Signed in as:
filler@godaddy.com
Our two-plus month forecasts indicate naturally occurring shifts in sentiment that create tailwinds and headwinds for the markets. Shifts occur periodically and are described as changes between:
We also identify periods of irrational exuberance and strong animal spirits. A shift between naturally occurring optimism and pessimism often acts as an exogenous catalyst for a change when there is an economic need for a price change.
To build these forecasts, we exploit variables related to those described in the Federal Reserve Bank of Atlanta's 2003 working paper "Playing the Field." This paper and other independent research indicate that solar energy variation affects human mood. Our physics-based drivers are objective measures of forces that cause solar energy variation.
Our research suggests that the impact of the physics-based drivers on the emotions of investors has been stable over many decades. Using these drivers, our forecasts indicate potential shifts in investor sentiment several months out.
Physics-based drivers:
In an ideal world, the movement of the stock market would be determined by economic and fundamental factors alone – solar energy variation would have no impact. Yet, we have found that natural shifts in optimism resulting from changes in solar energy have a greater impact than is commonly recognized (example below).
We believe that the total sentiment affecting the stock market at any given time consists of investor views on economic and fundamental conditions, current events, as well as these naturally occurring shifts. Investment professionals will make more effective decisions if they recognize and adjust for the naturally occurring shifts in sentiment.
Our research is described in this Institutional Investor article. Additional background is found in this LinkedIn article.
Data Products for Investment Professionals
We will also engage in consulting projects to transfer our tools and algorithms to a client's quantitative team, accelerating the development of their own physics-based investment tools.
The figure below shows a conservative example of our physics-based sentiment forecasts. It shows the S&P 500 (brown line, log scale) from December 2000 through April 2024. It shows the actual 14-week Relative Strength Index, a widely used momentum measure, and our predicted 14-week RSI.
The actual 14-week RSI is at the bottom of the figure (solid green, normalized). The predicted 14-week RSI is shown in the middle (dashed green, normalized).
For this example, we selected six out of our approximately two-dozen physics-based drivers that individually are significant in explaining the variability of the actual 14-week RSI over the period from 1940 through late 2000. We then blended those drivers together to determine the single mix (weights of the drivers) that tracked most closely the actual 14-week RSI over the same period. The predicted series shown above is based on those same drivers and weights for the following 20+ years (out-of-sample period) without change.
A regression analysis of the out-of-sample period indicates that the explanatory power (r-squared) of the physics-based drivers is over 70%. This means that over 70% of the variation in the actual 14-week RSI is explained by the physics-based drivers and less than 30% is explained by other influences.
One can see in the figure above that the peaks and troughs of the actual 14-week RSI are reasonably highlighted by the predicted series, as are distinct multi-month patterns (e.g., 2016 and 2017). This example demonstrates the stability and regularity of the physical processes we use to create our sentiment forecasts.
Regarding interpretation, one can infer that deviation between the actual and predicted RSI indicates periods when economics, fundamentals, and current events had a large impact on the market. Those real-world effects during periods such as early in the Global Financial Crisis (2007 to 2009), are more apparent after adjusting for the naturally occurring shifts in sentiment as seen in the figure above.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.