
Interest Rate Fundamentals
Describes the major interest rate quoting conventions, Nominal rate, EAR and continuously compounded rates and how they compare and contrast.
Consolidates the content in the previous video with a work through of a number of exercises that show practical applications of how they are used.
. Defines, compares and contrasts simple and compound interest with examples of the effect of compound interest on returns.
Defines the meaning of a discrete return with calculations of percentage returns for a holding period and on an annualised basis.
A ground up explanation of what is meant by continuous compounding with calculations that apply the concept.
Looks at how to calculate inflation adjusted returns over a multiple time horizon.
Starting with first principles, explaining the concept of time value of money and the process of compounding and discounting, using a single cash flow as an example.
Extends on the previous video to incorporate multiple cash flows occurring at different times and compares two investments by calculating the present values of their future cash flows.
Introduces the concept of Net Present Value (NPV) and the Internal Rate of Return (IRR), with worked examples.
Valuation involves discounting cash flows that occur in the future. However, we cannot be certain that our expected cash flows are accurate. This video explores ways in which we can account for the uncertainty.
An example of the practical application of time value of money principles as part of the valuation process.
An example of using time value of money as one step in valuing a property investment.
When calculating present and future values we need to input the correct numbers into the equations. This video presents those numbers.
Money markets involve single period compounding and discounting for periods of less than or equal to one year. We introduce the concept of day count conventions and accruals so that the inputs into our formula are accurate.
Explains what discount factors are and how they are used in calculating present values. If you work in interest rate based markets, it is essential to be familiar with the concept.
In this video we calculate and apply discount factors to arrive at the present value of a single cash flow occurring within the next one year. If you work in interest rate based markets, it is essential to be familiar with the concept.
This brief re-cap covers the three major measures of central tendency, mean mode and median and looks at which one is the most appropriate measure to apply to an analysis of data.
The most popular measure of central tendency, but, not necessarily the most appropriate. Here we look at some of the issues involved in their use.
In financial markets we often need to measure returns over time. For example, what is the average annual profit over five years? The arithmetic average is likely to give an inaccurate figure, so here we explain the geometric mean and how to calculate it.
A run through of range, variance and standard deviation, including bottom up calculations of variance and standard deviations.
A step by step explanation of probability distributions, with this first video introducing the concept and explaining some of the terminology. We use the example of throwing a pair of dice to show how to construct the associated probability distribution.
Following on from the understanding of a probability distribution, this video takes it a step further and covers the cumulative distribution function, the process of adding individual probabilities. We show how to use the cdf to ascertain probabilities of various outcomes in a simple and effective manner
Builds a historic distribution from scratch using a set of financial market data
Describes the major characteristics of the ubiquitous normal distribution, explains why there an infinite number of them and some situations where they might not be appropriate to use in financial markets.
A step by step appreciation of the features of a lognormal distribution, why it is used in financial markets and explores its basic characteristics by comparing it to a normal distribution.
A step by step appreciation of the features of a lognormal distribution, why it is used in financial markets and explores its basic characteristics by comparing it to a normal distribution.
There are an infinite number of normal distributions. They can all be ‘standardised’ into one standard normal curve. This video looks at the standard normal curve, explains z-scores and introduces the spreadsheet functions that allow us to work with them.
Standard deviation, volatility and risk are essentially the same thing. Here we define the convention of how volatility is quoted and explain the four different types of volatility terms that are commonly referenced in the markets.
Two simple examples of volatility in action in the world of risk management and options.
A detailed look at the methodologies that allow us to convert an annual volatility to a period volatility and vice versa.
Shows how to construct a Simple (Arithmetic) moving average along with a brief explanation of how they are used by financial market participants.
An in depth view of exponentially weighted moving averages with a step by step illustration of how to construct them.
The first look at how the movement in the price, or return, of one asset is reflected in the movement of the price or return of another asset. Do they tend to move in the same direction or in opposite directions? Covariance is one measure and we calculate covariance from first principles.
