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I am pleased to announce the public release of our flagship working paper, “The Ternary Regime Asset Framework (TRAF): A Regime-Aware Approach to Tactical Asset Allocation,” now hosted on SSRN.

This paper serves as the intellectual anchor for the quantitative philosophy we employ at TradeRounds. While traditional tactical models often rely on isolated momentum signals, the TRAF framework introduces a multi-dimensional method for identifying market “regimes”, allowing for a more robust adaptation to shifting volatility and liquidity environments.

Key Insights from the Research:

• The “TRAF Sticky” Strategy: We provide a full breakdown of the mechanics behind this core strategy, which has demonstrated a 0.63 Sharpe ratio in long-term backtesting, offering superior risk-adjusted metrics compared to traditional buy-and-hold benchmarks.

• Regime-Aware Dynamics: The research formalizes how we categorize market environments into distinct regimes to optimize asset rotation and defensive positioning.

• Academic Submission: This paper is currently under formal editorial consideration for publication in a leading peer-reviewed finance journal.

To read the full article on SSRN click here

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In the current market landscape, the heavy concentration of mega-cap names has made the S&P 500 price chart a potentially deceptive indicator of true market health, while the index may climb to new highs, the underlying participation of its constituent stocks often tells a different story. The following analysis, built upon the framework established by Cedric Thompson at StockCharts, utilizes the S&P 500 Bullish Percent Index ($BPSPX) to identify when the internal engine of the market is actually shifting gears, moving beyond the noise of market-cap weighting.

Visualizing the Breadth Shift

The chart provided by StockCharts below illustrates the critical relationship between the $BPSPX and the S&P 500 ($SPX) through late April 2026, it highlights how breadth serves as a confirming indicator during periods of volatility.

Source: StockCharts.com, Cedric Thompson. Data as of April 24, 2026.

The Logic of Probabilistic Breadth

The $BPSPX is unique because it is built on Point and Figure charting, which ignores the passage of time and minor price fluctuations to focus purely on trend reversals, a stock only contributes to the bullish side of this index when it triggers a definitive P&F buy signal. By measuring the percentage of S&P 500 stocks currently in bullish patterns, we gain a clear view of market participation, when the $BPSPX crosses above the 50 percent mark, as seen in the recent April surge, it signifies that a majority of the index is participating in the uptrend.

It is vital to remember that these signals represent an increase in probabilities, not a guaranteed outcome, history shows that when the $BPSPX clears 50, the S&P 500 has a 69 percent chance of being higher one year later. While these are favorable odds for a return to a bull regime, the remaining 31 percent represents the “failure rate” where macro shocks or hidden sectoral weakness can still derail the momentum.

The Bearish Blindspot: Why This is Not an “Exit” Tool

Despite the strength of the bullish signals, we must address a significant critique of the $BPSPX method, it is a poor bear market timing tool. Because the index is a lagging indicator, breadth often only confirms a breakdown after a significant portion of the price damage has already occurred, furthermore, bearish signals, such as a cross below 70 or 50 are statistically less predictable and lack the high-probability “edge” found in the bullish recovery signals.

In a modern regime dominated by high index concentration, the $BPSPX can remain deceptively high while the largest caps begin to roll over, or conversely, it can “trap” traders into exiting too early during a healthy mid-cycle correction. For the TradeRounds member, this means the $BPSPX should be used to “get long,” but your primary price-based stop-losses and macro filters must be the tools that “get you out.”

TradeRounds Strategy Integration

For a structural 60:40 framework, the current chart positioning offers a clear set of actionable, risk-adjusted regimes:

• The Recovery Signal: The bounce off the red 30-line in late March was the high-probability entry signal to begin shifting toward equity exposure.

• The Momentum Confirmation: The current reading of 62.00, comfortably above the dotted 50-line, indicates a healthy environment where a standard 60:40 allocation is well-supported by internal participation.

• The Risk Management Clause: Because the $BPSPX has a “bearish blindspot,” the 40 percent bond or cash cushion remains your primary defense, do not wait for a $BPSPX cross below 50 to protect capital, instead, use that signal only as a final confirmation that the regime has officially shifted to defensive.

Final Verdict

The latest data confirms that the “wind is at the back” of the S&P 500, with 62 percent of the index currently on P&F buy signals, the rally has the broad participation necessary to sustain itself into late 2026. While the $BPSPX is a masterful tool for identifying the start of a bull regime, it requires the discipline of a structured 60:40 exit strategy to account for its inherent lag during market downturns.

The Systematic Edge

In our original research, we established a rules-based framework for navigating market volatility. This approach identifies the relative momentum across Large, Mid, and Small-cap stocks while keeping a finger on the pulse of the “Canary in the Coal Mine”: TIP (Inflation-Protected Treasuries). Read our full paper on Regime-Aware Market Capitalization Rotation on SSRN and our summary article on TradeRounds.

Most investors suffer from “Index Bias,” staying anchored to the S&P 500 regardless of the underlying regime. Our Regime-Aware Market Capitalization Rotation seeks alpha where it lives while maintaining a hard-coded exit strategy.

The Strategy: The 13612 Momentum Engine

This strategy uses a blended momentum score; the average of 1, 3, 6, and 12-month returns.

• The Canary (TIP): If TIP momentum is positive, the regime is “Risk-On.”

• The Engine (SPY/MDY/IJR): We rotate into the market-cap ETF with the strongest relative momentum.

• The Emergency Brake (BIL): If TIP momentum turns negative, we move to the sidelines in T-Bills (BIL).

Why 2008 to 2026? A Stress-Test of Three Regimes

Readers often ask why our backtest begins in 2008. The start date is dictated by the launch of our “Safety” asset, BIL, which began trading in 2007. Combined with our 12-month momentum lookback, this allows for a clean simulation starting in May 2008.

While this interval is shorter than some historical backtests, it is actually the ultimate “stress test.” It forces the strategy to navigate three distinct and difficult market regimes:

1. The Deflationary Crisis (2008): As the global financial system buckled, the TIP canary correctly triggered a “Risk-Off” signal. By holding BIL, the strategy avoided the catastrophic 50%+ drawdown seen in equities.

