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Credit Risk Modelling
19
Credit Risk Modelling using Logistic Regression in R
Welcome
Syllabus
I : Foundations of Financial Data Analysis in R
Introduction to Financial Data
1
Types of financial data
Time Series Analysis in R
2
Importing stock price Data
3
Converting data into time series data
4
Decomposition of Time series data in R
5
Calculation of Returns in R (Daily, Weekly, Monthly & Annual)
6
Graphing techniques
7
Descriptive Statistics of Returns
II : Technical Analysis in R
Applying Technical Indicators
8
Importing Stock Price Data for Technical Analysis
9
Technical Indicators: Support Resistance Levels
10
Technical Indicators: Momentum Indicators
11
Technical Indicators: Volume Indicators
12
Technical Indicators: Trend Indicators
13
Technical Analysis using Quantmod package in R
III : Portfolio Management and Fixed Income Securities
Portfolio Models
14
Sharpe Model
15
CAPM model
Fixed Income Securities in R
16
Measuring market risk for fixed Income securities
17
Immunization of Fixed income Portfolio
18
Pricing a Convertible Bond
IV : Credit Risk and Advanced Analytics
Credit Risk Modelling
19
Credit Risk Modelling using Logistic Regression in R
20
Credit Default Data Analysis
21
Fitting Model & predicting the probabilities
22
Checking accuracy
Customer and Bank Data Analysis
23
Segmentation of the Financial Customer Data using Cluster Analysis
24
Factor Analysis of Bank Data
References
Credit Risk Modelling
19
Credit Risk Modelling using Logistic Regression in R
19
Credit Risk Modelling using Logistic Regression in R
IV : Credit Risk and Advanced Analytics
20
Credit Default Data Analysis