U.S. Mega Cap 10 Model

Detailed Fact Sheet & Historical Analysis

Nov 1990 – Nov 2025 Benchmark: S&P 500 Total Return Equal Weight iQUANT Proprietary Alpha

Dear Investment Advisor,

At iQUANT, we have plenty of index-aware, index-beating all-cap, hedge, and global models. But until now, we have not had a model clearly designated as a pure mega-cap strategy, and none that is strictly equal weight.

The iQUANT U.S. Mega Cap 10 Model is our answer to that gap: one clear, consistent rule set applied only to America’s corporate giants, with every position pulling its own weight.

— The iQUANT Research Team

At a Glance

Objective

Long-term capital growth

Structure

10 stocks, equal weighted

Universe

Top 90 U.S. companies

Reconstitution

Quarterly (Feb, May, Aug, Nov)

Selection Process

1

Financial Strength

Favors companies with solid balance sheets and consistent earnings.

2

Earnings Power

Looks at earnings relative to price after recent volatility.

3

Quality & Margins

Emphasizes profit margins and real pricing power.

Composite Ranking & Risk Management

The strategy uses a "Screen-of-Screens" approach, ranking every company across all three factors simultaneously rather than sequentially. These rankings create a composite score to identify multi-dimensional strength.

The model selects the top 10 candidates, applying strict industry caps to ensure diversification. This process repeats quarterly to adapt to changing market data.

Proprietary Alpha

iQUANT Proprietary Alpha

Growth of $10,000 Nov 1990 – Nov 2025 (Log Scale)

iQUANT

S&P 500

        Annualized Return
        18.3%
      

Win Rate (Mo) 58.2%

Upside Capture 112%

Downside Capture 81%

Annual Returns Breakdown

Year	iQUANT	S&P 500
1991	30.6%	30.5%
1992	2.6%	7.6%
1993	5.5%	10.1%
1994	5.3%	1.3%
1995	29.5%	37.6%
1996	26.3%	23.0%
1997	30.6%	33.4%
1998	78.7%	28.6%
1999	47.8%	21.1%
2000	11.3%	-9.1%
2001	0.9%	-11.9%
2002	-17.8%	-22.1%

Year	iQUANT	S&P 500
2003	34.8%	28.7%
2004	10.9%	10.9%
2005	22.1%	4.9%
2006	18.7%	15.8%
2007	14.8%	5.5%
2008	-32.5%	-37.0%
2009	36.6%	26.4%
2010	21.7%	15.1%
2011	9.3%	2.1%
2012	13.0%	16.0%
2013	36.6%	32.4%
2014	7.9%	13.7%

Year	iQUANT	S&P 500
2015	7.6%	1.4%
2016	12.1%	12.0%
2017	30.1%	21.8%
2018	2.0%	-4.4%
2019	28.2%	31.5%
2020	56.7%	18.4%
2021	25.6%	28.7%
2022	-11.6%	-18.1%
2023	32.2%	26.3%
2024	30.5%	25.0%
2025*	37.4%	17.8%

Market Behavior

Dot-Com Bubble / September 11 (Jan 2000 – Dec 2002)

Excess: +29.9%

Held profitable tech leaders while keeping a core in staples and health care.

Post-Dot-Com Recovery (Jan 2003 – Dec 2003)

Excess: +6.1%

Shifted into undervalued growth names as the market bottomed.

Global Financial Crisis (Oct 2007 – Feb 2009)

Excess: +5.9%

Concentrated in household brands and cash-generative businesses.

Post-GFC Recovery (Mar 2009 – Dec 2009)

Excess: +2.5%

Captured the rebound by rotating into high-quality cyclical leaders.

COVID Crash (Feb 2020 – Mar 2020)

Excess: +5.9%

Tilted toward digital infrastructure and health-care leaders.

Post-COVID Rebound (Apr 2020 – Dec 2020)

Excess: +31.8%

Emphasized businesses that kept the world running.

2022 Bear Market (Jan 2022 – Dec 2022)

Excess: +6.5%

Favored companies with demonstrated pricing power.

Post-2022 Rebound (Jan 2023 – Dec 2023)

Excess: +5.9%

Leaned into businesses able to defend profitability.

Historical Context Summary

The historical record highlights a distinct advantage of this rules-based approach: the ability to generate positive excess returns across diametrically opposed market environments. As evidenced by the timeline, the model has historically acted as a shock absorber during crises—significantly limiting drawdowns during the Dot-Com and 2008 crashes—while pivoting effectively to capture upside during subsequent recoveries. This dual capability stems from its unconstrained ability to rotate between defensive value and high-quality growth based purely on fundamental data.