2. The Quantitative Easing Era (2010–2021): During this decade of Large-Cap dominance, the model effectively rotated between SPY and MDY, capturing the momentum of the “Magnificent” era without losing its defensive posture.

3. The Inflationary Pivot (2022–Present): Unlike a traditional 60/40 portfolio, where bonds and stocks crashed together in 2022, our Regime-Aware approach utilized BIL and the TIP signal to preserve capital during the fastest rate-hiking cycle in history.

Backtest Performance: Surviving the Bear, Catching the Bull

By successfully navigating these regime changes, the strategy has outperformed a static “Buy and Hold” on a risk-adjusted basis.

By using the TIP canary, we effectively cut the “Greatest Loss” in half. The model sat safely in BIL during the worst of the 2008 Global Financial Crisis and the 2022 inflationary rout, waiting for the signal to return to equities.

Current Signal: The Pivot to Small Caps (IJR)

As of mid-April 2026, the signal has shifted. While 2025 was dominated by Large-Cap (SPY) leadership, our model triggered a rotation into IJR (S&P Small-Cap 600) at the end of March.

Current Momentum Comparison:

• IJR (Small Cap): 0.1439 (The Leader)

• MDY (Mid Cap): 0.1169

• SPY (Large Cap): 0.0998

Despite the headlines focusing on the S&P 500, Large Caps currently have the weakest momentum profile of the three tiers. We are seeing a classic “breadth” expansion where smaller, more sensitive companies are beginning to outpace the behemoths.

Regime Status: RISK ON

The “Canary” (TIP) is still singing with a momentum score of +0.016. While this is a lean signal, it confirms that the current environment remains supportive of equity risk.

Why Not a Standard 60/40?

Many readers have asked how this compares to the traditional 60/40 Stock Bond Portfolio. In a world of volatile interest rates, bonds have often failed to provide the “cushion” they once did. By replacing the bond component with a regime-aware cash trigger (BIL), we avoid the “hidden” drawdowns of fixed income while staying concentrated in the highest-momentum equity tier.

The TradeRounds Playbook

• Current Positioning: 100% IJR (Small-Cap 600).

• Action: We stay long Small Caps as long as IJR maintains relative leadership and TIP stays above zero.

• Next Review: End of April. If TIP momentum turns negative, we exit all equity positions and move to BIL.

How to Follow This Signal

For those looking to implement this “Regime-Aware” rotation:

1. Monitor the Close: We only rebalance on the last trading day of the month.

2. Check the Canary: If TIP’s 1,3,6,12 average is negative, go to cash (BIL).

3. Find the Leader: If TIP is positive, buy whichever has the highest score: SPY, MDY, or IJR.

Stay disciplined. Follow the regime, not the noise.

Disclaimer: This article is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results.

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About the Author: Peter Richman, MD, MBA is a Professor of Emergency Medicine and former Registered Investment Advisor. At TradeRounds, he applies the same evidence-based diagnostics used in medicine to financial markets.

The 60/40 portfolio—60% stocks, 40% bonds—is the bedrock of modern asset allocation. But while the allocation is timeless, the maintenance is often stuck in the past. Most investors rebalance on a rigid schedule: every quarter, or every year, regardless of what the market is actually doing.

In my recent SSRN paper, The Safety Tripwire: Architectural Efficiency of Threshold-Based Rebalancing in a 60/40 Regime, I argue that this “calendar-blind” approach is fundamentally inefficient. To maximize the 60/40’s potential, you need to stop trading the clock and start trading the drift.

The Problem with Calendar Rebalancing

Calendar-based rebalancing (e.g., “I rebalance every December 31st”) assumes the market cares about our Gregorian calendar. It doesn’t. This approach creates two distinct types of architectural waste:

1. The “Nothing” Trade: You rebalance because the date arrived, even if your portfolio only drifted to 61/39. You pay commissions and spread for a negligible change in risk.

2. The “Delayed” Trade: A massive market move happens in February, pushing you to 70/30. If you wait until June to rebalance, you’ve spent four months exposed to significantly higher drawdown risk than you intended.

Introducing the “Safety Tripwire”

The “Safety Tripwire” is a threshold-based strategy. Instead of looking at the date, you look at the deviation. You only trigger a trade when the portfolio drifts past a predetermined boundary—for example, a 5% absolute deviation.

In this regime, your 60/40 stays “hands-off” as long as it fluctuates between 55/45 and 65/35. The moment it hits 65.1%, the “tripwire” snaps, and you rebalance back to the 60/40 target.

Why It’s “Architecturally Efficient”

My research highlights that threshold rebalancing isn’t just about “timing”; it’s about architectural efficiency. By moving away from the calendar, you achieve three critical advantages:

• Reduced Transaction Costs: By ignoring minor drifts, you execute fewer trades over the long run, saving on slippage and fees.

• Capturing the Rebalancing Premium: Thresholds allow the “winners” to run just enough to capture momentum, but force a sell-high/buy-low action precisely when the risk-reward profile has skewed too far.

• Volatility Targeting: The Safety Tripwire acts as a mechanical risk-off switch. It forces you to buy bonds during equity crashes and sell stocks during irrational exuberance—not because you “felt” like it, but because the architecture demanded it.

Practical Implementation for Traders

If you’re managing a 60/40 split, you don’t need a complex algorithm to start. You can implement a Safety Tripwire using a simple Python script or even basic platform alerts.

Pro Tip: For most retail portfolios, an absolute threshold of 5% (e.g., rebalancing at 65% stocks) or a relative threshold of 10% of the asset’s weight (e.g., rebalancing when the 60% stock portion hits 66%) provides the best balance between risk control and cost-efficiency.

The 60/40 regime isn’t dead—it just needs a smarter trigger. By replacing your calendar with a Safety Tripwire, you stop being a passenger to time and start being a manager of drift.

History is filled with tragic conflicts, yet from an investment standpoint, the “War Puzzle” remains one of the most counter-intuitive phenomena in finance. While common sense suggests that military intervention should trigger prolonged market chaos, the data often tells a different story.

