FRM CFA Quant Strategy
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Transcript of FRM CFA Quant Strategy
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FRM/CFA Demystifying Quant
(Financial Engineering)
By Shivgan Joshi
http://stockcreditfinancecfa.blogspot.com
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Content
Resources and Recommended Readings
Toughness Ranking
Areas of Maths Strategy for Non Maths people
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List of Areas of Quant
1. Demystifying Calculus
2. Demystifying distributions
3. Demystifying Regression
4. Moments for Statistical Analysis
5. Bivariate and Multivariate
6. Normal Distributions
7. Matrix
8. Monte Carlo Simulations
9. GARCH10. Black Scholes
11. Martingale
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Quant vs No Quant
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Quant vs. No Quant
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FRM Handbook
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J. Hull Book for Derivatives
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Toughness Ranking (B. Engg Maths)
GARCH
Multivariate
Distributions Rest all is easy
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Demystifying Calculus
What is stochastic calculus
Duration
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Stochastic Calculus
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Itos Formula
Chain Rule
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Risk Neutral Method
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Demystifying distributions
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Demystifying Regression
Linear, two and multiple variables
R-square
Beta (of stock with market and with Future)
Why t distribution
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Moments for Statistical Analysis
How to link moments
What are moments?
1st to 4th moment and how are they important
Standardized variables
Why divided by sigma
What is difference between powers 3 vs 5, or 4 vs
6 Also the meaning of Skewness (positive and
negative) and Kurtosis (fat and thin tails)
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Covariance
How to land up with the formula
http://mathworld.wolfram.com/CorrelationCoefficient.html
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Bivariate and Multivariate
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Normal Distributions
Exp to power negative square
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Binomial Distributions
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Matrix
Correlation Matrix
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Monte carlo
Weiner
Ito
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GARCH
AutoRegressive Conditional Heteroskedasticity
Function of past
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Black Scholes Model
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Martingale
Wiener Process is a Martingale
http://en.wikipedia.org/wiki/Risk-neutral_measure
http://en.wikipedia.org/wiki/Martingale_%28probability_theory%29
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Distribution
1. Bernoulli's
2. Poisson's
3. Weibull distribution (shape & scale, mix of 2
functions)
4. Chi-squared distribution (tricky, division createsproblems)
5.Logistic distribution
6. Generalized extreme value distribution
7. F Distribution (used in regression)
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Chi-squared distribution
Variance of sample to population
Linked to normal distribution
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F Distribution
Both numerator and denominator has degrees
of freedom
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Binomial to Poisson
How things gets converted
Coin to Poisson
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Sample distribution Formula
Variance of sample derivation
Error
http://en.wikipedia.org/wiki/Standard_deviation
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Weibull distribution
Hybrid of exp and ra
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Hypothesis testing
Confusing terms
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References
Wiki
Schaums Outline of Probability
Syllabus of Respective Exams