IMPORTANT DISCLOSURES & PUBLISHER EXEMPTION
iQUANT.pro is a data publisher and is not a registered investment adviser. This document serves as a publication of general circulation and does not constitute individualized investment advice. The U.S. Mega Cap 10 Model is a hypothetical, rules-based simulation, not an actual portfolio. iQUANT does not manage assets or execute trades. Performance shown (Nov 1990–Nov 2025) is backtested, assumes a 0.50% annual fee, and was generated with the benefit of hindsight. Returns do not reflect trading costs, taxes, or liquidity constraints. Backtested results have inherent limitations and do not represent actual trading. Past performance is not indicative of future results.

Strategic Analysis

The Structural Alpha of Equal Weighting

Traditional cap-weighted indices often create unintentional concentration risks, where a handful of mega-cap stocks dictate performance. While this momentum can be powerful, it leaves portfolios vulnerable to single-sector reversals. The iQUANT Mega Cap 10 addresses this by enforcing an equal-weight discipline. By systematically rebalancing to 10% positions, the model naturally harvests volatility—selling winners into strength and buying high-quality laggards before they rebound. This structural mechanism, combined with rigorous selection, provides a mathematical edge over passive allocation.

Consistency as an Asset Class

In investment management, consistency is often more valuable than sporadic outperformance. With a historical Yearly Win Rate of 75.0%, this strategy has demonstrated an ability to outperform the S&P 500 in three out of every four years over a multi-decade test period. This reliability suggests that the model’s alpha is not a product of luck or a single lucky regime, but rather the result of a robust, repeatable process that identifies fundamental strength regardless of the macroeconomic backdrop.

Efficiency & Risk Control

Risk-adjusted returns are the true measure of a strategy's worth. With a Sharpe Ratio of 1.10 and an Information Ratio of 0.78, the model has historically delivered significantly more return per unit of risk than the benchmark. Furthermore, the Alpha of 6.68% indicates that a substantial portion of these returns is idiosyncratic—generated by stock selection skill rather than simple market beta. For allocators, this profile offers a compelling complement to core beta holdings, enhancing the efficiency of the broader equity sleeve.

Key Risk Metrics
Annualized Return	18.34%
Sharpe Ratio	1.10
Down Market Beta	0.87
Down Market Correlation	0.71
Alpha (Annualized)	6.68%
R-Squared	0.72
Information Ratio	0.78
Downside Capture	80.0%
Ulcer Index	8.45
Ulcer Index (S&P 500)	13.65

IMPORTANT DISCLOSURES & PUBLISHER EXEMPTION
iQUANT.pro is a data publisher and is not a registered investment adviser. This document serves as a publication of general circulation and does not constitute individualized investment advice. The U.S. Mega Cap 10 Model is a hypothetical, rules-based simulation, not an actual portfolio. iQUANT does not manage assets or execute trades. Performance shown (Nov 1990–Nov 2025) is backtested, assumes a 0.50% annual fee, and was generated with the benefit of hindsight. Returns do not reflect trading costs, taxes, or liquidity constraints. Backtested results have inherent limitations and do not represent actual trading. Past performance is not indicative of future results.

Glossary of Terms

Annualized Return (CAGR)

The Compound Annual Growth Rate measures the mean annual growth rate of an investment over a specified period of time longer than one year.

Win Rate

The percentage of periods where the portfolio outperformed its benchmark. A win rate above 50% generally indicates consistent outperformance over time.

Annualized Volatility (Std Dev)

A statistical measurement of volatility that indicates how much an investment's returns deviate from its average return. Higher values indicate higher volatility.

Sharpe Ratio

A measure of risk-adjusted return calculated by subtracting the risk-free rate from the return and dividing by the standard deviation. A Sharpe Ratio > 1.0 is considered good.

Down Market Beta

A measure of the volatility, or systematic risk, of a portfolio in comparison to the market specifically during months when the market return is negative. Defensive strategies typically have a Beta < 1.0.

Down Market Correlation

A statistical measure of how strongly the portfolio's returns move in relation to the benchmark's returns during negative market months. Lower correlation in down markets is generally preferred.

Alpha

A measure of the active return on an investment compared to a suitable market index. An alpha of 1.0 means the strategy has outperformed its benchmark index by 1%. A positive Alpha indicates value added.

R-Squared

A statistical measure that represents the percentage of a strategy or security's movements that can be explained by movements in a benchmark index.

Information Ratio

A measurement of portfolio returns beyond the returns of a benchmark compared to the volatility of those returns. Generally, > 0.50 is good, and > 0.75 is excellent.

Ulcer Index

A measure of the depth and duration of drawdowns in prices from earlier highs. It incorporates both the magnitude of the drawdown and the time it takes to recover. Lower values indicate lower risk.

Upside Capture

Measures a strategy's performance in up-markets relative to the index. A value > 100% indicates the strategy has outperformed the benchmark during periods of positive returns.

Downside Capture

Measures a strategy's performance in down-markets relative to the index. A value < 100% indicates the strategy has lost less than the benchmark during periods of negative returns.

U.S. Mega Cap 10 Model