In my recent TradeRounds analyses of tactical methods to invest in market cap ETFs and the magnificent 7 technology stocks, we explored how concentration creates internal fragility. Today, we look at how those same concentrated indices react to external shocks—specifically military interventions

The Historical Snapshot

Looking at major U.S. military interventions, we often see a “V-shaped” emotional response from the S&P 500:

Why Does This Happen?

1. Pre-War Jitters vs. Certainty: Markets hate uncertainty more than they hate bad news. Often, the “dip” happens in the months leading up to the first shot. Once conflict begins, the uncertainty is replaced by a known risk that can be modeled and priced.

2. The Volatility Paradox: Research (notably by Schwert, 1989) shows that stock volatility is actually 33% lower during wartime. Massive government spending creates stable, predictable revenue streams for a wide swath of the economy, from defense and energy to tech and logistics.

3. The “Oil Dividend”: While energy spikes cause initial fear, historical data shows that unless oil prices rise by 75-100% and stay there, the broader economy often absorbs the shock within 12 months.

The Takeaway for Tactical Investors:

While the ‘War Puzzle’ shows that markets often defy gravity during conflict, navigating these periods requires more than just historical trivia—it requires a systematic framework. For those interested in the deep math behind these strategies, I invite you to read my two recent peer-reviewed publications on the Social Science Research Network:

• Tactical Asset Allocation: A Quantitative Framework

• Risk Management in Volatile Regimes: The Magnificent 7 Stocks

The "Magnificent Seven" (Mag 7) have dominated the market narrative for years, often acting as the sole engine for U.S. equity returns. But for the tactical investor, the biggest risk isn't missing the rally—it’s staying at the party too long after the music stops.

I have just published a new research paper on SSRN titled “A Systematic Momentum-Based Approach to Allocating Between the Magnificent Seven and Broad Equity Indices.” In this study, I apply a quantitative framework to determine exactly when to ride the Mag 7 wave and when to take cover in broad market indices or defensive assets.

The Concentration Risk Dilemma

Most investors are “accidentally” over-concentrated in the Mag 7 through passive index funds. While this was a winning hand in 2023 and parts of 2024, the risk of a “reversion to the mean” is a constant threat.

My research introduces a Dual-Momentum Framework designed to navigate this concentration risk.

The Strategy: Relative Strength meets Regime Awareness

The methodology I developed for this paper focuses on three core pillars:

1. Relative Momentum: We compare the performance of the Magnificent Seven (via equal-weighted or cap-weighted baskets) against the S&P 500 and Nasdaq-100.

2. The “Canary” Filter: Using a regime-awareness trigger (similar to the Hybrid Asset Allocation model), the strategy identifies when the broad macro environment is no longer supportive of high-beta growth stocks.

3. Adaptive Rotation: When momentum is high and the regime is “Risk-On,” the strategy concentrates in the Mag 7. When the trend falters or risk rises, it systematically rotates back to the broader market or defensive T-Bills.

Key Findings from the Study

• Enhanced Alpha: By rotating into the Mag 7 only during periods of confirmed relative strength, the strategy significantly outperformed a static “buy and hold” approach to the S&P 500.

• Downside Protection: The inclusion of a trend-following filter successfully mitigated the deep drawdowns often associated with concentrated tech positions during market corrections.

• Reduced Volatility: The systematic rotation provided a smoother equity curve compared to the “boom or bust” nature of holding concentrated tech leadership indefinitely.

Why This Matters for TradeRounds Followers

Quantitative trading isn’t about guessing which AI stock will double next; it’s about process over prediction. This paper provides a mathematical blueprint for handling the market’s most influential stocks without falling victim to the “concentration trap.”

Read the Full Paper

For the full breakdown of the data, the specific ETFs used in the backtest (including MAGS/METU and SPY/QQQ), and the performance metrics, you can access the complete study here:

A Systematic Momentum-Based Approach to Allocating Between the Magnificent Seven and Broad Equity Indices

Stay disciplined,
Dr. Pete
TradeRounds.com

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Hybrid Asset Allocation (HAA), originally developed by Keller and Keuning (2023), integrates absolute momentum and relative momentum within a regime-aware structure using a canary asset to determine market risk conditions. The framework has been widely discussed as a systematic approach to managing drawdowns while maintaining exposure to higher-return assets during favorable regimes.

In a new working paper, I extend the Hybrid Asset Allocation framework to U.S. market capitalization rotation, applying regime filtering to large-, mid-, and small-cap equity exchange-traded funds. Rather than relying on static exposure or single-lookback momentum signals, this approach evaluates both regime state and cross-sectional momentum when allocating across capitalization segments.

Specifically, the model combines:

• Relative momentum measured across multiple horizons (1-, 3-, 6-, and 12-month lookbacks)

• Absolute momentum of a Treasury Inflation-Protected Securities (TIP) canary asset to determine risk-on versus risk-off regimes

• Short-term U.S. Treasury exposure (SHY) as the designated defensive allocation during adverse regimes

The objective of this research is not simply return maximization, but improved risk-adjusted performance and drawdown control across changing equity market environments. By incorporating regime awareness into market capitalization allocation decisions, the framework seeks to address the well-documented cyclicality of relative performance between large-, mid-, and small-cap equities.

The paper evaluates whether capitalization segments respond differently to regime filtering and whether a structured rotation approach can improve capital efficiency relative to static market exposure. The analysis is intended to contribute to the growing literature on regime-aware tactical asset allocation and extensions of the Hybrid Asset Allocation methodology.

The complete working paper is available on SSRN:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6096427

Keywords: Hybrid Asset Allocation, Market Cap Rotation, Regime-Aware Investing, Tactical Asset Allocation, Absolute Momentum, Relative Momentum, ETF Rotation

References

Keller, Wouter J. and Keuning, Jan Willem, Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA) (February 3, 2023). Available at SSRN: https://ssrn.com/abstract=4346906 or http://dx.doi.org/10.2139/ssrn.4346906

Richman, Peter, A Regime-Aware Market Capitalization Rotation Strategy Using Hybrid Asset Allocation Momentum (January 18, 2026). Available at SSRN: https://ssrn.com/abstract=6096427 or http://dx.doi.org/10.2139/ssrn.6096427

In technical analysis, few signals carry as much weight as the 200-day moving average (200DMA). It acts as the dividing line between long-term bull and bear markets for institutions and retail traders alike.

