The Predictive Power of Investor Sentiment

Be fearful when others are greedy and greedy when others are fearful. This classic Buffett quote has echoed through the ranks of investors for decades. But does the data support the methodology? Does investor sentiment, which for many investors is widely considered a contrarian indicator, have enough predictive power to warrant our time and attention?

Considering Unreliability when Consulting the Data on Investor Sentiment.

• The best source of objective data on investor sentiment is the weekly AAII survey. They ask member investors about their expectations for the market each week.
• While these surveys are ostensibly trustworthy, what investors say and do often don’t correlate. So, the data they gather has to be taken with a grain of salt.

The Methodology of the AAII Survey.

• AAII researched sentiment behavior and subsequent market returns: Is the AAII Survey a Contrarian Indicator?
• They looked at the instances where bullish or bearish sentiment was extreme and measured it in levels of standard deviations. For example, they asked whether bearish/bullish sentiment was one, two, or three standard deviations below its average. Then they calculated those extreme readings relative to the subsequent 26-week and 52-week performance in the S&P 500 to see if the sentiment was a contrarian indicator.
• Metrics other than the S&P 500, such as bonds or gold, could have been used to make the study more exhaustive, but weren’t.

Takeaways from the AAII Survey.

• High bullish sentiment is not a great contrarian indicator.
• In the 44 periods where bullish sentiment was more than two standard deviations above average, they found that in the following six months, the S&P was only up 48% of the time, which is well within the standard range or error. Even with extreme levels of bullish sentiment, half of the time the market was up, and half of the time, it was down.
• Low bullish sentiment works better as a contrarian signal.
• Bullish sentiment has been below two standard deviations of its historical mean 16 times during the survey’s history. Low bullish sentiment led to an average six-month gain for the S&P was about 14%, which is a more interesting takeaway.
• High bearish sentiment generally leads to market bottoms.
• High bearish sentiment was followed by the S&P rising by a median of 5.6% during the following 26 weeks. High bearish sentiment led to rising stocks 66.3% of the time, according to this study. That is significant enough to say that super-high levels of pessimism generally leads to market bottoms. When people are overly fearful and let their emotions really get the best of them – terrible headlines, huge news stories, panic selling – it’s probably a good time to jump in and start nibbling!
• When stocks and markets reverse, it doesn’t have to come from a peak in sentiment.
• In the 2008 July 3rd – July 17th period, right before the market started to crash that summer, the bullish sentiment was unusually low (23%, 22%, 25%).
• People are generally bullish until markets go down, then they’re bearish.
• People don’t flip flop between bullish and bearish each month. If people are bullish and then the markets go up, they remain bullish until some outside force causes them to change their sentiment.
• If people are really bearish on the market, we could be seeing a bottoming process happen in the next six months. The research would say that 66.3% of the time, the market bottomed in the next six months.

Why TD Ameritrade IMX Research Might be More Trustworthy.

• The IMX is TD Ameritrade’s ‘Investor Movement Index’.
• This research helps get a sense of what people are doing with their money, versus what they say they’re going to do with their money. What TD Ameritrade does with the IMX is take all of the data that they have on client accounts and look at what people are actually doing with their money.

Evidence of Contrarian Indicators According to TD Ameritrade IMX Research.

• According to the last three or so years of the IMX charts, periods where the IMX was really high lines up in many cases with market tops, or at least periods in which the market stalls.
  

• December 2017 was one of the highest readings on their metrics, and the market completely stalled for about a year. The next highest reading was September of 2018, right before the market went through a huge drawdown heading into Christmas. Another one happened right at the beginning of 2020, where the indicators started to rise from September 2019 through January 2020. This time the thing that pricked the bubble was coronavirus.
• Therefore, this research potentially reveals what could have been good contrarian indicators.
• The same thing happens in reverse. When you look at IMX, where people have really low levels of activity, this often leads to periods where markets start to bottom.

Takeaways from the AAII and IMX Research.

• Things need to be taken with a grain of salt. But, you generally get an ebb and flow, where when things get overbought, they get oversold.
• This doesn’t mean things will turn on a dime. It’s a process, but it tells you where you are generally in the process, so you can keep your head on a swivel.

Research Study from the Federal Reserve Bank of San Francisco.

• Research Methodology:
• The Federal Reserve Bank of San Francisco went through research on investor sentiment and consumer sentiment and momentum combined to see if any of those two things could potentially predict market returns in the S&P.
• This is a very short period for predicting, but it is what it is. The research can be found here: Using Sentiment and Momentum to Predict Stock Returns
• The Value of Combining Metrics in Research and Investing.
• When you look at metrics independently of one another, they’re not that great. When you start combining them, i.e., sentiment plus momentum, and combining indicators and technicals, or methodologies, that’s where a lot of power lies.
• This applies to trading as well as far as the idea of correlation. A combination of investment strategies or technical indicators together in a portfolio oftentimes leads to the best results.
• Findings:
• When you look at the predictive power of sentiment alone, it is pretty useless.

• The same thing is true of momentum in that one-month period.

• Sentiment and momentum combined created a more robust predictor of one-month returns in the market.

• They found that when periods saw sentiment declining over the past year, and the market recently went through a decline, this was predictive that the next month would be a decline.

Today’s Main Takeaway:

• Sentiment shifts over time, and it is these broad shifts, not pinpoints of vertical sentiment spikes, that create tops and bottoms in markets.
• Overly optimistic/pessimistic investors, consumers, attitudes, and characteristics are usually typical of market tops and bottoms. But, they don’t create new stock prices to change direction all the time.
• Be cautious when you see these spikes. But, don’t say, “Yes, everyone’s pessimistic. It’s going to be a bottom,” or, “Yes, everyone’s really optimistic, it’s going to be a market top.”
• There’s definitely pockets of predictability in sentiment extremes. Still, it’s not enough to say that all the time at this one level, or that one level, it’s going to cause the market to completely reverse.
• Investor sentiment is something you should keep an eye on, but it’s not something you need to religiously check every week.

Option Trader Q&A w/ Lasan

Trader Q&A is our favorite segment of the show because we get to hear from one of our community members and help answer their questions live on the air. Today’s question comes from Lasan:

Hey, Kirk. This is Lasan. I have been listening to your podcasts and they’re really helpful. I have a really important question for you. One of the strategies that I use and I use it and it’s one of the best is selling the strangles and straddles. The issue with them is that our downside is like – and the potential of losing is unlimited. I wanted to know how the allocation works in here because you said that we should allocate the maximum risk and the maximum loss amount to 1% to 5% of the portfolio. But on the strangle, we don’t have any maximum loss. How does this work? Please explain. Thank you.

Remember, if you’d like to get your question answered here on the podcast or LIVE on Facebook & Periscope, head over to OptionAlpha.com/ASK and click the big red record button in the middle of the screen and leave me a private voicemail. There’s no software to download or install and it’s incredibly easy.