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As i can see, you are getting the average quantile from the formula, Formula=Integral of qp dp from confidence level alpha(here in formula i think alpha is confidence level) to 1/(1-confidence level alpha)=weighted average of the quantiles qp to the right of Loss quantile=1.96 with each...

The n days volatility is scaled by sqrt(m/n) to get m days volatility thus m days volatility, m-period volatility = n-period volatility * sqrt[m/n] m-day volatility = n-day volatility * sqrt[m/n] Here n=2 days, n-day volatility =x=1.2%,m=20 days using, m-day volatility = n-day...

Yes Brian I think he means that all the parameters used in the equation be well defined, that is If i used the equation , EL=PDxLGD then EL,PD and LGD should be well defined that is what is EL,PD and LGD. EL=Expected Loss, PD=Probability of default and LGD=Loss given Default. Some more...

To boost your confidence in maths: you can try these books https://forum.bionicturtle.com/threads/supplementary-beginner-maths-book-for-frm.3476/#post-9423 I think you should spend as much time as possible to improve your math. thanks

please visit the links: 1)https://forum.bionicturtle.com/threads/what-level-of-calculus-is-assumed.185/#post-717 2)https://forum.bionicturtle.com/threads/question-about-math-background-required-for-frm.248/#post-1063 thanks

Hi, Use formula for ES=NORM.S.DIST(CDF,0)/alpha=pdf/alpha for 97.5%, ES=NORM.S.DIST(1.96,0)/0.025=2.338 thanks

X1=2,X2=4,Z=X2^2=16 then Z is the perfect linear function of X1 and X2,Z=aX1+bX2,. then Z=2a+4b=16=>a+2b=8 X1=3,X2=5,Z=X2^2=25, Z=3a+5b=25 thus from above solving we get,b=-1 and a=10, function Z=10X1-X2 We could have data that satisfies the linear function Z=10X1-X2 so that Z is a linear...

Yes Z is a linear function of X1 and X2. thanks

Yes Brian there is OVB as Z = X2^2 is a determinant of Y.But dont you think if majority of the explanation is being done by X2 alone then why its power is required?,R^2 shall not change by much,even if OVB is there it would not pose much threat. Also even if X2 and Z are related non-linearly...

Hi, you can also do it as Risk increases from B1= 0.5 to B2 = 1.5 that is by 1.5-.5=1 unit the return increases from 6% to 12% by 12%-6%=6% therefore for every 1 unit increases in Risk (beta) the return on asset increases by 6%.Thus increase in return for every 1 unit increases in Risk (beta) is...

This was the conversation i had with SM may be helpful for others, 1. While first studying the FRM curriculum did you attempt only BT end of chapter questions or questions for the respective topic from the Q Bank as well? 1. While first studying the FRM curriculum did you attempt only BT end of...

Hi Stephen, 1. i should say start with one you feel you are comfortable with i mean what you feel like,if you are more enthusiastic about FRM and feel like you have more interesting stuff to study in FRM then start with FRM otherwise if you are more enthusiastic about CFA and feel like you have...

Hi Brian , Yes Brian after a long time. Yes Brian i am talking in context of perfect multicollinearity,that is if you add a power like X3^2 then its possible(if possible??) that this X3^2 is a perfect linear function of the other regressors then multicollinearity does holds then OVB is not...

AIC formula=EXP (2k/T) * (SSE/T) LN(AIC formula)=LN(EXP (2k/T)) * (SSE/T)) ..tale log on both sides LN(AIC formula)=LN(EXP (2k/T))+LN(SSE/T) LN(AIC formula)=2k/T + LN(SSE/T) T*LN(AIC formula)=T*(2k/T + LN(SSE/T))...multiply both sides by T T*LN(AIC formula)=T*(2k/T + LN(SSE/T)) T*LN(AIC...

chi-square for n-1 degrees of freedom=(s^2/sigma^2)*(n-1) where s is a sample variance and sigma is the hypothetical population variance with which the sample variance is to be compared. thanks

Brian according to your second question, I think that's why Brian there is an assumption of multicollinearity ,yes you are right that there shall always be OVB if we consider variables likes this but dont you think that the assumption of multicollinearity shall be violated that the independent...

According to sources from the net I researched results shall be mailed by 5th Jan. thanks

housing bubble burst ->collapse in the prices of the houses ->the credit spread of the mortgages went up as the creditworthiness of borrowers came into question due to collapse in the prices of the house which served as collateral to mortgages ->the credit spread of the Mortgage backed...

Yes PFE is the potential future exposure its the maximum exposure that can occur in the future,its the 99th percentile quantile on the exposure distribution above.Whereas the EE is the expected exposure is the mean of the positive future exposures. The expected terminal value that Malz found is...

Hi, Credit spread is the spread/difference between the interest rate on the mortgages and the risk free rate.Its given by interest rate on the mortgages-risk free rate. Its also defined as credit spread=Probability of default*loss given default,during the crisis both the Probability of default...