Submission deadline: August 15th, 11:59
EDT Author notification: September 12th Final version due: October 3rd
Call For Papers
The purpose of this workshop is to bring
together practitioners, researchers, vendors, and scholars from the complementary
fields of computational finance and high performance computing, in order
to promote an exchange of ideas, discuss future collaborations and develop
new research directions. Financial companies increasingly rely on high
performance computers to analyze high volumes of financial data, automatically
execute trades, and manage risk.
As financial market data continues to
grow in volume and complexity, computational capabilities of emerging hardware
also increases. Extracting high performance from emerging architectures
requires a combination of domain knowledge and specialized technical skills.
The workshop will explore how researchers, scholars, vendors and practitioners
are collaborating to address high performance computing research challenges.
We have peer-reviewed paper submissions
that cover various aspects of computational finance. In addition to submissions
that deal with performance and programmability challenges, theoretical
analysis, algorithms, and practical experience in computational finance,
we have focussed on submissions that demonstrate or result from the collaboration
between financial practitioners, and academics, researchers, or vendors.
For 2016, we are particularly interested
in submissions addressing the following emerging topics in high performance
computational finance: · High performance machine learning
for financial trading · Use of the FPGAs for high frequency
trading · XVA pricing · Adjoint algorithmic differentiation (AAD) · Many-core implementation of derivative
pricing, calibration, risk management · Use of high performance Python
and R
Additional topics of interest to this
workshop include, but are not restricted to: · Use of accelerator platforms
for stream processing · Fast algorithms for algorithmic
trading and high frequency risk management · Scalable in-memory data processing
platforms for large-scale computations · Software infrastructure for high
performance and high productivity · Use of parallel design patterns
for mapping of applications to parallel hardware · Financial libraries and run-times · Use of accelerator platforms
for stream processing · Use of heterogeneous hardware
in computational finance · Financial applications of high
performance computing: risk algorithms, derivative pricing, algorithmic
trading, arbitrage · High-bandwidth/low-latency streaming
of market data · Cluster computing for computational
finance · Financial data center engineering · Computational algorithms for
finance · Move from capacity to capability
computing in financial applications
Author Instructions
Submitted papers must be no more than
8 pages in length. The camera ready version of accepted papers must be
in ACM Proceedings format (http://www.acm.org/publications/proceedings-template)
. Each submission will receive at least
three reviews from the technical program committee and authors of selected
submissions will have 30 minutes to present their work at the workshop. Papers should be submitted in electronic
form to jmoreira@xxxxxxxxxxx
Program Committee
John Ashley, NVIDIA Corp Michael Creel, Universitat Autònoma
de Barcelona Dirk Eddelbuettel, Ketchum Trading Mike Giles, Oxford University Juho Kanniainen, Tampere University
of Technology Hicham Lahlou, Xcelerit Peter Lankford, STAC John Lockwood, AlgoLogix Pat Miller, Jump Trading Uwe Naumann, RWTH Aachen Cornelis W. Oosterlee, CWI Brian Peterson, DV Trading José Antonio García Rodríguez, Universidade
da Coruña Jason Sewall, Intel Corporation Brad Spiers, Micron Jacques Du Toit, NAG Muhammad Zubair, Old Dominion University
Steering Committee
Matthew Dixon, Illinois Institute of
Technology Jose Moreira, IBM Thomas J. Watson Research
Center Shih-Hau Tan, University of Greenwich
José E. Moreira Research Staff Member Future POWER Systems Concept Team IBM Thomas J. Watson Research Center Yorktown Heights NY 10598-0218 phone: 1-914-945-1709, fax: 1-914-945-4425 e-mail: jmoreira@xxxxxxxxxx URL: http://www.research.ibm.com/people/m/moreira
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