Remember Algosave last LinkedIn Article : “Eurovision LGD Contest” ?
We then examined Point-in-Time (PiT) and forward looking LGDs of a sample portfolio of 7 Western oil majors : BP Plc., Exxon Mobil, Royal Dutch Shell, Total SA, Husky Energy, Chevron and ENI Spa.
Algosave unique modelling technology, – surprisingly – revealed that Husky Energy – the lowest credit rating – offered the lowest LGDs. On the other hand, BP plc. was also – and surprisingly – “disappointing”, with the highest and the most scenario-sensitive senior unsecured LGD.
This Algosave exclusive BP dashboard summarizes those findings (right click “Open image in new tab” for a better view) :
By the way, the same Algosave dashboard is available on demand for each of those corporates. Do not hesitate to ask.
Let’s go one step further into portfolio management and look into some core issues of credit dependencies : Domino Effect <=> from single borrower management (single PD) to portfolio management (conditional PD)
Let’s define a “Domino Effect” as being the sensitivity of a given borrower PD to the default of another borrower.
The same data granularity and “real-life” rich universe of possibilities which help ALGOSAVE deliver unique insights into Loss Given Default, are also instrumental in Algosave FinTech delivering powerful insights into issues of credit dependencies for portfolio and risk managers alike.
First, and to make things crispier, let’s enlarge the portfolio to also include Statoil, Repsol and Suncor Energy and ask how severe is the domino effect – a.k.a Conditional Default Probability – in this sample portfolio of 10 oil majors ?
Portfolio = BP Plc., Exxon Mobil, Royal Dutch Shell, Total SA, Husky Energy, Chevron, ENI Spa, Statoil, Repsol and Suncor Energy.
Here is Algosave full insight into issues of credit dependencies produced from its database, with Algosave unique conditional default probabilities and toxicity score (right click “Open image in new tab” for a better view).
Let’s read thru those Algosave insights into portfolio domino effect with a few examples :
For instance, let’s start simple. If Total was to default, how would Statoil 5-year cumulative PD be affected ?
- Algosave answer : it will jumps from its current 1.3% to 2.3% if FP (Total SA) defaulted.
For instance, knowing that Total SA current 5-year cumulative PD is 2.2%, will this PD jump – on average – to 4%, 6% or 8% if one the other 9 corporates defaults over the next 5 years ?
- ALGOSAVE answer : on average, Total SA 5-year PD will jump from 2.2% to 5.6% if one of the other 9 oil majors defaults on its debt. And, this average hides a broad range of possibilities, whereby some corporate defaults are more friendly while some are far more “toxic” to Total SA.
If so, which of the other 9 corporates is the “friendliest” and which is the most “toxic” for Total ? and does it have to do with credit rating ?
- ALGOSAVE answer : the friendliest is ENI. Indeed, if ENI was to default, Total SA 5-year PD will hardly move from its current 2.2% to 2.3%.
- ALGOSAVE answer : the most toxic is Chevron. Indeed, If Chevron was to default, Total SA 5-year PD will jump from its current 2.2% to 9% (more than 4 times !)
- And yes, this is somehow related to Credit Rating, but in a “reversed” way. Indeed, since Chevron enjoys one of the highest credit rating of the portfolio, it is logical that if it were to default, it would very likely do so on the grounds of systemic/industry risk. Hence a higher degree of toxicity. Inversely, if ENI – one of the lowest rating of the sample – was to default, it would probably have to do more with idiosyncratic risk. Hence a lower level of toxicity.
Which of those 10 oil majors are the 2 least and the 2 most exposed to domino effect (significant jump in their respective PD upon default of others) over the next 5 Years ?
- ALGOSAVE answer : the two least exposed to domino effect are ENI and Statoil. On average, and upon default of one of the other 9 corporates, ENI 5-year cumulative PD will move up 1.5 times, while Statoil PD will move up 1.6 times.
- ALGOSAVE answer : the two most exposed to domino effect are Exxon Mobil and Chevron. On average, and upon default of one of the other 9 corporates, Exxon 5-year cumulative PD will move up 2.4 times, and Chevron will shoot up 2.9 times !
Finally, and assuming I want to increase my exposure to this sample portfolio with a 5-year unsecured Revolver Credit Facility – which is the best and which is the worst candidate from a portfolio management perspective ?
- In order to answer this question, Algosave assigns to each borrower a toxicity score which corresponds to the borrower level of toxicity for each of its peer.Score = 1, being the least toxic (i.e. causing the least increase in PD) andScore = 9 being the most toxic (i.e. causing the greatest increase in PD)
- ALGOSAVE answer : the best candidate for an increased exposure is ENI with an average toxicity score of 1.9. The second best is Statoil with an average toxicity score of 3.
- ALGOSAVE answer : the worst candidate is Chevron with an average toxicity score of 8.3 ! The second worse being Exxon with a average toxicity score of 7.
Now, your turn to put Algosave FinTech to the test with your own challenging questions.
- Example of challenge for Algosave : when this domino effect happens, what is the probability of being in a low, average or high LGD regime ?
- Another challenge for Algosave : from a domino effect point-of-view, which is the most and which is the least “toxic” industry for this oil basket ?
All the Best
Algosave Team, 30-May-2018