Skip to 0 minutes and 18 seconds It’s true that single risky events cannot be predicted with certainty. So we can’t predict the return on any individual financial asset, such as a stock or a bond. However, when we have a large number of events, individual uncertainties can partly offset each other. And sometimes we may be able to make some fairly accurate predictions on the aggregate. For instance, demographers can make quite precise predictions about the rate of growth of large populations on the basis of the average birth rates and death rates. Although we cannot know who is going to be born and who is going to die, we can still make accurate predictions for the population as a whole.
Skip to 1 minute and 5 seconds We take a similar statistical approach to the management of risk, based on the law of large numbers in statistics.
Skip to 1 minute and 17 seconds The most important implication for finance of a statistical approach to risk management is that it becomes possible to reduce risk effectively by forming a portfolio of diversified assets. In essence, this is simply applying the rule of not putting all your eggs in one basket. If you carefully diversify your investment, you can significantly reduce risk without sacrificing return. In general, when you implement strategies that reduce your risk, you are hedging. Diversification can be a very effective hedging tool. There are circumstances, however, when an investor may decide to increase their risk. This is what is known as speculation.
Skip to 2 minutes and 3 seconds You can sometimes take out insurance against an adverse event. There are also a number of financial instruments that can be used to reduce your risk. For instance, financial derivatives - futures and options - enable you to take an offsetting position in an asset you own when they are available. We’ll study futures and options in week 3 of the course.
How can risk be managed?
Risk is about unpredictable events: how can it possibly be managed?
In this short video, Prof Pasquale Scaramozzino explores how applying a statistical approach to risk management can significantly reduce risk without sacrificing return.