The Foundation

The Foundation

Videos
IFT 2015 - CFA Level II FRA Long Lived Assets Summary 13:06
IFT 2015 - CFA Level II FRA Long Lived Assets Summary
IFT 2015 - CFA Level II FRA Inventories Summary 5:36
IFT 2015 - CFA Level II FRA Inventories Summary
IFT 2015 - CFA Level II Economics of Regulation Summary 33:17
IFT 2015 - CFA Level II Economics of Regulation Summary
IFT 2015 - CFA Level II Econ Economic Growth Summary 42:48
IFT 2015 - CFA Level II Econ Economic Growth Summary
IFT 2015 - CFA Level II Econ Currency Exchange Rates Summary 47:54
IFT 2015 - CFA Level II Econ Currency Exchange Rates Summary
IFT 2015 - CFA Level II Quant Time Series Summary 17:33
IFT 2015 - CFA Level II Quant Time Series Summary
IFT 2015 - CFA Level II Quant Multiple Regression Summary 20:10
IFT 2015 - CFA Level II Quant Multiple Regression Summary
IFT 2015 - CFA Level II Quant Correlation and Regression Summary 17:05
IFT 2015 - CFA Level II Quant Correlation and Regression Summary
Log odds interpretation of logistic regression 5:24
Log odds interpretation of logistic regression
Maximum Likelihood estimation of Logit and Probit 9:17
Maximum Likelihood estimation of Logit and Probit
Least squares comparison with Maximum Likelihood - proof that OLS is BUE 4:34
Least squares comparison with Maximum Likelihood - proof that OLS is BUE
Least Squares as a Maximum Likelihood estimator 7:37
Least Squares as a Maximum Likelihood estimator
Maximum Likelihood: Bernoulli random variables estimator variance part 2 2:46
Maximum Likelihood: Bernoulli random variables estimator variance part 2
Maximum Likelihood: Bernoulli random variables estimator variance part 1 5:39
Maximum Likelihood: Bernoulli random variables estimator variance part 1
Maximum likelihood: Normal error distribution - estimator variance part 1 3:13
Maximum likelihood: Normal error distribution - estimator variance part 1
Maximum likelihood: Normal error distribution - estimator variance part 3 5:02
Maximum likelihood: Normal error distribution - estimator variance part 3
Maximum Likelihood estimators of population mean and variance - part 2 3:45
Maximum Likelihood estimators of population mean and variance - part 2
Maximum likelihood: Normal error distribution - estimator variance part 2 6:01
Maximum likelihood: Normal error distribution - estimator variance part 2
Maximum Likelihood estimators of population mean and variance - part 3 3:13
Maximum Likelihood estimators of population mean and variance - part 3
Maximum Likelihood estimators of population mean and variance - part 1 7:03
Maximum Likelihood estimators of population mean and variance - part 1
Level I CFA Corporate Finance Reading Summary: Corporate Governance 10:47
Level I CFA Corporate Finance Reading Summary: Corporate Governance
Екатерина Шульман. Как правильно смотреть в будущее? 60:00
Екатерина Шульман. Как правильно смотреть в будущее?
Score test (Lagrange Multiplier test) - introduction 6:42
Score test (Lagrange Multiplier test) - introduction
Wald Test - introduction 6:19
Wald Test - introduction
Likelihood ratio test - introduction 6:09
Likelihood ratio test - introduction
Maximum Likelihood - Cramer Rao Lower Bound Intuition 7:59
Maximum Likelihood - Cramer Rao Lower Bound Intuition
Why maximise 'log' likelihood? 7:18
Why maximise 'log' likelihood?
The Cramer-Rao Lower Bound: Inference in Maximum Likelihood Estimation 5:12
The Cramer-Rao Lower Bound: Inference in Maximum Likelihood Estimation
Nonlinear discrete choice models - an introduction 5:34
Nonlinear discrete choice models - an introduction
Maximum Likelihood estimation - an introduction part 2 7:07
Maximum Likelihood estimation - an introduction part 2
Maximum Likelihood estimation - an introduction part 1 8:24
Maximum Likelihood estimation - an introduction part 1
Maximum Likelihood estimation - an introduction part 3 3:59
Maximum Likelihood estimation - an introduction part 3
Nonlinear discrete choice model estimation 8:28
Nonlinear discrete choice model estimation
Discrete choice models - partial effect part 2 3:14
Discrete choice models - partial effect part 2
Discrete choice models - partial effect part 1 6:33
Discrete choice models - partial effect part 1
Discrete choice models - introduction to logit and probit 9:56
Discrete choice models - introduction to logit and probit
The problems with the linear probability model - part 2 8:46
The problems with the linear probability model - part 2
The problems with the linear probability model - part 3 2:52
The problems with the linear probability model - part 3
The problems with the linear probability model - part 1 4:58
The problems with the linear probability model - part 1
The linear probability model - example 4:31
The linear probability model - example
Panel data conditions for consistency and unbiasedness of estimators 6:59
Panel data conditions for consistency and unbiasedness of estimators
Panel data conditions for BLUE estimation and inference 6:42
Panel data conditions for BLUE estimation and inference
The linear probability model - an introduction 4:39
The linear probability model - an introduction
Lecture 15: Factor Modeling 85:48
Lecture 15: Factor Modeling
Lecture 14: Portfolio Theory 84:54
Lecture 14: Portfolio Theory
Lecture 13: Commodity Models 80:44
Lecture 13: Commodity Models
Lecture 12: Time Series Analysis III 77:38
Lecture 12: Time Series Analysis III

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