But signals are rarely crystal clear in the moment. They often arrive amidst “macro noise” like fears of inflation, geopolitical tension, or policy shifts that make pulling the trigger difficult.

In this guide, we will break down exactly what a “200DMA Reclaim” is, why it matters, and analyze a specific historical example. We will look at the May 2025 reclaim which kicked off a massive rally despite a “wall of worry.”

What Is the 200-Day Moving Average?

The 200-day moving average (200DMA) is the average closing price of a stock or index over the past 200 trading days, or about 10 months. It smoothes out short-term volatility to reveal the dominant long-term trend.

• Price > 200DMA: generally signals a bullish trend and institutional accumulation.

• Price < 200DMA: generally signals a bearish trend and distribution.

As John Murphy noted in Technical Analysis of the Financial Markets, this line acts as a major support or resistance level. When the price crosses it, the market is making a statement.

The Anatomy of a “Reclaim”

A reclaim occurs when the S&P 500 trades below this key level but then powers back above it. This crossover often signals a potential trend reversal or renewed market strength.

However, context is everything. Not all reclaims stick. The most reliable reclaims typically have three characteristics:

1. Breadth: A majority of individual stocks are participating in the move.

2. Volume: The move is supported by institutional buying (high volume).

3. Persistence: The index closes above the line for multiple consecutive days.

Case Study: The May 2025 Reclaim

Let’s look back at a textbook example from earlier this year.

The Setup (May 23, 2025) The S&P 500 had been chopping in a corrective phase. Sentiment was fearful. Headlines were dominated by renewed trade tensions and policy comments regarding tariffs. The VIX (volatility index) was edging higher.

Technically, however, the picture was improving. On May 23, the S&P 500 closed at 5,802.82, crossing back above its 200DMA (which was then at ~5,773).

At the time, we noted several bullish confirmations in TradeRounds:

• Momentum: The MACD was in bullish territory and RSI was above 50.

• Breadth: Over 50% of S&P 500 stocks were trading above their own 200DMAs.

• Structure: Short-term averages (20-day and 50-day) were sloping upward.

The “Wall of Worry” Despite the technical buy signal, it was difficult to be bullish. Macro headwinds were front and center. Many investors stayed on the sidelines, waiting for “clarity” on trade policy that never came. Meanwhile, price, which is the only thing that pays, kept moving higher.

The Result: +19% in 7-Months

Fast forward to December 26, 2025.

That reclaim wasn’t a fake-out. It was the start of a sustained uptrend. The S&P 500 never looked back, holding the 200DMA as support and climbing to 6,929.95.

• Entry (May 23): 5,802

• Current (Dec 26): 6,929

• Total Gain: +19.4%

Investors who waited for macro clarity missed nearly 20% gains in just over half a year. Those who trusted the technicals, specifically the 200DMA reclaim combined with breadth, captured the move.

Historical Performance of Reclaims

The May 2025 event wasn’t an anomaly. Historical data supports the bullish bias of this signal.

(Note: Table below reflects historical probabilities of forward returns after a confirmed 200DMA crossover)

What to Watch For Next

If you missed the May entry, don’t chase blindly. Instead, use the 200DMA as your risk management guide.

1. The “Checkback”: Often, after a strong rally, the index will pull back to test the 200DMA. If it bounces, that is a secondary entry point.

2. Breadth deterioration: If the market keeps rising but fewer stocks are above their 200DMA (a divergence), be cautious.

3. Volume: Watch for heavy selling volume if the price approaches the 200DMA again.

Conclusion

The 200-day moving average is more than a line on a chart. It is a behavioral trigger for the market. The May 2025 case study proves that when technicals align (price, breadth, and momentum), they often override the bearish macro narrative.

Keep watching the levels, and let the price dictate your strategy.

Glossary

• S&P 500: A stock index representing 500 large U.S. companies.

• Breadth: The percentage of stocks participating in a move. Broad participation generally means a healthy market.

• VIX: Volatility Index. This measures expected market turbulence.

• MACD: A momentum indicator that tracks the convergence or divergence of moving averages.

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The financial media industry is built on a single, flawed premise: that the future can be predicted.

Every day, pundits shout forecasts about interest rates, earnings reports, and geopolitical events. Retail investors consume this noise, try to connect the dots, and make decisions based on gut feelings, fear, or Fear of Missing Out (FOMO).

The result is predictable. The average investor consistently underperforms the market, buying high when euphoria peaks and selling low when panic sets in.

Quantitative trading offers a different path. It is the antidote to emotional investing.

At TradeRounds, we believe that successful investing isn’t about being smarter than the market or having a crystal ball. It’s about having a system. Quantitative (or “systematic”) trading removes guesswork by using mathematical models, historical data, and strict rules to make trading decisions.

This guide outlines the five foundational pillars of a robust quantitative trading framework. In future articles, we will dive deep into the specific mechanics of each, but below we review the core concepts and the academic evidence that supports them.

Pillar 1: Tactical Asset Allocation (TAA)

The Engine of Adaptability

Most investors are familiar with Strategic Asset Allocation—the classic “60/40” portfolio. While better than nothing, this static approach ignores the current market environment, forcing you to hold falling assets during a bear market.

Tactical Asset Allocation (TAA) is a dynamic approach. It uses quantitative signals to shift the portfolio’s weightings based on what is actually happening in the market right now. If the data indicates a high-risk environment for stocks, a TAA strategy might mechanically reduce equity exposure, moving the difference into cash or defensive assets.

The Evidence: Data in Action

The power of TAA was popularized by Meb Faber in his seminal paper, A Quantitative Approach to Tactical Asset Allocation. Faber tested a simple timing model (buying when price > 10-month moving average, selling when < 10-month MA) across five asset classes from 1973 to 2012.

The results were statistically significant:

• Returns: The TAA model generated equity-like returns (approx. 10.4% annualized) comparable to the S&P 500.

• Risk: Crucially, it did so with bond-like volatility. The maximum drawdown (peak-to-trough decline) was approximately 50% lower than a buy-and-hold strategy (Faber, 2007).

The Takeaway: TAA allows investors to participate in bull markets while sidestepping the catastrophic losses of bear markets.

