Jane Street runs a large trading business on software written almost entirely in OCaml, a statically typed functional language. Yaron Minsky shows the reasons for choosing Ocaml and how it worked out.
Allard Buijze introduces CQRS and related concepts along with case studies showing how it is used in finance, gaming and healthcare to meet the demands of modern web-based applications.
The authors present design patterns and use cases of capital market firms that are incorporating big data technologies into their credit risk analysis, price discovery or sentiment analysis software.
Chris Swan discusses user experience for banking and financial mobile applications, architectures, and the frameworks and containers that ease the way to secure deployment into production.
Stephane Dubois shares insight in Xignite’s road building a business model providing APIs for accessing financial data.
Charles Cai, Ashwani Roy discuss a robust, cost effective, hypothetical solution to address extreme challenges in financial institutions, from decision making support to pricing and risk management.
John Davies walks through a reference implementation of a in-memory database meant to combine dozens of different legacy databases developed by banks over time.
Andrew Sheppard overviews the driving forces behind GPU’s adoption by the financial industry, and explains the use of the Monte Carlo technique on GPUs.
Ari Zilka informs on the cloud tools and process changes needed to take place for the financial and banking institutions to become interested in the technologies cloud computing has to offer.
Uri Cohen discusses several types of queues with their pros and cons used in financial and trading industries for highly parallelized data processing.
Frank Tarsillo , John Davies, Jon Vernon and Ari Zilka (moderator) discuss the technologies and architectures used these days to manage large amounts of sensitive data in top financial institutions.
James Spooner discusses the need to make good use of the underlying silicon using Dataflow computing and parallelism to improve throughput and latency for optimized data processing performance.