Since the US Presidential election, the S&P 500 has been range-bound, as investors digest the news of tariffs, inflation, and what the Fed may do next.
However, Tech and AI stocks may be in the beginning innings of a move higher, potentially setting up for a breakout of the S&P 500 to new all-time highs.
In this week’s video, I discuss the charts I am watching and the emerging opportunity in tech names.
Since early December, the S&P 500 has been range-bound, accompanied by a weakness in market breadth. The number of stocks trading above their respective 50-day and 200-day moving averages continues to decline, indicating underlying weakness in the stock market.
The chart below shows a sideways pattern in the S&P 500, as well as a downward trend in the number of stocks trading above their 50-day and 200-day moving averages:
One of my favorite tools, which I use daily, is Relative Rotation Graphs (RRG). They allow us to view the rotation of the stock market and allows us to see which areas have increasing momentum and rising relative strength.
Typically, I focus on weekly RRG charts since the timeframe in my investment models is weeks to months instead of hours to days.
If you are unfamiliar with RRGs, please check out this post: “How to Use Relative Rotation Graphs for Selecting the Best Sectors”.
Looking back to the beginning of December, the RRG shows the beginning of this sideways trading range:
The above chart shows us the slowing and rotation of the major indices, which I like to track. The trend for the major US indices is starting the initial stages of rotation into the lower right-hand, weakening quadrant.
Fast forward to today, the RRG is showing the continued rotation towards the lagging quadrant:
I tend to look for opportunities when sectors/stocks are in the lagging quadrant and have begun to rotate in an NW direction towards the upper right, leading quadrant.
Currently, the majority of the indices are not there yet, indicating more hesitation among investors. However, taking a look at the daily version of the above RRG charts, we can see similar weakness as the majority of sectors are in the weakening quadrant:
As the sectors within the daily relative rotation graph rotate into the lagging, then improving quadrant, we may begin to see an opportunity in the weekly RRG chart indicating an end to the sideways trading pattern and a resumption of the upward trend of the S&P 500 index.
John Rothe, CMT
2/10/2025
In my years of working in finance, one thing has become abundantly clear: human emotions and cognitive biases play a significant role in financial decision-making. Traditional financial theories often assume investors act rationally, but my experience tells a different story.
Behavioral finance, an interdisciplinary field that combines insights from psychology, sociology, and traditional finance, offers a more nuanced understanding of how individuals and markets behave.
I’ve seen firsthand how acknowledging these psychological factors can lead to better investment outcomes. In this article, I’ll share what I’ve learned about behavioral finance, its historical development, and its implications for investors. By understanding the psychological underpinnings of financial decisions, we can all strive to make more informed and rational choices.
Behavioral finance delves into how psychological factors influence financial decisions and, by extension, financial markets. It challenges the traditional notion that markets are always efficient and that investors always act rationally. From my perspective, this field has been a game-changer in understanding why people often make irrational financial choices.
Key concepts in behavioral finance include cognitive biases, heuristics, and prospect theory. These ideas help explain why we sometimes deviate from what traditional economic theories would predict.
For instance, cognitive biases are systematic errors in thinking that can lead to poor decision-making. Heuristics are mental shortcuts we use to make decisions quickly, which can sometimes lead us astray. Prospect theory, developed by Daniel Kahneman and Amos Tversky, describes how we make decisions under risk and uncertainty, often in ways that defy logic.
The journey of behavioral finance began in the mid-20th century and gained momentum in the 1970s and 1980s. It’s fascinating to see how the field has evolved over the years.
In the early days, pioneers like Herbert Simon and Daniel Ellsberg laid the groundwork. Simon introduced “bounded rationality” in 1955, suggesting that our decision-making is limited by the information we have, our cognitive capabilities, and time constraints. Ellsberg’s paradox, presented in 1960, showed that people often prefer known risks over unknown ones, even if the known risk is less favorable.
The 1970s were a turning point. Daniel Kahneman and Amos Tversky’s 1974 paper introduced cognitive biases in decision-making, and their 1979 Prospect Theory challenged the Expected Utility Theory.