Pillar 2: Momentum Investing

The Premier Market Anomaly

If you learn only one quantitative concept, make it Momentum.

Momentum is the empirically validated tendency for assets that have performed well in the recent past (3 to 12 months) to continue performing well in the near future. It challenges the Efficient Market Hypothesis, yet it persists due to deep-seated human behavioral biases like anchoring and herding.

The Evidence: Data in Action

In 1993, researchers Narasimhan Jegadeesh and Sheridan Titman published Returns to Buying Winners and Selling Losers, the study that put momentum on the academic map. Analyzing U.S. stock data from 1965 to 1989, they found that a strategy of buying the top 10% of past performers (”winners”) and selling the bottom 10% (”losers”) generated an average excess return of roughly 12% per year (Jegadeesh & Titman, 1993).

This “anomaly” has since been validated across nearly every asset class and geography, spanning over 200 years of financial history.

The Takeaway: Momentum is not a fad; it is a pervasive market force driven by human psychology.

Pillar 3: Relative Strength

Finding the Market Leaders

While momentum often looks at an asset’s own past performance, Relative Strength (RS) looks at its performance compared to everything else.

In any market environment, capital is flowing somewhere. Even in a flat stock market, certain sectors (like Technology or Healthcare) may be booming while others lag. A quantitative system uses RS to identify where that capital is flowing and rotates the portfolio into leadership.

The Evidence: Data in Action

Gary Antonacci refined this concept in his development of “Dual Momentum,” which combines absolute momentum (is the trend up?) with relative momentum (is it outperforming others?).

In his backtests of the “Global Equities Momentum” (GEM) model from 1974 to 2013, the strategy of switching between US stocks, International stocks, and Bonds based on relative strength returned 17.4% annually, compared to just 10.4% for the S&P 500, with significantly lower volatility (Antonacci, 2012).

The Takeaway: Don’t just own “the market.” Use Relative Strength to mathematically determine which parts of the market are leading, and own those.

Pillar 4: Moving Average Tactics

The Essential Trend Filters

Quantitative trading requires binary signals: Buy or Sell. Risk-On or Risk-Off. The cleanest tools for generating these signals are Moving Averages (MAs), specifically the long-term averages like the 200-day Simple Moving Average (SMA).

The Evidence: Data in Action

Professor Jeremy Siegel, in his book Stocks for the Long Run, analyzed the Dow Jones Industrial Average from 1886 to 2006. He tested a strategy of buying the Dow only when it was above its 200-day moving average and moving to cash when it fell below. The result was a dramatic improvement in risk-adjusted returns, preserving capital when it mattered most (Siegel, 2014).

This protection has held true during the major crises of the modern era:

• The Great Financial Crisis (2008-2009): The S&P 500 broke below its 200-day average in late 2007/early 2008. A quantitative trend filter would have moved an investor to safety (cash or bonds) long before the market collapsed 50%, avoiding the devastating losses of late 2008.

• COVID-19 (Winter 2020): While the crash was rapid, the index broke its long-term trend in late February 2020. Trend followers were signaled to exit weeks before the market bottomed in March, bypassing the most volatile days of the panic.

• The 2022 Bear Market: As inflation soared, the market entered a slow, grinding downtrend. The 200-day average acted as a reliable ceiling, keeping quantitative investors in a “Risk-Off” posture for the majority of the year, while buy-and-hold investors suffered a drawdown of nearly 20% (and significantly more in the tech sector).

The Takeaway: Moving averages act as an objective “circuit breaker” for your portfolio. They may not catch the exact top, but they are highly effective at preventing catastrophic drawdowns during sustained market failures.

Pillar 5: Portfolio Risk Management

The Math of Survival

Novice traders obsess over returns. Professional quantitative traders obsess over risk. This is due to the punishing mathematics of loss recovery: a 50% loss requires a 100% gain just to break even.

The Evidence: Data in Action

Modern quantitative funds often use “Volatility Targeting”—adjusting position sizes based on the current volatility (VIX) of the market.

Research by the Man Group and Research Affiliates has shown that volatility targeting significantly improves Sharpe Ratios (return per unit of risk). For instance, during the COVID-19 crash of early 2020, a standard S&P 500 portfolio suffered drawdowns of roughly -34%. A volatility-targeted portfolio, which would have systematically reduced leverage as volatility spiked in late February, saw drawdowns of less than -10% in many models (Harvey et al., 2018).

The Takeaway: Survival is the prerequisite for success. By mathematically managing position size and volatility, you ensure you are always around to play the next hand.

Conclusion

Quantitative trading is not a magic bullet. It requires the discipline to follow the rules when your gut tells you otherwise. However, as the academic literature demonstrates, a systematic approach based on Tactical Allocation, Momentum, Relative Strength, Moving Averages, and Risk Management offers a proven path to superior risk-adjusted returns.

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References

1. Antonacci, G. (2012). Risk Premia Harvesting Through Dual Momentum. Portfolio Management Consultants.

2. Faber, M. T. (2007). A Quantitative Approach to Tactical Asset Allocation. The Journal of Wealth Management.

3. Harvey, C. R., et al. (2018). The Impact of Volatility Targeting. Journal of Portfolio Management.

4. Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance.

5. Siegel, J. J. (2014). Stocks for the Long Run: The Definitive Guide to Financial Market Returns & Long-Term Investment Strategies. McGraw-Hill Education.

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Can you beat the market using a simple rotation between U.S. and international equities, and step aside when neither looks good?

That’s the promise of Gary Antonacci’s Dual Momentum strategy, a fan-favorite in tactical allocation circles. Built on behavioral and academic underpinnings, the model combines relative momentum (which asset is stronger?) with absolute momentum (is it rising at all?) to supposedly deliver superior returns and lower drawdowns.

But 10+ years after its popularization, how has Dual Momentum really held up? Let's break it down.

📘 The Original Model

From Antonacci’s book Dual Momentum Investing (2015), the core strategy goes like this:

1. Universe: U.S. equities (e.g., SPY) vs. International equities (e.g., VEU)

2. Relative Momentum: Look at 12-month total return of each.

3. Absolute Momentum: If the winning asset has a positive 12-month return, invest in that. If not, move to cash or short-term bonds (e.g., BIL).

