Finance and Accounting

Mathematics:
1. Calculus: It is very important to gain a more precise understanding of space, time and motion
2. Differential Equations: They are used to model the behavior of complex systems
3. Linear Programming: Method to achieve best outcome, maximize profit – minimize loss
4. Mathematical Modeling: It helps to provide a systematic approach to modeling and analysis
5. Stochastic Processes: Helps in modeling and analysis of real world phenomena in terms of stochastic processes.

Probability Theory:
1. Conditional Probability and Distributions: Helpful in analyzing investment data
2. Discrete and General Variables: Can be used to model uncertainty from incomplete or simplified models
3. Limit Theorems:
4. Random Walk: Important in understaning the efficient market hypothesis
5. Independence and Correlation: Helpful tools in risk management

Econometrics:
1. Multiple Linear Regression: Models the relationships between two or more explanatory variables and a response variable
2. Weighted Least Squares: Provides a method for dealing with heteroskedasticity
3. Ordinary Least Squares: Useful in the development of economic models
4. Logistic Regression: Used to predict a binary response from a binary predictor
5. Dummy Variables: A numerical value helpful in regression analysis to represent subgroups of a sample in a particular study
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