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Home Artificial Intelligence

Exent AI Beat S&P 500 by 10x Over 8 Years

June 3, 2026
in Artificial Intelligence, GlobeNewswire, Web3
Reading Time: 7 mins read
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NEW YORK, June 02, 2026 (GLOBE NEWSWIRE) — An eight-year performance analysis of Exent AI’s proprietary Kambo Score market regime signal shows a roughly 1,400 percentage point outperformance gap versus the S&P 500, translating to approximately 10x the benchmark’s total return.

Performance analysis data for the Kambo Score, a proprietary market regime indicator that powers Exent AI’s portfolio intelligence platform, shows the signal’s regime classifications producing significant outperformance versus the S&P 500 over an eight-year evaluation window. A strategy following the Kambo Score’s regime signals delivered a total return of +1,577.8%, compared to +151.3% for a buy-and-hold S&P 500 position over the same period. That is a roughly 1,400 percentage point outperformance gap, or approximately 10x the benchmark’s return.

image1

8-year performance analysis: KAMBO 2x Graduated strategy delivered +1,577.8% total return versus +151.3% for S&P 500 buy-and-hold. Sharpe of 2.39 versus 0.50, with a max drawdown of -19.9% versus -34.1%.

What the Kambo Score Measures

The Kambo Score is a quantitative market regime indicator developed by Exent AI’s research team. It identifies whether broad market conditions favor risk-on or risk-off positioning by synthesizing four sub-scores (liquidity, capital stress, cycle, and sentiment) into a single time-series signal.

image4

The Kambo Score breaks down into four sub-scores: liquidity, capital stress, cycle, and sentiment, each independently tracked.

A Framework Built on Institutional Inputs

Most retail-facing market timing tools rely on a single category of data, typically price-derived technical indicators like moving averages, RSI, or MACD. These describe what the market has already done, not the underlying conditions driving it. The Kambo Score is built on a different premise: that market regime is best understood through the same multi-factor framework institutional asset managers use, where price action is one of many inputs.

Liquidity tracks Federal Reserve balance sheet data (WALCL), the Treasury General Account, reserve balances, USD strength, and SOFR. Capital Stress monitors the NFCI, high-yield credit spreads, and the MOVE index. Cycle integrates the 10-year Treasury yield trajectory, the copper-to-gold ratio, and business condition indices. Sentiment captures positioning extremes through the VIX, options skew, and investor surveys.

image2

A look beneath the Kambo Score: each sub-score is built from multiple institutional-grade indicators, including FRED data series for the Fed balance sheet, Treasury General Account, Reverse Repo, US Dollar, M2 Money Supply, and SOFR Rates, among more than 20 proprietary Exent macro inputs.

This is the kind of multi-factor regime framework used inside hedge funds and large asset managers. Until Exent AI built it, individuals had to rely on oversimplified retail signals or assemble institutional-grade data themselves across multiple paid terminals.

Regime Win Rates Support the Framework

Beyond cumulative returns, regime-level statistics show how reliably the Kambo Score’s classifications aligned with market direction since 2018. Across 14 Risk-On episodes, the signal aligned with positive S&P 500 outcomes 92.9% of the time, averaging +6.52% per episode. Across 16 Risk-Off episodes, the signal correctly anticipated negative or weak market periods 93.8% of the time, with an average decline of -4.37%.

image3

The S&P 500 over the past five years with Kambo Score regime classifications overlaid. Green periods mark Risk-On regimes, red periods mark Risk-Off regimes, illustrating how the signal mapped to actual market direction in real time.

image5

Kambo Score regime win rates since 2018: 92.9% accuracy on Risk-On signals, 93.8% on Risk-Off signals.

Methodology

The eight-year analysis applied the Kambo Score’s regime signals across multiple strategy variants. The flagship 2x Graduated strategy achieved a Sharpe ratio of 2.39 versus 0.50 for the S&P 500 buy-and-hold, with a maximum drawdown of -19.9% versus -34.1% for the benchmark, meaning the strategy delivered both higher returns and lower peak-to-trough losses than the index. Returns were modeled on a gross basis using publicly available index data. Results reflect performance the strategy would have generated under historical conditions and do not represent actual trading.

“We built the Kambo Score because the average self-directed investor has no way to systematically know when market conditions favor risk-taking versus capital preservation. The 8-year analysis is a research benchmark, not a guarantee, but it demonstrates the kind of edge a regime-aware framework can provide when applied with discipline.” Exent AI Research Team

The Kambo Score is available to retail investors through Exent AI’s portfolio intelligence platform, alongside the Radar multi-factor screening engine, AI-driven portfolio diagnostics, and a curated market event calendar.

About Exent AI

Exent AI is a portfolio intelligence platform built for self-directed investors. Through its proprietary Kambo Score market regime indicator, the Radar screening engine, AI-driven portfolio diagnostics, market event intelligence, and direct access to its investment research team, Exent AI gives retail investors institutional-grade tools historically reserved for hedge funds and asset managers. The platform consolidates concentration analysis, correlation mapping, sector exposure diagnostics, Wall Street price target gap analysis, customizable multi-factor screening, AI-summarized portfolio activity, and a curated calendar of macro, earnings, and central bank events into a single workspace. For more information, visit exent.ai.

IMPORTANT DISCLOSURE: All performance data referenced in this release reflects historical performance analysis. The figures do not represent actual trading and are subject to numerous limitations, including the benefit of hindsight, the absence of real-world transaction costs, and the inability to account for actual investor behavior. The Kambo Score is a research signal and is not investment advice. Past performance is not a reliable indicator of future performance. All investing involves risk, including the loss of principal. Investors should consult a qualified professional before making investment decisions.

For more information or general inquiries, please contact Exent AI directly at support@exent.ai

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