Remember me

Register  |   Lost password?


Introduction to QuantLib Development - Intensive 3-day Training Course - September 10-12th, 2018 - Download Registration Form Here

 

All site blogs

Evaluating the Building Blocks of a Dynamically Adaptive Systematic Trading Strategy. (arXiv:1812.02527v1 [q-fin.ST])

December 6, 2018 by Quantitative Finance at arXiv   Comments (0)

Financial markets change their behaviours abruptly. The mean, variance and
correlation patterns of stocks can vary dramatically, triggered by fundamental
changes in macroeconomic variables, policies or regulations. A trader needs to
adapt her trading style to make the best out of the different phases in the
stock markets. Similarly, an investor might want to invest in different asset
classes in different market regimes for a stable risk adjusted return profile.
Here, we explore the use of State...

Simulation of Stylized Facts in Agent-Based Computational Economic Market Models. (arXiv:1812.02726v1 [econ.GN])

December 6, 2018 by Quantitative Finance at arXiv   Comments (0)

We study the qualitative and quantitative appearance of stylized facts in
several agent-based computational economic market (ABCEM) models. We perform
our simulations with the SABCEMM (Simulator for Agent-Based Computational
Economic Market Models) tool recently introduced by the authors (Trimborn et
al. 2018a). The SABCEMM simulator is implemented in C++ and is well suited for
large scale computations. Thanks to its object-oriented software design, the
SABCEMM tool enables the creation of new...

Assessing progress in automation technologies

December 6, 2018 by The Practical Quant   Comments (0)

[A version of this post appears on the O'Reilly Radar.]When it comes to automation of existing tasks and workflows, you need not adopt an “all or nothing” attitude.In this post, I share slides and notes from a keynote Roger Chen and I gave at the Artificial Intelligence conference in London in October 2018. We presented an overview of the state of automation technologies: we tried to highlight the state of the key building block technologies and we described how these tools might evolve in the...

Tools for generating deep neural networks with efficient network architectures

December 6, 2018 by The Practical Quant   Comments (0)

[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning.In this episode of the Data Show, I spoke with Alex Wong, associate professor at the University of Waterloo, and co-founder of DarwinAI, a startup that uses AI to address foundational challenges with deep learning in the enterprise. As the use of machine learning and analytics become more widespread, we’re beginning...

On dynamics of wage-price spiral and stagflation in some model economic systems. (arXiv:1812.01707v1 [q-fin.GN])

December 5, 2018 by Quantitative Finance at arXiv   Comments (0)

This article aims to present an elementary analytical solution to the
question of the formation of a structure of differentiation of rates of return
in a classical gravitation model and in a model of the dynamics of price-wage
spirals.

The Alpha-Heston Stochastic Volatility Model. (arXiv:1812.01914v1 [q-fin.MF])

December 5, 2018 by Quantitative Finance at arXiv   Comments (0)

We introduce an affine extension of the Heston model where the instantaneous
variance process contains a jump part driven by $\alpha$-stable processes with
$\alpha\in(1,2]$. In this framework, we examine the implied volatility and its
asymptotic behaviors for both asset and variance options. Furthermore, we
examine the jump clustering phenomenon observed on the variance market and
provide a jump cluster decomposition which allows to analyse the cluster
processes.

AI for the Common Good?! Pitfalls, challenges, and Ethics Pen-Testing

December 4, 2018 by Complexity Digest   Comments (0)

Recently, many AI researchers and practitioners have embarked on research visions that involve doing AI for "Good". This is part of a general drive towards infusing AI research and practice with ethical thinking. One frequent theme in current ethical guidelines is the requirement that AI be good for all, or: contribute to the Common Good. But what is the Common Good, and is it enough to want to be good? Via four lead questions, I will illustrate challenges and pitfalls when...