Click on each image below for a selection of SP500 constituent stock forecasts and a table of factors for each forecast. The factor table includes the top 4 variables for each forecast. Variable names can be looked up on quandl.com if you want to analyze in more detail what is driving each projection model. Next week I plan to release a new 'Macro' panel of forecasts that includes projections for gold, silver, the SP500, FTSE, DAX, Nikkei, oil, interest rates, and the USD index. Stay tuned ...

July 2016 - 12 Month S&P 500 Forecast

Below is the latest (simple) using only Federal Reserve macroeconomic indices and commodity futures data. The general forecast trend is similar to February's forecast (see previous post below) though the overall S&P level is 10%-15% higher. After approaching 2300 in September, weakness is projected to emerge as we get closer to the election and should continue until the end of the year. The S&P 500 is projected to continue to increase due to monetary policy and favorable sentiment phenomena, despite global macro and political risks gaining momentum.

The major factors include (cross validation error is ~11%, with an R squared of 95%):

*Real M2 Money Supply (increasing, momentum slowing)

*M1 Money Supply - 15 month rate of change (slowly increasing though trajectory is uncertain)

*Manufacturing Employment (declining)

*Appreciation/Depreciation of Commercial Bank Debt Securities (still increasing)

Latest 12 Month Sector ETF Forecasts

Below are the latest sector ETF forecasts for March 2016 through March of 2017. Each forecast was generated with a unique set of independent factors and relies on fundamental economic data. Utilities and Industrials are expected to remain weak over the next year though Materials and Financials may provide outperforming returns. Forecasts for XLK and XLE are still in development and could be significantly revised when new projections are updated in April/May. Backtested results are still forthcoming though preliminary tests suggest that relying on these forecasts (starting in 2011) would have been a very profitable strategy, and in some cases would have generated 2x-3x+ returns over a buy and hold strategy.

Latest SP500 Forecast

Below is the latest 12 month S&P 500 Forecast (as per 2/21/2016). The same type of modeling approach (as was used for the Dow constituents) was also utilized here. The basic outlook is that the S&P will rally until the summer and experience extended weakness as we near election season and the end of the fourth quarter. Key inputs to this forecast include the slope of the yield curve, trends in industrial production, market sentiment, and a selection of employment indices. Most of the indicator factors have correlations with leading 12 month returns that exceed 60%. The mean absolute error of the system of models is ~5.8%, as the average of cross-validation (7-fold) errors.

Forecasts, Selected Dow 30 Constituents

Below is the first entry in a likely long enduring series of security specific forecasts that I will be generating for the Dow constituents and ultimately for all S&P 500 candidates. The underlying forecasts were generated using a proprietary series of algorithms built in R that, through a series of cross validation tests, select an optimal array of factors that feed into a number of final models (multiple regression, neural network, logistic regression, etc). 7 cross validation 'folds' were used and a final hold out sample was utilized to confirm and backtest results. In future posts I will publish the results of the backtest model and provide context on the top 5 factors that feed into each forecast model. Each forecast is generally based on 15 indicators that all vary from security to security.

As you can see, some Dow constituents are projected to increase over the next year though there are a few outliers. Specifically, energy company share prices should improve as market sentiment shifts and banking stocks the same as investors react to the new interest rate/money supply paradigm.

Simply click the image below to see specific detail on the constituent forecasts. If you would like the underlying data feel free to message me or run the image through an OCR converter...