One of the most popular measures of the link between price changes or returns of two assets. The video explains how to calculate correlation and what interpretation we can put on the correlation number.
If the S&P500 market index goes moves by 1.00%, by how much do we expect the price of any individual share to move by? Linear regression attempts to address that question. This section looks at the methodology behind constructing the regression line.
A step by step explanation of how to construct the regression line. In financial markets, the slope of the regression line is referred to as beta. We take a first look at the meaning and interpretation of beta.
When we use beta in our analysis, we need to take care. Here’s why.
When we use beta in our analysis, we need to take care. Here’s why.
There is no getting around the fact that working in financial markets comes with the need to have some understanding of maths, if you really want to make a success of it.
The ability to collect, organise, evaluate and analyse data is the key to understanding the value of assets and their associated risk. Armed with this ability, we can make rational decisions... not just financial ones, but, those that affect many other aspects of our lives.
it doesn't matter whether you work in, sales and trading, asset management, risk, personal investing, corporate finance, or which product you deal with, bonds, equities, derivatives or commodities; the same techniques are common to all.
And here's the good news. Contrary to popular belief, the maths is not that difficult!
In 4.50 hours and 8 modules, the course covers the maths needed to get you started on your journey.
The course videos are short, subject matter is broken down into digestible parts, all the terminology and methodology is explained with examples using clearly set out spreadsheets.
Module 1 Interest Rates
We've all heard the term. But, what's the difference between a Nominal rate, Simple rate, Effective rate, continuously compounded rate and period rate? This module looks at each of these, compares and contrasts them, and defines the convention used when we see an interest rate quote.
Module 2 Calculating Returns
Calculating the returns on investments can be done in a number of ways; for the period that we held it or, more usually, on an annual basis, or on an inflation adjusted basis (real return). Furthermore, they can be calculated on a discrete or continuously compounded basis.
We look at these various ways, with explanations and examples of how to calculate them.
Module 3 Time Value of Money
This one is the real deal. Time Value of Money is one of the most important concepts in business and finance. Its principles are at the heart of understanding value and therefore, making rational investment decisions. It provides clarity to most of the what is going on in the financial world.
And the best thing about it is that it's not that hard to understand.
Module 4 Measures of Central Tendency and Dispersion
This one is a recap of the statistics you probably did at school. We look at measures of central tendency, mean, mode and median as well as measures of dispersion such as range and standard deviation (the first introduction to the concept of risk).
Module 5 Probability Distributions
How often had you heard someone say 'equity markets are too high, they're going to crash', or 'We expect equities to provide a 10% return in the coming year.' Rarely will there be a mention of the chances of either of those happening, or not.
Probability distributions allow us to quantify the chances of an expected outcome.
There are numerous types of distributions. Here we look at two of the most common ones, normal distributions and lognormal distributions.
Module 6 Volatility
Risk and return are two of the things we need to consider when investing. When we invest we expect a return, but, we also have to accept the risk of things not working out as expected.
Risk is one of the key metrics in evaluating investments. To achieve high returns we usually have to take on high risk, Conversely, if you are risk averse, then you cannot usually expect a high return As they say, 'There is no such thing as a free lunch.'
Volatility is a proxy for risk. Here we look at the different types of volatility and how volatility is measured and calculated.
Module 7 Moving Averages
Should we buy or should we sell?
Moving averages are a way of smoothing price changes over time and potentially allow for the identification of trends.
The construction and uses of Simple and Exponentially weighted moving averages are explained here.
Module 8 Relationships Between Assets
When constructing a portfolio, hedging against adverse price movements or establishing a trading strategy with two or more securities, an analysis of whether securities move in the same direction or not, is essential.
This is where covariance, correlation, regression and beta come into play.
Asset managers try to construct portfolios that provide the maximum expected return for the lowest level of risk. Some hedge funds pursue long/short strategies.
All involve the use of the simple statistical techniques above.
This module describes them, shows how to do the calculations as well as highlighting some of the pitfalls of using them.