The 1980s and 1990s saw figures like Richard Thaler and Robert Shiller questioning the Efficient Market Hypothesis and providing evidence of market inefficiencies due to investor psychology.
From the 2000s to the present, behavioral finance has gained mainstream acceptance, with Nobel Prizes awarded to Kahneman in 2002 and Thaler in 2017. Today, behavioral finance influences policy-making, investment strategies, and financial product design.
source: thetechincaltraders.com
Cognitive biases are systematic errors in thinking that can lead to poor decision-making. Some common ones in investing include:
Heuristics are mental shortcuts we use to make decisions quickly. While useful sometimes, they can lead to errors. Examples include:
Prospect Theory, developed by Kahneman and Tversky, describes how we make decisions under risk and uncertainty. Key aspects include:
Reference Point: Evaluating gains and losses relative to a reference point.
Loss Aversion: Feeling losses more strongly than equivalent gains.
Diminishing Sensitivity: The impact of gains or losses diminishes as their magnitude increases.
Behavioral finance helps explain various market anomalies that traditional finance theories struggle to account for, such as:
Understanding behavioral finance can have significant implications for investors:
Recognizing cognitive biases and emotional influences can help investors make more rational decisions.
For example, being aware of confirmation bias can encourage seeking diverse perspectives and challenging one’s own assumptions.
Insights from behavioral finance can help investors better understand and manage risk. Recognizing loss aversion can help avoid panic selling during market downturns.
Behavioral tendencies can inform portfolio construction strategies. For instance, using dollar-cost averaging can mitigate the impact of market timing biases.
Behavioral finance suggests that markets may not always be efficient, creating opportunities for skilled investors to exploit mispricings.
Insights from behavioral finance have led to new financial products and services, like robo-advisors that help automate investment decisions and reduce emotional biases.
Behavioral finance has influenced policy-making, leading to initiatives like automatic enrollment in retirement savings plans to overcome inertia and procrastination biases.
The dot-com bubble of the late 1990s and early 2000s offers a compelling example of behavioral finance principles in action. During this period, investors exhibited several cognitive biases:
The result was a massive bubble in technology stocks, followed by a painful crash. This episode highlights the importance of understanding and managing behavioral biases in investing.
Behavioral finance has revolutionized our understanding of financial markets and decision-making. By acknowledging the role of psychology in financial behavior, it provides a more nuanced and realistic view of how individuals and markets operate.
For investors, the insights from behavioral finance offer valuable tools for improving decision-making, managing risk, and potentially achieving better investment outcomes.
However, it’s important to note that while behavioral finance provides valuable insights, it doesn’t offer a perfect solution to all investment challenges.
Markets are complex systems influenced by numerous factors, and human behavior is just one piece of the puzzle. Nonetheless, by incorporating behavioral finance principles into their investment approach, investors can potentially make more informed decisions and avoid common pitfalls.
As the field continues to evolve, it promises to yield further insights that can help investors navigate the complexities of financial markets. By staying informed about behavioral finance research and applying its principles, investors can strive to become more rational, disciplined, and successful in their financial endeavors.
Stagflation refers to the rare combination of high inflation, slow economic growth, and high unemployment. In a typical business cycle, inflation rises during periods of strong growth and falls during recessions when unemployment spikes. But in the 1970s, the U.S. experienced the worst of both worlds – soaring prices coupled with a stagnant economy and rising joblessness.
The unemployment rate significantly rose during the mid 1970’s:
While inflation data rapidly rose as well:
Several factors fueled the stagflationary environment:
– Excessive government spending on the Vietnam War and social programs
– Easy monetary policy and the end of the gold standard in 1971
– Oil price shocks in 1973 and 1979 engineered by OPEC
– Declining productivity growth
Inflation peaked at over 14% in 1980. The unemployment rate reached nearly 11% in the 1981-82 recession. And real GDP growth averaged a meager 3.2% for the decade, well below the 4.3% pace of the 1960s.
