CISC 849 : Applications in Fintech

ARUNPRABHU SADAIYAPPANDept of Computer & Information Sciences

University of Delaware

BIG DATA APPROACH TO ANALYZING MARKET VOLATILITY

CISC 849 : Applications in Fintech

WHY BIG DATA TECHNOLOGY?

CISC 849 : Applications in Fintech

BIG DATA IN FINANCE SERVICES• Markets

• Customers

• Channels

• Products

• Regulations

• Competitors

• Suppliers

• Employees

CISC 849 : Applications in Fintech

MARKET LIQUIDITY

Market's ability to facilitate the purchase or sale of

an asset without causing drastic change in the asset's

price

CISC 849 : Applications in Fintech

LIQUIDITY INDICATOR• VOLUME SYNCHRONISED PROBABILITY OF

INFORMATION TRADING

CISC 849 : Applications in Fintech

TECHNIQUES FOR BIG DATA ANALYSIS

• EFFICIENT FILE ORGANISATION FOR STORING TRADING RECORDS

• EFFICIENT ALGORITHM FOR COMPUTING VPIN

• PARALLELIZATION OF COMPUTATIONAL TASKS

CISC 849 : Applications in Fintech

FILE ORGANIZATION

• 67 Months worth of data (Liquid futures trade information)

• File Format : CSV (Comma separated value)

• File Size : 140 GB

Processing time for computing VPIN values : 142 seconds

CONVENTIONAL METHOD:

CISC 849 : Applications in Fintech

FILE ORGANIZATION

• Same amount of data (for 67 months)

• File Format : HDF5 (Hierarchical Data Format)

• File Size : 41 GB

Processing time for computing VPIN values : 0.4 second

PROPOSED METHOD:

CISC 849 : Applications in Fintech

FILE ORGANIZATION

• 29% gain in memory storage

• Less time in reading/writing the file

• Better organization for data

Reason behind the Efficiency: HDF5 files store data in binary form

IMPROVEMENT:

CISC 849 : Applications in Fintech

ALGORITHM FOR COMPUTING VPINInitially, Data arrives at irregular frequency

Volume BarsVolume Bars

Bulk Volume Bulk Volume ClassificationClassification

BucketsBuckets

VPINVPIN

CISC 849 : Applications in Fintech

VOLUME BAR• SHELL SORT – To order trades in a volume

bar

• To compute Median Prices

CISC 849 : Applications in Fintech

SHELL SORT ANALYSIS

• BEST CASE (LOWER BOUND): O(N(log N )^2) • WORST CASE (UPPER BOUND): Θ(N^2)

In this paper, the runtime is mentioned as O(log N )

In-place Sorting (Space complexity is O(N) )

CISC 849 : Applications in Fintech

ALGORITHM FOR COMPUTING VPIN

Time Taken to construct Volume bars with different nominal prices

CISC 849 : Applications in Fintech

BULK VOLUME CLASSIFICATION• Trades are classified as “Buyer-initiated” or

“Seller-initiated”

• BVC assigns a fraction of volume as buys

The remainder as sells based on normalized sequential price change

CISC 849 : Applications in Fintech

BUCKETS

• When forming buckets Each volume bar is considered as a single trade with the nominal price

• 30 Volume bars in a buckets (maximum upto 50)

• Most recent buckets with buy and sell volumes Kept in Fixed Memory

CISC 849 : Applications in Fintech

BUCKETS

Pseudocode for storing Volume in Buckets

CISC 849 : Applications in Fintech

CALCULATING VPIN

FORMULA:

PSEUDOCODE:

CISC 849 : Applications in Fintech

EXPERIMENTAL RESULTS

Statistics on prices for volume bars and the resulting VPIN:

(Overall trades of ES)

CISC 849 : Applications in Fintech

EXPERIMENTAL RESULTS

CISC 849 : Applications in Fintech

PARALLELIZATION

PREFERRED IMPLEMENTATION: POSIX THREADS

Instrument with large number of trades assigned first

CISC 849 : Applications in Fintech

HEDGE ANALYTICS – SWISS BASED STARTUP

•RISK FACTOR ANALYSIS

•PERFORMANCE ANALYSIS

•NEW CUSTOMER WIN RATE ANALYSIS

Universal Meta data Search Engine

Incorporated NoSQL Technology to avoid inconsistency

CISC 849 : Applications in Fintech

THANK YOU!