r”)
while (length(oneLine <- readLines(con, n = 1, warn = FALSE)) > 0) {
# do stuff, for example
print(oneLine)
}
close(con)
The line by line approach will be slow. For a very large file it may not be possible to read the
whole file into memory in which case one would typically use an incremental approach but
reading in chunks rather than lines (read.table allows that).
Note
One problem you have to solve for Assignment 1 is that there are two types of
message with different fields. There are different ways to approach this, and it’s left to
you to decide what to do.
Why don’t you start right a way and load some of the sample data for Assignment 1 into R.
Data Output
There is a function write.table, however for Assignment 1 one you may just want to write
each output line as it is produced (rather than store the output and only write it to a file in
the end).
One way to write the output incrementally is with cat.
price <- 100
cat(file=”test.out”,”The price is”, price, “\n”)
Now look in your working directory and you will find the file test.out.
file.show(“test.out”)
The price is 100
(END)
For Assignment 1 you may want to append to a file, which cat does as follows:
price <- 101
cat(file=”test.out”,append=TRUE,”The price is now”, price, “\n”)
file.show(“test.out”)
The price is 100
The price is now 101
(END)
By the way, cat will write to the console if a file is not provided to it as an argument.
One other function you will need is format. The best way to check that your program for
Assignment 1 is correct is to run it on the sample input and compare your output with the
sample output; the easiest way to do this is with a text file comparison tool such a diff on
Linux/Unix systems. For diff tools on other platforms see
http://stackoverflow.com/ques…
Anyway, use these diff tools to make your output identical to the sample output, and
format can help you do that. For example,
prices <- c(800.5, 800.25, 800)
cat(prices, ‘\n’)
800.5 800.25 800
cat(format(prices,nsmall=2),’\n’)
800.50 800.25 800.00
Calling the function pricer
You need to make sure that when your source code is sourced with something like
source(‘x3xx.R’)
that is gives no errors, and, will then allow the automatic tests to call pricer somewhat like
what follows.
pricer(infile=”PATH_TO_INPUT”,outpfile=”PATH_TO_OUTPUT”,targetsize=50)
Do not include the call to pricer in the file you submit.
That’s it. Good luck, and if you have questions please ask in the practicals or in the lectures.
MAKE SURE YOU READ THIS DOCUMENT CAREFULLY – ALMOST ALL THE
INFORMATION YOU NEED TO COMPLETE THIS ASSIGNMENT IS EITHER HERE IN
THIS DOCUMENT OR IN THE SLIDES OR WORKSHEETS.
WX：codehelp