For more than a decade following the Global Financial Crisis, markets operated in an environment defined by low inflation, suppressed volatility, and extraordinary policy support. This paper argues that those conditions were not permanent, but rather the product of a unique macroeconomic and policy regime that has since broken down. As supply constraints, persistent inflation, deglobalization, and more active fiscal policy reshape the economic landscape, volatility is increasingly becoming a structural feature of markets rather than a temporary disruption. The result is a growing disconnect between how markets are priced and how the system now functions.

INTRODUCTION

A common view is that the pandemic volatility shock was just that: a shock. An exogenous disruption that temporarily pushed markets and the economy off course, but one that is now largely behind us. Inflation has moderated, markets have stabilized, and it is tempting to believe the system is gradually returning to something like the pre-pandemic environment.

Our view is different. We do not believe the pandemic was a one-off disruption to a stable low-volatility regime but was instead the catalyst that exposed the limits of that regime and forced an exit from it. We will argue in this piece that the stability of the post-GFC period was never a natural equilibrium. It depended on a specific macroeconomic backdrop: weak demand, low inflation, disinflationary globalization, and a policy framework able to suppress volatility and inflate asset prices. Those conditions no longer reliably hold.

The result is not simply a more volatile version of the old environment. It is a different regime: one defined by more binding supply constraints, less stable inflation, more active fiscal policy, and a policy framework that is more constrained and less predictable. In that world, volatility is not as easily suppressed. It becomes a structural feature of the system.

Markets have not fully internalized that shift. Asset prices, risk premia, and portfolio construction still reflect assumptions forged in the post-GFC regime, even as the foundation for those assumptions has eroded. The mismatch between how the system is priced and how it now functions is the central risk this piece explores.

HOW AND WHY THE LOW-VOLATILITY REGIME WAS ENGINEERED

To understand why that regime was transitory, it is necessary to understand what created it. The low-volatility environment that followed the Global Financial Crisis was not simply a byproduct of subdued inflation or calmer markets. It emerged from a specific macroeconomic problem, debt deflation, and a specific policy response, asset price reflation.

Debt deflation is dangerous because falling asset prices weaken balance sheets, force deleveraging, reduce credit creation, and push asset prices lower still, creating a self-reinforcing downward spiral. The policy response was therefore clear. If falling asset prices were the problem, rising asset prices were the solution. After the GFC, the Federal Reserve and other major central banks pursued that goal through zero- and negative-rate policy, quantitative easing, forward guidance, and direct asset purchases. These tools did not just stimulate demand. They changed the market pricing of risk: duration risk, term premia, credit risk, equity risk, and volatility itself. Policymakers were not simply trying to restart growth. They were trying to reflate the asset base of the economy.

The Mechanics of Volatility Suppression

Put another way, the tools used to stabilize the post-GFC economy worked in part by suppressing specific market risks. Policymakers could not quickly improve the fundamentals underlying asset prices, but with trillion-dollar balance sheets, they could engineer higher prices by distorting the risks embedded in those prices. Quantitative easing reduced duration risk by removing long-term bonds from the market, inflating the price of duration and, by extension, all long-duration assets from bonds to low-current-cash-flow equities and beyond. Forward guidance compressed uncertainty around the future path of short rates, lowering term premia, and making near-term cash flows less attractive relative to more uncertain, longer-duration ones. Zero-rate policy reduced the time value of money and pushed investors outward along the risk curve. Together, by broadly compressing risk premia, these policies lowered credit spreads, inflated valuations for the longest-duration equities, reinforced the correlation structure that underpinned risk parity and 60/40 portfolios, supported private equity, and made volatility itself appear less risky. But because that market structure depended on inflation remaining low enough for policymakers to keep suppressing risk, it was always more conditional than it appeared.

The Pandemic and the Regime Shift

The pandemic initially triggered an even more aggressive version of the post-GFC policy response. Rates returned to zero, the Fed’s balance sheet nearly doubled from roughly $4 trillion to almost $9 trillion, and fiscal policy was deployed on a scale far beyond the prior cycle, with pandemic relief legislation totaling roughly $5 trillion versus less than $1 trillion for the American Recovery and Reinvestment Act after the GFC.

But unlike the post-GFC period, the result was not a prolonged demand shortfall and subdued inflation. It was a rapid recovery in nominal demand, disrupted supply, and the first sustained inflation shock in decades. Once inflation became binding, the Fed was forced to reverse the very policies that had supported the low-volatility regime. Rates rose sharply, balance sheet policy shifted from expansion to runoff, term premia began to reprice, and the negative stock-bond correlation that underpinned the 60/40 portfolio broke down. In 2022, a traditional 60/40 portfolio declined roughly 16–18%, depending on construction, one of its worst performances in modern history. Morgan Stanley estimated 2022 was the worst year for a 60/40 portfolio since 1937 and the fourth-worst in roughly 200 years¹.

The issue was not simply that the pandemic was an extreme shock. It was that an extreme shock hit a market structure engineered to treat extreme shocks as unlikely, temporary, and ultimately containable. In that sense, the pandemic did not merely interrupt the low-volatility regime; it exposed the condition on which it had always depended: inflation had to remain low enough for policymakers to keep suppressing market risk.

As markets stabilized, it became tempting to view the pandemic and inflation shock as a one-off disruption to an otherwise durable low-volatility regime. But the low-volatility regime was not a stable equilibrium to which the economy would necessarily naturally return. In this piece, we will argue that low-volatility regime was a conditional construct that depended on macroeconomic and policy conditions that no longer reliably exist. Put simply, when low and stable inflation can no longer be taken for granted, the asset-inflating policies that defined the post-GFC regime can no longer be relied upon either.

