25 October 2022

How asset managers used margin forecasting and stress testing to manage collateral and liquidity risk during the mini-crisis in the UK Bond Markets.


What are the lessons asset managers can learn from the recent market events?

Earlier this month, fresh of the back of the mini-budget announcement, made by the now ex Chancellor of the UK,  we explored the reasons behind the mini crisis in the UK debt markets. There has been a lot of coverage since then in the financial press covering the impacts felt across the sector. The situation is still very fluid and evolving daily. (We have indeed had 2 Prime Ministers since the start of drafting this article!)

If we were to pinpoint one outcome over the last few weeks, it’s that Portfolio Managers now have a heightened sense of awareness of the potential liquidity risks their portfolios are subject to.

However, not all market participants were caught out by the market volatility.

Here we explore some techniques used by such firms, which should in fact be used by all firms looking to protect their liquidity risk over time.

The need for Stress Testing and Forecasting Margin

Market performance across all major benchmarks, not just UK government bonds has been extremely volatile; where equity markets are at year-to-date lows, inflation at record highs and rates continually rising.

The Bank of England published its annual stress test scenarios recently – Key elements of the 2022 annual cyclical scenario stress test published | Bank of England– ; which highlight some very alarming and real scenarios such as Inflation peaking at 17%, UK Bank rate rising to 6% and US interest rates at 6.5%.

Calibrating for such scenarios is something that not only the participating UK banks should stress their books for; but in this current environment all market participants from Asset Managers, Hedge Funds, Family Offices; Sovereign and Pension Funds, should use to forecast their cash and collateral obligations.

Forward looking money managers actively stress their initial margin (IM) and variation margin (VM) requirements across all relationships using tools that they can calibrate to either standard market scenarios or bespoke scenarios their funds may have specific risk to.

Stress Testing and Forecasting Examples

Taking the example of how the GBP FX rate against the dollar moved drastically between July and September, with the pound devaluing over 10% against the dollar. Below, we constructed a trade package including a Long Straddle with a strike at 90% of the spot and a Synthetic Forward at the Forward Rate on GBP/USD, with a 3-month expiry executed at the end of July. Each leg of the package is assuming a 100 million GBP at the time of execution.

Evaluating the package under ISDA SIMM™ methodology at the time of execution when the FX rate was 1.2043 and at the end of September  – where it dropped to 1.068 – shows a surprisingly large jump in the Uncleared Margin Rules (UMR) margin.

Article Series: How asset managers used margin forecasting and stress testing to manage collateral and liquidity risk during the mini-crisis in the UK Bond Markets.

Another example of using such techniques is looking at an example of a cross asset portfolio of cleared interest rate and inflation swaps with long dated duration. Here we run the portfolio under current market conditions and recalibrate it under March 2020 conditions to project IM impact.

The results can be alarming, with Day 1 IM jumping up by 37% under the stress period scenario.

Changes to VM are even more important when evaluating the impact of a stressed market on a portfolio.If we add a VM forecast scenario that looks at the expected VM over a 10-day time horizon, the amount of margin required to be posted across IM and VM is 70% higher than the current IM and  VM.

Stress testing collateral pools in addition to margin

Stress testing and Forecasting of margin is clearly an important tool for firms to use to manage their future liabilities. Knowing how much liquid collateral to hold to cover unlikely, but possible, market scenarios is the first step.

However, estimating IM and VM based on current portfolio and market factor stresses is not sufficient to have complete collateral coverage for liquidity.

Overlaying an additional stress test on collateral assets is a key component when evaluating a firms liquidity position. This was evident in the UK Bond market following the mini-budget events a few weeks ago, where government bond assets which are traditionally used as collateral suddenly dropped in value having a dual impact on firms.

Sophisticated firms are able to model the impact of a market move on their collateral assets, implying a potentially decreasing value of collateral in a stressed market. Modelling the wrong way risk of increasing margin requirements in conjunction with decreasing collateral values in a stressed scenario gives portfolio managers the visibility they need on the risks contained within seemingly conservative portfolios.

Further stressing on the market impact on eligibility terms, collateral haircuts and limits can help complete the liquidity picture.


Not all firms will have readily available liquid buffers to meet collateral obligations during periods of stressed markets. This is true for traditional asset managers and pension funds, as was seen recently in the UK, as well as highly levered hedge funds who look to deploy all assets at their disposal for revenue generation.

Whether trading bilaterally, cleared OTC, Futures & Options or under Prime Brokerage agreements, tools to project and forecast overall liquidity under stressed conditions are essential. Only then can portfolio managers ensure they are not caught out in a collateral or liquidity squeeze, having to liquidate holdings or raise liquidity in unfavorable market conditions.

Using stress testing and forecasting provides the basis for planning overnight and term liquidity. This stressing and forecasting framework must include a holistic view across the portfolio of trading positions as well as the collateral assets held and the agreement terms they are able to be deployed under.

Only when these tools are used by liquidity managers can the ultimate goal of collateral resilience be achieved.

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