In jmazar/obmodeling: Modeling, Analysis, and Graphics of Limit Order Book Data

# setup block that doesn't show up in the output
knitr::opts_chunk$set(echo = FALSE)
#knitr::opts_chunk$set(cache = TRUE)
require(obmodeling)
require(quantstrat)
require(knitr)
require(pander)
panderOptions("digits", 2)
Sys.setenv(TZ='GMT')

Introduction

obmodeling is an R package which uses xts time series objects to manipulate and analyze:

• Market depth statistics

• Price movement, liquidity changes [@Cartea2015]

• Market spread [@DeJong2009, pp. 91–96]

• Measures of volatility [@DeJong2009 p. 92, and @Cartea2015]

• PIN/VPIN [@Easley1996, @Easley2012a]

• Price pressure [@Hendershott2014, @Cont2014]

• Trade imbalance [@Cont2014]

Setup

# load the data here, ob_trades & ob_quotes

load.quotes(system.file('extdata/ob_quotes.csv',package = 'obmodeling'))
load.trades(system.file('extdata/ob_trades.csv',package = 'obmodeling'))

• obmodeling uses an environment to store parsed trades and quotes
• you can access that environment via getOB()
• currently supports Reuters data format, more to come

Calling Functions

head(effective.spread('ESH6', store=TRUE),2)

• When applicable functions contain a store function, saving the data in the environment

ob <- getOB()
names(ob$ESH6)

Current Functions

• bidask.changes
• effective.spread
• load.quotes
• load.trades
• market.depth.stats
• quoted.spread
• ticks.wide
• trade.imbalance
• trade.size.stats
• vpin
• wmp

Visualize Order Book

chart.depth('ESH6')

Future Visalizations

{width=50%}

Future Analysis

• Market Toxicity Measures

• Event Analysis [@Almgren2012]

Thanks

Thank You for Your Attention

find it on github at: https://github.com/jmazar/obmodeling

install via:

install_github('jmazar/obmodeling')

Patches and contributions welcome!

References {.smaller}

jmazar/obmodeling documentation built on March 27, 2022, 12:55 a.m.