A Simulation Comparison of Aggregation Periods for Estimating Correlations within Operational Loss Data

18 Pages Posted: 2 Jul 2016

See all articles by Kevin Panman

Kevin Panman

North-West University

L Haasbroek

North-West University

W Pieters

Standard Bank Group Ltd.

Date Written: June 27, 2016

Abstract

We investigate the differences in the values of correlations based on different aggregation periods of time series loss data. The aggregation periods considered for this study were annual, quarterly and monthly, ie, the losses were binned in one year, one quarter and one month buckets, respectively. We conducted a simulation study in order to cover a wide spectrum of frequencies (sample sizes), severity distributions and dependencies between the severities, choosing the parameters of the simulation study to obtain severity and frequency distributions popular in operational risk loss modeling. Our main conclusion is that the difference in values of the correlation coefficients calculated from aggregate loss severities only becomes material when the inherent correlation in the loss-generating process exceeds approximately 0.5. From a risk management perspective, where annual aggregation is desired due to loss horizons typically being annual, this result implies that aggregation periods shorter than annual can be used, which will increase the number of observations to improve the stability of correlation estimates, and the diversification benefit due to estimating correlation values using a shorter aggregation period will not result in a material misstatement of the diversification benefit, since the differences in the values of the correlations are minimal.

Keywords: correlation estimation, loss aggregation period, time series data, operational risk, capital calculation

Suggested Citation

Panman, Kevin and Haasbroek, L and Pieters, W, A Simulation Comparison of Aggregation Periods for Estimating Correlations within Operational Loss Data (June 27, 2016). Journal of Operational Risk, Vol. 11, No. 2, 2016, Available at SSRN: https://ssrn.com/abstract=2802654

Kevin Panman (Contact Author)

North-West University ( email )

Private Bag X6001
Faculty of Economic and Management Sciences
Potchefstroom, Northwest 2520
South Africa

L Haasbroek

North-West University ( email )

Private Bag X6001
Faculty of Economic and Management Sciences
Potchefstroom, Northwest 2520
South Africa

W Pieters

Standard Bank Group Ltd. ( email )

30 Baker Street
Rosebank, Gauteng 2196
South Africa

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