I wish I had put more money into this stock. I should have trusted my technical analysis. I need to trust my broker. My gut feeling told me I should have cut my losses. Aren't these all statements that we have heard individuals involved in stock markets say at some point?

With a stock price, you can instantly see the impact of getting forecast right or wrong. It pays to be right. But if it were so simple, anyone could forecast the closing price of a blue-chip share and make millions. Maybe if it were so simple, there wouldn't be anything to distinguish investors, and the returns for everyone investing would be smaller, as the winning prize would be split across millions of investors. The ability to make the right call on investment decisions is what differentiates successful and unsuccessful investors and brokers.

In this chapter, we will look at statistical methodologies for forecasting stock prices. Is the financial world only interested in forecasting the price of one stock, or a basket of stocks? Are statistical models supposed to behave independently of the other intricacies of the decision process about where to invest? To answer these questions, we will explore:

• Portfolio forecasting
• Decisions involved in managing portfolios
• The forecasting process
• Visualizations of time series data
• Modeling techniques to solve a business problem
• Evaluating techniques to select the best solution