Exam Feedback November 2018 Part 2 Exam Feedback

Linghan

Active Member
Clustering identifies outliers that do not have strong connections with the rest of the data. You can't predict PD with clustering only.

For example , you can use clustering to divide the applicants into 10 classes. But without any PD information about some applicants in each class. You will not know the PD of each class.
But the question mentioned data sources are unstructured - metadata and various other sources from app or other channels, so it should be unsupervised learning
 

fxlprasetyo

New Member
But the question mentioned data sources are unstructured - metadata and various other sources from app or other channels, so it should be unsupervised learning
Unstructured data has nothing to do with being able to use Supervised vs Unsupervised learning. Emails for example is an unstructured data, so is an image, etc. and one can definitely apply supervised learning for these data types.
 

FreemanMI

Member
I'm not sure what the answer was but I just did DV01 times the position / dv01 of the hedge... but that seemed to easy, but my answer was there.
Yes indeed, nothing difficult there, just divide one dv01 to the second, then multiply by value we had, just not sure which one is the divisor..but i just followed the logic, as he had some bond with around 0.12 dv01, and the treasury one had something like 0.06, so it makes sense that to hedge one bp move had to be twice the hedging treasury bond
 

mshahawy

New Member
Yes indeed, nothing difficult there, just divide one dv01 to the second, then multiply by value we had, just not sure which one is the divisor..but i just followed the logic, as he had some bond with around 0.12 dv01, and the treasury one had something like 0.06, so it makes sense that to hedge one bp move had to be twice the hedging treasury bond
You still need to multiply with the beta
 

voichi

New Member
The answer wouldn't be linear programming since, the option is "Linear Programming where transaction cost can't be incorporated explicitly", which is not true, unfortunately, which is my answer as well. Many answers required a very detail knowledge of the topic, as this was a tricky exam indeed.
Indeed.
 

runal

New Member
Does any one remember the question of volatility smiles with 4 graphs in the options? Also what was the correct choice for it ?
 

runal

New Member
It was 1 year spot rate at 3% initially, and then 1 year forward rates (1 year from now) are given as 3.8% (up node) and 2.8% (down node). The compounding is to be done semi annually. Equal real world probabilities are to be assumed to get present value of 2 year ZCB.
I got 93940 as the answer. Can someone verify the same
 

FreemanMI

Member
Does any one remember the question of volatility smiles with 4 graphs in the options? Also what was the correct choice for it ?
The correct one was the volatility frown where the ATM option had higher volatility due to expected huge decrease or increase of stock price after the deal if it fails or not
 

Linghan

Active Member
Unstructured data has nothing to do with being able to use Supervised vs Unsupervised learning. Emails for example is an unstructured data, so is an image, etc. and one can definitely apply supervised learning for these data types.
Classificaition trees are applied to situation where data is divided into groups rather than investigating a numerical response and its relationship to a set of descriptor variables.....
 

FreemanMI

Member
The problem is...that we are brainstorming here on the forums...but the biggest problem is, that we will never find out which were the correct answers..hehe :(
 

fxlprasetyo

New Member
But for dependent variable which is a factorial number (non-continuous) that works too for trees?
The choice is not only Classification. The option A) Penalized Regression and Classification. I'm assuming, this is to be used in tandem, ie. one can use classification to decide if there's a default or not, than use the penalized regression to find the PD, which is what the question asked.
 

Linghan

Active Member
The choice is not only Classification. The option A) Penalized Regression and Classification. I'm assuming, this is to be used in tandem, ie. one can use classification to decide if there's a default or not, than use the penalized regression to find the PD, which is what the question asked.
Sounds like you are the correct choice!!
 

serg1993

New Member
The correct one was the volatility frown where the ATM option had higher volatility due to expected huge decrease or increase of stock price after the deal if it fails or not
I think the correct answer was volatility jump picture, because of the extremly uncertain situation
 
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