Motivations of Lenders and shareholders
Comparison between Debt and Equity Claims Debtholders, also known as lenders, provide a company with finite-term financial capital. In return, the issuers agree to make regular interest payments and repay the principal on predetermined dates. Lenders do not possess decision-making…
Functional Forms for Simple Linear Regression
To address non-linear relationships, we employ various functional forms to potentially convert the data for linear regression. Here are three commonly used log transformation functional forms: Log-lin model: In this log transformation, the dependent variable is logarithmic, while the independent…
Predicted Value and Prediction Interval of a Dependent Variable
We calculate the predicted value of the dependent variable, \(Y\), by inserting the estimated value of the independent variable, \(X\), into the regression equation. The predicted value of the dependent variable, \(Y\), is determined using the following formula: $$\hat{Y}=\hat{b}_0+\hat{b}_1X$$ Where:…
Analysis of Variance (ANOVA)
The sum of squares of a regression model is usually represented in the Analysis of Variance (ANOVA) table. The ANOVA table contains the sum of squares (SST, SSE, and SSR), the degrees of freedom, the mean squares (MSR and MSE),…
Measures of Fit and Hypothesis Tests of Regression Coefficients
The sum of Squares Total (SST) and Its Components The sum of Squares Total (total variation) is a measure of the total variation of the dependent variable. It is the sum of the squared differences of the actual y-value and…
Assumptions Underlying Linear Regression
Assume that we have samples of size \(n\) for dependent variable \(Y\) and independent variable \(X\). We wish to estimate the simple regression of \(Y\) and \(X\). The classic normal linear regression model assumptions are as follows: Strengthen your CFA…
Introduction to Linear Regression
Linear regression is a mathematical method used for analyzing how the variation in one variable can explain the variation in another variable. Let \(Y\) be the variable we wish to explain. As such, the observation of this variable is \(Y_i\),…
Applications of Big Data and Data Science
Data science is an interdisciplinary field that uses developments in computer science, statistics, and other fields to extract information from Big Data or data in general. Data Processing Methods Data analysts and scientists in big data analysis use different data…
Big Data
Big data is a term that describes large, complex datasets. These datasets are analyzed with computers to uncover patterns and trends, particularly those related to human behavior. Big data includes traditional sources like company reports and government data and non-traditional…
Introduction to Big Data Techniques
Fintech refers to technological innovation in designing and delivering financial services and products. At its core, fintech has helped companies, business owners, and investment managers better manage their operations through specialized software and algorithms. Note that the term fintech is…
