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Introduction to QuantLib Development with Luigi Ballabio - London, November 14 - 16th, 2016 - http://bit.ly/QuantLib-2016

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When Big Data Fails! Relative success of adaptive agents using coarse-grained information to compete for limited resources. (arXiv:1609.08746v1 [physics.soc-ph])

September 28, 2016 by Quantitative Finance at arXiv   Comments (0)

The recent trend for acquiring big data assumes that possessing
quantitatively more and qualitatively finer data necessarily provides an
advantage that may be critical in competitive situations. Using a model complex
adaptive system where agents compete for a limited resource using information
coarse-grained to different levels, we show that agents having access to more
and better data can perform worse than others in certain situations. The
relation between information asymmetry and individual...

A stylized model for wealth distribution. (arXiv:1609.08978v1 [math.PR])

September 28, 2016 by Quantitative Finance at arXiv   Comments (0)

The recent book by T. Piketty (Capital in the Twenty-First Century) promoted
the important issue of wealth inequality. In the last twenty years, physicists
and mathematicians developed models to derive the wealth distribution using
discrete and continuous stochastic processes (random exchange models) as well
as related Boltzmann-type kinetic equations. In this literature, the usual
concept of equilibrium in Economics is either replaced or completed by
statistical equilibrium.

In order to...

28Sep/FAQs on "Supervisory framework for measuring and controlling large exposures" published by the Basel Committee

September 28, 2016 by The Bank for International Settlements   Comments (0)

Press release about the Basel Committee publishing FAQs on "Supervisory framework for measuring and controlling large exposures", 28 September 2016

Clustering Approaches for Financial Data Analysis: a Survey. (arXiv:1609.08520v1 [q-fin.GN])

September 27, 2016 by Quantitative Finance at arXiv   Comments (0)

Nowadays, financial data analysis is becoming increasingly important in the
business market. As companies collect more and more data from daily operations,
they expect to extract useful knowledge from existing collected data to help
make reasonable decisions for new customer requests, e.g. user credit category,
confidence of expected return, etc. Banking and financial institutes have
applied different data mining techniques to enhance their business performance.
Among these techniques,...

27Sep/Financial inclusion: guidance on the regulation and supervision of institutions published by the Basel Committee

September 27, 2016 by The Bank for International Settlements   Comments (0)

The Guidance published today identifies 19 of the total 29 Basel Core Principles where additional guidance is needed in the application of the Core Principles to the supervision of financial institutions engaged in serving the financially unserved and underserved. The Guidance also specifies the "Essential Criteria" and ...

QuantLib and SWIG

September 27, 2016 by Implementing QuantLib   Comments (0)

Hello everybody. This post has been on my to-do list for a while. It’s going to describe the tricks we use in our SWIG interfaces to export QuantLib to a handful of languages (for example, you might know that I’m fond of using it from Python).