This is my seventh annual forecast of the S&P 500 Index return for the year. It is based on the simple linear regression model. The model uses Gross Domestic Product (GDP) as explanatory variable to the performance of the S&P 500 Index. The model predicts the S&P 500 Index to closed between 2,891 and 2,906 at the end of the year 2019. This represents the return between 15.36% and 15.96% for the year 2019. If my forecast is correct, the year 2019 should be a very good year for investors.
During the last six years, the model had proven to predict a general direction of the stock market performance. Projections by the model and actual stock market performance track each other (see Chart 1).
First, let’s look at the year 2018 and measure up my forecast to the actual stock market performance. The model may provide a general understanding whether the stock market is overprices or inexpensive. The model does not guarantee or precisely predicts the outcome. It correctly projected up and down markets five out of six years (see table 1). The year 2018 was the year when the model failed to predict a negative stock market performance. The forecast was for a positive 3.2% stock market return in 2018 vs. the actual stock market decline of 6.2%. Despite a significant margin of error, the model does give a general feel for the value of the stock market. It does track the performance of the stock market.
Failure to predict the stock market decline of 2018 can be explained by a volatile and steep sell off at the end of the year. The stock market declined sharply by more than 9% in December 2018 and became oversold. The stock market had a nice recovery since then. The S&P500 index increased by 7.8% in January 2019 (Yahoo! Finance).
The forecast model may provide the basis to evaluate the stock market and to determine if it is oversold or underbought. There is also a wide margin of error. The expected performance for the S&P 500 Index may have a wide deviation from the actual index each year.
Now, let’s forecast where the S&P 500 Index will close one year from now, on December 31, 2019.
Based on the statistical analysis and the process described further in this article, I expect the S&P 500 Index to close between 2891 and 2906 at the end of 2019. Based on this range, the midpoint for the S&P 500 Index is predicted to be at 2,898 on December 31, 2019. That is a potential annual upside of 15.6% from the close price of 2,506.85 on December 31, 2018.
This prognosis is based on expected Gross Domestic Product (GDP) of the United States in nominal terms, current USD terms. First, I will take a look at the most recent GDP number. It will be the base from which I calculate the expected nominal GDP. According to the Bureau of Economic Analysis, the current dollar GDP was $19,485.4 billion for the year 2017 (January 26, 2018). Due to government shutdown in 2019, no new data is available for GDP. I will assume the GDP has increased by 6.9% for the year 2018 to $20,752.00 billion in current US dollars.
According to the economic projections of Federal Reserve Bank Board Members and Federal Reserve Bank Presidents made in December 2018, the real GDP is expected to increase between 2.3% and 2.5%, and Personal Consumption Expenditure – between 2.0% and 2.1% for the year 2019. As a result, the nominal GDP estimated to rise between 4.3% and 4.6% in 2019.
By multiplying the estimated current dollar GDP for 2018 by expected nominal change for the year, I calculate the GDP for the year 2019 to be between $21,644.28 and $21,706.54 billion. Now I can forecast where the S&P 500 Index will close at the end of 2018.
I am using the Excel spreadsheet to run a linear regression model where the S&P 500 is a dependent variable, and GDP is the independent variable. Based on the last 13 years of annual data, I forecast the S&P 500 Index to close between 2,891 and 2,905 at the end of 2019 (see table 2).
Limitations to the forecast:
Based on my prior research, the GDP alone can only explain between 67%-89% of the performance in the S&P 500 Index (see my prior articles on http://www.ecnfin.com). The remaining 11%-33% is not influenced by the GDP growth. There might be other factors that are difficult to predict; such as, geopolitical risk, rise in inflation, and black swan events that nobody expects.
By using a smaller sample of data, I am able to focus on the current economic environment. This may not prevent the forecast error because the model does not incorporate information from historical economic cycles.
Forecast of the future S&P 500 Index is based on historical data and future expectations that may not be correct. This paper was written as an opinion only. The data is not guaranteed to be accurate or complete. Please consult with your financial advisor before making an investment decision.
ECNFIN.com is not associated with nor does it necessarily represent the opinion or advice of Culver Investment Company LLC. Past performance doesn’t guarantee future results.
Bureau of Economic Analysis (January 26, 2018). https://www.bea.gov/newsreleases/national/gdp/gdpnewsrelease.htm
The Federal Reserve Bank (December 18-19, 2018) https://www.federalreserve.gov/monetarypolicy/files/fomcprojtabl20181219.pdf
U.S. Department of Commerce. Bureau of Economic Analysis. Gross Domestic Product data was retrieved from http://www.bea.gov
Yahoo! Finance. S&P 500 Price Data was retrieved from http://finance.yahoo.com