The sections that follow explain why the conditions that made volatility suppression possible have eroded.

WHY THE CONDITIONS THAT SUPPRESSED VOLATILITY HAVE BROKEN DOWN

The low-volatility regime was not a naturally occurring phenomenon but was instead the product of a policy framework designed to suppress market risk and inflate asset prices. While policymakers still want to support markets, the question is whether they can still do so without creating larger problems elsewhere. In a higher-inflation environment, easing policy to support markets can backfire by reigniting inflation pressure, pressuring bond yields, and creating new instability. Thus, even as the desire for a policy put may still exist, exercising that put now risks creating the very instability it is meant to prevent.

2. Inflation Can No Longer Be Treated as Dormant

Inflation can no longer be assumed to be safely contained. In the post-GFC period, inflation was persistently too low: core PCE inflation averaged below the Fed’s 2% target for most of the decade following the crisis, even as unemployment fell below 4% by 2018. Structural forces like demographics, globalization, technology, and anchored expectations were keeping inflation subdued and the persistence of those factors gave the Fed and other major central banks room to keep policy easy, use forward guidance and balance-sheet expansion. Those policies suppressed volatility and supported asset prices with few immediate inflationary consequences.

The pandemic broke that assumption. It showed that when policy supports demand into a constrained supply environment, inflation can re-emerge quickly and forcefully. More importantly, it showed that inflation is not as inert as previously believed. It is not simply a lagging outcome that can be managed over time, but a variable that can move rapidly when conditions change.

Inflation is No Longer Consistently Low and Stable

The pandemic may also have changed pricing behavior itself. After a long period in which firms were reluctant to raise prices and consumers were conditioned to expect price stability, the inflation shock made price increases more visible, more frequent, and more accepted as a response to cost pressure. That does not mean inflation will remain high indefinitely, but it does suggest pricing behavior may be more dynamic than it was during the post-GFC period. In that environment, inflation can become less inert and more responsive to shocks.

Core PCE Inflation (%y/y)

This fundamentally changes the policy framework. There is an obvious incentive, from both policymakers and markets, to return to the pre-pandemic model. But as the economy has suffered from persistent supply constraints, inflation has also proven more persistent than hoped. At the same time, asset markets remain acutely sensitive to sharp moves higher in government bond yields, and policymakers can no longer assume that weakness in growth or markets will automatically create room to ease. The Fed is now operating with a constraint that was largely absent in the post-GFC period: the risk that policy support itself reignites inflation.

4. Fiscal Policy Has Become a Source of Volatility

Another important shift is the role of fiscal policy. In the post-GFC period, fiscal policy was generally more constrained, particularly in the U.S. After the initial crisis response, many advanced economies moved toward austerity or at least fiscal restraint, in part because markets had become more intolerant of high and rising sovereign debt burdens. Europe was the clearest example: countries with the weakest fiscal positions experienced the sharpest sovereign bond-market volatility, with spreads and yields in countries like Italy and Greece rising sharply, while countries with stronger balance sheets were less exposed. That distinction matters because it shows that fiscal sustainability itself can become a source of market instability. In the post-GFC period, that pressure pushed policy toward restraint, reinforcing the demand shortfall and reducing pressure on inflation.

Fiscal restraint also supported the low-volatility goals of monetary policy more directly. Lower deficits meant reduced Treasury issuance, which helped keep term premia and duration risk contained. Combined with QE, this created a powerful dynamic: central banks were removing duration from the market at the same time that governments were not meaningfully increasing its supply. The result was a structurally lower level of long-term yields, compressed risk premia, and reduced rate volatility. Fiscal and monetary policy were aligned in actively suppressing market risk.

Annual Fiscal Deficits Remain Historically Large Outside Recession

That alignment has broken down. Fiscal policy has become larger, more persistent, and less tied to the cyclical stabilization role it played in the post-GFC framework. The pandemic marked a clear turning point, with deficits expanding dramatically and fiscal support continuing well into the recovery. Since then, fiscal policy has remained active through industrial policy, defense spending, energy transition investments, and supply-chain resilience programs, including legislation such as the CHIPS Act, the Inflation Reduction Act, and increased defense commitments.

Federal Debt to GDP Exceeded 100% This Year, The First Time Since WWII

The issue is not just the scale of fiscal policy, but also its composition. More recent fiscal support has often been directed toward defense, transfers, subsidies, industrial policy, and energy security rather than higher-multiplier public investment. To the extent that this spending sustains demand without generating a commensurate increase in near-term supply, it can be more inflationary and less growth-enhancing. That makes fiscal policy a less reliable stabilizer and a more direct source of volatility.

Fiscal policy now works in the opposite direction of the post-GFC regime. Instead of reinforcing demand weakness, it can amplify demand at a time when supply is already constrained. Larger deficits also mean increased Treasury issuance, which can put upward pressure on long-end yields even as the Fed attempts to manage financial conditions. In that environment, efforts to support markets, whether through easier monetary policy, fiscal stimulus, or public pressure to keep financial conditions loose, can be offset or even overwhelmed by the bond market’s reaction to fiscal expansion.

