Q:
# How do you calculate the expected return on market?

Forecasting the rate of return of instruments with prices determined on open markets is difficult. It is not possible to calculate future returns or losses precisely.

Continue ReadingAccording to New York University Stern School of Business, as of 2014, the U.S. stock market returned an average of about 10 percent a year since the beginning of the 20th century.

The Motley Fool covers the concept of the stock market average that was conceived by Charles Dow in the late-19th century with his creation of the Dow Jones Industrial Average. Its calculation has been changed several times. The companies included in it are monitored closely, and replacements are routinely made. Average market returns in the United States are usually measured by the Dow Jones Industrial Average or the Standard & Poor's 500 Index.

There are many different methods for forecasting future market returns. Some individuals and organizations have devoted their entire lives in pursuit of perfecting these methods. According to Investopedia, some of the best widely accepted market forecasters include Warren Buffett, Peter Lynch, George Soros, William O'Neil and John Bogle.

A great deal of literature follows different participants in financial markets and their use of different methods for attempting to forecast future returns, which include fundamental analysis, technical analysis and quantitative analysis. Zacks explains that fundamental analysis is concerned with understanding the financial strength of a company, industry or economy, its profitability, its growth prospects, its competitive position, and how the market values it. The Chadwick Research Blog explains that technical analysis is the study of the relation between price, volume, time, the profile of a market and the details of its participants. Quantitative analysis combines elements of both fundamental and technical analysis and sometimes incorporates data from other sets, such as weather and news events, and it analyzes them using rigorous, computerized and often proprietary methods.

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