Exposure Curves

Discussion in 'SP8' started by redzer, Apr 17, 2017.

  1. redzer

    redzer Member

    Hi,

    I've a quick question on exposure curves. I don't get why the diagonal line of on an exposure curve graph defines total losses and that you can't have a line below the diagonal.

    Thanks,
    R
     
  2. Simon Partne

    Simon Partne Member

    I think (although a tutor might correct me!) that the answer lies in the definitions. The variable Y represents losses as a proportion of the total exposure or EML.

    I think another way of thinking about it, would be that if the curve ran underneath, one would be claiming, for example that you expected to lose 101USD from a 100USD limit... which wouldn't be rational.
     
  3. redzer

    redzer Member

    Thanks for the reply but i still don't get it.

    A straight line means that Y has the same value as G(Y).

    Total SI = 1000
    Risk premium = 100

    what is the risk premium for limit of 500?

    So if Y=0.5 (500/1000) that is losses are 50% of the total exposure and G(0.5)=0.5 this means to get our risk premium is 50.

    What does this tell me about total losses?

    Thanks,
    R
     
    Last edited by a moderator: Apr 18, 2017
  4. Katherine Young

    Katherine Young ActEd Tutor Staff Member

    It doesn't tell you anything about total losses. The joy of loss curves is that IF you can reasonably estimate the total loss cost, you can use this to estimate losses for a layer.

    It doesn't. (A diagonal exposure curve would mean that if you increase the limit by a certain proportion, the expected loss cost would also increase by the same proportion. But it is extremely unlikely that this would happen across the board, I mean at all points of the loss distribution.)

    Let's say you have 3 losses, loss A = 3000, loss B = 2000 and loss C = 1000. The average of these (ie the expected loss) is 2000.
    Now let's say you impose a limit of 2000. Loss A is now reduced to 2000 (because the insurer won't pay more than the limit). Loss B and loss C are still 2000 and 1000 respectively. So the average of these (ie the limited expected value, the LEV) is 1,667.
    Now let's say you reduce the limit still further, to 1000. The insurer will only pay the first 1000 of each claim. So the limited expected value is now 1000.

    In summary then, we have:
    • limit 1000: LEV = 1000
    • limit 2000: LEV = 1667
    • no limit: EV = 2000
    So you can see the LEV is an increasing function (or more specifically, a non-decreasing function) of the limit, and it is increasing at a decreasing rate. This means the exposure curve can't lie below the diagonal ... if it did, these two conditions wouldn't hold for all points on the curve.

    Well, since the loss curve is a function of the LEV, it must also have the same shape.
     
    Last edited: Apr 18, 2017
  5. redzer

    redzer Member

    Hi Katherine,

    Thank you very much for your answer. It really helps.

    My confusion was caused by Q5 Part 5 (v) Sept 2010

    • Exposure curves should be concave or the straight line y = G(y).
    • The straight line occurs where the only type of loss is a total loss.
    • As we start to allow partial losses the curve will move above the diagonal.
    • Hence it is impossible to get a proper curve below the diagonal.
    • Therefore, C cannot be a suitable curve to use
    Do you have an insight into the 2nd point.

    Thanks,
    R
     
    Last edited by a moderator: Apr 18, 2017
  6. Katherine Young

    Katherine Young ActEd Tutor Staff Member

    Ah I see, the confusion comes from your terminology. The straight line doesn't "define total losses" as you said, rather a straight line exposure curve can only occur when the only type of claim you can get is a total loss claim.

    Let's use an argument similar to the one I gave you earlier: Let's say a total loss is 3000, and again you have 3 losses, but this time they are all total losses. So of course loss A = 3000, loss B = 3000 and loss C = 3000. The average of these is 3000.
    Now let's say you impose a limit of 2000. All losses are now reduced to 2000 and the LEV is therefore 2000. Similarly, if you reduce the limit still further, to 1000, the insurer will only pay 1000 on every claim and the limited expected value is now 1000.

    In summary then, if all losses are total losses, we have:
    • limit 1000: LEV = 1000
    • limit 2000: LEV = 2000
    • limit 3000: LEV = 3000
    and again, the exposure curve will follow a similar shape, so we have a straight line diagonal.

    So what's the moral of this story?

    Well, if a high proportion of your loss cost is made up of very large losses (including some total losses, say), then you get a curve that is very close to the main diagonal. Conversely, the more attritional losses you have, the more the exposure curve will rise above the main diagonal. (Clearly then, a portfolio is more attractive if the exposure curve is very "curved".)
     
  7. redzer

    redzer Member

    Ok, I now see what the reference to total losses was about.

    Thank you very much for your explanation. It has been extremely helpful.

    R
     
  8. Qayanaat

    Qayanaat Ton up Member

    ST8 - September 2010 Question 5

    Hi,

    I'm getting confused with the solution given for part (ii) and hence (iii) of this question.

    I thought the closer the lines are to the diagonal, the more severe are the losses. Hence for part (ii) I would have said that G(0.5) for curve B would give a higher Y (i.e. relative loss severity) than curve A.

    G(0.5) for curve A from the graph is slightly less than 0.2 while
    G(0.5) for curve B ~ 0.35

    Since B would have more severe losses, I would have thought the premiums using curve B would be higher than A, as a result of the more severe losses.

    And therefore for part (iii) distribution of claim size for B would contain higher proportion of severe losses (hence higher expected claim cost, larger spread, more volatility and all)

    The answers given in the solution are the complete opposite, please guide me as to what am I failing to understand. Thanks a lot.
     
  9. Ian Senator

    Ian Senator ActEd Tutor Staff Member

    The curve gives you G(0.5). G(0.5) is about 0.95 for curve A and 0.75 for curve B. y is on the x-axis, and G(y) is on the y axis - maybe that's where you're getting confused?
     
    Qayanaat likes this.
  10. Qayanaat

    Qayanaat Ton up Member

    Yes thank you, sorry my bad, that was a stupid question! :D
     

Share This Page