Overall, the 1970s was a lost decade for stock investors. The S&P 500 eked out nominal gains of just 17% for the 10-year period, far below the rate of inflation. In real (inflation-adjusted) terms, the S&P 500 lost nearly 50% of its value during the 1970s.
The Dow Jones Industrial Average opened the decade at 809 and closed 1979 at just 839, almost no gain. Steep bear markets in 1973-74 and 1977 took a heavy toll. Corporate earnings grew at a 9% annual clip in the 70s, but the price-to-earnings multiple investors were willing to pay for those profits was cut in half by the end of the decade.
However, some sectors and investment classes did manage to outperform in the stagflationary environment:
Energy Stocks
With oil prices spiking over 1000% from $3 per barrel to $40 during the decade, energy was by far the best-performing stock market sector. Oil & gas companies saw earnings soar. Exxon, for example, grew profits at a 17% annual rate in the 1970s.
Exxon 1970-1979. Source: Macrotrends
Precious Metals and Mining
Gold was the single best-performing asset class of the 1970s, rising from $35 an ounce to over $800, a 2200% gain. Silver and other precious metals also posted huge returns as investors sought inflation hedges.
The Price of Gold Soared During the 1970s. Source: Macrotrends
Gold mining stocks posted huge returns during this time. Companies involved in gold, silver, and copper extraction saw their valuations rise dramatically.
Real Estate
Real estate investment trusts (REITs) and direct property ownership provided a partial inflation hedge, with rental prices and property values rising along with the general price level. Farmland values rose at a 14% annual rate. Residential real estate was more of a mixed bag, with some regions like California seeing huge gains while others stagnated under rent controls.
Commodities
Besides precious metals, a wide range of commodities posted big gains in the 1970s:
– Oil prices rose over 1000%
– Agricultural goods like wheat, corn and soybeans more than tripled
– Lumber prices increased fivefold
– Copper and other industrial metals also saw large gains[
Value Stocks & Defensive Sectors
Source: JPMorgan
Among equities, cheaper-value stocks outperformed higher-priced growth stocks. Defensive sectors like consumer staples, healthcare, and utilities held up better than economically-sensitive areas like autos, steel, and housing. Blue-chip dividend payers were favored for their income in an era of paltry stock market gains.
Consumer staples stocks like General Foods (which later became Kraft and then Mondelez and Kraft Heinz) held up better than the broader market. Defensive sectors like consumer staples, healthcare and utilities outperformed as investors favored companies with pricing power that could maintain profit margins even with high inflation
While commodities and hard assets thrived, financial assets broadly struggled during the stagflationary 70s:
Bonds
Fixed income investors suffered as rising interest rates caused bond prices to plummet. 10-year Treasury yields soared from around 6% in 1970 to over 15% by 1981 as the Federal Reserve belatedly raised rates to combat inflation. In 1979 alone, long-term government bonds lost 8.6%.
Growth Stocks
High-flying growth stocks sporting lofty price-to-earnings ratios were hit hard as soaring inflation and interest rates compressed valuations. The “Nifty Fifty” group of premier growth stocks like Xerox, IBM, and Polaroid that had led the bull market of the 1960s plunged during the 1973-74 bear market. Many former darlings saw their stock prices cut 60-90%.
Sectors that struggled during this time included:
Autos, Housing and Consumer Discretionary
Source: Fred, Riverbend Investment Management
Economically-sensitive sectors were among the worst hit in the stagflationary environment. Auto sales slumped as rising gas prices and interest rates made vehicles unaffordable for many households. Housing starts fell nearly 50% from 1972-1982 as mortgage rates climbed to 18%. Consumer discretionary stocks broadly underperformed as stagflation curtailed household spending.
While no two periods of history ever perfectly rhyme, the stagflationary 1970s offer some important takeaways for investors confronting high inflation and slowing growth today:
1. Diversify beyond stocks and bonds. Equities and fixed income both struggled during the 1970s. Exposure to real assets like commodities, real estate, and precious metals provided an important bulwark.
2. Emphasize value and quality. Richly-valued growth stocks are vulnerable to valuation compression as inflation and interest rates rise. Cheaper value stocks and high-quality blue chips tend to fare better.
