⚠️ Important: All figures in this article are hypothetical illustrative backtested results generated using our proprietary backtesting engine. They are NOT actual trading results. Past performance does not predict future results. Not investment advice.

Overview

Our backtest on an AAOIFI-screened equity universe produced an illustrative net profit of 4,433.315% — growing a hypothetical $100,000 to $4,533,315 over the backtest period. Equally important is a positive alpha of 0.103, demonstrating that the strategy generated genuine excess returns beyond simply tracking the market.

4,433%
Net Profit (illustrative)
19.4%
CAGR
65%
Win Rate
0.617
Sharpe Ratio

Alpha: 0.103 — A Key Advantage

An alpha of 0.103 means the strategy returned 10.3% above what its market exposure (beta: 0.465) would predict. This positive alpha is significant — it shows the multi-factor methodology generates real excess value, not just leveraged market exposure. Combined with a low beta of 0.465, the strategy achieves this outperformance with substantially less market sensitivity than a typical index fund.

How the Strategy Is Built

The Nucore algorithm combines ethical screening with a systematic multi-factor approach to stock selection. Here is a high-level overview — implementation details are proprietary.

Step 1: Ethical Universe Construction

The strategy begins by applying a rigorous AAOIFI-aligned screen to US-listed equities, filtering out companies that fail business activity, revenue purity, debt, or interest income tests. This produces a clean investable universe of ethically permissible stocks, re-screened periodically to reflect updated company financials.

Step 2: Quantitative Stock Ranking

Within the ethical universe, the algorithm ranks each stock using a proprietary combination of quantitative factors. Top-ranked stocks are selected for portfolio inclusion; lower-ranked holdings are flagged for exit. This systematic ranking process removes emotional bias and applies consistent logic across all market conditions.

Step 3: Risk-Managed Position Sizing

Position sizes are determined by a systematic risk-management framework that accounts for volatility and portfolio concentration. The strategy uses no leverage, no short-selling, and no derivatives — consistent with ethical investing principles.

Step 4: Disciplined Rebalancing

The portfolio is rebalanced systematically as signals change — entering new top-ranked positions and exiting positions that have dropped in ranking. This disciplined, rules-based approach produced 2,755 total orders over the backtest period, averaging fees of approximately $9.18 per trade.

Additional Metrics

0.103
Alpha
0.465
Beta
0.283
Treynor Ratio
0.324
Information Ratio
0.240
Expectancy
$120M
Strategy Capacity

Important Limitations

See the Full Backtest

Visit our backtesting demonstration page for the complete Backtest metrics, cumulative return chart, and full methodology disclosure. Subscribers can also access live backtest results within the platform.