Interest Costs are Climbing Towards Levels Last Seen During the Inflation Crisis

Taken together, these changes mean the policy framework that suppressed volatility after the GFC has fewer degrees of freedom. Weak demand, low inflation, elastic global supply, fiscal restraint, and stable financial conditions gave policymakers room to ease aggressively without immediately creating offsetting risks. That room has narrowed. Policy support can still stabilize markets, but it can also push demand into bottlenecks, reignite inflation pressure, raise long-end yields, weaken credibility, or force a larger adjustment later. The policy put has not disappeared, but it has become more costly to exercise and therefore less reliable.

MARKETS ARE STILL PRICED FOR THE OLD REGIME

If the post-GFC regime was defined by suppressed volatility, compressed risk premia, and a policy framework that reliably supported asset prices, then the implications of its reversal are not subtle. Markets are still priced as if much of that regime remains intact, even as the conditions that supported it have weakened.

The starting point is the price of risk. Risk premia are often discussed as abstract valuation concepts, but in practice they determine how much leverage the system can support, how expensive hedging is, how tight credit spreads can remain, how high equity multiples can go, and how low long-end yields can stay. When risk premia are compressed, the same cash flows support higher asset prices. When risk premia rise, those prices fall, even if the cash flows themselves have not changed.

Term premia are the clearest example. By 2019, term premia had fallen to roughly -150 basis points, a level difficult to justify under any normal understanding of risk pricing. Investors were not merely receiving too little compensation for duration risk. They were effectively paying to hold it. As inflation returned and the Fed tightened policy, term premia moved toward roughly +50 basis points. That repricing was part of the broader rate shock that helped break the traditional 60/40 portfolio in 2022.

Markets may be treating that repricing as finished when it was only the first adjustment. Even after the move from deeply negative levels, term premia remain well below longer-run averages and far below levels reached when inflation risk was priced more aggressively. What markets are treating as a completed adjustment may still reflect a significant degree of complacency. If the macro environment has changed, a further move higher in term premia would raise long-end yields even without a change in expected short rates, tighten financial conditions, pressure equity multiples, and force investors to reprice long-duration assets across the system.

ACM 10yr Treasury Term Premium

That is why term premia matter. They are not an abstract bond-market concept. They are one of the prices that determine the valuation of every long-duration asset in the system. When term premia are low, long-duration assets look safer, equity multiples can rise, bonds can hedge equities, credit spreads can remain tight, and leverage can build. When term premia rise, all of that changes.

This is the broader mistake markets may be making. Many of the features investors came to treat as constants were actually regime-specific variables. Negative stock-bond correlation was not a permanent law of portfolio construction; it depended on low and stable inflation. Higher valuations for long-duration equities were not a permanent feature of superior business models; they depended on low discount rates and low required returns. Tight credit spreads were not simply evidence of stronger corporate fundamentals; they were partly the result of investors being pushed outward along the risk curve. Private equity valuations were not insulated from the public-market regime; they were one of its clearest expressions.

That is the key point. The post-GFC regime did not just raise asset prices. It changed the way investors understood risk. It made duration look safer, leverage look more sustainable, illiquidity look less costly, and volatility look more suppressible. Those assumptions worked because inflation was low, policy was predictable, and central banks could respond to weakness by easing. If those conditions no longer hold, then the assumptions built on top of them no longer hold either.

THIS IS HOW THE OLD ASSUMPTIONS BREAK

If the assumptions of the post-GFC regime are still embedded in prices, then the consequences are not theoretical. Many assets and portfolios still reflect assumptions about inflation, policy, and risk that no longer reliably hold. As those assumptions are tested, the adjustment will show up in how risk is priced across markets. Some of that adjustment has already happened. The mistake is assuming it is finished.

3. Diversification Still Depends on the Inflation Regime

One of the most important assumptions carried forward from the post-GFC period was that bonds would reliably diversify equity risk. That assumption mattered most for risk parity and other volatility-targeted strategies, which depended not only on bonds rallying when equities fell, but on the stock-bond correlation remaining stable enough to support leverage. The traditional 60/40 portfolio benefited from the same structure, but risk parity, which gained traction in the post-GFC period, was more directly exposed to it. When inflation shocks pushed stocks and bonds down together in 2022, the problem was not simply that bonds failed to hedge equities. It was that a core input into the portfolio construction process had changed.

Rolling Monthly Stock Bond Correlation

That relationship is not a law of nature. It depends on the inflation regime. In a low and stable inflation environment, shocks tend to be growth shocks. Policy can ease in response, bond yields fall, and bonds hedge equities. That dynamic underpinned the performance of balanced portfolios for much of the post-GFC period.

In a higher and less stable inflation environment, that relationship becomes less reliable. Shocks are more likely to be inflation shocks, or a combination of inflation and growth. In that case, policy cannot respond as easily, bond yields can rise alongside equity volatility, and the hedge weakens or disappears.

That is what happened in 2022, when both stocks and bonds declined sharply. The point is not that diversification no longer works. It is that diversification is conditional. Portfolios that appear diversified across asset classes may still be concentrated in a single underlying assumption: that inflation remains low and that policy can respond to weakness without constraint.

The economy is increasingly leveraged to asset prices not falling, while the tools used to support those prices are increasingly constrained by inflation, deficits, and the bond market. That is the tension running through this regime shift. The policy put has not disappeared, but it is less reliable, less powerful, and more costly to exercise. The excesses of the post-GFC regime have not been fully unwound. They have been carried forward into a new environment that is less capable of sustaining them. Markets are still priced for stability in a system that is becoming structurally less stable.

