How To Position In A "Slowdown" Regime | Market Radar

Key Concepts

• Risk-Off/Risk-On Regimes: Market states characterized by aversion to or appetite for risk, respectively.
• Growth & Inflation Impulses: Momentum indicators for economic growth and inflation, used to define market regimes.
• Regime Map: A visual representation of market regimes based on growth and inflation impulses.
• Term Premium: The extra return investors demand for holding longer-term bonds, reflecting uncertainty about future interest rates and inflation.
• Systematic Trading: Utilizing pre-defined rules and models for investment decisions, minimizing emotional bias.
• Dispersion: The degree to which asset class returns diverge from each other.
• Net Liquidity: A measure of liquidity in the financial system, often tracked through Fed balance sheet changes and money supply.
• Tariff Impacts: The influence of trade policies (like tariffs) on inflation and economic growth.

Market Regime Shift and Systematic Trading Insights

The conversation centers around a shift in market dynamics from a clear risk-off environment in early October to a more ambiguous “slowdown regime” as of late 2024/early 2025. The Market Radar team (Gamma and Arty) discuss how their quantitative models are navigating this complexity and their outlook for 2026.

1. From Risk-Off to Slowdown: A Regime Transition

The initial risk-off trigger in October was linked to Trump’s China tariff announcement, but the models had already signaled deteriorating growth before this event. This highlights the importance of forward-looking indicators. The current regime is characterized by impulses that are neither strong enough to trigger a sustained downside move nor strong enough to confidently initiate aggressive risk-on positioning.

Quote: “We’re no longer in risk off. We’ve left risk off. We’re in this regime now where the impulses are not strong enough to give you clear conviction to the downside and they’re obviously not strong enough to the upside either.” – Gamma

Growth impulses began to recover in mid-November, a leading indicator suggesting a potential end to the choppiness. However, a sustained risk-on environment requires growth impulses to decisively break above the trend line.

2. Dispersion and Quant Performance

A key observation is the increased dispersion in performance across asset classes. While gold has maintained a consistent bull trend, Bitcoin has experienced a bearish trend (according to their models). This dispersion poses challenges for quantitative models that rely on consistent trending markets.

Quote: “One of the reasons you’re seeing a lot of dispersion across large macro fund performances…is due to the fact that most quant models…are basically betting on a trending market which when markets don’t trend you’re facing a bunch of headwinds.” – Gamma

The Nasdaq (NQ) has shown limited net progress despite a 15% year-to-date gain, requiring significant volatility to achieve that return. This illustrates the difficulty in capturing sustained trends.

3. Model Signals and the Role of Growth & Inflation

The team’s models signaled a risk-off environment in late September/early October, before the tariff announcement. The models are designed to prioritize selling at the top with leverage, recognizing the greater risk of being caught in a liquidity cascade.

Currently, growth expectations are improving, but the regime remains a “slowdown” – not a full-blown recessionary risk-off. The inflation index is also playing a role, preventing a deflationary scare.

Quote: “We have been seeing over the last few weeks that growth expectations have actually been ticking up and we are now in more of a slowdown environment which doesn't necessarily mean like full-blown risk off where you get that deflation scare, that growth scare.” – Arty

4. The Impact of External Events & Data Interpretation

The government shutdown in late 2024 coincided with model-driven risk-off signals, but the team believes the slowdown was occurring regardless of the political event. They emphasize that markets will price in information regardless of official data releases.

The team highlights the importance of distinguishing between short-term noise (like tariff announcements) and underlying trends. They noted that their models were already signaling a risk-off environment before the tariff news, which exacerbated the move.

5. Liquidity and Fed Policy

The discussion delves into the complexities of interpreting Fed policy and liquidity. They differentiate between short-term liquidity (reserves and repo) and long-term liquidity (QE). They argue that the Fed’s ability to communicate its intentions is crucial, as market expectations are heavily influenced by forward guidance.

Quote: “The idea that the Fed can set overnight rates is one thing, but it's their guidance on future overnight rates that set the benchmark rates and set everyone's expectations.” – Arty

They also point out that the market is less sensitive to short-term rate cuts if long-term rates (and therefore term premium) rise in response to uncertainty about the Fed’s commitment to its inflation target.

6. Systematic Trading & Avoiding Emotional Bias

The team emphasizes the importance of systematic trading to remove emotional bias. Their models are designed to execute pre-defined rules, prioritizing risk management and avoiding the pitfalls of discretionary trading.

Quote: “We just decided to make just set rules and remove all of that noise from our trading.” – Gamma

They caution against relying on simplistic correlations (e.g., M2 and Bitcoin) and emphasize the need for multi-factor models that can adapt to changing market conditions.

7. 2026 Outlook

Looking ahead to 2026, the team is cautiously optimistic. They anticipate potential growth tailwinds in Q2, but emphasize that a sustained risk-on environment requires a decisive break in growth impulses. They believe the Fed’s communication and ability to manage term premium will be critical. They expect markets to generally trend upwards over the long term, but acknowledge the potential for continued choppiness in the near term.

Conclusion

The conversation highlights the challenges of navigating a complex market environment characterized by shifting regimes, dispersion in asset class performance, and the need for sophisticated quantitative models. The Market Radar team emphasizes the importance of forward-looking indicators, systematic trading, and a nuanced understanding of Fed policy and liquidity dynamics. Their outlook for 2026 is cautiously optimistic, but they stress the need for adaptability and a reliance on model signals to guide investment decisions.