4. Rebalance: Monthly

This is sometimes called the Global Equity Momentum (GEM) model.

📈 Backtest Brilliance: What the Hype Promised

Antonacci’s original backtest (1974–2013) showed:

• CAGR: ~17.4%

• Max Drawdown: ~-22%

• Sharpe Ratio: ~0.9

That’s compared to a ~9–10% CAGR and -50% drawdown for a U.S. equity buy-and-hold investor.

Pretty impressive. But let’s fast-forward to real world results.

📉 Real-World Returns (2015–2024)

⚖️ What It Does Well

• Risk Management: Avoids major crashes (e.g., 2008, early 2022) if rebalancing timing aligns

• Behavioral Edge: Reduces panic selling by systematizing exits

• Tax Efficiency: Monthly rebalancing makes this better for IRAs or deferred accounts

🚩 Major Drawbacks

1. Overreliance on a Single Lookback (12 months):

   • Doesn’t adapt to different volatility regimes

   • Suffers in choppy or sideways markets

2. Binary Decision Tree:

   • Either fully in SPY or VEU or fully in cash — no partial positioning

   • May lead to whipsaws or missed rebounds

3. Post-Hoc Bias Risk:

   • 12-month momentum is academically robust, but its use here might be optimized in hindsight

4. International Weakness:

   • VEU underperformance dragged down the whole model in 2010s

   • Concentration in U.S. assets would have worked better with hindsight

🔧 Ways to Potentially Improve It

• Add Volatility Targeting: Risk-adjusted momentum (e.g., Sharpe over 12 months)

• Blend Multiple Lookbacks: Combine 3-, 6-, and 12-month momentum

• Expand the Universe: Add small caps, gold, REITs, or bonds for diversification

• Smooth Transitions: Use moving averages or multi-step allocation shifts to reduce whipsaws

🤔 Final Verdict

Dual Momentum is a beautifully simple model with academic justification and backtested success. But real-world data since its popularization shows that it may struggle in extended U.S. bull markets and may underperform in environments where cash is penalized by inflation or rate volatility.

That said, it still shines as a low-volatility, behavioral-friendly strategy, especially for conservative investors or tax-deferred accounts.

For active users, consider using Dual Momentum as a base layer — and then adapt it with volatility filters, multiple timeframes, or a broader asset class universe.

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📚 Appendix: Key Terms & Definitions

• Dual Momentum
  A tactical investment strategy that combines relative momentum (which asset is stronger?) and absolute momentum (is the asset rising at all?) to select between two or more risk assets, or move to cash if neither asset is strong.

• Relative Momentum
  A rule that compares the total return of two or more assets over a fixed lookback period (e.g., 12 months) and selects the one with the highest performance.

• Absolute Momentum (Trend Following)
  A filter that only allows investment in an asset if its historical return over the lookback period is positive. If not, the portfolio moves to a safe asset like cash or short-term bonds.

• Lookback Period
  The number of days, months, or years used to measure past performance or volatility. Common lookbacks include 3, 6, and 12 months.

• CAGR (Compound Annual Growth Rate)
  The average annual growth rate of an investment over a period of time, assuming profits are reinvested. Smoothed metric that ignores volatility.

• Max Drawdown
  The maximum percentage decline from peak to trough in a portfolio’s value. Measures the worst historical loss and is a key risk metric.

• Volatility Targeting
  An approach that adjusts position sizing based on recent price volatility, aiming to keep portfolio risk constant over time. For example, a riskier asset gets a smaller weight.

• Sharpe Ratio
  A measure of risk-adjusted return, calculated by dividing the portfolio’s excess return over the risk-free rate by its standard deviation. Higher is better.

• Rebalance Frequency
  How often a portfolio is updated or realigned to follow a model’s rules — monthly rebalancing is standard in most momentum strategies.

• Whipsaw
  A scenario where a trading model rapidly flips between positions due to short-term noise, often buying high and selling low. Common in sideways markets.

• Backtest
  A simulation that applies a trading or investment strategy to historical data to estimate how it would have performed in the past.

• Overfitting
  A modeling error where a strategy is too closely tailored to past data, including noise, making it less robust in future real-world conditions.

• Risk-On / Risk-Off
  A framework used in tactical models to describe asset exposure based on market conditions. Risk-on assets include stocks and commodities; risk-off includes cash, bonds, or gold.

• Momentum Decay
  The idea that returns from momentum strategies can diminish over time due to crowding, changing market regimes, or model commoditization.

About the Author: Peter Richman, MD, MBA is a Professor of Emergency Medicine and former Registered Investment Advisor. At TradeRounds, he applies the same evidence-based diagnostics used in medicine to financial markets.

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In the world of tactical investing, the Mama Bear and Papa Bear portfolios—introduced by Brian Livingston in Muscular Portfolios (2018)—aim to beat the market by avoiding its worst crashes. Both use ETF momentum to rotate into strength, but they differ in style, scope, and temperament.

💡 Strategy Comparison

📈 Performance Metrics (Jan 2006 – May 2025)

Source: ETFscreen.com – Mama Bear, Papa Bear

🧰 ETF Universes

Mama Bear Portfolio:

• SPY – U.S. Large-Cap Stocks

• IWM – U.S. Small-Cap Stocks

• EFA – Developed International Stocks

• EEM – Emerging Market Stocks

• TLT – Long-Term Treasury Bonds

• VNQ – U.S. Real Estate (REITs)

• GLD – Gold

• DBC – Commodities

• SHY – Short-Term Bonds (Cash Proxy)

Papa Bear Portfolio adds:

• VUG – U.S. Large-Cap Growth

• VTV – U.S. Large-Cap Value

• LQD – Investment Grade Corporate Bonds

• BNDX – International Bonds

✅ Which One Should You Use?

👶 Newer or Risk-Averse Investor? Choose Mama Bear.

• Lower volatility and simpler ETF set.

• Higher Sharpe and Sortino ratios.

• Easier to rebalance manually.

🚀 Comfortable with Slightly More Risk and Complexity? Choose Papa Bear.

• Broader diversification and more style factors.

• May benefit from market regimes that favor international or factor investing.

