Quantitative Methods

Expand

Lesson Content

0% Complete 0/6 Steps

a. interpret interest rates as required rates of return, discount rates, or opportunity costs and explain an interest rate as the sum of a real risk-free rate and premiums that compensate investors for bearing distinct types of risk

b. calculate and interpret different approaches to return measurement over time and describe their appropriate uses

c. compare the money-weighted and time-weighted rates of return and evaluate the performance of portfolios based on these measures

d. calculate and interpret annualized return measures and continuously compounded returns, and describe their appropriate uses

e. calculate and interpret major return measures and describe their appropriate uses

Curriculum End of Chapter Questions

Time Value of Money in Finance 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. calculate and interpret the present value (PV) of fixed-income and equity instruments based on expected future cash flows

b. calculate and interpret the implied return of fixed-income instruments and required return and implied growth of equity instruments given the present value (PV) and cash flows

c. explain the cash flow additivity principle, its importance for the no-arbitrage condition, and its use in calculating implied forward interest rates, forward exchange rates, and option values

Curriculum End of Chapter Questions

Statistical Measures of Asset Returns 5 Topics

Expand

Lesson Content

0% Complete 0/5 Steps

a. calculate, interpret, and evaluate measures of central tendency and location to address an investment problem

b. calculate, interpret, and evaluate measures of dispersion to address an investment problem

c. interpret and evaluate measures of skewness and kurtosis to address an investment problem

d. interpret correlation between two variables to address an investment problem

Curriculum End of Chapter Questions

Probability Trees and Conditional Expectations 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. calculate expected values, variances, and standard deviations and demonstrate their application to investment problems

b. formulate an investment problem as a probability tree and explain the use of conditional expectations in investment application

c. calculate and interpret an updated probability in an investment setting using Bayes’ formula

Curriculum End of Chapter Questions

Portfolio Mathematics 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. calculate and interpret the expected value, variance, standard deviation, covariances, and correlations of portfolio returns

b. calculate and interpret the covariance and correlation of portfolio returns using a joint probability function for returns

c. define shortfall risk, calculate the safety-first ratio, and identify an optimal portfolio using Roy’s safety-first criterion

Curriculum End of Chapter Questions

Simulation Methods 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. explain the relationship between normal and lognormal distributions and why the lognormal distribution is used to model asset prices when using continuously compounded asset returns

b. describe Monte Carlo simulation and explain how it can be used in investment applications

c. describe the use of bootstrap resampling in conducting a simulation based on observed data in investment applications

Curriculum End of Chapter Questions

Estimation and Inference 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. compare and contrast simple random, stratified random, cluster, convenience, and judgmental sampling and their implications for sampling error in an investment problem

b. explain the central limit theorem and its importance for the distribution and standard error of the sample mean

c. describe the use of resampling (bootstrap, jackknife) to estimate the sampling distribution of a statistic

Curriculum End of Chapter Questions

Hypothesis Testing 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. explain hypothesis testing and its components, including statistical significance, Type I and Type II errors, and the power of a test.

b. construct hypothesis tests and determine their statistical significance, the associated Type I and Type II errors, and power of the test given a significance level

c. compare and contrast parametric and nonparametric tests, and describe situations where each is the more appropriate type of test

Curriculum End of Chapter Questions

Parametric and Non-Parametric Tests of Independence 3 Topics

Expand

Lesson Content

0% Complete 0/3 Steps

a. explain parametric and nonparametric tests of the hypothesis that the population correlation coefficient equals zero, and determine whether the hypothesis is rejected at a given level of significance

b. explain tests of independence based on contingency table data

Curriculum End of Chapter Questions

Simple Linear Regression 7 Topics

Expand

Lesson Content

0% Complete 0/7 Steps

a. describe a simple linear regression model, how the least squares criterion is used to estimate regression coefficients, and the interpretation of these coefficients

b. explain the assumptions underlying the simple linear regression model, and describe how residuals and residual plots indicate if these assumptions may have been violated

c. calculate and interpret measures of fit and formulate and evaluate tests of fit and of regression coefficients in a simple linear regression

d. describe the use of analysis of variance (ANOVA) in regression analysis, interpret ANOVA results, and calculate and interpret the standard error of estimate in a simple linear regression

e. calculate and interpret the predicted value for the dependent variable, and a prediction interval for it, given an estimated linear regression model and a value for the independent variable

f. describe different functional forms of simple linear regressions

Curriculum End of Chapter Questions

Introduction to Big Data Techniques 4 Topics

Expand

Lesson Content

0% Complete 0/4 Steps

a. describe aspects of “fintech” that are directly relevant for the gathering and analyzing of financial data.

b. describe Big Data, artificial intelligence, and machine learning

c. describe applications of Big Data and Data Science to investment management

Curriculum End of Chapter Questions

Quantitative Methods

Course Content

About Instructor

Olawale Keshinro

Course Includes