FROM THE RELEVANT MINIMUM OF WAVE 2/3/3 OF THE ELLIOTT WAVE ANALYSIS.
(Next real results on June 30, 2025)

GRAPHS AND STATISTICS:

FIVE YEAR ALGORITHM WITHOUT MONEY MANAGEMENT (3€/PIP)

ALPHA (color) VS. S&P Index (black) +8798€

FIVE YEAR ALGORITHM WITH MONEY MANAGEMENT (3€/PIP in progression)

ALPHA (color) VS. S&P Index (black) +878966€

TECHNICAL OVERVIEW

S&P ALPHA is a fully automated, long-only trading system engineered to operate on the S&P 500 index (US SPX 500 Cash) using the ProRealTime platform. The strategy employs a hybrid logic that blends neural-pattern recognition and volatility breakout structures, enabling precise entries during directional shifts and sustained momentum bursts.

Finalized in April 2025, this algorithm represents an advanced evolution in AI-assisted rule-based trading. It is deployable in dual configuration modes—with and without capital scaling—allowing traders to adapt position sizing to match both conservative and aggressive account mandates.

TECHNICAL SPECIFICATIONS

• Algorithm Name: S&P ALPHA
• Target Market: S&P 500 (US SPX 500 Cash)
• Position Type: Long-only (no short trades)
• Timeframe: 30-minute candles
• Platform: ProRealTime
• Programming Language: ProBuilder
• Trading Hours: UTC +1
• Trade Frequency: Moderate (5–9 trades per week)

STRATEGY PARAMETERS

• Stop Loss: ~1.20%
• Take Profit: ~9.00%
• Break-even Activation: At +0.15%
• Trailing Stop: Enabled, AI-modulated trailing logic
• Entry Conditions: Neural pattern detection, breakout range filters, volume surge detection

Money Management:

• Without MM: Fixed size (1 €/pip for €2,000 capital)
• With MM: Progressive pip sizing from 0.5 €/pip with equity scaling (starting from €2,000)

PERFORMANCE COMPARISON

Starting capital: €2,000

MONTECARLO SIMULATION RESULTS

Methodology: 100,000 randomized permutations of historical trades

Probability of Profit:

Average Profit:

Additional Metrics:

• Projected Max Drawdown (VaR 99%): -6.9% | -17.1%
• Standard Deviation of Equity Curves: €5,600 | €360,000

EXTENDED TECHNICAL CONCLUSION

S&P ALPHA represents a step forward in hybrid-system trading, leveraging neural pattern recognition to predict breakout continuations within the broader S&P 500 framework. Its adaptability to changing volatility profiles makes it a strong performer across both trending and mean-reverting regimes.

The non-money-managed version offers a well-balanced profile of risk and reward, making it especially suitable for traders managing evaluation accounts or prioritizing risk stability. Its statistical consistency, low average drawdown, and steady return curve position it as a viable core strategy for diversified portfolios.

In contrast, the money-managed version exhibits accelerated equity expansion, facilitated by smart pip-size scaling. This version is ideal for traders targeting exponential compounding, while still maintaining strong statistical resilience even under randomized trade sequences.

Backtested over years of market regimes and subjected to stress tests including inverse logic simulations, latency offsets, and slippage perturbations, S&P ALPHA stands as a robust and scalable engine for institutional-grade retail trading.

This system is optimal for:

• AI-based breakout exploitation in the S&P 500
• High-confidence neural entry logic with wide exits
• Dual-mode operation for conservative and aggressive profiles
• Long-term account growth supported by statistically validated resilience

Its architecture supports future integration with advanced machine learning filters or portfolio-wide risk-adjusted capital allocators. S&P ALPHA is not just a strategy—it is a framework for AI-enhanced equity growth.

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