Financial assets' market values are volatile. As evidence, review the news reports for the days after Britain's June 2016 Brexit vote or the US elections later that year. Prices for bonds, currencies, stocks, and other assets swung dramatically, frequently lower at first, followed by subsequent sharp rallies for some asset classes. But it doesn't take a historic political decision or other significant event to move prices sharply. If you follow the price of a stock like Apple or Facebook over the course of a few weeks, you're likely to find high levels of intraday volatility and a wide range between the stocks' high and low prices over the period, even in the absence of major news developments.
This chapter reviews how you can use MATLAB® to measure and forecast uncertainty and include that analysis in your work. The methods covered include descriptive measures that consider past results (mean, standard deviation, etc.) and forecasting methods like simulations that attempt to predict future values.
There are two important points about uncertainty and risk to keep in mind. First, most investors hold more than one asset in their portfolios. Consequently, in the financial markets we usually view risk from a portfolio perspective, not just for a single asset. What matters is how an asset's inclusion and performance affects the risk and return of the overall portfolio, unless that asset comprises the entire portfolio.