• Still well-protected against major market drops.

📌 Summary:
If you want stability, pick Mama Bear.
If you want diversification, try Papa Bear.
Either one is far more tactical and protective than passive buy-and-hold investing.

If you are interested in how momentum strategies generally outperform buy-and-hold, check out our [Dual Momentum Strategy Analysis] for a deeper dive

📘 Glossary for Newer Investors

• CAGR: Compound Annual Growth Rate. Average yearly growth accounting for compounding.

• Max Drawdown: Worst peak-to-trough portfolio loss. Smaller is better.

• Standard Deviation: Volatility; how bumpy the ride is.

• Sharpe Ratio: Reward per unit of total risk.

• Sortino Ratio: Reward per unit of downside risk only.

• Ulcer Index: Measures depth and duration of drawdowns.

• Martin Ratio: Performance adjusted for pain from drawdowns.

• Momentum Strategy: Buys ETFs that have performed best recently.

• ETF: Exchange-Traded Fund. A basket of investments you can trade like a stock.

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About the Author: Peter Richman, MD, MBA is a Professor of Emergency Medicine and former Registered Investment Advisor. At TradeRounds, he applies the same evidence-based diagnostics used in medicine to financial markets.

Author’s Note on Content Creation
I use AI tools like ChatGPT and Gemini to assist with data gathering, historical research validation, and draft refinement. I also regularly review and analyze third-party research, market commentary, and white papers. The final strategies, opinions, and trading insights presented here are entirely my own, grounded in my experience as an investor and educator. AI helps streamline my process, but the conclusions and voice are all mine.

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By most technical definitions, a major market moment just happened: the S&P 500 reclaimed its 200-day moving average (200DMA). Traders and investors often interpret this move as a bullish signal — but like many signals, context is everything.

In this article, we’ll cover:

• What the 200DMA is and why it matters

• What typically happens after the S&P 500 reclaims it

• Whether the May 2025 reclaim qualifies as a "good reclaim"

• What traders should watch for next

What Is the 200-Day Moving Average?

The 200-day moving average (200DMA) is the average closing price of a stock index over the past 200 trading days (about 10 months). It’s widely used to identify long-term trends:

• Above the 200DMA → bullish trend, increasing investor optimism

• Below the 200DMA → bearish trend, concern about the market's direction

It acts as a kind of technical dividing line between long-term uptrends and downtrends (Murphy, Technical Analysis, 1999).

What Does It Mean to "Reclaim" the 200DMA?

A reclaim occurs when the S&P 500, after trading below its 200DMA, crosses back above it. This often signals a potential trend reversal or renewed market strength. However, not all reclaims are created equal.

What Has Happened Historically After 200DMA Reclaims?

Here’s what the historical data shows:

(Sources: Ned Davis Research, Bespoke Investment Group, Strategas Research Partners, 1950–2023)

Reclaims are most reliable when they are:

• Accompanied by strong market breadth (i.e., many stocks also moving above their 200DMA)

• Confirmed with high volume

• Followed by multiple closes above the 200DMA

May 2025: Is This a “Good Reclaim”?

As of May 23, 2025, the S&P 500 has crossed back above its 200DMA, currently sitting at ~5773, with a closing price of 5802.82. Looking at the chart above, several key bullish elements are in place:

• The 20-day and 50-day moving averages are sloping upward, supporting short-term momentum

• The MACD (Moving Average Convergence Divergence) remains in bullish territory, with the signal line trending upward

• RSI (Relative Strength Index) is above 50 (currently 56.1), signaling positive momentum

Moreover, market breadth is improving: over 50% of S&P 500 stocks are now trading above their 200DMA (Bespoke, May 2025). Volume has been moderate but steady, and the reclaim is holding for more than a day — all signs of a potentially strong reclaim.

However, macro headwinds remain:

• Volatility (VIX) has edged higher due to renewed trade tensions, following policy comments by former President Trump suggesting new tariffs (Investor’s Business Daily, May 23, 2025).

• Investor sentiment remains cautious, and recent pullbacks highlight the market’s sensitivity to geopolitical and policy shifts.

Conclusion: While not a perfect setup, this reclaim has many characteristics of a “good reclaim” — breadth, momentum, and moving average alignment — but requires ongoing confirmation. A few more closes above the 200DMA with broad participation would likely convert this from a hopeful rally to a confirmed trend reversal.

Key Terms Explained

• S&P 500: A stock index representing 500 large U.S. companies

• 200DMA: 200-day moving average — used to assess long-term trend direction

• Reclaim: When a price moves back above a key average it had fallen below

• Breadth: % of stocks participating in a move; broad = healthy

• VIX: Volatility Index — measures expected market turbulence

• MACD: Indicator that tracks momentum via convergence/divergence of moving averages

• RSI: Relative Strength Index — a momentum oscillator that identifies overbought/oversold levels

What to Watch Next

1. Closes Above the 200DMA: A sustained hold above the line

2. Breadth Expansion: Ideally 60–70% of stocks above their own 200DMA

3. Macro Stability: Signs of resolution or reduced noise on trade, inflation, and rates

4. Earnings Season: Continued strength from tech and consumer sectors could drive next leg

If you found this helpful, subscribe to TradeRounds for monthly strategy breakdowns, tactical insights, and data-backed technical deep dives — written by a physician-investor who actually reads the footnotes.

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Note: For readers who may not be familiar with all the financial terms used here, I’ve included a helpful glossary at the end of the article.

The financial world loves to warn you against buying at market peaks. Ask any investor and they’ll likely caution, “You never buy at all-time highs…” as if it’s a sacred law of investing.

Meb Faber, founder of Cambria Investment Management, politely disagrees.

I had the pleasure of meeting Meb over 15 years ago, back when he was managing just a few million dollars (he now oversees billions). Even then, I thought: this guy is sharp. He remains one of the best thinkers in tactical investing today and has always been generous in sharing his data-driven research.

In his white paper, “All Time Highs: A Good Time to Invest? No. A Great Time,” Faber lays out one of the simplest yet most contrarian tactical strategies you’ll find: buy assets when they’re near their highs, not after they’ve crashed. Let’s explore the data, the method, the risks, and where things stand today.

