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ML And AI Models

22 posts
TTrading Strategies
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  • 6 minute read

Algorithmic Pyramiding: Building an ML Model to Determine Optimal Scaling Points

  • byQuantStrategy.io Team
  • February 8, 2026
The art of pyramiding—the strategy of scaling into a profitable position—is one of the most powerful techniques in…
TTechnical Indicators
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  • 6 minute read

Using Machine Learning to Predict ATR Shifts and Dynamic Stop Loss Adjustments

  • byQuantStrategy.io Team
  • January 31, 2026
The core challenge in futures risk management lies in adapting quickly to rapid changes in market temperament. Traditional…
TTechnical Indicators
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  • 6 minute read

Leveraging AI to Detect Spoofing and Iceberg Orders in High-Frequency Futures Trading

  • byQuantStrategy.io Team
  • January 29, 2026
High-Frequency Trading (HFT) in futures markets is a domain defined by microseconds, vast datasets, and intense competition. While…
CCustom Strategies
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  • 6 minute read

Building and Deploying Machine Learning Models for Automated Futures Strategy Execution

  • byQuantStrategy.io Team
  • January 28, 2026
The transition from manual decision-making based on complex indicators to fully automated execution driven by artificial intelligence represents…
CCustom Strategies
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  • 6 minute read

Using Predictive AI to Optimize Stop-Loss Placement and Position Sizing in Futures Trading

  • byQuantStrategy.io Team
  • January 27, 2026
The transition from mechanical, rigid trading rules to dynamic, adaptive strategies marks a major evolution in quantitative finance.…
RResearch
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  • 5 minute read

Leveraging Machine Learning Models to Predict Futures Market Direction and Volatility

  • byQuantStrategy.io Team
  • January 26, 2026
The complexity and high leverage of futures markets necessitate predictive tools far more sophisticated than simple moving averages…
CCustom Strategies
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  • 6 minute read

Integrating Machine Learning Models into High-Frequency Futures Trading Algorithms

  • byQuantStrategy.io Team
  • January 26, 2026
Integrating Machine Learning Models into High-Frequency Futures Trading Algorithms The evolution of algorithmic trading has transitioned from reliance…
RResearch
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  • 6 minute read

Leveraging Machine Learning to Predict Short-Term Price Movement from Order Book Dynamics

  • byQuantStrategy.io Team
  • January 16, 2026
The highly complex, rapid-fire environment of modern trading requires tools that can process immense amounts of data faster…
RResearch
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  • 6 minute read

Leveraging AI and Machine Learning for Predictive Order Book Modeling in HFT

  • byQuantStrategy.io Team
  • January 13, 2026
High-Frequency Trading (HFT) market making is a relentless pursuit of informational edge, primarily centered on understanding and predicting…
RResearch
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  • 6 minute read

Developing ML Models to Predict Implied Volatility Skew for NVDA Options Pricing

  • byQuantStrategy.io Team
  • January 8, 2026
The landscape of high-volatility options trading, especially concerning stocks like NVIDIA (NVDA), demands precision far beyond standard pricing…
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