Methodology

The Problem with Traditional Value Indices

Traditional value indices — including the S&P 500 Value, Russell 1000 Value, and MSCI Value — rely on a small set of fundamental ratios: price-to-book (P/B), price-to-earnings (P/E), price-to-sales (P/S), and dividend yield. While these metrics have decades of academic backing, they share a common blind spot: they treat every publicly listed share as equally accessible and equally informative.

A company where 95% of shares float freely has genuine price discovery driven by broad market participation. A company where 10% of shares float — with the remaining 90% held by insiders, sovereign wealth funds, or cross-holdings — may have a market price that reflects the views of a tiny minority of participants. A value index that ignores this distinction systematically overweights stocks whose prices may be unreliable.

Equally, market depth matters. A $500 billion tradable market capitalization implies deep institutional liquidity, extensive analyst coverage, and efficient information incorporation. A $500 million float implies the opposite. Traditional indices treat both identically if their P/E ratios are the same.

The MAVI Solution

The Market-Adjusted Value Index (MAVI) addresses both gaps by incorporating float ratio and market depth as multiplicative factors alongside earnings yield. Rather than treating float as an after-the-fact weighting mechanism (as float-adjusted market-cap indices do), MAVI penalizes low-float, shallow-market stocks directly in its value score. A stock must earn its way into the portfolio not just through cheap earnings, but through genuine market accessibility.

The MAVI Formula

Or equivalently, in its decomposed form:

Earnings Yield (EY)

EY = 100 ÷ P/E — Using the reciprocal of P/E gives a linear measure of earnings per dollar invested. A stock with a P/E of 10 returns 10% in earnings per dollar of market price (EY = 10); a stock with a P/E of 50 returns only 2% (EY = 2). EY is the primary value signal and carries the most weight in the composite score.

Float Ratio (FR)

FR = Float Shares ÷ Total Shares Outstanding — FR acts as a penalty multiplier. A stock with 10% float receives an FR of 0.10, reducing its MAVI score by 90% relative to an otherwise identical stock with full float. The economic rationale is threefold:

• Prices discovered among tiny floats are less trustworthy as signals of fundamental value.
• Insiders may extract private benefits not reflected in the share price.
• The stock may simply be unavailable for purchase at the quoted price in meaningful size.

Market Depth (D)

D = log₁₀(Float Shares × Current Price) — D is log-scaled to prevent raw market capitalization from dominating the index. The difference between a $10 billion and $100 billion float market cap is one point (log₁₀(10B) = 10.0 versus log₁₀(100B) = 11.0), as is the difference between $10 million and $100 million. This logarithmic scaling gives small- and mid-cap stocks a fair chance while still rewarding genuine market depth and institutional accessibility.

Edge Cases and Exclusion Rules

The following rules govern which stocks are included in the MAVI universe at each rebalancing period:

Condition	Treatment	Rationale
Negative P/E (EPS ≤ 0)	MAVI = 0	No earnings-based value can be computed
P/E > 500	Excluded from universe	Extreme outliers distort quintile rankings
P/E ≤ 0	Excluded from universe	Unprofitable companies incompatible with value framework
Zero float shares	MAVI = 0	No market price discovery exists
Missing data (any field)	Excluded for that period	Incomplete inputs produce unreliable scores

Quarterly Rebalancing Protocol

The backtest follows a strict quarterly rebalancing schedule designed to mimic implementable portfolio management:

• Frequency: Quarterly, on the first trading day of January, April, July, and October
• Universe: S&P 500 constituents (refreshed from Wikipedia at each run)
• Selection: All stocks ranked by MAVI score, descending; top 20% selected
• Weighting: Equal-weighted to avoid mega-cap domination
• Minimum threshold: 20 stocks required; if fewer qualify, the period is skipped
• EPS calculation: Trailing twelve-month (TTM) earnings, using the four most recently reported fiscal quarters before each rebalancing date (strictly point-in-time to eliminate look-ahead bias)
• Price: Monthly closing price for the month ending on or before the rebalancing date

Potential Applications

MAVI is designed as a research-oriented equity valuation index. Potential use cases include:

• Investment screening tool — Identifying undervalued stocks with accessible float and sufficient market depth
• Basis for a passive ETF — The systematic, rules-based methodology and quarterly rebalancing make MAVI suitable as the foundation for a systematic index fund
• Benchmark for value-oriented strategies — Complementing traditional value indices by adding float and depth dimensions
• Academic research — Studying the interaction of earnings quality with market accessibility as a distinct value factor

Known Limitations

The backtest results should be interpreted with the following qualifications:

Source Citation

This methodology is documented in the MAVI White Paper and the MAVI Comprehensive Backtest Validation (2021–2026), both authored by Dr. Mohamed Elrefai (July 2026). See the Publications page for full references.