In a previous article, I outlined both the purpose and construction of the Simple Stock Model. Keep reading for a quick run down if you're new to the model, otherwise you can skip down to "Technicals" for the updated data.
Investors are constantly exposed to sound bites and data points presented without any proper context. You might have read an article about how stocks have historically bounced when sentiment has reached a negative extreme. Or that you should be out of the market if it's trading below its 200-day moving average.
When I come across articles like that, I always thought it was shortsighted to base an opinion on the S&P on only one indicator without also considering a wide variety of other inputs.
The goal of the model is to help you form a data-based outlook on the S&P. Additionally, at the end of this article, I showcase a composite model that incorporates all of the indicators I use, so your view can be comprehensive, as opposed to having tunnel vision on only one indicator.
How the Model Works
Each article is broken down into four main sections: technicals, sentiment, rates, and macro. Each section includes a number of different indicators. For each indicator, there's a "filter rule" for when to be out of the market. In the spirit of simplicity, the filter rule is always binary, dictating either 100% long exposure to the S&P or a 100% cash position. The S&P is represented by the SPDR S&P 500 Trust ETF (NYSEARCA:SPY). Let's dive into an example graph.
All graphs can be found on my website, simplestockmodel.com. The website is completely free and I solely use Seeking Alpha to publish longer form weekly recaps.
The above data is from Yahoo Finance. The graph shows the price momentum indicator within the technicals section. The bottom portion plots the momentum metric over time, and the top portion plots the historical performance of following the filter rule.
For each indicator, new data each weekend is used to generate a long SPY or cash position for the next week. For the above momentum example, SPY's dividend-adjusted close as of Friday is the main input. Using this, I calculate the 12-month total return. For each indicator on this site (except for the macro data), I take a 4-week average of the main indicator input.
So for this example, I'm taking the 4-week average of 12-month total return momentum. Why four weeks? To reduce false positives and whipsaws when an indicator is bouncing slightly above or below its filter rule. There's nothing special about a 4-week average. You could use two or eight weeks and reach similar results.
Data is compiled as of Friday's close. Buying or selling decisions occur on Monday's close. I do this, as opposed to making trades at Monday's open, simply because I had a more reliable data source for dividend-adjusted close data. It's also important to reflect realistic transaction costs. Each historical performance graph factors in a $10 trade commission and a 0.02% spread on SPY for each buy or sell. Commissions and spreads are lower now, but considering SPY started in 1993, I chose to use these above-average numbers.
Now you understand the methodology behind the model. Each week, I'll cover a handful of indicators, especially those that have changed positioning over the past week. Let's get started with some technicals.
Wednesday's FOMC meeting is the big event of the week. Historically, stock prices have tended to rise more often than average in the days leading up to a FOMC meeting. Since 1993, being long during this period has beaten the returns of a buy & hold strategy while only being invested in the S&P 2/3 of the time. Data is from Yahoo Finance.
We just entered the corporate buyback blackout period for Q3 earnings announcements. As a percentage of total NYSE volume, corporate buybacks have increased over the past few years. Most companies suspend both insider transactions, and share repurchases during the five weeks leading up to their quarterly earnings announcements. Data is from Yahoo Finance.
A weekly sentiment survey has been conducted by the American Association of Individual Investors for decades. The AAII asks participants if they are bullish, neutral, or bearish on stocks over the next six months. Survey results are typically used as contrarian indicators, meaning extreme bullishness is perceived as bearish and vice-versa.
There are a number of ways to analyze AAII data, and I choose to use the spread between the percentage of bulls and percentage of bears (as opposed to just looking at bulls or bears in isolation). As of now, the spread is negative, meaning there are more bears than bulls. Data is from the AAII.
The NAAIM Exposure Index measures how bullish or bearish active investment managers are on the S&P. Currently, the index is very high, meaning active managers are extremely bullish. Last week did see a slight drop in the index as active managers got scared by a 2.5% drop on Friday, September 9. Data is from the National Association of Active Investment Managers.
The difference between the interest rate of a high yield (NYSEARCA:HYG) bond and a Treasury of comparable maturity is called a high yield spread. The narrower the spread, the more optimistic investors are about the probability of risky U.S. corporations being able to cover their interest payments and eventually pay off their debts.
When investors grow more uncertain, they will demand a higher rate on high yield bonds and cause spreads to widen. Currently, high yield spreads are below their 12-month average. Data is from the St. Louis Federal Reserve Economic Database.
Last week, industrial production data disappointed by missing expectations. Industrial production measures the total value of output for all manufacturing, mining, and electric, and gas utility facilities located in the United States. It's a leading economic indicator and is a good way to quickly gauge how the manufacturing portion of the U.S. economy is doing. As of now, industrial production is negative YoY; historically, a bad sign. Data is from the St. Louis Federal Reserve Economic Database.
We also got new data on retail sales last week. Like industrial production, it also missed economist expectations. Retail sales reflect the total value of sales at the retail level. It's a primary measure of consumer spending, which accounts for the majority of economic activity in the U.S. Data is from the St. Louis Federal Reserve Economic Database.
The unemployment rate is the percentage of the total work force that is unemployed and actively seeking employment during the previous month. It is a lagging economic indicator, but a persistently rising unemployment rate indicates a weak labor market and thus potentially weak consumer spending. The current unemployment rate of 4.9% is below its 12-month average of 5.0%. Data is from the St. Louis Federal Reserve Economic Database.
That wraps up the weekly update on some of the individual indicators. Now for the composite model.
Think of each indicator as a building block that helps form an overall opinion. One study might say current sentiment has historically been bullish for stocks. Who cares, that's just one data point in isolation. I'm interested in a bigger-picture view with more context. A picture that also factors in what's going on with macro data, interest rates, etc. The composite model does just that.
Here's how it works: Each indicator is given a score of 1 or 0 depending on its current reading relative to its filter rule. If S&P earnings are down over the past year and the filter rule for that metric is to be out of the market if yearly earnings growth is below 0%, then that indicator gets a 0. The table below summarizes data from all the previous sections and assigns a 1 or 0 to each indicator based on its current reading.
For each category of indicators (technicals, macro, etc.), an average is calculated. Currently, the average score for technicals is 0.6. All four category average scores are then averaged to form the composite score. If the composite score is greater than 0.6, the model is invested in SPY. Think of 0.6 as the overall filter rule for the composite model.
There's nothing special about 0.6 - it results in being invested in SPY about 2/3rd of the time. I could have used a higher filter rule like 0.75 to only be exposed to the S&P when more indicators are saying to be invested, but this results in less time exposed to the market, since it's a "stricter" cut-off. The charts below plot each individual category average score and the overall composite score.
So where do we stand? Technical data is a mixed bag, since on one hand, the market has positive momentum and we're within positive FOMC drift period, but on the other hand, it's a seasonally weak time of year and the buyback blackout period just started.
Some sentiment measures like the NAAIM Exposure Index reflect excess optimism. High yield spreads are below their long-term average. Finally, the macro picture is mixed, with weak manufacturing sector data contrasted by healthy conditions in the labor market.
Overall, the composite model is still invested, since the composite score is 0.73, above the cut-off filter of 0.60. I hope this article can help you out in your own investing endeavors. Do let me know if you've got any questions in the comments below!
Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Additional disclosure: The information in this article is for personal use only. Investing involves a great deal of risk, including the loss of all or a portion of your investment. Nothing in this article should be construed as investment advice or as a warranty of investment results. All risks, losses and costs associated with investing, including total loss of principal, are your responsibility.
Editor's Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.