Lecture_7-_Diversification_-_Portfolio_Theory

Lecture_7-_Diversification_-_Portfolio_Theory - Money...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Money Markets and Finance Lecture 7 Diversification: Portfolio Theory 1. Lecture Overview During this lecture, we will discuss the concepts of portfolio theory and diversification . Diversification allows an individual to reduce the risk of their investment without sacrificing any expected return simply by spreading their wealth over a portfolio comprising a number of assets in an appropriate way. During the course of the lecture we will discuss: What diversification is; How including multiple assets in a portfolio can achieve diversification; Which assets to include in order to achieve the greatest level of diversification; and, How to construct a diversified portfolio in practice. 2. Review of Statistics Before we start discussing portfolio theory and the concept of diversification, we will briefly review the statistical terms discussed last lecture. These terms are important to understand as they are central to portfolio theory. More specifically, we will revisit the definitions of: Random variables; Expected values; and, Standard deviation and variance. 2. Review of Statistics Random Variables: A random variable is one that can take on any number of different values. Each value has an associated probability of occurring. The uncertainty associated with the outcome of a random variable is described by a probability distribution, with the most commonly used distribution being the normal distribution , see below:-7 5-6 5-5 5-4 5-3 5-2 5-1 5-5 5 1 5 2 5 3 5 4 5 5 5 6 5 7 5 0.020 0.018 0.016 0.014 0.012 0.010 0.008 0.006 0.004 0.002 0.000 P ro b a b ility d e n s ity Stock market return 2. Review of Statistics Expected Values: The value we expect a random variable ( X ) to take is known as its expected value or mean. Standard Deviation: Standard deviation, , is a measure of spread. It is based on how far each value of X varies from the mean. A small standard deviation means that the data doesnt vary a lot from the mean. A large standard deviation means that the data is more spread out. Variance: The variance, 2 , is simply the standard deviation squared. 3. Diversification Recall from last week the assumption that investors are risk averse and therefore prefer less risk to more. Diversification provides a means of reducing risk faced by investors without sacrificing expected return by combining assets that dont move perfectly together in a portfolio. Note that the ideas we are about to discuss can be extended to consider more than 2 assets. You will consider these extensions in FINM3001 Investments. 3.1 Measuring How Assets Move Together Correlation and Covariance: The covariance between variables X and Y , XY , is a measure of association between the two variables. For example, we may be interested in whether there is an association between the return on a companys stock and the return on the stock market in general: If the market always went up at the same time companys stock went up, the covariance would be positive;...
View Full Document

This note was uploaded on 10/13/2011 for the course FINM 1001 taught by Professor Miss during the Three '10 term at Australian National University.

Page1 / 5

Lecture_7-_Diversification_-_Portfolio_Theory - Money...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online