December 3, 2016

August 1, 2016

In partnership with CWP Energy, we explore different machine learning algorithms in order to first identify reliable signals and factors that in turn can be incorporated into a forecasting model for day-ahead electricity prices in Canadian markets.

May 1, 2016

In this paper we introduce a new coherent cumulative risk measure on a subclass in

the space of càdlàg processes. This new coherent risk measure turns out to be tractable enough within a class of models where the aggregate claims is driven by a spectrally positive Lévy...

December 1, 2015

The Markov-switching GARCH model allows for a GARCH structure with time-varying parameters. This flexibility is unfortunately undermined by a path dependence problem which complicates the parameter estimation process. This problem led to the development of computationa...

November 30, 2015

In partnership with National Bank of Canada, we look at "zero-intelligence" simulator models in order to reproduce high-frequency signatures and limit-order-book features of assets of interest. This project involves event-driven simulation model developing as well as t...

September 5, 2015

The field of risk theory has traditionally focused on ruin-related quantities. In particular, the so-called expected discounted penalty function (Gerber and Shiu. N Am Actuar J, 2(1):48–78, 1998) has been the object of a thorough study over the years. Although interest...

August 1, 2015

In [12], the concept of natural risk statistics is introduced as a data-based risk measure, i.e. as

an axiomatic risk measure defined in the space Rn. In this note, we set to generalize this notion to

bivariate data sets (more generally, multivariate data sets) by defi...

April 7, 2015

In partnership with a private broker, we explored various machine learning methods in order to produce a trend-detecting algorithm that would ultimate optimize trading orders. An algorithmic trading algorithm was implemented.

July 1, 2014

In partnership with CIBC Asset Management, we explored the applications of Self-organizing maps in detecting macro-economical regime changes in financial data series.