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Hi, The test is that: H0: populn mean(B1)=0 and Ha: populn mean(B1)!=0 where B1 is populn value that corresponds to sample vale of b1. we know that for confidence level 95% t-stat~2 we know that for a sampling distribution(assumed t-distribution here) the sample mean must lie within B1 +/-...

EWMA: Cov(n)=lambda*Cov(n-1) + (1-lambda)*x(n-1)*y(n-1) where Cov(n-1) is the covariance estimate for day n-1 and x(n-1)*y(n-1) is the cross product of the returns for x and y on day n-1. for GARCH: Cov(n)=omega+beta*Cov(n-1) + alpha*x(n-1)*y(n-1) where omega is the LT average Covariance...

Thanks Nicole,please let it accrue... thanks

Hi Gargi, df=1 for intercept term+no of independent variables=1+1=2 for this question(we need to consider intercept term also along with the other independent variables) hence SER=sqrt(SSR/n-df)=sqrt(SSR/n-2) thanks

I) since the vega is very large and positive we need to short long term option position so as to create a large negative vega and neutralise the vega thus Sell long term (LT) and Buy short term(ST) options + Sell long term (LT) options shall create a net positive gamma neutralising the gamma...

1) Here p values are given so just compare p value with the significance level here of .05 if p-value<.05(no table required here) then reject the null hypothesis otherwise accept the null hypothesis. In F test we test the joint hypothesis that is Ho: β1 = 0 and β2 = 0 Ha: atleast one of β1 or β2...

1) For Loan A we need to find 3 month PD ,1-(1-3 month PD)^4=1 year PD =>3 month PD=1-(1-1 year PD)^(1/4)=1-(1-.025)^(1/4)=.00631 =>EL(3mnths)=.00631*50%=.3155% Loan B: 9 month PD=1-(1-1 year PD)^(.75)=1-(1-.011)^(.75)=.00826=>EL(9mnths)=.00826*65%=.5369% Loan C: 6 month PD=1-(1-1 year...

Hi, The forward price, F(o,t)= S0*exp(rt) and Expected spot price=E(St)=S0*exp(kt) where k is the systematic mkt risk thus F(o,t)/E(St)= S0*exp(rt)/S0*exp(kt) =>F(o,t)=E(St)*exp((r-k)*t).In normal backwardation F(o,t)<E(St) =>exp((r-k)*t)<1 =>(r-k)*t<0 =>r<k or k>r for high systematic risk the...

Hi There are a number of states in which stock has value ST>K out of n possible states. Multiply by probability in those states(where S(T)>K) with the stock value to get the net expected value E(S(T)|S(T)>K) that the stock shall have in the future after time T when it expires ITM ,let the...

Hi when storage cost in%(continuously compounded) let it be c=4% and risk free rate=5%,spot price=100,T=1 Then forward price= 100*exp((r+c)*T)=100*exp(.05+.04)*1=100*exp(.09)=109.42 when storage cost in $ forward price=(100+PV of storage costs)*exp(rT) ,let PV of storage costs=4$ then forward...

Hi, EL is not a risk as its already being accounted for what is risk are the losses that can happen beyond and above the expected loss therefore this losses above the EL are unpredictable are called the unexpected losses is the risky part. Thus EL+UL is a risk because the component UL is a...

Hi, The futures curve plots the futures price Vs Time to maturity(T). So that if r=5% and delta=4%, S0=100 then the future price=100*exp((5%-4%)T) hence if T increases the future price increases therefore the futures curve the plot of futures price Vs Time to maturity(T) is upward sloping. thanks

Hi, (1-lambda)*lambda^0*u(n-1)^2 + (1-lambda)*lambda^1*u(n-2)^2... =(1-lambda)*u(n-1)^2 + lambda^1*((1-lambda)*lambda^0*u(n-2)^2+.....) =(1-lambda)*u(n-1)^2 + lambda*(sigma(n-1)^2 ) is other form (since sigma(n-1)^2 =(1-lambda)*lambda^0*u(n-2)^2+.....) thanks

Hi, normally we use continuous compounding for discounting purpose becuse its more simple to discount this way rather than discounting via discrete compounding. Hull uses continous compunding rather than discerte to simplify calculations. Thanks

Hi First one quoted futures price = cash futures price - accrued price is the right one. Second gives the CTD(cheapest to deliver) quoted futures price. thanks

please use the search tab in the site you would find most of the answers. thanks

hi please let it accrue. thanks

Hi, R^2 is determined using the sample data its not necessary that the high R^2 applies to out of sample data also sometimes this is called in-sample over fitting. Therefore the model may not be accurate when applied to out of sample. Thus new measures are required to overcome this like the...

Hi, Yes R^2 is just a numerical value for us to compare how good various independent variables are at predicting a dependent variable.Do not get confused with Adjusted R^2 ,we have Adjusted R^2 to overcome deficiency of R^2 that always increases with addition of independent variable,Adjusted...