Systematic and multifactor risk models revisited

12/18/2013
by   Michel Fliess, et al.
0

Systematic and multifactor risk models are revisited via methods which were already successfully developed in signal processing and in automatic control. The results, which bypass the usual criticisms on those risk modeling, are illustrated by several successful computer experiments.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/09/2023

Convex Quaternion Optimization for Signal Processing: Theory and Applications

Convex optimization methods have been extensively used in the fields of ...
research
08/30/2021

Reactive and Risk-Aware Control for Signal Temporal Logic

The deployment of autonomous systems in uncertain and dynamic environmen...
research
03/31/2019

Risk Averse Robust Adversarial Reinforcement Learning

Deep reinforcement learning has recently made significant progress in so...
research
11/25/2020

Optimal risk in wealth exchange models: agent dynamics from a microscopic perspective

In this work we study the individual strategies carried out by agents un...
research
08/14/2018

A note on representation of BSDE-based dynamic risk measures and dynamic capital allocations

In this paper, we provide a representation theorem for dynamic capital a...
research
04/05/2021

Managing Research the Wiki Way: A Systematic Approach to Documenting Research

As a master's student, knowing how to manage your personal research is n...
research
08/13/2011

Ensemble Risk Modeling Method for Robust Learning on Scarce Data

In medical risk modeling, typical data are "scarce": they have relativel...

Please sign up or login with your details

Forgot password? Click here to reset