FINANCIAL MODELING EXAM 2025/2026 QUESTIONS
WITH ANSWERS GRADED A+
✔✔what is a efficient portfolio - ✔✔feasible portfolio maximizing Er for a given variance
✔✔efficient frontier - ✔✔set of all efficient portfolios
✔✔Annulaization of mean Er - ✔✔12* Mean
✔✔Annulaization of Standard Deviation - ✔✔sqrt(12)*standard deviation
✔✔using solver for optimzation of portfolio - ✔✔Minimize variance
keep weights sum equal to one
keep desired return
✔✔What is the separation theorem - ✔✔we only need two envelope portfolios to find
the whole envelope
✔✔Formulae for separation theorem - ✔✔Solve optimization for two different targets
use these new weights and incorporate them in to the formula W = ax +(1-a)*y and then
solved Er and Standard deviation (remember X and Y are a series of weights)
✔✔Characterization theorem - ✔✔Using constant C to derive portfolio Weights
✔✔How to solve for Z in characterization therom - ✔✔Minverse(S)*(E(r)-c) = Z
✔✔How to solve for portfolio X weights in Characterization theorem - ✔✔X = z/ sum(All
Z)
✔✔When is the tangent method used - ✔✔when there are short sale constraints
✔✔how to implement the tangent mehtod - ✔✔maximize theta using solver
✔✔Formula for theta in tangent method - ✔✔(E(Rp) - C)/standardDevP
✔✔what is the variance of a risk free asset - ✔✔0
✔✔standard deviation for a portfolio with a risk free asset - ✔✔weight(risky asset) *
variance
✔✔Expected return for a portfolio with a risk free asset - ✔✔weight(risky asset) *E(r) +
weight(risk free asset)*E(r))
, ✔✔What is the sharpe ration - ✔✔slope for capital allocation line CAL also known as
the enhanced efficient frontier because now it has risk free assets by seperation
theorem
✔✔Sharpe ratio formula - ✔✔RP - Rm / Standard deviation P
✔✔Use the Rf ad constant C in the characterization theorom and then use in tangent
method - ✔✔yeah thats pretty much it
✔✔how to calculate Beta in OLS - ✔✔covariance(x,y)/variance (x)
✔✔how to calculate alpha - ✔✔E(y)-betaE(x)
✔✔T-statstistic for Betas - ✔✔Beta/ SE(b)
✔✔When to use intercept function - ✔✔When there is one factor in the model
✔✔When to use slope Function - ✔✔When there is one factor in the model
✔✔What is the first pass regression - ✔✔regress excess returns on risky assets on
excess returns of market to determine betas
✔✔What is the second pass regression - ✔✔regress betas on mean excess returns of
risky assets to get market risk premium
✔✔What is the capital market line CML - ✔✔the CAL between the Risk free rate and the
Market portfolio
✔✔Profit Buy Underlying - ✔✔=St- S0
✔✔Profit Sell Underlying - ✔✔S0 - St
✔✔Profit Long Call - ✔✔Max(St-X,0) - C0
✔✔Profit Short Call - ✔✔C0- Max(St-x,0)
✔✔Profit Long Put - ✔✔Max(X-St,0)- P
✔✔Profit Short Put - ✔✔P-Max(St-x,0)
✔✔Profit Protective put - ✔✔St-S0 + Max(X-St,0) - P
✔✔Bull Spread - ✔✔Sum (profit Call long ) (Profit call Short)
WITH ANSWERS GRADED A+
✔✔what is a efficient portfolio - ✔✔feasible portfolio maximizing Er for a given variance
✔✔efficient frontier - ✔✔set of all efficient portfolios
✔✔Annulaization of mean Er - ✔✔12* Mean
✔✔Annulaization of Standard Deviation - ✔✔sqrt(12)*standard deviation
✔✔using solver for optimzation of portfolio - ✔✔Minimize variance
keep weights sum equal to one
keep desired return
✔✔What is the separation theorem - ✔✔we only need two envelope portfolios to find
the whole envelope
✔✔Formulae for separation theorem - ✔✔Solve optimization for two different targets
use these new weights and incorporate them in to the formula W = ax +(1-a)*y and then
solved Er and Standard deviation (remember X and Y are a series of weights)
✔✔Characterization theorem - ✔✔Using constant C to derive portfolio Weights
✔✔How to solve for Z in characterization therom - ✔✔Minverse(S)*(E(r)-c) = Z
✔✔How to solve for portfolio X weights in Characterization theorem - ✔✔X = z/ sum(All
Z)
✔✔When is the tangent method used - ✔✔when there are short sale constraints
✔✔how to implement the tangent mehtod - ✔✔maximize theta using solver
✔✔Formula for theta in tangent method - ✔✔(E(Rp) - C)/standardDevP
✔✔what is the variance of a risk free asset - ✔✔0
✔✔standard deviation for a portfolio with a risk free asset - ✔✔weight(risky asset) *
variance
✔✔Expected return for a portfolio with a risk free asset - ✔✔weight(risky asset) *E(r) +
weight(risk free asset)*E(r))
, ✔✔What is the sharpe ration - ✔✔slope for capital allocation line CAL also known as
the enhanced efficient frontier because now it has risk free assets by seperation
theorem
✔✔Sharpe ratio formula - ✔✔RP - Rm / Standard deviation P
✔✔Use the Rf ad constant C in the characterization theorom and then use in tangent
method - ✔✔yeah thats pretty much it
✔✔how to calculate Beta in OLS - ✔✔covariance(x,y)/variance (x)
✔✔how to calculate alpha - ✔✔E(y)-betaE(x)
✔✔T-statstistic for Betas - ✔✔Beta/ SE(b)
✔✔When to use intercept function - ✔✔When there is one factor in the model
✔✔When to use slope Function - ✔✔When there is one factor in the model
✔✔What is the first pass regression - ✔✔regress excess returns on risky assets on
excess returns of market to determine betas
✔✔What is the second pass regression - ✔✔regress betas on mean excess returns of
risky assets to get market risk premium
✔✔What is the capital market line CML - ✔✔the CAL between the Risk free rate and the
Market portfolio
✔✔Profit Buy Underlying - ✔✔=St- S0
✔✔Profit Sell Underlying - ✔✔S0 - St
✔✔Profit Long Call - ✔✔Max(St-X,0) - C0
✔✔Profit Short Call - ✔✔C0- Max(St-x,0)
✔✔Profit Long Put - ✔✔Max(X-St,0)- P
✔✔Profit Short Put - ✔✔P-Max(St-x,0)
✔✔Profit Protective put - ✔✔St-S0 + Max(X-St,0) - P
✔✔Bull Spread - ✔✔Sum (profit Call long ) (Profit call Short)