CONCLUSION

After a rupture, continuity is the most seductive illusion: the belief that the old order is still there, temporarily obscured but fundamentally intact. For more than a decade, that instinct was not only understandable; it was profitable. It was also enforced by central banks, which penalized investors who positioned against it. The post-GFC regime trained investors to think in a certain way: buy duration, buy dips, own the market, accept illiquidity, add leverage, trust that bonds would hedge equities, and assume that policymakers would eventually step in. Those were not irrational choices. They were the correct choices for a world of low inflation, weak demand, compressed risk premia, and policy-suppressed volatility. But they were regime-specific choices, not universal truths — and habits formed in one regime can become liabilities in the next.

If the regime has changed, then the question is not whether 60/40 is “dead,” whether equities are “too expensive,” or whether bonds “work” again. Those questions are too narrow. The better question is whether investors are still using a playbook built for a world that no longer exists. A 60/40 portfolio may still look diversified, but if both sides depend on low inflation and low term premia, it is less diversified than it appears. Private assets may still look smooth, but smoothing is not the same thing as safety. Long-duration equities may still have great businesses behind them, but great businesses can still be bad assets at the wrong discount rate.

The trade, broadly speaking, is not to assume disaster. It is to stop assuming rescue. It is to stop treating volatility as a policy mistake that will always be corrected and start treating it as a feature of the new environment. That means caring more about valuation, cash flow timing, liquidity, inflation sensitivity, and whether the hedge is really a hedge. It means recognizing that many portfolios that look diversified by asset class may actually be concentrated in one underlying exposure: the assumption that risk will remain underpriced.

Regime changes are rarely recognized cleanly in real time. They often arrive as a series of events that look separate at first: an inflation shock, a bond bear market, a 60/40 drawdown, a yield spike, a growth scare. Each can be explained away on its own. But taken together, they may be evidence of something larger: not repeated disruptions to the old regime, but the emergence of a new one.

The low-volatility regime made leverage look prudent, illiquidity look safe, long-duration cash flows look inherently superior, and diversification look almost automatic. A higher-volatility regime is likely to reverse that illusion. It does not eliminate opportunity, but it changes where opportunity lies. It favors assets whose returns come from current cash flows and reasonable starting valuations, not from falling discount rates, multiple expansion, or policy rescue. The opportunities will still be there, but not for portfolios built on yesterday’s assumptions. Those assumptions will be obstacles, not guides.

IMPORTANT DISCLOSURE

REFERENCES​

¹ Morgan Stanley Investment Management. ‘BIG PICTURE: Return of the 60/40.’ Morgan Stanley Investment Management, April 2024, https://www.morganstanley.com/im/publication/insights/articles/article_bigpicturereturnofthe6040_ltr.pdf. Accessed 5/13/2026.

² Bloomberg. ‘US Data Center Boom Relies on Hard-to-Find Electrical Equipment.’ Bloomberg, April 1, 2026, https://www.bloomberg.com/news/newsletters/2026-04-01/us-data-center-boom-relies-on-hard-to-find-electrical-equipment. Accessed 5/13/2026.

³ Board of Governors of the Federal Reserve System. ‘Labor Force Growth, Breakeven Employment, and Potential GDP Growth.’ Federal Reserve, April 2, 2026, https://www.federalreserve.gov/econres/notes/feds-notes/labor-force-growth-breakeven-employment-and-potential-gdp-growth-20260402.html. Accessed 5/13/2026.

⁴ U.S. Bureau of Labor Statistics. ‘Notice of CPI Collection Reductions.’ Bureau of Labor Statistics, 2025, https://www.bls.gov/cpi/notices/2025/collection-reduction.htm. Accessed 5/13/2026.

⁵ Board of Governors of the Federal Reserve System. ‘Labor Market Data: Signal or Noise?’ Federal Reserve, February 23, 2026, https://www.federalreserve.gov/newsevents/speech/waller20260223a.htm. Accessed 5/13/2026.

⁶ J.P. Morgan Asset Management. ‘Guide to the Markets.’ J.P. Morgan Asset Management, https://am.jpmorgan.com/us/en/asset-management/adv/insights/market-insights/guide-to-the-markets/. Accessed 5/13/2026.

⁷ Shiller, Robert. ‘Online Data Robert Shiller.’ Yale University Department of Economics, http://www.econ.yale.edu/~shiller/data.htm. Accessed 5/13/2026.

LEGAL DISCLAIMER

This presentation includes statements that may constitute forward-looking statements. These statements may be identified by words such as “expects,” “looks forward to,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates,” “will,” “project” or words of similar meaning. In addition, our representatives may from time to time make oral forward-looking statements. Such statements are based on the current expectations and certain assumptions of Graham’s management, and are, therefore, subject to certain risks and uncertainties. A variety of factors, many of which are beyond Graham’s control, affect the operations, performance, business strategy and results of the accounts that it manages and could cause the actual results, performance or achievements of such accounts to be materially different from any future results, performance or achievements that may be expressed or implied by such forward-looking statements or anticipated on the basis of historical trends.
This document is not a private offering memorandum and does not constitute an offer to sell, nor is it a solicitation of an offer to buy, any security. The views expressed herein are exclusively those of the authors and do not necessarily represent the views of Graham Capital Management. The information contained herein is not intended to provide accounting, legal, or tax advice and should not be relied on for investment decision making.