3. Tilt toward inflation beneficiaries. Sectors with direct exposure to rising commodity prices (energy, mining, agriculture) or that demonstrate strong pricing power (consumer staples, healthcare) have outperformed during stagflationary periods.
4. Tactical investment strategies may provide opportunities during flat, yet volatile market cycles.
While the future is always uncertain, the historical experience of the 1970s provides a useful roadmap for navigating the potentially stagflationary environment ahead.
Sources:
[1] https://www.schroders.com/en-us/us/individual/insights/how-does-stagflation-impact-investment-returns/
[2] https://www.fool.com/terms/s/stagflation/
[3] https://www.investopedia.com/terms/s/stagflation.asp
[4] https://www.winvesta.in/blog/what-happens-to-the-markets-during-stagflation
[5] https://www.forbes.com/advisor/investing/stagflation/
[6] https://www.investopedia.com/articles/economics/08/1970-stagflation.asp
[7] https://www.investopedia.com/articles/economics/08/stagflation.asp
[8] https://www.reddit.com/r/investing/comments/tdvcb2/stagflation_in_the_1970s_stagflation_in_the_in/
[9] https://willowdaleequity.com/blog/what-assets-do-well-in-stagflation/
[10] https://finance.yahoo.com/news/stagflation-definition-10-best-stagflation-183011442.html
[11] https://finance.yahoo.com/news/stagflation-definition-11-best-stagflation-174922577.html
[12] https://www.gsam.com/content/gsam/us/en/institutions/market-insights/gsam-connect/2022/what-investors-can-do-stagflation-risk.html
[13] https://www.kiplinger.com/investing/economy/want-to-beat-stagflation-invest-like-its-the-1970s
[14] https://www.schroders.com/en-ch/ch/professional/insights/inflation-back-to-the-1970s/
[15] https://www.schiffsovereign.com/trends/what-worked-and-didnt-work-during-1970s-stagflation-27738/
[16] https://www.marketwatch.com/story/stock-market-investors-should-still-brace-for-70s-style-stagflation-warn-strategists-39dc3675
[17] https://www.kiplinger.com/investing/stocks/604318/5-superb-stocks-to-shield-against-stagflation
[18] https://www.dbresearch.com/PROD/RPS_EN-PROD/PROD0000000000523476/Investing_during_Stagflation:_What_happened_in_the.pdf
Volatility is a crucial concept that every investor needs to know, as it measures the degree of variation in the price of a security over time. Understanding and managing volatility is essential to minimize risk and optimize portfolios.
Volatility, as measured by the VIX (Volatility Index), can provide insights into market sentiment. Changes in volatility can serve as warning signs for potential trend reversals in individual stocks as well. Indicators, like the Average True Range (ATR) and Wilder’s Volatility Stop Loss, can help identify significant changes in volatility that may signal a shift a change in trend and help limit portfolio losses.
The VIX, often referred to as the “fear index,” is a widely used measure of market volatility. It is calculated based on the implied volatility of S&P 500 index options and provides a gauge of expected market volatility over the next 30 days.
When the VIX rises, it indicates increased fear and uncertainty among market participants, often coinciding with market downturns or periods of heightened risk aversion. During times of market stress, such as economic crises, geopolitical events, or unexpected news, the VIX tends to spike, reflecting the elevated levels of fear and uncertainty in the market.
For example, during the 2008 financial crisis, the VIX reached an all-time high of 89.53 on October 24, 2008, as investors grappled with the collapse of major financial institutions and the ensuing market turmoil.
Investors can use the VIX as a tool to assess the overall market sentiment and adjust their risk management strategies accordingly. When the VIX is rising, it may be prudent to adopt a more defensive approach, such as reducing exposure to risky assets or implementing hedging strategies to protect against potential market downturns.
While the VIX provides a broad measure of market volatility, changes in volatility at the individual stock level can also offer valuable insights. A sudden increase in volatility can often precede a trend reversal, particularly when the stock has been in a prolonged upward trend.