💡 What Is the All Time Highs Strategy?

The system is simple:

At the end of each month, check if an index (e.g., U.S. stocks) is within 5% of its all-time high.

• If yes: Stay invested in the asset.

• If no: Move to 10-year U.S. Treasury bonds.

Faber’s backtest from 1926–2019 compared this to standard buy-and-hold investing.

Buy-and-Hold U.S. Stocks:

• Annual Return: 10.07%

• Volatility: 18.65%

• Sharpe Ratio: 0.36

• Maximum Drawdown: -83.66%

All Time High Switch Strategy:

• Annual Return: 9.61%

• Volatility: 10.84%

• Sharpe Ratio: 0.57

• Maximum Drawdown: -29.13%

The takeaway? A small tradeoff in return buys you a huge reduction in “gut-wrenching loss” risk. If you’ve ever watched your portfolio fall 50%+ during a bear market, you understand why this matters.

🌎 It Works Internationally Too

Faber applied the same rule to foreign stocks with even better results.

Foreign Stocks Buy-and-Hold:

• Annual Return: 7.91%

• Volatility: 15.83%

• Sharpe Ratio: 0.28

• Maximum Drawdown: -70.35%

Foreign Stocks All Time High Strategy:

• Annual Return: 9.81%

• Volatility: 10.27%

• Sharpe Ratio: 0.62

• Maximum Drawdown: -30.82%

Not only did risk drop dramatically, but returns actually improved. That’s a rare two-for-one in investing.

🔧 The 12-Month High Variation

One issue with all-time high filters is that markets can stay below prior highs for years (think Japan in the ‘90s).

So Faber also tested switching based on 12-month highs instead. Allocate Smartly’s analysis of this tweak found:

12-Month High Strategy:

• Annual Return: 10.68%

• Volatility: 10.68%

• Sharpe Ratio: 0.62

• Maximum Drawdown: -43.98%

This version kept the risk control benefits but captured more upside after deep drawdowns.

📉 What About the Past Decade?

It’s important to note: most momentum models—including this one—have underperformed since 2010.

U.S. stocks had a historic bull market with few deep corrections. Momentum strategies like Faber’s often exited briefly, only to miss quick rebounds. As Allocate Smartly and others have shown, this led to “whipsaw losses.”

That doesn’t mean the strategy is broken. It reminds us no model works in all environments. Momentum shines in volatile, trending markets, but struggles in long steady rallies.

🛠️ Practical Implementation with ETFs

Thanks to exchange traded funds (ETFs), investors can implement this approach easily.

An ETF (Exchange Traded Fund) is a low-cost basket of assets that trades like a stock.

Here’s a practical ETF lineup for an All Time High or 12-Month High strategy:

Asset Class (choices of ETFs for each)

• U.S. Stocks: SPY, VOO, IVV (S&P 500 stocks)

• Foreign Stocks: EFA, VEA (Developed country international stocks)

• Emerging Markets: EEM, VWO (Emerging market stocks)

• U.S. Bonds: IEF (ten-year U.S. Treasuries), TLT (long-term US Treasuries), AGG (broad bond market)

• Real Estate Investment Trusts (REITs): VNQ, IYR

• Commodities: DBC (broad commodities), GLD (Gold), IAU (Gold)

How do you know if an ETF is within 5% of its high?

You can use:

• Yahoo Finance (free)

• TradingView (charts)

• PortfolioVisualizer.com (backtests + price histories)

• ETF provider websites (Vanguard, iShares)

• Morningstar

Quick DIY method:
Check if current price ÷ recent high ≥ 95%.
Example: SPY all-time high = $480, current price = $460 → 460/480 = 95.8% → stay invested.

This makes the strategy extremely approachable for DIY investors with nothing more than basic spreadsheet skills and access to free online data.

🤝 Buy-and-Hold vs Trend Following? A False Choice.

Faber’s Trinity Portfolio (ETF ticker: TRTY) combines buy-and-hold, momentum, and value investing. Why? Because each strategy takes turns being “in the doghouse.”

That’s also my philosophy: don’t obsess over which strategy is “best.” Build a robust toolkit to give yourself the best chance of long-term success.

📝 The Bottom Line

Meb Faber’s All Time Highs system is no magic bullet. But it may help you avoid catastrophic losses while keeping you in the game.

If you can stick with it—through the inevitable dry spells—you may avoid the fate of countless investors who panic-sell at the worst moments.

To quote Meb’s paper: don’t be the guy who passed on The Beatles to sign The Tremeloes.

📖 Glossary of Key Terms

• Annual Return: Average yearly increase or decrease of an investment.

• Volatility: How much prices fluctuate; high = more risk.

• Sharpe Ratio: A measure of risk-adjusted return.

• Maximum Drawdown: Largest % loss from peak to bottom.

• ETF (Exchange Traded Fund): A fund that holds a basket of assets and trades on an exchange.

• Momentum Strategy: Investing in assets with strong recent performance.

• Buy-and-Hold Strategy: Owning an asset long-term, regardless of price moves.

• Trend-Following Strategy: Buying assets moving higher, selling when they weaken.

• Tactical Asset Allocation: Actively adjusting your mix of assets based on market conditions.

• 12-Month High: The highest price reached by an asset in the last year.

• All Time High: The highest price ever reached by an asset.

• DIY (Do-It-Yourself): A personal, hands-on approach to investing or portfolio management without relying on professional advisors.

📚 Sources

• Faber, M. All Time Highs: A Good Time To Invest? No. A Great Time.

• Allocate Smartly. Meb Faber's 12-Month High Switch (2024)

• Allocate Smartly. Buying Global Stocks at All-Time Highs (2019)

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About the Author: Peter Richman, MD, MBA is a Professor of Emergency Medicine and former Registered Investment Advisor. At TradeRounds, he applies the same evidence-based diagnostics used in medicine to financial markets.

Author’s Note on Content Creation
I use AI tools like ChatGPT and Gemini to assist with data gathering, historical research validation, and draft refinement. I also regularly review and analyze third-party research, market commentary, and white papers. The final strategies, opinions, and trading insights presented here are entirely my own, grounded in my experience as an investor and educator. AI helps streamline my process, but the conclusions and voice are all mine.