Trend-following is among the most established and longest-standing investment strategies, with an estimated $350 billion¹ in assets under management globally. Rooted in the premise that markets tend to exhibit persistent directional movements over time, trend-following seeks to capture these trends across a broad set of asset classes using disciplined, rules-based processes. By taking both long and short positions in liquid global markets, the strategy has historically demonstrated low correlation to traditional assets and the ability to perform across a range of market environments. As investors increasingly seek diversification and resilience in portfolios, trend-following has become a strategic allocation within many institutional investment frameworks. This primer outlines the key characteristics of trend-following and explores how the strategy can impact a broader investment portfolio when implemented as a long-term, strategic allocation.

WHAT IS TREND-FOLLOWING?​

Trend-following strategies use a systematic process, whereby algorithmic models seek to identify price trends in markets, with the expectation that upward trending markets may continue to rally and downward trending markets may continue to decline. These strategies take long positions in positively trending markets and short positions in negatively trending markets, using indicators based on price and volatility of the underlying assets to identify trends of various lengths. Trend followers seek to run diverse portfolios, typically trading liquid, centrally-cleared futures and currency markets, with the number of markets potentially ranging from tens to hundreds. These strategies often target consistent volatility within a predetermined range and try to preserve upside potential and limit downside risk by running with winners and cutting losing positions.

Theoretical Foundation: Why Do Markets Trend?
Trend-following performance depends on the existence of trends, or sustained directional moves in markets. Trends may exist both in times of market duress or during relatively stable market environments. A substantial body of academic research supports the existence of trends and offers several explanations for why they persist across asset classes:

• Behavioral Bias and Herding Investors extrapolate recent price movements into the future and “follow the crowd,” reinforcing trends (Barberis, Shleifer, and Vishny, 1998; Bikhchandani, Hirshleifer, and Welch, 1992).
• Anchoring and Underreaction Investors adjust too slowly to new information, leading prices to trend as markets gradually incorporate news (Tversky and Kahneman, 1974; Hong and Stein, 1999).
• Disposition Effect Investors sell winners too early and hold onto losers (Frazzini, 2006).
• Risk Management Risk constraints can force investors to buy or sell assets as volatility or risk limits change, amplifying existing price moves (Danielsson, Shin, and Zigrand, 2012).
• Macroeconomic Regimes Shifts in monetary and fiscal policy can drive sustained trends across asset classes as markets reprice growth and inflation expectations (Ang and Bekaert, 2007).
• Time-Varying Risk Premia Changes in the compensation investors require to hold risky assets can lead to prolonged price movements across asset classes (Moskowitz, Ooi, and Pedersen, 2012).

Together, these behavioral and structural forces help explain why trends can emerge and persist, forming the foundation for trend-following strategies.

Illustrative Example: Why Trends Exist

TREND IDENTIFICATION

Trend-following strategies identify trends by systematically analyzing historical market prices. Algorithms evaluate price movements over lookback periods ranging from intraday to several months to determine whether a market is exhibiting sustained upward or downward momentum. When prices rise consistently, models may take long positions; when prices decline, they may take short positions.

Models also incorporate price volatility and other risk measures to determine position sizing and overall portfolio exposure. More volatile markets typically receive smaller allocations, while less volatile markets may receive larger/f positions to maintain balanced risk across a diversified set of assets such as equities, interest rates, currencies, and commodities.

Illustrative Example: How Trends are Identified

Signal Generation

Moving average and breakout models are two prominent strategies used by most trend-followers for initial signal generation. While these models may be parameterized differently, the raw signals generated are often highly correlated over time because of their common dependence on past prices.

Breakout models compare the current price with a threshold to signal long, short, or no position. The threshold is determined by either a “price breakout” (past maximum or minimum price) or “channel breakout” (past price at a given lookback and trading range.)

Moving Average Models use moving averages of past prices to generate a trading signal. The difference between two moving averages, a “fast” and a “slow” one, determines a long or a short position. A crossover between the two will signal a trend reversal.

While these approaches differ in construction, they share a common objective: detecting persistent directional movement in prices. A key factor influencing how these models behave is the speed at which they respond to new information, which is largely determined by parameter choices such as lookback windows and signal thresholds.

THE SPEED OF TREND-FOLLOWING

A key dimension of trend-following strategies is speed, which refers to how quickly a model responds to emerging price movements. Speed is primarily determined by model parameters such as the length of moving averages and breakout lookback windows. Models that use shorter lookback periods are typically considered faster (short-term trend-following), as they respond more quickly to recent price changes and may identify new trends earlier. Slower models, which rely on longer lookback horizons (long-term trend-following), tend to react more gradually but may be less sensitive to short-term market noise. As a result, faster models can adapt more quickly to changing market conditions but may experience more frequent position changes and potential “whipsaws,” while slower models may capture longer, more persistent trends with fewer trades.

Signal Speed and Market Conditions

Evidence across time suggests that model speed can influence performance depending on market conditions. As shown in the heatmap below, which compares the performance of trend models across different time horizons, intermediate- to longer-term models have, on average, fared better than shorter-term models. When longer-term signals performed well, faster models often produced similar gains, though the reverse was less frequently the case.

However, faster models can be particularly valuable during periods of sudden market dislocation, when trends emerge quickly. For example, during episodes of sharp market stress such as the early stages of the COVID-19 crisis in 2020, faster signals were able to react more quickly. As a result, incorporating shorter-term models can help strategies respond more quickly during abrupt market events, complementing slower models that capture more persistent trends.

