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## Credit Risk Modeling using Excel VBA

 1 Cumulative probability distribution 2 Logistic distribution = 1 / (1+e**-x) 3 Defaults are independent 4 ln => x**y = y ln(x) 5 1st Derivative 6 2nd Derivative 7 dependent variable 8 Central Limit Theorem 9 Excess Kurtosis - indicates existence of outliers 10 Kurtosis = 0 = Normal Distribution 11 Positive Excess Kurtosis = many observations away from mean compared to Normal Dist 12 Negative Skewness = extreme observations on left 13 + Skewness = extreme observations on right 14 ND = 99% are +/- 2.58 stdev from mean 15 data mining - negative term for finding something that's not there 16 Derivative = slope at a point X**2 = 2X - 1 17 Y = mx + b where m is the slope and b is the intercept 18 Max Likelihood 19 Sum product symbol 20 First Derivative 21 Newton's method to find 1st derivative 22 y = dependant variable 23 x = explanatory variable 24 log likelihood function 25 Globally concave 26 gradient vector 27 Hessian matrix 28 Lambda prediction 29 Excel Linest 30 regression statistics 31 default variables 32 Minverse = matrix inverse 33 mmult = matrix multiply 34 t-ratio 35 t-distribution 36 standard error 37 standard normal distribution 38 p-value 39 normal distribution 40 null hypothesis 41 chi squared 42 pseudo r squared 43 r squared 44 inverse relationship 45 significance = p-value 46 chi squared distribution with 2 degrees of freedom 47 Out of sample test 48 scenario analysis 49 Goal seek 50 Solver
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