One way to measure volatility at the stock level is through the use of the Average True Range (ATR) indicator. ATR measures the average range between the high and low prices of a stock over a specified period, typically 14 days.
Source: Investopedia
A significant increase in ATR, such as a reading that is two to three times the standard deviation or greater, can indicate a heightened level of volatility and potentially signal an impending trend reversal.
For example, let’s consider the case of XYZ stock, which has been in a steady uptrend for several months. If the ATR suddenly spikes to a level that is three times its average value, it could be a warning sign that the upward momentum is losing steam and a reversal may be on the horizon. Investors holding XYZ stock may want to consider tightening their stop-loss orders or reducing their position size to manage risk in case of a potential trend reversal.
Another useful tool for identifying changes in volatility is Wilder’s Volatility Stop Loss. Developed by J. Welles Wilder, this indicator calculates a stop-loss level based on the ATR and a multiplier. When the stock price closes below the Wilder’s Volatility Stop Loss level, it suggests that the upward trend may be losing momentum and a reversal could be imminent.
To illustrate the use of Wilder’s Volatility Stop Loss, let’s revisit the example of XYZ stock. Suppose the current price of XYZ is $100, and the ATR is $2. Using a multiplier of 3, the Wilder’s Volatility Stop Loss would be calculated as follows:
Wilder’s Volatility Stop Loss = Current Price – (ATR * Multiplier)
= $100 – ($2 * 3)
= $94
If XYZ stock closes below $94, it would trigger a sell signal based on Wilder’s Volatility Stop Loss, indicating that the upward trend may be coming to an end and it’s time to exit the position or implement risk management strategies.
By monitoring changes in volatility, both at the market level through the VIX and at the individual stock level using indicators like ATR and Wilder’s Volatility Stop Loss, investors can enhance their risk management strategies. When volatility rises significantly, it may be prudent to take the following actions:
Real-World Examples:
Volatility is a critical factor to consider when managing risk in the stock market. By understanding how the VIX reflects market fear and how changes in volatility at the individual stock level can signal potential trend reversals, investors can make more informed decisions and adjust their risk management strategies accordingly.
Utilizing indicators like ATR and Wilder’s Volatility Stop Loss can help identify significant changes in volatility that may warrant action, such as tightening stop losses, reducing position sizes, diversifying holdings, or implementing hedging strategies.
Real-world examples, such as the market volatility during the COVID-19 pandemic and the case of Tesla stock, demonstrate the importance of monitoring volatility and adapting risk management strategies accordingly. By incorporating volatility analysis into their investment approach, investors can navigate market uncertainties with greater confidence and potentially enhance their overall risk-adjusted returns.
1. Wilder, W. (1978). New Concepts in Technical Trading Systems. Trend Research.
2. “VIX – CBOE Volatility Index.” CBOE, https://www.cboe.com/tradable_products/vix/.
3. “Understanding the VIX: What It Is, How It Works.” Investopedia, https://www.investopedia.com/terms/v/vix.asp.
4. “VIX Historical Price Data.” Yahoo Finance, https://finance.yahoo.com/quote/%5EVIX/history?p=%5EVIX.
5. “Average True Range (ATR).” Investopedia, https://www.investopedia.com/terms/a/atr.asp.
6. “VIX Surges to Record High as Stocks Plunge Amid Global Recession Fears.” CNBC, https://www.cnbc.com/2020/03/16/vix-surges-to-record-high-as-stocks-plunge-amid-global-recession-fears.html.
7. “Tesla, Inc. (TSLA) Stock Historical Volatility.” Macroaxis, https://www.macroaxis.com/volatility/TSLA/Tesla.
8. “Tesla, Inc. (TSLA) Stock Historical Prices & Data.” Yahoo Finance, https://finance.yahoo.com/quote/TSLA/history?p=TSLA.
9) “Wilder Volatility Stop” https://www.optuma.com/kb/optuma/tools/volatility/wilder-volatility-stop
Featured Image: Image by macro vector on Freepik
John Rothe CMT is the Founder and Chief Investment Officer of Riverbend Investment Management
