| obAnalytics-package {obAnalytics} | R Documentation |
obAnalytics.
Description
Limit order book analytics.
Main functionality
Limit order book event processing.
Visualise order book state and market impacts.
Order book reconstruction and analysis.
Data processing
The main focus of this package is reconstruction of a limit order book.
The processData function will perform data processing based on
a supplied CSV file, the schema of which is defined in the
processData function documentation. Example preprocessed limit
order data are also provided (see lob.data) which has been
derived from the example raw data provided the inst/extdata directory.
The data processing consists of a number of stages:
Cleaning of duplicate and erroneous data.
Identification of sequential event relationships.
Inference of trade events via order-matching.
Inference of order types (limit vs market).
Construction of volume by price level series.
Construction of order book summary statistics.
Limit order events are related to one another by volume deltas (the change in volume for a limit order). To simulate a matching-engine, and thus determine directional trade data, volume deltas from both sides of the limit order book are ordered by time, yielding a sequence alignment problem, to which the the Needleman-Wunsch algorithm has been applied.
Visualisation
The package provides a number of functions for the visualisation of limit order events and order book liquidity. The visualisations all make use of the ggplot2 plotting system:
- plotTimeSeries
General time series plotting.
- plotTrades
Plot
tradesdata.- plotCurrentDepth
Visualise the shape of an
orderBook.- plotPriceLevels
Visualise volume by price level through time.
- plotVolumePercentiles
Visualise order book liquidity through time.
- plotEventMap
Visualise sequential limit order events by price level.
- plotVolumeMap
Visualise sequential limit order events by volume.
- plotEventsHistogram
Convenience function.
The plotPriceLevels visualisation is designed to show the
ebb and flow of limit order volume at all price levels including the
interplay between the bid/ask spread. It is possible to identify interesting
market participant behaviour and to visualise market shocks and resilience
with this function.
The plotEventMap function is useful for studying systematic
market participant behaviour. Interesting sequential patterns can be observed
in this visualisation as algorithms react to various market events by
repositioning orders.
The plotVolumeMap function shows a visualisation of cancelled
volume through time. It is possible to identify and filter out individual
trading algorithms from this graph.
The plotVolumePercentiles visualisation is inspired by the size
map chart included in many articles from
Nanex research and is intended to
show available market liquidity.
In all visualisations it is possible to filter the data by time, price and volume.
Analysis
In addition to the generated lob.data which are intended to be
used as a basis for further research, the package currently provides a
limited set of trade and order book analysis functions:
- filterDepth
Filter
depthdata by time period.- getSpread
Extract the bid/ask quotes from the
depth.summarydata.- orderBook
Reconstruct a Limit order book from
eventsdata.- tradeImpacts
Group
tradesinto individual impact events.
Additional functionality will be added to the package in the future.
Author(s)
Philip Stubbings phil@parasec.net
References
http://parasec.net/transmission/order-book-visualisation