BOOTCAMP Stats for Finance
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| Sn | Topics | |
| Probability | ||
| 01 | Probability | |
| 02 | Bayesian Analysis | |
| Random Variables | ||
| 01 | Descriptive Statistics - Mean, Variance, Skewness, Kurtosis | |
| 02 | Properties of Random Variables | |
| 03 | Common Univariate Random Variable aka Probability Distributions | |
| 04 | Discrete Distributions - Uniform, Benoulli, Binomial, Poisson | |
| 05 | Continuous Distributions - Exponential, Gamma, Weibull, Beta | |
| 06 | Normal and Log normal Distributions | |
| 07 | Checking Distribution of Financial Returns | |
| 08 | Covariance & Correlation | |
| Sampling Theory | ||
| 01 | Sampling Distributions | |
| 02 | Central Limit Theorem | |
| Hypothesis Testing | ||
| 01 | Testing of Means & Difference of Means | |
| 02 | Testing of Variance | |
| 03 | Testing of ratio of Variance | |
| 04 | Bonferroni Test (Multiple Testing) | |
| Regression | ||
| 01 | 7 Ways to get Regression Output | |
| 02 | ANOVA, Regression Statistics and Hypothesis Testing | |
| 03 | Gauss Markov Assumptions | |
| 04 | Detecting & Correcting Heteroskedasticity | |
| 05 | Detecting & Correcting Multicollinearity | |
| 06 | Detecting & Correcting Omitted Variable Bias | |
| 07 | Regression Output Uncertainity | |
| Time Series Modelling | ||
| 01 | Time Series Mind Map | |
| 02 | Non Stationary Time Series - Trend & Seasonality | |
| 03 | Covariances for AR & MA Models | |
| 04 | Use of ACF & PACF | |
| 05 | ARMA Parameter Estimation using MLE | |
| 06 | Building ARMA forecasts | |
| 07 | Checking White Noise (Ljung Box & Box Pierce Q statistic) | |
| 08 | Forecasting accuracy of model | |
| 09 | Improving error terms by including ARCH GARCH terms |
ABOUT THE TRAINER
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No content
| Sn | Topics | |
| Probability | ||
| 01 | Probability | |
| 02 | Bayesian Analysis | |
| Random Variables | ||
| 01 | Descriptive Statistics - Mean, Variance, Skewness, Kurtosis | |
| 02 | Properties of Random Variables | |
| 03 | Common Univariate Random Variable aka Probability Distributions | |
| 04 | Discrete Distributions - Uniform, Benoulli, Binomial, Poisson | |
| 05 | Continuous Distributions - Exponential, Gamma, Weibull, Beta | |
| 06 | Normal and Log normal Distributions | |
| 07 | Checking Distribution of Financial Returns | |
| 08 | Covariance & Correlation | |
| Sampling Theory | ||
| 01 | Sampling Distributions | |
| 02 | Central Limit Theorem | |
| Hypothesis Testing | ||
| 01 | Testing of Means & Difference of Means | |
| 02 | Testing of Variance | |
| 03 | Testing of ratio of Variance | |
| 04 | Bonferroni Test (Multiple Testing) | |
| Regression | ||
| 01 | 7 Ways to get Regression Output | |
| 02 | ANOVA, Regression Statistics and Hypothesis Testing | |
| 03 | Gauss Markov Assumptions | |
| 04 | Detecting & Correcting Heteroskedasticity | |
| 05 | Detecting & Correcting Multicollinearity | |
| 06 | Detecting & Correcting Omitted Variable Bias | |
| 07 | Regression Output Uncertainity | |
| Time Series Modelling | ||
| 01 | Time Series Mind Map | |
| 02 | Non Stationary Time Series - Trend & Seasonality | |
| 03 | Covariances for AR & MA Models | |
| 04 | Use of ACF & PACF | |
| 05 | ARMA Parameter Estimation using MLE | |
| 06 | Building ARMA forecasts | |
| 07 | Checking White Noise (Ljung Box & Box Pierce Q statistic) | |
| 08 | Forecasting accuracy of model | |
| 09 | Improving error terms by including ARCH GARCH terms |
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