Fitting financial time series returns distributions: a mixture normality approach

Riccardo Bramante; Diego Zappa

Fitting financial time series returns distributions: a mixture normality approach

Riccardo Bramante
, Diego Zappa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Value at Risk has emerged as a useful tool to risk management. A relevant driving force has been the diffusion of JP Morgan RiskMetricsTM methodology and the subsequent BIS adoption for all trading portfolios of financial institutions. To improve the accuracy of VaR estimates in this paper we propose the use of mixture of truncated normal distributions in modelling returns. An optimization algorithm has been developed to obtain the best fit by using the minimum distance approach. Results show evidence to fit return distributions at a satisfactory level, completely maintaining local normality properties in the model

Original language	English
Title of host publication	Fifth International Conference MAF 2012
Pages	1-9
Number of pages	9
Publication status	Published - 2012
Event	MAF 2012 - Venezia Duration: 10 Apr 2012 → 12 Apr 2012

Conference

Conference	MAF 2012
City	Venezia
Period	10/4/12 → 12/4/12

Keywords

Minimum Distance
Mixture of truncated distributions
Value at Risk

Cite this

@inproceedings{ee9c634c415944dfa6e27eaf848cd12f,

title = "Fitting financial time series returns distributions: a mixture normality approach",

abstract = "Value at Risk has emerged as a useful tool to risk management. A relevant driving force has been the diffusion of JP Morgan RiskMetricsTM methodology and the subsequent BIS adoption for all trading portfolios of financial institutions. To improve the accuracy of VaR estimates in this paper we propose the use of mixture of truncated normal distributions in modelling returns. An optimization algorithm has been developed to obtain the best fit by using the minimum distance approach. Results show evidence to fit return distributions at a satisfactory level, completely maintaining local normality properties in the model",

keywords = "Minimum Distance, Mixture of truncated distributions, Value at Risk, Minimum Distance, Mixture of truncated distributions, Value at Risk",

author = "Riccardo Bramante and Diego Zappa",

year = "2012",

language = "English",

pages = "1--9",

booktitle = "Fifth International Conference MAF 2012",

note = "MAF 2012 ; Conference date: 10-04-2012 Through 12-04-2012",

}

TY - GEN

T1 - Fitting financial time series returns distributions: a mixture normality approach

AU - Bramante, Riccardo

AU - Zappa, Diego

PY - 2012

Y1 - 2012

N2 - Value at Risk has emerged as a useful tool to risk management. A relevant driving force has been the diffusion of JP Morgan RiskMetricsTM methodology and the subsequent BIS adoption for all trading portfolios of financial institutions. To improve the accuracy of VaR estimates in this paper we propose the use of mixture of truncated normal distributions in modelling returns. An optimization algorithm has been developed to obtain the best fit by using the minimum distance approach. Results show evidence to fit return distributions at a satisfactory level, completely maintaining local normality properties in the model

AB - Value at Risk has emerged as a useful tool to risk management. A relevant driving force has been the diffusion of JP Morgan RiskMetricsTM methodology and the subsequent BIS adoption for all trading portfolios of financial institutions. To improve the accuracy of VaR estimates in this paper we propose the use of mixture of truncated normal distributions in modelling returns. An optimization algorithm has been developed to obtain the best fit by using the minimum distance approach. Results show evidence to fit return distributions at a satisfactory level, completely maintaining local normality properties in the model

KW - Minimum Distance

KW - Mixture of truncated distributions

KW - Value at Risk

KW - Minimum Distance

KW - Mixture of truncated distributions

KW - Value at Risk

UR - http://hdl.handle.net/10807/29393

M3 - Conference contribution

SP - 1

EP - 9

BT - Fifth International Conference MAF 2012

T2 - MAF 2012

Y2 - 10 April 2012 through 12 April 2012

ER -

Fitting financial time series returns distributions: a mixture normality approach

Abstract

Conference

Keywords

Other files and links

Fingerprint

Cite this