Return Heatmap: Model Time-Frames Performance²

As a result, when selecting the speed of trend signals, many managers use a blend of signal speeds to balance responsiveness, cost efficiency, and robustness across different market environments.

MARKETS TRADED

Trend-following typically trades a diversified set of liquid global markets, most commonly through exchange-traded futures and forwards. These instruments provide efficient access to major asset classes, including equities, fixed income, currencies, and commodities, and allow trend-followers to take both long and short positions. Because futures markets are liquid, centrally cleared, and relatively low cost to trade, portfolios often include dozens – or up to hundreds – of markets across global regions. Diversification across markets is a core feature of trend-following, as trends can emerge in different asset classes at different times.

Markets Commonly Traded by Trend-Followers

Considerations in Market Selection
Considerations for including markets in a trend-following portfolio include the potential alpha opportunity, correlation with existing holdings, liquidity, price history, transaction costs, and operational complexity. While some alternative or niche markets may exhibit strong trends, they can be more difficult to trade at scale due to lower liquidity, wider spreads or operational complexity. As a result, managers must weigh the incremental diversification and return potential against implementation challenges and costs. Legal and regulatory constraints also play an important role, as certain instruments or jurisdictions may impose restrictions on derivatives usage, margin requirements, reporting, or fund structures, particularly in vehicles such as UCITS or ‘40 Act funds. These considerations can influence which markets are included and how exposures are implemented within a given strategy.

PORTFOLIO CONSTRUCTION

Beyond choices related to signal generation, model speed, and the markets traded, portfolio construction plays a critical role in determining how signals are combined across the portfolio, how risk is allocated across markets, and how exposures are scaled while maintaining disciplined risk management.

Combining and Weighting Signals
Managers must determine how to combine and weight signals from multiple models and time horizons into a composite forecast that reflects the overall strength and direction of trends in each market. Considerations include historical signal quality, volatility and correlation to other signals, among other factors. Combining signals helps reduce reliance on any single model specification and can improve the consistency of trend detection.

Volatility Targeting and Leverage
Many trend-following strategies employ volatility targeting to maintain a relatively stable level of portfolio risk. Position sizes are scaled based on the volatility of each market, so more volatile assets receive smaller allocations and less volatile markets receive larger positions. Because futures markets require relatively little margin to gain exposure, leverage is often used to scale the overall portfolio to a target level of risk.

Volatility targeting can be implemented in different ways. Managers may differ in how volatility is measured and targeted across time horizons to balance responsiveness and stability, with the choice reflecting a preference for either stability or adaptability to changing market environments while maintaining overall portfolio risk within a desired range. Some managers use constant volatility targeting, adjusting exposures to maintain a fixed portfolio volatility level over both short and long time horizons. Others use dynamic volatility targeting, allowing the volatility to vary with market conditions or changes in risk estimates.

Risk Management
Managers typically apply risk controls such as position limits for individual markets, caps on sector or asset class exposure, and portfolio-level constraints. These measures help prevent excessive concentration in correlated markets and aim to ensure that portfolio risk remains diversified and controlled across changing market environments.

PERFORMANCE CHARACTERISTICS OF TREND-FOLLOWING

Trend-following has historically shown low correlation to traditional assets and the ability to perform in both rising and falling markets. Over time, it has delivered positive long-term returns with convex performance during sustained trends, including periods of market stress.

Please note: Equities and bonds are represented by the MSCI World Index and the Bloomberg Global Aggregate Index, respectively, unless otherwise noted. Please refer to the important disclosures at the end of this presentation.

IMPLEMENTATION CONSIDERATIONS

Because the market universe is liquid and the rules-based investment approach is scalable, many trend following funds available through liquid investment vehicles – including managed accounts, UCITS and ‘40Act (mutual fund) structures – with daily, weekly or monthly liquidity without lockups, gates or other constraints. These formats often translate to a high degree of transparency, including position-level reporting, and competitive fee structures.

Favorable Investment Structure

IMPLICATIONS FOR AN INVESTMENT PORFTOLIO

Traditional portfolios typically allocate to bonds to protect capital during equity downturns. However, the incorporation of asset classes beyond stocks and bonds can create many more opportunities for diversification in a portfolio. Over the long-term, allocating to trend following with a buy and hold approach over time has the potential to enhance returns while reducing volatility, drawdowns, and beta to equities.
Importantly, the value of trend-following lies not only in its return potential but in its diversifying role across market environments. By participating in both upward and downward trends across global asset classes, trend following can provide a complementary return stream that behaves differently from traditional assets, particularly during periods of sustained market stress or macroeconomic transition. As a result, incorporating trend-following within a broader portfolio may improve overall resilience, helping investors navigate a wider range of market conditions while maintaining a more balanced risk profile over time.

Impact on a Stock/Bond Portfolio

Since SG Trend Index Inception (Jan-00 to Dec-25)

IMPORTANT DISCLOSURE

REFERENCES​

¹ Total AUM in Trend-Following Strategies is sourced from BarclayHedge and represents estimated assets under management for the managed futures industry utilizing AUM information provided by contributing CTA managers as of September 30 2025.

