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This Is What The Stock Market Is Saying About Trump’s Re-Election

ElectionOracle / US Presidential Election 2020 Oct 10, 2020 - 03:56 PM GMT

By: Avi_Gilburt

ElectionOracle

While reading of the title of this article may cause you to make certain assumptions about what you are about to read, I can assure you that this is not a politically motivated article. In fact, politics has absolutely nothing to do with the analysis and conclusions presented herein.

I want to start with the assumption that we have spoken about so often, and that it is social mood which directs our actions in life, including our willingness to buy stocks. As Robert Prechter noted in a study he published in 2012 on this topic, “[s]ocionomic theory proposes that unconscious social mood regulates social actions.”


The basic premise is that when people feel good they engage in positive actions, and vice versa. But, that really is an oversimplistic perspective of the theory. Ultimately, it suggests that biological responses have more to do with the mass sentiment as compared to exogenous events. Rather, exogenous events are actually caused by the mass sentiment of the public. Moreover, it suggests that mass sentiment directs our stock market in addition to causing exogenous events. Therefore, viewed from this perspective, the common understanding of causation for market direction is completely opposite of that which most believe. And, this premise is supported by many studies performed over the last 30 years.

I think it is best summed up within a paper entitled “Large Financial Crashes,” published in 1997 in Physica A., a publication of the European Physical Society:

“Stock markets are fascinating structures with analogies to what is arguably the most complex dynamical system found in natural sciences, i.e., the human mind. Instead of the usual interpretation of the Efficient Market Hypothesis in which traders extract and incorporate consciously (by their action) all information contained in market prices, we propose that the market as a whole can exhibit an “emergent” behavior not shared by any of its constituents. In other words, we have in mind the process of the emergence of intelligent behavior at a macroscopic scale that individuals at the microscopic scales have no idea of. This process has been discussed in biology for instance in the animal populations such as ant colonies or in connection with the emergence of consciousness.”

Moving back to the relationship between the stock market and the election, in his study, Robert Prechter used the stock market as a gauge of the public’s social mood to determine if there was some causality between social mood and an incumbent’s re-election prospects. Within the study, they utilized data going back to 1792, and performed testing using various factors. The goal was to determine the effect of social mood upon an incumbent’s re-election potential.

As Mr. Prechter noted in his conclusions:

“We found that the stock market is significant predictor of election results in all cases. As surmised, the best result was the 3-year period prior to the election. One of our landslide tests obtained a perfect score.”

Moreover, they even compared their results to the results they would achieve if focusing on other economic variable such as GDP, unemployment, inflation, etc. Yet, they concluded that “[w]e found that the stock market outperformed every one of the economic variables.”

In sum, Mr. Precther concluded:

“We believe our study helps demonstrate that aggregate voting at the margin—swing voters—are not so much rationally weighing the potential value of each candidate but rather voting primarily based on how they feel. When a positive trend in social mood induces investors to push the stock market upward during the three years prior to an incumbent’s re-election bid, it also induces voters to credit the incumbent for their good moods and vote to retain him in office. When a negative trend in social mood induces investors to push the stock market downward during the three years prior to an incumbent’s re-election bid, it also induces voters to blame the incumbent for their bad moods and vote to reject him from office.”

In the period beginning three years prior to the 2020 election (November 2017), the stock market was within the 2550SPX region, and has risen more than 20% higher since. Therefore, if the market maintains these levels or higher into the election, it is likely that Trump would win by a landslide, based upon Prechter’s historical analysis.

Currently, I view the support for the SPX within the 3250/3300SPX region. As long as that support holds, I see the potential for a rally back up to the 3450-3500SPX region. Should that support break in the coming weeks, then we will likely see a test of the 3050SPX region. However, even that is 20% above the level at which we found ourselves 3 years prior to the 2020 election.

So, I will be watching the market over the coming weeks to gain a bit more insight as to whom the winner will be in the next election for President of the United States of America.

Avi Gilburt is a widely followed Elliott Wave analyst and founder of ElliottWaveTrader.net, a live trading room featuring his analysis on the S&P 500, precious metals, oil & USD, plus a team of analysts covering a range of other markets. He recently founded FATRADER.com, a live forum featuring some of the top fundamental analysts online today to showcase research and elevate discussion for traders & investors interested in fundamental rather than technical analysis.

© 2020 Copyright Avi Gilburt - All Rights Reserved Disclaimer: The above is a matter of opinion provided for general information purposes only and is not intended as investment advice. Information and analysis above are derived from sources and utilising methods believed to be reliable, but we cannot accept responsibility for any losses you may incur as a result of this analysis. Individuals should consult with their personal financial advisors.


© 2005-2022 http://www.MarketOracle.co.uk - The Market Oracle is a FREE Daily Financial Markets Analysis & Forecasting online publication.


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