The Impulsive Approach to procyclicality; measuring the reactiveness of risk-based initial margin models to changes in market conditions using impulse response functions

In recent years, many derivatives market participants received large margin calls in episodes of elevated market volatility such as the onset of the Covid-19 global pandemic and the illegal Russian invasion of Ukraine. The lack of some market participants’ preparedness to meet these calls resulted in liquidity stress and reinvigorated the policy debate about how reactive margin should be to changes in market conditions. This debate has been hampered by the lack of a generally accepted way of measuring the reactiveness of the models used to calculate initial margin. The first contribution of this paper is to provide such a measure. We consider a step function in volatility, and examine the responses of various initial margin models to paths of risk factor returns consistent with this impulse, introducing the impulse response function as a convenient means of presenting this reaction. The results presented demonstrate that a model's impulse response is a robust and useful measure of its reactiveness. This approach could be used both to measure initial margin model reactiveness, or procyclicality as it is often termed, and to capture the uncertainty in this measurement. It also provides significant, novel insights into the behaviour of some economically important margin models. In particular, the tendency of some filtered historical simulation value at risk models to over-react to sharp stepwise increases in volatility is demonstrated and the reasons for it are explored. The behaviour of two widely-used anti-procyclicality tools, the buffer and the use of a stressed period, are also analysed: the latter is found to be more successful at mitigating procyclicality than the former. The paper concludes with a discussion of the policy implications of the results presented.

Authors

Institutions

Publication Details

Journal
Borsa Istanbul Review
Published
2025-07-05
DOI
https://doi.org/10.1016/j.bir.2025.06.006
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Impulsive Approach to procyclicality; measuring the reactiveness of risk-based initial margin models to changes in market conditions using impulse response functions

David Murphy, Pedro Gurrola-Pérez
Borsa Istanbul Review
Complex Systems and Time Series Analysis
article

The Impulsive Approach to procyclicality; measuring the reactiveness of risk-based initial margin models to changes in market conditions using impulse response functions

David Murphy, Pedro Gurrola-Pérez
article en

Abstract

In recent years, many derivatives market participants received large margin calls in episodes of elevated market volatility such as the onset of the Covid-19 global pandemic and the illegal Russian invasion of Ukraine. The lack of some market participants’ preparedness to meet these calls resulted in liquidity stress and reinvigorated the policy debate about how reactive margin should be to changes in market conditions. This debate has been hampered by the lack of a generally accepted way of measuring the reactiveness of the models used to calculate initial margin. The first contribution of this paper is to provide such a measure. We consider a step function in volatility, and examine the responses of various initial margin models to paths of risk factor returns consistent with this impulse, introducing the impulse response function as a convenient means of presenting this reaction. The results presented demonstrate that a model's impulse response is a robust and useful measure of its reactiveness. This approach could be used both to measure initial margin model reactiveness, or procyclicality as it is often termed, and to capture the uncertainty in this measurement. It also provides significant, novel insights into the behaviour of some economically important margin models. In particular, the tendency of some filtered historical simulation value at risk models to over-react to sharp stepwise increases in volatility is demonstrated and the reasons for it are explored. The behaviour of two widely-used anti-procyclicality tools, the buffer and the use of a stressed period, are also analysed: the latter is found to be more successful at mitigating procyclicality than the former. The paper concludes with a discussion of the policy implications of the results presented.

Borsa Istanbul ReviewVol. 25(6)
Ion Exchange (India) (IN), London School of Economics and Political Science (GB)
Openalex Percentile: Top 77%
Complex Systems and Time Series Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.