You are a risk manager ?
ALGOSAVE SCENARIO SIMULATION PLATFORM is a tool that lets you easily check how your credit portfolio default probability withstand stress-tests and “in-house” simulations. It also allows you to measure single borrower forward looking Loss Given Default as well as its correlation with its industry, its rating bucket and its competitors. Use ALGOSAVE SCENARIO SIMULATION PLATFORM to increase the POWER and REACH of your simulations.
Along the line of best-in-class financial institution, you, as a risk manager need to simulate 5 scenarios on the bank’s credit portfolio.
Scenario 1 : Average
Scenario 2 : Good
Scenario 3 : Very Good
Scenario 4: Bad
Scenario 5 : Stress-Tested
Proposed portfolio : a basket of 9 retaillers
WALMART INC. ;
CASINO GUICHARD-PERRACHON;
THE KROGER CO.,
RALLYE SA,
SUPERVALU,
KONINKLIJKE AHOLD DELHAIZE N.V.,
COSTCO WHOLESALE CORPORATION;
TESCO PLC
CARREFOUR SA
All the deliverables displayed here are available in Algosave Database.
1 – How does each of those 5 scenarios affect each borrower Asset Value distribution – EV – at the 99,9 confidence interval ?
For clarity purpose, we will only show each borrower EV distribution in the extreme (Very good and Stress-Tested) and central cases.
EV is distribution critical to debt pricing : indeed debt holders are sellers of a put option on the EV of the borrower to equity holders.
a few observations :
a – Traditional credit models assume a log-normal distribution of borrower’s asset value (Enterprise Value)
In the present portfolio, this assumption ONLY holds true for the most solid borrower : Walmart (at the top of those graphs)
But, ALL the other EV distributions – without any exception – are at-least bi-modal, thereby illustrating and materializing the “gone concern” status of the firm priced into the market side by side with the “going concern” state of nature. Ignoring the heavily-skewed distribution characteristic of those EV puts the bank at risk.
b – as expected, the EV distribution of the riskier borrowers show a a heavier left-hand tail
c – One of the reason why Algosave FinTech is able to work with such a diversity of scenarios, is linked to the fact that current credit model are either calibrated on Equity Capitalization (Structural & Option-type models) or on Bond/CDS (reduced form models). Algosave FinTech takes it all : it is both calibrated on Equity as well as on bond spread data (when available).
This double “allegiance” , is instrumental into Algosave including both the optimistic view on corporate valuation as well as the more pessimistic one. Let’s not forget that debt holders are sellers of a put option to equity holders. Hence, where the latter enjoy unlimited upside, the former only have downside.
Also, and departing from “thru the cycle” ratings, this market live foot-print gives Algosave simulation platform a refreshing “live” and Point in Time flavor.
2 – How does each of those 5 scenarios affect each borrower multiyear default cumulative probability term structure – the PD curve- ?
For clarity purpose, we will only show each borrower PD curve in the extreme (Very good and Stress-Tested) and central cases.
Interestingly, the gap between ALGOSAVE central and ALGOSAVE stressed-tested scenario is indeed, sustantial : for instance Carrefour 5-year cumulative PD spikes out from its current 5% to 16%. It only compresses to 3% in ALGOSAVE very good macro-economic scenario.
3 – How does each scenario affect the term structure of each borrower scenario and seniority specific Loss Given Default – the LGD curve- ?
For clarity purpose, we will only show each borrower PD curve in the extreme (Very good and Stress-Tested) and central cases.
For ease of reading, we wil only show a few of those simulations
For each borrower, Algosave delivers 3 LGDs : Secured, Unsecured and Subordinated.
A bit of explanation on those deliverables which come directly out of Algosave Simulation Platform.
– x-axis = Years from 1 to 10
– y-axis = Loss Given Default in percentage of initial credit exposure
– The color of the bars correspond to 3 scenarios : Very Good Scenario (in green), Central Scenario (in blue), and Stressed Scenario (in red).
– Top Graph = Secured Loss Given Defaut term structure, Middle graph : unsecured LGD term structure, Bottom Graph : subordinated LGD term structure
a – WALMART LGDs :
b- CASINO LGDs : Very Good Scenario (in green), Central Scenario (in blue), and Stressed Scenario (in red)
c – KROGER LGDs : Very Good Scenario (in green), Central Scenario (in blue), and Stressed Scenario (in red)
d – RALLYE LGDs : Very Good Scenario (in green), Central Scenario (in blue), and Stressed Scenario (in red)
Reassuringly, in all those cases, the secured average LGD – from 1 to 10 years – firmly stands at 15%, which is the minimum LGD chosen by Algosave.
Interestingly, only WALMART offers a non-100% LGD in the very good scenario.
Algosave also offers 1-to-10 year senario and seniority sensitive LGD distribution for every borrower
ALGOSAVE 