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Book Notes - blog notes [bn] >

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 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
36.standard error
37.standard normal distribution
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

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