² Societe Generale Prime Services & Clearing (2025). Keeping Up With the Trend-Followers: CTA Industry Update. Societe Generale Corporate & Investment Banking.
Barberis, Nicholas, Andrei Shleifer, and Robert Vishny. A Model of Investor Sentiment. Journal of Financial Economics 49, no. 3 (1998): 307–343.
Tversky, Amos, and Daniel Kahneman. Judgment under Uncertainty: Heuristics and Biases. Science 185, no. 4157 (1974): 1124–1131.
Hong, Harrison, and Jeremy C. Stein. A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets. Journal of Finance 54, no. 6 (1999): 2143–2184.
Frazzini, Andrea. The Disposition Effect and Underreaction to News. Journal of Finance 61, no. 4 (2006): 2017–2046.
Bikhchandani, Sushil, David Hirshleifer, and Ivo Welch. A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades. Journal of Political Economy 100, no. 5 (1992): 992–1026.
Danielsson, Jon, Hyun Song Shin, and Jean-Pierre Zigrand. Endogenous Risk. In Handbook of the Economics of Finance, Vol. 2, edited by George M. Constantinides, Milton Harris, and René M. Stulz, 292–317. Amsterdam: Elsevier, 2012.
Ang, Andrew, and Geert Bekaert. Stock Return Predictability: Is It There? Review of Financial Studies 20, no. 3 (2007): 651–707.
Moskowitz, Tobias J., Yao Hua Ooi, and Lasse Heje Pedersen. Time Series Momentum. Journal of Financial Economics 104, no. 2 (2012): 228–250.

LEGAL DISCLAIMER

Source of data: Graham Capital Management (“Graham”), unless otherwise stated
This document is neither an offer to sell nor a solicitation of any offer to buy shares in any fund managed by Graham and should not be relied on in making any investment decision. Any offering is made only pursuant to the relevant prospectus, together with the current financial statements of the relevant fund and the relevant subscription documents all of which must be read in their entirety. No offer to purchase shares will be made or accepted prior to receipt by the offeree of these documents and the completion of all appropriate documentation. The shares have not and will not be registered for sale, and there will be no public offering of the shares. No offer to sell (or solicitation of an offer to buy) will be made in any jurisdiction in which such offer or solicitation would be unlawful. No representation is given that any statements made in this document are correct or that objectives will be achieved. This document may contain opinions of Graham and such opinions are subject to change without notice. Information provided about positions, if any, and attributable performance is intended to provide a balanced commentary, with examples of both profitable and loss-making positions, however this cannot be guaranteed.

It should not be assumed that investments that are described herein will be profitable. Nothing described herein is intended to imply that an investment in the fund is safe, conservative, risk free or risk averse. An investment in funds managed by Graham entails substantial risks and a prospective investor should carefully consider the summary of risk factors included in the Private Offering Memorandum entitled “Risk Factors” in determining whether an investment in the Fund is suitable. This investment does not consider the specific investment objective, financial situation or particular needs of any investor and an investment in the funds managed by Graham is not suitable for all investors. Prospective investors should not rely upon this document for tax, accounting or legal advice. Prospective investors should consult their own tax, legal accounting or other advisors about the issues discussed herein. Investors are also reminded that past performance should not be seen as an indication of future performance and that they might not get back the amount that they originally invested. The price of shares of the funds managed by Graham can go down as well as up and be affected by changes in rates of exchange. No recommendation is made positive or otherwise regarding individual securities mentioned herein.

This presentation includes statements that may constitute forward-looking statements. These statements may be identified by words such as “expects,” “looks forward to,” “anticipates,” “intends,” “plans,” “believes,” “seeks,” “estimates,” “will,” “project” or words of similar meaning. In addition, our representatives may from time to time make oral forward-looking statements. Such statements are based on the current expectations and certain assumptions of Graham’s management, and are, therefore, subject to certain risks and uncertainties. A variety of factors, many of which are beyond Graham’s control, affect the operations, performance, business strategy and results of the accounts that it manages and could cause the actual results, performance or achievements of such accounts to be materially different from any future results, performance or achievements that may be expressed or implied by such forward-looking statements or anticipated on the basis of historical trends.

Tables, charts and commentary contained in this document have been prepared on a best efforts basis by Graham using sources it believes to be reliable although it does not guarantee the accuracy of the information on account of possible errors or omissions in the constituent data or calculations. No part of this document may be divulged to any other person, distributed, resold and/or reproduced without the prior written permission of Graham.

INDEX DISCLOSURE​

The below are widely used indices that have been selected for comparison purposes only. Indices are unmanaged, and one cannot invest directly in an index. Except for HFR indices, which do reflect fees and expenses, the indices do not reflect any fees, expenses or sales charges. Unlike most asset class indices, hedge fund indices included in this presentation have limitations, which should be considered in connection with their use in this presentation. These limitations include survivorship bias (the returns of the indices may not be representative of all the hedge funds in the universe because of the tendency of lower performing funds to leave the index); heterogeneity (not all hedge funds are alike or comparable to one another, and the index may not accurately reflect the performance of a described style); and limited data (many hedge funds do not report to indices, and the index may omit funds which could significantly affect the performance shown; these indices are based on information self-reported by hedge fund managers which may decide at any time whether or not they want to continue to provide information to the index). These indices may not be complete or accurate representations of the hedge fund universe and may be affected by the biases described above.

