Running Fed Stress Scenarios in RiskSmart

Trouble at the Fed: Running Stress Scenarios in RiskSmart

In previous posts, we explored the possibility that US President Donald Trump might fire Federal Reserve Chair Jerome Powell and assessed the potential impact of the leading candidates to replace him.

But how do we accurately capture the risks associated with each scenario across all asset classes?

To apply these shocks, we’ve used a model portfolio with diversified exposure across multiple asset classes and exposures. This covers credit, global equity, commodities, rates and cash and FX. The breakdown can be seen as follows:

The shocks defined above can be entered into TS Imagine’s flexible input source tables before the stresses are applied. In terms of the types of shocks that can be performed these are as follows:

Methodology

Global Shift – this applies a singular value shift to the associated risk factor provided in the benchmark. For example, shocking the USD FX risk factor by 20%
Predictive – this shock takes the input benchmark and calculates the beta against each risk factor associated with the risk type in your portfolio and multiplies this through by the change amount. For example, if you held Apple Stock and it had a beta of 1.1 against your benchmark of the S&P500 which you are shocking by -15% then Apple would be shifted to -16.5%

Risk Type

fx – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to FX.
eq – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Equity Underlyings.
ir_spot – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Interest Rate Underlyings.
commo – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Commodity Underlyings.
fx_vol – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to FX Volatility.
eq_vol – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Equity Volatility.
ir_vol – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Interest Rate Volatility.
commo_vol – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Commodity Volatility.
csm – this applies the shocks to all risk factors within the instruments held in your portfolio that are associated to Credit Spread Matrices.

Change Type

rel – this applies a relative shock to the change amount entered. For example a rel of 20 would be a 20% shift
abs – this applies an absolute shock to the change amount entered. For example a abs of 100 to the 1M tenor on an ir_spot shock would increase the yield curve by 100bps for that section of the yield curve

Benchmark – the benchmark will either be the underlying component you are shocking or the underlying component the system will calculate a beta against for its relevant shock (depending on your selection for a global or predictive methodology)
Change Amounts – For all Risk Types other than Interest Rate and Commodity underlying shocks these can be entered within one field. For Interest Rate and Commodity there is the added option to add shocks along the yield curve or roll curve depending on if the front or back end of the curve needs to be adjusted slightly for the shifts.

The shocks defined in the scenarios above we have translated below:

Outputs and Data Visualisations in TS Imagine

TS Imagine’s Stress Testing engine is very powerful, and it is possible to get a variety of metrics out of the system. Whether it be the value of your Delta Exposure before and after the stress, the change in your Dv01 exposure, or any other risk or input metric you wish to display (for example, underlying model prices before and after). However, for the purpose of simplicity, we have just taken the difference in the fair value before and after these shocks and displayed these as a P&L output. We have then taken these P&L effects and displayed these as a % of the starting total value as well:

For our chosen model portfolio, the stress test results suggest that the most favorable overall market outcome would come from appointing Kevin Hassett, who delivers the highest total gain, driven by strong equity, credit, and rate market reactions — though this optimism may underweight inflation risks.

Scott Bessent emerges as the most balanced and credible candidate, offering solid equity support with minimal disruption to rates or credit.

Christopher Waller is viewed as an equity-friendly continuity pick with a dovish tilt, while Kevin Warsh presents a mixed picture — equity-positive but potentially unsettling for bond markets.

The worst-case scenario by far is firing Powell outright, which results in a large net loss to our portfolio, driven by severe stress in rates and credit, reflecting deep concerns over Fed independence and policy credibility.

Visualising stresses can also be performed using TS Imagine’s powerful and flexible Dashboards. Below are some examples of how this data could be visualised: