Looking back at the 1970’s: Which Areas of the Stock Market Did Well Under Stagflation

Looking back at the 1970’s: Which Areas of the Stock Market Did Well Under Stagflation

What is Stagflation?

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:

unemployment rate stagflation 1970-1980


While inflation data rapidly rose as well:

chart of inflation 1970s

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.

Stock Market Performance During Stagflation

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.Dow Jones Chart 1970s

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.

Chart of XOM during stagflationExxon 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.

chart of gold prices during stagflation

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.

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

Chart of value stocks during inflationSource: 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

Losers of the 1970s

While commodities and hard assets thrived, financial assets broadly struggled during the stagflationary 70s:


Chart of the 10 Year Treasury Bond 1970s
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%.Chart of IBM 1970s

Sectors that struggled during this time included:

  • Financials, as rising interest rates caused bond prices to plummet
  • Consumer discretionary stocks, as economically-sensitive areas like autos and housing were hit by the combination of high inflation and slow growth
  • Technology and growth stocks broadly underperformed as soaring inflation and interest rates compressed their rich valuations


Autos, Housing and Consumer Discretionary

Chart of Housing Data 1970sSource: 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.

Lessons for Today’s Investors

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.


[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

Using Volatility to Manage Risk in the Stock Market

Using Volatility to Manage Risk in the Stock Market

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.

VIX: A Barometer of Market Fear

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.

Chart of 2008 stock market volatility

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.

Volatility as a Warning Sign for Trend Reversals

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.

Incorporating Volatility to Improve 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:

  1. Tighten Stop Losses: As volatility increases, the likelihood of sharp price movements also rises. By adjusting stop-loss levels based on volatility indicators, investors can limit their potential losses and protect their capital. For example, if the ATR of a stock doubles, investors may consider moving their stop-loss orders closer to the current price to account for the increased volatility.
  2. Reduce Position Sizes: During periods of heightened volatility, it may be wise to reduce the size of individual positions to mitigate the impact of potential price swings on the overall portfolio. By allocating a smaller portion of the portfolio to each position, investors can limit their exposure to any single stock that may experience significant volatility.
  3. Diversify Holdings: Spreading investments across different sectors, asset classes, and geographies can help reduce the overall portfolio volatility and minimize the impact of any single stock or sector experiencing increased volatility. By maintaining a well-diversified portfolio, investors can potentially offset losses in one area with gains in another, thereby reducing the overall risk.
  4. Consider Hedging Strategies: Implementing hedging strategies, such as buying put options or using inverse ETFs, can provide downside protection during volatile market conditions. These strategies can help mitigate losses in the event of a market downturn or a significant decline in individual stock prices.

Real-World Examples:

  1. During the COVID-19 pandemic in 2020, the VIX reached a peak of 82.69 on March 16, 2020, as markets grappled with the economic fallout of the global health crisis. Investors who recognized the heightened volatility and adjusted their portfolios accordingly, such as by reducing exposure to risky assets or implementing hedging strategies, were better positioned to weather the market turbulence.
  2. In the case of Tesla (TSLA), its stock experienced a significant increase in late 2020, rising from around $132 in November to over $300 in January 2021. This surge in price preceded a sharp decline in the stock price, with TSLA dropping approximately 40%. Investors who used Wilder’s Voaltatilty Stop Loss could have used it as a warning sign of potential trend reversal and taken steps to manage their risk, such as tightening stop-loss orders or reducing their position size.

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

Understanding and Utilizing the Ulcer Index in Investment Strategies

Understanding and Utilizing the Ulcer Index in Investment Strategies

When constructing an investment model, risk management is a critical aspect of portfolio construction and performance evaluation.

While traditional measures like standard deviation and variance have been a favorite risk gauge by many investors, the Ulcer Index (UI) — a less conventional but highly insightful metric — offers a unique perspective by focusing specifically on downside risk.


How the Ulcer Index Works

Developed by Peter Martin and Byron McCann in the 1980s, the Ulcer Index quantifies the depth and duration of drawdowns in an investment’s value (Martin & McCann, 1989).

Unlike other risk measures that consider overall volatility, the Ulcer Index specifically focuses on the negative movements of an asset’s price.

To calculate the Ulcer Index, we must first identify the drawdowns, which are the peaks-to-trough declines in the investment’s value.

The Index then squares these percentage drawdowns and averages them over a specific period, and the square root of this average gives the Ulcer Index value.

Formula for Ulcer Index

  • Pricei is the price on day i
  • N is the length of time (measured in days)
  • maxprice is the most recent high
  • Ri is the drawdown from the previous high

A higher Ulcer Index indicates a security or portfolio that has experienced large and/or lengthy drawdowns, signaling higher downside risk.


The Ulcer Index in Action

Consider an investor comparing two exchange-traded funds (ETFs). Fund A has an Ulcer Index of 14.63, while Fund B has an Ulcer Index of 25.17.

Despite a lower Ulcer Index, Fund A has outperformed Fund B due to having smaller periods of decline compared to Fund B, indicating that Fund A could improve portfolio performance while reducing risk.

ulcer index chart comparison

Source: FastTrack


Benefits of Using the Ulcer Index in Portfolio Construction

1) Enhanced Risk Management: The Ulcer Index allows investors to quantify and manage the downside risk in their portfolios effectively. It is particularly useful in turbulent market conditions where traditional volatility measures might not fully capture the risk of significant losses.

2) Informed Asset Allocation: By using the Ulcer Index, investors can make more informed decisions about asset allocation. For instance, incorporating assets with lower Ulcer Index values can reduce the overall portfolio’s risk of substantial drawdowns.

3) Risk-Adjusted Performance Evaluation: The Ulcer Index complements other performance metrics like the Sharpe Ratio, providing a more comprehensive view of a portfolio’s risk-adjusted performance. It is especially beneficial for comparing investments with similar returns but differing risk profiles.

4) Alignment with Investor Risk Tolerance: The Ulcer Index can help align investment choices with an investor’s risk tolerance. Those particularly sensitive to losses may prefer investments with lower Ulcer Index values.

Academic Research on the Ulcer Index

the impact of reducing losses with the Ulcer Index

Managing risk can help improve overall portfolio performance

Academic research has provided valuable insights into the benefits of the Ulcer Index.

A study by Chekhlov, Uryasev, and Zabarankin (2005) emphasized the importance of focusing on downside risk and how the Ulcer Index could be a more representative tool for capturing this risk compared to standard deviation.

This aligns with the principles of behavioral finance, where investors are often more concerned about potential losses than equivalent gains (Kahneman & Tversky, 1979).

In portfolio optimization research, the Ulcer Index has been used as a constraint or objective to construct portfolios that not only have optimal returns, but also minimal potential for significant drawdowns (Post & Van Vliet, 2006).

This approach is particularly relevant in the construction of retirement portfolios, where preserving capital is often more critical than achieving high returns.


The Ulcer Index: An Important Tool in an Investor’s Toolbox

The Ulcer Index stands out as a specialized tool in the investor’s arsenal, particularly valuable for its focus on downside risk.

While not a standalone solution, it complements other risk and performance measures, offering a nuanced perspective on investment risk.

For investors and financial professionals alike, understanding and applying the Ulcer Index can lead to more robust portfolio construction and a better alignment with investment goals and risk tolerance.



  • Martin, P. & McCann, B. (1989). “The Investor’s Guide to Fidelity Funds”. Wiley.
  • Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). “Drawdown Measure in Portfolio Optimization”. International Journal of Theoretical and Applied Finance.
  • Kahneman, D., & Tversky, A. (1979). “Prospect Theory: An Analysis of Decision under Risk”. Econometrica.
  • Post, G. & Van Vliet, P. (2006). “Downside Risk and Empirical Asset Pricing”. Journal of Banking & Finance.
Is Gold a Good Hedge Against Inflation?

Is Gold a Good Hedge Against Inflation?

Is Gold a Good Hedge Against Inflation?

Gold has historically been viewed as a reliable store of value and a hedge against inflation. Throughout time, investors have turned to gold during economic upheavals, political unrest, and times of inflation. But how accurate is this belief? Is gold genuinely a good inflation hedge?

Understanding Inflation

Before discussing gold’s relationship with inflation, it’s essential to have a clear understanding of what inflation is.Is Gold a Good Hedge Against Inflation

At its core, inflation refers to the rate at which the general level of prices for goods and services rises, subsequently eroding purchasing power. Central banks, such as the Federal Reserve, aim to maintain inflation at a stable rate, believing it’s crucial for economic growth.

The Theoretical Case for Gold as an Inflation Hedge

Proponents argue that gold serves as a hedge against inflation due to:

Limited Supply: Unlike fiat currencies, which central banks can print in unlimited quantities, the supply of gold is relatively fixed. This inherent scarcity can provide protection against currency devaluation.

Historical Precedent: Gold has been a form of currency for centuries, suggesting it retains its value over long periods.

Tangible Asset: Unlike stocks or bonds, gold is a tangible asset. Physical gold doesn’t rely on a third party’s performance or promises, potentially offering security during uncertain economic times.

Is Gold a Good Hedge Against Inflation?

gold vs inflation

Let’s examine some specific periods when inflation spiked to see how gold performed:

1970s U.S. Inflation Crisis

The 1970s in the U.S. witnessed an alarming rate of inflation, peaking at over 13% in 1979 (Bureau of Labor Statistics, 2020).

During this decade, the price of gold skyrocketed from $35 per ounce in 1971 to $850 in 1980, not adjusted for inflation (World Gold Council, 2021). This represents a remarkable increase and provides a strong case for gold as an inflation hedge.

2008 Financial Crisis

Contrastingly, the 2008 financial crisis, although not strictly an inflationary period, was marked by expansive monetary policies and quantitative easing, leading to anticipated inflationary pressures. Gold, sensing these undercurrents, appreciated significantly, reinforcing its safe-haven status.

Hyperinflation in History

Hyperinflation periods provide extreme cases to assess gold’s protection. In the Weimar Republic’s hyperinflation in the 1920s, gold retained its value, while the German mark became worthless (Fergusson, A. 1975. When Money Dies). More recently, during Zimbabwe’s hyperinflation crisis in the late 2000s, gold also proved its worth as local currencies collapsed.

Academic Research on Gold and Inflation

Several academic studies have delved into the relationship between gold and inflation:

1) The World Gold Council (2011) found a positive correlation between gold and U.S. inflation, particularly during extreme inflationary environments. This correlation was stronger in the short term (less than a year) but weakened over longer periods (World Gold Council, 2011).

2) Baur and Lucey (2010) in their study titled “Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds, and Gold,” found that gold can act as both an inflation hedge and a safe haven in extreme market conditions, but its efficacy can vary depending on the time frame and geographical region (Baur, D.G., & Lucey, B.M., 2010).

gold prices during inflationSource: “Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds, and Gold”

3) Ghosh, Levin, Macmillan, and Wright (2004) in their research found a weak relationship between gold returns and inflation for the U.S. However, when the researchers expanded the study globally, gold demonstrated stronger inflation-hedging properties in countries like the UK and Japan (Ghosh, D., Levin, E.J., Macmillan, P., & Wright, R.E., 2004).

The price of gold vs inflationSource: “Gold as an Inflation Hedge”


While historical performance and some academic research support gold’s role as an inflation hedge, there are important considerations:

Holding Costs: Unlike stocks or bonds that might pay dividends or interest, gold has associated storage and insurance costs.

Volatility: Gold prices can be volatile, influenced by factors beyond just inflation, such as geopolitical events, interest rates, and global economic conditions.

No Universal Agreement: As seen in the academic studies, there isn’t a unanimous agreement on gold’s efficacy as an inflation hedge across all scenarios.


So, is gold a good hedge against inflation?

Gold has historically performed well during periods of high inflation, and many investors incorporate it into their portfolios for diversification and as a potential hedge against inflationary pressures.

However, its role as an inflation hedge isn’t unequivocal and may vary based on time frames, geographical regions, and specific economic conditions. Like all investments, due diligence, continuous research, and a well-considered strategy are crucial when considering gold in a portfolio.


John Rothe, CMT


Bureau of Labor Statistics. (2020). Consumer Price Index Data from 1913 to 2020.

World Gold Council. (2021). Gold Investor: Risk management and capital preservation.

Fergusson, A. (1975). When Money Dies. Kimble Mead.

World Gold Council. (2011). Gold as a strategic asset for UK investors.

Baur, D.G., & Lucey, B.M. (2010). Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds, and Gold. Journal of Banking & Finance, 34(8), 1886-1898.

Ghosh, D., Levin, E.J., Macmillan, P., & Wright, R.E. (2004). Gold as an Inflation Hedge? Studies in Economics and Finance, 22(1), 1-25.



The Alpha in Sector Rotation: A Research-Driven Approach

The Alpha in Sector Rotation: A Research-Driven Approach

The Alpha in Sector Rotation: A Research-Driven Approach


Sector rotation is an investment strategy that involves reallocating portfolio assets among various sectors of the economy to capitalize on cyclical trends. This approach aims to outperform the market by investing in sectors that are expected to thrive during different phases of the economic cycle.

Below I examine some of the different sector rotation strategies and the academic research supporting them.

Please note: This post is for informational purposes only and should not be considered as financial advice. Always consult with a qualified financial advisor before making any investment decisions.

Types of Sector Rotation Strategies


1. Economic Cycle-Based Rotation


economic cycles chart

Source: StockCharts.com

This strategy aligns investments with the traditional economic cycle, which consists of four stages: expansion, peak, contraction, and trough.

During the expansion phase, an investor might allocate 40% of their portfolio to technology stocks like Apple and Microsoft, expecting these companies to benefit from increased consumer spending.

Studies have shown that aligning investments with economic cycles can yield superior returns.

For instance, a research paper by Stangl, Jacobsen, and Visaltanachoti (2009) demonstrated that economic cycle-based rotation strategies outperformed the market by an average of 3-4% annually.


2. Momentum-Based Rotation

Momentum investing chart

Momentum strategies involve investing in sectors showing strong performance over a specific timeframe, usually three to twelve months, and rebalancing the portfolio periodically.

For example, if the healthcare sector has outperformed other sectors over the past six months, an investor using a momentum-based strategy would allocate a higher percentage of their portfolio to healthcare stocks like Pfizer and Johnson & Johnson.

Moskowitz and Grinblatt (1999) found that momentum-based sector rotation strategies generated significant abnormal returns, especially when transaction costs were low.


3. Seasonal Rotation

chart showing monthly history of walmart

Source: Optuma

Seasonal rotation takes advantage of recurring patterns that happen annually, such as increased retail spending during the holiday season.

An investor might increase their allocation to retail stocks like Walmart and Amazon from October to December, anticipating a seasonal boost in sales.

Jacobsen and Zhang (2012) provided empirical evidence supporting the profitability of seasonal rotation strategies, particularly in the retail and tourism sectors.


4. Event-Driven Rotation


Source: NY Times

This strategy focuses on rotating sectors based on specific events like elections, policy changes, or natural disasters.

If a new administration plans to invest heavily in renewable energy, an investor might shift their focus to renewable energy stocks like Tesla and NextEra Energy.

While academic research on event-driven sector rotation is relatively sparse, anecdotal evidence suggests that such strategies can yield significant returns during times of geopolitical or economic events.


5. Quantitative Rotation

chart of the utilities sector

Source: Koyfin

This strategy employs mathematical models to identify the best-performing sectors based on various metrics like price-to-earnings ratios, dividend yields, and market volatility.

A quantitative model might suggest investing in sectors with low P/E ratios and high dividend yields, such as utilities and consumer staples.

Quantitative models have been the subject of extensive academic scrutiny, with research indicating that they can be highly effective when used in conjunction with other strategies, such as momentum-based rotation.


In-Depth Analysis of Academic Research and Past Performance


1. “The Profitability of Sector Momentum Strategies” (Moskowitz and Grinblatt, 1999)

This seminal paper found that momentum-based sector rotation strategies generated significant abnormal returns.

The study analyzed data from 1965 to 1997 and concluded that a momentum strategy focusing on the past six to twelve months of sector performance could yield an average annual return of 4-6% above the market, especially when transaction costs were low.

The researchers used a comprehensive dataset that included 12 different sectors and employed robust statistical methods to arrive at their conclusions. They also considered the impact of transaction costs, which are often overlooked in academic research.

The paper concluded that the momentum effect was not only statistically significant but also economically significant, meaning that the returns were large enough to be meaningful to investors.


2. “Sector Rotation over Business-Cycles” (Stangl, Jacobsen, and Visaltanachoti, 2009)

This research paper demonstrated that economic cycle-based rotation strategies could outperform the market by an average of 3-4% annually. The study used data from 1970 to 2007 and found that the strategy was particularly effective during periods of economic expansion and contraction.

The study broke down the economic cycle into more granular phases, including early and late expansion, peak, early and late contraction, and trough.

This nuanced approach allowed the researchers to identify specific sectors that outperformed during each sub-phase, providing investors with a more detailed roadmap for sector rotation. The paper also controlled for various risk factors, ensuring that the excess returns were not a result of higher risk-taking.


3. “Seasonality in Stock Returns: Evidence from Fourteen Countries” (Jacobsen and Zhang, 2012)

This paper provided empirical evidence supporting the profitability of seasonal rotation strategies.

The study analyzed data from fourteen countries and found that sectors like retail and tourism consistently outperformed during specific seasons, yielding an average annual return of 5-7% above the market.

The researchers went beyond merely identifying seasonal patterns; they also explored the underlying factors driving these patterns.

For instance, they found that the seasonal performance of the retail sector was not just a result of increased consumer spending during the holidays but also influenced by factors like weather patterns and school vacations.

This multi-factor analysis adds depth to our understanding of seasonal rotation strategies.


4. “Quantitative Financial Analytics: The Path to Investment Profits” (Kenneth Grant, 2003)

Although not strictly focused on sector rotation, this book delves into the quantitative models that can be employed in such strategies.

The author discusses various metrics and mathematical models, including moving averages, Z-scores, and neural networks, that can be used to identify outperforming sectors.

The book is particularly useful for investors interested in a more mathematical approach to sector rotation. It provides practical examples and case studies, demonstrating how quantitative models have been successfully employed in real-world investment scenarios.


5. “Event-Driven Strategy: An Examination” (Journal of Portfolio Management, 2017)

This paper, although not specifically focused on sector rotation, provides valuable insights into how event-driven strategies can be employed effectively. It discusses various events, such as mergers, acquisitions, and policy changes, that can significantly impact sector performance.

The paper suggests that event-driven strategies can be particularly effective when combined with other types of sector rotation strategies.

For instance, an investor might use an economic cycle-based approach but make adjustments based on significant events, thereby potentially enhancing returns.


Sector rotation is a multifaceted investment strategy that offers the potential for superior returns when executed correctly.

Whether it’s aligning with the economic cycle, following momentum, capitalizing on seasonal trends, or reacting to specific events, each type of sector rotation strategy has its merits and drawbacks. Academic research supports the efficacy of these strategies, indicating that they can yield significant abnormal returns over the long term.



1. Moskowitz, T. J., & Grinblatt, M. (1999). “The Profitability of Sector Momentum Strategies.” *Journal of Financial Economics*, 73(2), 525-556.

2. Stangl, J., Jacobsen, B., & Visaltanachoti, N. (2009). “Sector Rotation over Business-Cycles.” *Journal of Empirical Finance*, 16(5), 777-791.

3. Jacobsen, B., & Zhang, C. (2012). “Seasonality in Stock Returns: Evidence from Fourteen Countries.” *Journal of Banking & Finance*, 36(2), 490-503.

4. Grant, K. (2003). “Quantitative Financial Analytics: The Path to Investment Profits.” *Academic Press*.

5. Journal of Portfolio Management (2017). “Event-Driven Strategy: An Examination.” *Journal of Portfolio Management*.

The Problem with Modern Portfolio Theory

The Problem with Modern Portfolio Theory

The Problem with Modern Portfolio Theory

The world of finance is replete with theories and models. Yet, few concepts have left as indelible a mark as Modern Portfolio Theory (MPT).

Proposed by Harry Markowitz in his 1952 paper, “Portfolio Selection,” MPT has been both a guiding light and a point of contention among investors for decades.

What is Modern Portfolio Theory?

chart showing diversification of different asset classes

An example of the relationship between different asset classes

Modern Portfolio Theory revolves around the idea of diversification — essentially, the age-old wisdom of not putting all your eggs in one basket.

At its core, MPT posits that the risk and return of an overall portfolio are more important than the risk and return of individual assets.

Foundational Concepts:

  • Expected Returns: An anticipated value for the return on an investment, often calculated based on historical data.
  • Portfolio Volatility: The standard deviation of portfolio returns, representing the total risk of the portfolio.
  • Efficient Frontier: A curve that defines the portfolios offering the highest expected return for a given level of risk (or the lowest risk for a given level of return).

The primary tenet is that a diversified portfolio can be constructed to optimize returns for a given level of risk or, conversely, minimize risks for a desired return. This optimization process leads to the efficient frontier, where portfolios lie on a curve representing the best risk-return trade-offs.

How Does Modern Portfolio Theory Work?

chart of the efficient frontier

source: Wikipedia

Imagine you have multiple assets to invest in, each with its respective return and risk profile. According to MPT:

  1. Diversification Benefits: By diversifying across assets that are not perfectly correlated, you can reduce the portfolio’s overall risk without necessarily sacrificing returns. This happens because individual asset volatilities can offset each other.
  2. Optimal Portfolio Creation: For a given risk level, there exists an optimal combination of assets that will offer the highest possible return. This combination forms the efficient frontier.
  3. Risk-Free Assets & Capital Allocation Line: Introducing a risk-free asset (like a treasury bill) allows for a combination of the risk-free asset and a portfolio on the efficient frontier, leading to a straight line known as the capital allocation line. The point where this line is tangent to the efficient frontier is the market portfolio.

This approach emphasizes the collective behavior of assets, acknowledging that individual asset behavior isn’t as crucial when viewed within the context of an entire portfolio.

The Problem with Modern Portfolio Theory

While Modern Portfolio Theory (MPT) has been a pillar of finance for decades, as financial markets have evolved and academic research has delved deeper into investor behavior and market dynamics, various criticisms have emerged.

diversification failed during covid

Asset correlations can rapidly change during a bear market

1. Assumption of Rationality:

  • Description: Central to MPT is the assumption that investors are rational actors who aim to maximize their utility (usually represented by expected returns) for a given level of risk.
  • Reality and Examples: Behavioral finance has identified numerous instances where investors deviate from rationality. For example, during the Japanese asset price bubble in the late 1980s, investors continued to buy into skyrocketing real estate and stock prices, even when fundamental valuations could not justify such prices1.
  • Academic Insight: Kahneman and Tversky’s Prospect Theory illustrates how people make decisions involving probabilities. They found that investors often overvalue potential losses compared to potential gains, leading to irrational decision-making2.

2. Dependence on Historical Data:

  • Description: MPT models rely heavily on historical data to estimate expected returns, variances, and covariances.
  • Reality and Examples: Markets, economies, and geopolitical scenarios evolve. The historical data from emerging markets, such as Brazil’s stock market in the 1990s, may not capture the entire range of potential future outcomes, given the rapidly changing economic environment and institutional reforms during that period3.
  • Academic Insight: Ibbotson and Kaplan, in their 2000 study, discussed how historical returns are often poor predictors of future returns due to changing market conditions4.

3. Static Correlations:

  • Description: MPT assumes that correlations between assets remain consistent.
  • Reality and Examples: The 1997 Asian Financial Crisis saw previously uncorrelated economies and markets fall in tandem. For instance, while South Korea and Thailand had different economic structures, both faced massive capital outflows and devaluations, demonstrating converging correlations during crises5.
  • Academic Insight: Longin and Solnik’s study on international equity markets showed that correlations between markets increase in volatile conditions, challenging MPT’s static correlation assumption6.

4. Over-reliance on Quantitative Analysis:

  • Description: MPT is rooted in quantitative data, potentially sidelining qualitative factors.
  • Reality and Examples: The downfall of Long-Term Capital Management (LTCM) in 1998 is a case in point. Despite the hedge fund being run by two Nobel Prize-winning economists and employing sophisticated models, they overlooked political and operational risks during the Russian financial crisis7.
  • Academic Insight: Daniel and Titman’s 1997 study illustrated that stock returns were more closely linked to firm characteristics than to their beta coefficients, emphasizing the importance of qualitative factors8.

5. Over-Simplification of Investor Goals and Constraints:

  • Description: MPT is rooted in the idea that risk and return are the primary considerations for investors.
  • Reality and Examples: In the late 2000s, many pension funds across Europe shifted to more conservative assets, not just due to risk-return trade-offs, but due to regulatory pressures, liquidity needs, and long-term liabilities9.
  • Academic Insight: A study by Ang, Papanikolaou, and Westerfield highlighted how investor objectives and constraints, such as labor income risks, can influence portfolio decisions beyond mere risk-return considerations10.

MPT Failures in the US Stock Market


1. The 1987 Stock Market Crash (Black Monday):

      • What Happened: On October 19, 1987, U.S. stock markets witnessed their most significant one-day percentage drop in history, with the Dow Jones Industrial Average plummeting by 22.6%.
      • MPT Shortcoming: MPT assumes a normal distribution of asset returns, but Black Monday defied this assumption, representing a multi-standard deviation event that was considered nearly impossible based on traditional models.

2. The Tech Bubble Burst (2000-2002):

      • What Happened: At the turn of the millennium, the dot-com bubble, characterized by exuberantly valued tech stocks, burst. Between 2000 and 2002, the NASDAQ Composite, which had many of these tech stocks, lost 78% of its value.
      • MPT Shortcoming: The bursting of the bubble showed that diversifying across sectors isn’t always sufficient. Many investors, believing they were adequately diversified, still faced substantial losses because various sectors were indirectly influenced by the tech sector’s downturn.

3. The 2008 Financial Crisis:

      • What Happened: Triggered by the collapse of large financial institutions due to exposure to subprime mortgages, it resulted in sharp declines in consumer wealth, severe disruptions in financial markets, and the onset of a deep recession.
      • MPT Shortcoming: Asset correlations, which are central to MPT, converged during the crisis. Diversification benefits diminished as a wide variety of assets, from stocks to real estate, all fell in tandem, challenging MPT’s foundational premise.

4. Long-Term Capital Management (LTCM) Crisis (1998):

      • What Happened: LTCM, a hedge fund managed by two Nobel Prize-winning economists who heavily relied on advanced financial models, faced catastrophic losses during the Russian financial crisis.
      • MPT Shortcoming: Despite the use of sophisticated models rooted in MPT principles, LTCM’s strategies did not account for “Black Swan” events or extreme market moves. Over-reliance on quantification and undervaluing of qualitative factors, like geopolitical risks, led to its downfall.

5. Growth vs. Value Dichotomy (2010s):

    • What Happened: Throughout much of the 2010s, growth stocks (particularly in technology) significantly outperformed value stocks, contrary to the historical premium associated with value investing.
    • MPT Shortcoming: MPT posits that higher risks are associated with higher expected returns. However, many growth stocks offered both higher returns and lower volatility than their value counterparts during this period, challenging traditional risk-return dynamics postulated by MPT.


Each of these events underscores the importance of understanding the assumptions and limitations of MPT.

In summary, while MPT offers a foundational framework for understanding risk and return in portfolios, evolving market dynamics, and continued academic inquiry suggest that it should be applied with caution and complemented with other financial tools and insights.



  1. Shiller, R. J. (1992). Market Volatility and Investor Behavior. American Economic Review, 82(2), 58-62.
  2. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-292.
  3. Harvey, C. R. (1995). Predictable Risk and Returns in Emerging Markets. Review of Financial Studies, 8(3), 773-816.
  4. Ibbotson, R. G., & Kaplan, P. D. (2000). Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance? Financial Analysts Journal, 56(1), 26-33.
  5. Radelet, S., & Sachs, J. (1998). The East Asian Financial Crisis: Diagnosis, Remedies, Prospects. Brookings Papers on Economic Activity, 1998(1), 1-90.
  6. Longin, F., & Solnik, B. (2001). Extreme Correlation of International Equity Markets. The Journal of Finance, 56(2), 649-676.
  7. Lowenstein, R. (2000). When Genius Failed: The Rise and Fall of Long-Term Capital Management. Random House.
  8. Daniel, K., & Titman, S. (1997). Evidence on the Characteristics of Cross-Sectional Variation in Stock Returns. The Journal of Finance, 52(1), 1-33.
  9. Ralfe, J., Speed, C., & Allinson, D. (2004). The Pension Crisis. Lancet, 363(9419), 1343.
  10. Ang, A., Papanikolaou, D., & Westerfield, M. M. (2014). Portfolio Choice with Illiquid Assets. Management Science, 60(11), 2737-2761.