BLOOMBERG GLOBAL AGGREGATE INDEX (“GLOBAL BONDS”): The Bloomberg Global Aggregate Index is a broad-based market capitalization weighted measure of the global investment grade fixed-rate debt markets. This multi-currency benchmark includes treasury, government-related, corporate and securitized fixed-rate bonds from both developed and emerging markets issuers. There are four regional aggregate benchmarks that largely comprise the Global Aggregate Index: The US Aggregate, the Pan-European Aggregate, the Asian-Pacific Aggregate and the Canadian Aggregate Indices. The Global Aggregate Index also includes Eurodollar, Euro-Yen, and 144A Index-eligible securities, and debt from five local currency markets not tracked by the regional aggregate benchmarks (CLP, MXN, ZAR, ILS and TRY).
BLOOMBERG US AGGREGATE BOND INDEX (“U.S. BONDS”): The Bloomberg US Aggregate Bond Index is a broad-based flagship benchmark that measures the investment grade, US dollar denominated, fixed-rate taxable bond market. The index includes Treasuries, government-related and corporate securities, fixed rate agency MBS, ABS and CMBS (agency and non-agency).
HFRI FUND WEIGHTED COMPOSITE INDEX (“HEDGE FUNDS”): The HFRI Fund Weighted Composite Index is an equal-weighted index that includes over 2000 constituent funds which have at least $50M under management or have been actively traded for at least 12 months. The e are no fund of funds included in this index. All funds are reported in USD and returns are reported net of all fees on a monthly basis. Individuals cannot invest directly into this index.
MSCI WORLD INDEX (“GLOBAL EQUITIES”): A market cap weighted stock market index of 1,652 global stocks and is used as a common benchmark for ‘world’ or ‘global’ stock funds. The index includes a collection of stocks of all the developed markets in the world, as defined by MSCI. The index includes securities from 23 countries but excludes stocks from emerging and frontier economies.
S&P 500 TOTAL RETURN INDEX (“U.S. EQUITIES”): An unmanaged, market value-weighted index measuring the performance of 500 U.S. stocks chosen for market size, liquidity, and industry group representation.  Includes the reinvestment of dividends. The S&P 500 index components and their weightings are determined by S&P Dow Jones Indices.
60/40 PORTFOLIO or GLOBAL 60/40 PORTFOLIO:  Reflects a hypothetical portfolio with a 60% allocation to equities and a 40% allocation to bonds as represented by the MSCI World Index and the Bloomberg Global Aggregate Index, rebalanced monthly. Performance of the underlying stock and bond indices is calculated on a gross basis and includes the reinvestment of dividends. This is a hypothetical composite portfolio that is not investable. Please refer to important disclosures at the end of this document regarding hypothetical performance.
HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS. NO REPRESENTATION IS BEING MADE THAT ANY ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY ACHIEVED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS WHICH CAN ALSO ADVERSELY AFFECT TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS AND ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS.
Equities and bonds are represented by the MSCI World Index and the Bloomberg Global Aggregate Index, respectively, unless otherwise noted.

Key themes include:

• Macro Relevance Today: With rising geopolitical tensions, shifting rate policies, and persistent inflation, global macro has reemerged as a critical diversifier. Ken shares why macro strategies remain essential as traditional asset correlations evolve.
• Talent and Tenure in a Dynamic Industry: The conversation explored what it takes to build and sustain a culture that retains top talent for decades.
• Discretionary and Quantitative Synergy: Ken speaks about the complementary strengths of discretionary and systematic macro approaches, noting how combining the two can lead to more robust outcomes and better adaptability across varied market environments.
• The Role of Innovation and Data: As data becomes increasingly central to investment decision-making, Ken reflected on how innovation must be paired with sound judgment to truly create an edge.
• Risk Management in a Shifting World: From regional conflicts to policy-driven shocks, the conversation covered how managers must evolve their risk frameworks to remain resilient in a more volatile and uncertain environment.

Kenneth G. Tropin is the Chairman and the founder of Graham Capital Management, L.P. (“Graham”). Mr. Tropin founded Graham in 1994 and over the last 30 years has grown the firm into an industry leading alternative investment manager focusing on global macro discretionary and quantitative hedge fund strategies. Mr. Tropin is currently the Chairman of the firm’s Executive and Investment Committees and a member of the firm’s Risk Committee. Additionally, Mr. Tropin is responsible for managing the strategic investment of the firm’s proprietary capital. Prior to founding Graham, Mr. Tropin had significant experience in the alternative investment industry, including five years (1989 to 1993) as President and Chief Executive Officer of John W. Henry & Company, Inc. and seven years (1982 to 1989) as Senior Vice President and Director of Managed Futures at Dean Witter Reynolds. Mr. Tropin has also served as Chairman of the Managed Funds Association and its predecessor organization, which he was instrumental in founding during the 1980s.

Thomas Feng, Ph.D., is Chief Investment Officer – Quant Strategies of Graham. He is currently responsible for the management and oversight of the firm’s Quantitative Strategies team, including the Quantitative Operations and Execution, Research, and Data Science teams. Dr. Feng is also a member of the firm’s Investment and Risk committees. He became an Associated Person of Graham effective February 7, 2013 and a Principal on April 30, 2014. Dr. Feng joined Graham in April 2009 as a portfolio manager/quantitative research analyst. Prior to joining Graham in April 2009, Dr. Feng was part of a portfolio management team trading quantitative strategies at Fortress. From 1997 to 2006, Dr. Feng held roles of increasing responsibility, including Managing Director of Interest Rate Derivatives Research and Managing Director of Quantitative Proprietary Trading, at RBS Greenwich Capital. Dr. Feng received a Ph.D. in Mathematics from Princeton University in June 1997 and a B.S. in Mathematics from Yale in May 1993.

About CAASA
The Canadian Association of Alternative Strategies & Assets (CAASA) was formed to bring together alternative investment managers, service providers and investors in a conducive environment for collaboration while engaging investors to be a strong part of the conversation.