It seems to me that the important material from this topic is primarily associated with VaR, Option Pricing, and Fixed Income...which is really only 3 of the assigned readings.....i.e., Reading 21 for VaR = Allen, Reading 22 for Binomial and Black Scholes = Hull, and Reading 23 for Fixed Income...
I may be slightly non-technical here but I'll give it a try. The normal distribution DOES have higher order moments. Indeed, it has an infinite number of moments, as do (most) continuous distributions. The unique characteristic of the normal distribution, although not unique to the normal...
Anyone else have a problem with the way this problem is worded? C or D seem sufficient, particularly since we were told (weren't we told in one of the videos?) to not worry about direction, so to speak. Am I way off?
Thanks,
Brian
David, You have a well-developed ability to offer positive reinforcement in your responses....your efforts are appreciated!
Thanks for your kind words...(maybe I'll forward this feedback to my boss! kidding...) Thanks for your response.
Brian
I am annoyed that I cannot follow the Treasury Bond quotes on Hull's page 133.
Hull states that 124.150 is equal to 124 and 15.0/32. I get this.
He later states that 120-105 is equal to 120 and 10.5/32. I get this too.
Now, Hull then states that 117-157 is equal to 117 and 15.75/32. How...
David,
I noticed that the denominator in the heteroskedacticity F-statistic is 1 - rho^2 in the reference text but you indicate that it is 1 - 2*rho in both your notes and in your video.
Which expression is correct?
Thanks.
Brian
The pages I quoted were associated with the second edition but I believe the pictures are the same in both editions, but the page numbers may differ.
Also, what you are saying seems reasonable, irenab (thank you).
Still, I think the illustration was meant to compare a normal distribution...
A distribution with positive (excess) kurtosis (leptokurtosis) is MORE peaked than a normal distribution with lower probabilities at (around) plus and minus 1 standard deviation AND more probabilities in the tails, i.e., fatter tails than the normal distribution. The picture presenting kurtosis...
Miller mentions at the bottom of page 50 that many practitioners inaccurately believe that the ordering of the mean, median, and mode is just that (from left to right) for negatively skewed distributions (and mean, median, and mode (from right to left) for right skewed or positively skewed...
These readings are available in the GARP texts....you may be able to find them (individually) a bit cheaper on E-Bay or elsewhere online. I think it is pretty unfortunate the GARP is no longer selling individual readings.
I would also argue that (since this particular reading is introductory,)...
I feel terrible asking what I assume is an elementary question, but alas, this is why I am here.
David - I do not believe that you address the F statistic's representation as ESS/k / RSS/n-k-1 explicitly anywhere in the S and W videos. Is there some reason this was not covered? Is it...
This notion of OVB is confusing to me.
In order for OVB to be present, the regression equation must omit a variable that is correlated with a variable that is included in the regression equation and also, the dependent variable and omitted variable must be dependent, essentially.
So, I...
Interestingly, I have seen that a regression equation is linear if and only if it is linear in the parameters....i.e., if it is linear in the coefficients. (I have also seen definitions of linear regression equations requiring linearity in both the coefficients and the independent variables...
This site uses cookies to help personalise content, tailor your experience and to keep you logged in if you register.
By continuing to use this site, you are consenting to our use of cookies.