What Will I Learn
When you are done with this course, you will be able to:

Curriculum
Time Value of Money
 Interpret interest rates as required rates of return, discount rates or opportunity costs
 Calculate and interpret the effective annual rate, given the stated annual interest rate and the frequency of compounding
 Solve time value of money problems for different frequencies of compounding
 Calculate and interpret the future value (FV) and present value (PV) of a single sum of money, an ordinary annuity, an annuity due, a perpetuity (PV only) and a series of unequal cash flows
 Use of a time line in modelling and solving time value of money problems
Discounted Cash Flows (DCF)
 Calculate and interpret the net present value (NPV) and the internal rate of return (IRR) of an investment
 Contrast the NVP rule to the IRR and identify problems associated with the IRR rule
 Calculate and interpret a holding period return (total return)
 Calculate and compare the moneyweighted and timeweighted rates of return of a portfolio based on these measure
 Calculate and interpret the bank discount yield, holding period yield, effective annual yield and money market yield for US Treasury bills and other money market instruments
 Convert among holding period yields, money market yields, effective annual yields and bond equivalent yields
Statistical Concepts and Market Returns
 Descriptive statistics and inferential statistics, between a population sample and among the types of measurement scales
 Define a parameter, a sample statistic and a frequency distribution
 Relative and cumulative relative frequencies and their calculation
 Properties of a data set presented as a histogram or a frequency polygon
 Measures of central tendency including the population mean, sample mean, arithmetic mean, weighted average or mean, geometric mean, harmonic mean, median and mode
 Quartiles, quintiles, deciles and percentiles
 Calculate and interpret a range and a mean absolute deviation and the variance and standard deviation of the mean using Chebyshev’s inequality
 Calculate and interpret the coefficient of variation and the Sharpe ratio
 Skewness and the meaning of a positively or negatively skewed return distribution
 The relative locations of the mean, median and mode for a unimodal, nonsymmetrical distribution
 Measures of sample skewness and kurtosis
 Use of arithmetic and geometric means when analyzing investment returns
Probability Concepts
 Random variable, an outcome, an event, mutually exclusive and exhaustive events
 Properties of probability and empirical subjective and priori probabilities
 Probability of an event in terms of odd for and against the event
 Unconditional and conditional probabilities
 Multiplication, addition and total probability rules
 Calculate and interpret joint probability of two events, the probability that at least one of the two events will occur given the probability of each and the joint probability of two events, joint probability of any number of independent events
 Unconditional probability using total probability rule
 Use of conditional expectation in investment application
 Use of a tree diagram to represent an investment problem
 Covariance and correlation
 Calculate and interpret an updated probability using Bayes’ formula
 Factorial, combination and permutation concepts
Common Probability Distributors I
 Probability distribution
 Discrete and continuous random variables and their probability function
 Cumulative distribution function
 Discrete uniform random variable, a Bernoulli random variable and binomial random variable
 Calculate and interpret probabilities given the discrete uniform and the binomial distribution functions
 Construction of a binomial tree to describe stock price movement
 Continuous uniform distribution and its calculation
Common Probability Distributors II
 Normal distribution
 Univariate and multivariate
 The role of correlation in multivariate normal distribution
 Standard normal distribution and its calculation and how to standardize a random variable
 Shortfall, calculate the safetyfirst ratio and select an optimal portfolio using Roy’s safetyfirst criterion
 Normal and lognormal distribution
 Discretely and continuously compounded rates of return
 Monte Carlo simulation and historical simulation
Sampling and Estimation I
 Simple random sampling and a sampling distribution
 Sampling error
 Distinguish between simple random and stratified random sampling
 Time series and crosssectional data
 Central limit theorem
 Calculate and interpret the standard error of the mean sample
Sampling and Estimation II
 Learn the desirable properties of an estimator
 A point estimate and a confidence interval estimate of a population parameter
 Describe properties of students tdistribution and calculate and interpret its degrees of freedom
 Calculate and interpret a confidence interval for a population mean, given a normal distribution
 Calculate and interpret covariance given a joint probability function
 Calculate and interpret an updated probability using bayes’ formula; identify the most appropriate method to solve a particular counting problem and solve counting problems using factorial, combination, and permutation concepts.
A known population
An unknown population variance
An unknown population variance and a large sample size
The issues regarding selection of the appropriate sample size, datamining bias, sample selection bias, lookahead bias and timeperiod bias
Hypothesis Testing
 Define hypothesis, the steps of hypothesis testing
 Null and alternative hypothesis
 Onetailed and twotailed tests of hypothesis
 A test statistic, Type I and Type II errors, a significance level and its uses in a hypothesis
 A decision rule, the power of a test and the relation between confidence intervals and hypothesis tests
 A statistical result and an economically meaningful result
 Explain and interpret the pvalue as it relates to hypothesis testing
 Identify the appropriate test statistic and interpret the results for a hypothesis test concerning the population mean of large and small samples when the population is normally or approximately normally distributed and the variance is
Known
Unknown  Identify the appropriate test statistic and interpret the results for a hypothesis test concerning the mean difference of two normally distributed population
 Parametric and nonparametric tests and describe the situations in which the uses of nonparametric tests may be appropriate
Technical Analysis
 Principles of technical analysis, its application and its underlying assumptions
 Construction of different types of technical analysis charts and interpret them
 Uses of trend, support, resistance lines and changes in polarity
 Common chart patterns
 Common technical analysis indicators
 Explain how technical analysts use cycles
 The key tenets of Elliot Wave Theory and the importance of Fibonacci numbers
 Intermarket analysis as it relates to technical analysis and asset allocation
 Elliot Wave Theory
How It works
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