Our research division transforms massive datasets into actionable market intelligence. Every study, analysis, and insight is grounded in systematic examination of historical patterns and quantified market behavior.
Published: August 2025
An in-depth analysis of how gamma exposure drives market movements, based on comprehensive examination of 50+ million gamma-related options transactions. This study reveals the mechanics behind institutional hedging and its predictable impact on price action.
Key Findings:
Published: July 2025
A comprehensive examination of implied volatility behavior during bull markets, bear markets, and sideways trading periods. Analysis includes over 200 million volatility data points across 15 years of market history.
Key Insights:
Published: June 2025
Investigation into unusual options activity and its correlation with subsequent price movements. Based on analysis of 150+ million options transactions flagged as anomalous volume or open interest.
Research Highlights:
Status: In Progress
Investigating the correlation between social media sentiment, news flow, and options pricing anomalies. This study examines how modern information flow affects traditional options pricing models.
Expected Completion: September 2025
Status: Development Phase
Developing advanced algorithms to identify subtle patterns in options flow that human analysis might miss. Focus on improving trade setup identification accuracy.
Expected Completion: October 2025
Status: Data Collection
Comprehensive analysis of how equity options behavior correlates with bond, commodity, and currency markets. Goal is to develop multi-asset trading signals.
Expected Completion: November 2025
Our research is built on rigorous data collection and analysis standards:
Data Sources:
Quality Controls:
Statistical Rigor:
Backtesting Standards:
Peer Review Process:
40 pages | Published August 2025
A comprehensive examination of how institutional traders use advanced options analytics and how these same techniques can be applied by individual traders.
28 pages | Published July 2025
Advanced risk management techniques that go beyond traditional Greeks analysis, incorporating real-world trading scenarios and portfolio-level risk assessment.
35 pages | Published June 2025
Deep dive into how options markets function at the microstructure level and how pricing inefficiencies can be systematically identified and exploited.
Updated every Monday with comprehensive analysis of market-wide gamma positioning and its implications for the trading week ahead.
Recent Reports:
In-depth analysis of implied volatility trends, term structure changes, and volatility trading opportunities.
Recent Publications:
A comprehensive educational series that explains options concepts through actual market data and historical examples.
15 pages | Beginner Level
Learn options fundamentals using actual trade examples from our database, showing how theoretical concepts play out in real markets.
22 pages | Intermediate Level
Beyond textbook explanations, see how Delta, Gamma, Theta, and Vega behave in actual trading scenarios with historical validation.
31 pages | Advanced Level
Complex options strategies analyzed through years of historical performance data, showing when they work and when they don't.
Input any stock symbol and analyze historical volatility patterns across different timeframes and market conditions.
Search our database of historical options transactions to find patterns similar to current market conditions.
Calculate real-time and historical gamma exposure levels for individual stocks or market-wide analysis.
Test options trading strategies against historical data with comprehensive performance analytics.
We collaborate with leading academic institutions to advance options trading research:
Working with industry professionals to validate research findings:
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Ph.D. Financial Engineering, [University]
Specializes in options market microstructure and systematic trading strategy development. 15+ years of experience in quantitative finance.
M.S. Statistics, [University]
Expert in statistical analysis and machine learning applications to financial markets. Former risk analyst at [Major Bank].
M.S. Computer Science, [University]
Develops algorithms for pattern recognition and anomaly detection in large financial datasets. Background in high-frequency trading systems.
Have questions about our research methodology or findings? Interested in collaboration opportunities?
Research Inquiries: research@modigin.com Data Requests: data@modigin.com Media Inquiries: media@modigin.com
Academic Collaboration: We welcome collaboration with academic researchers, graduate students, and institutions working on options trading and market microstructure research.
All research published by Modigin adheres to strict ethical and methodological standards:
This research is for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or solicitation to buy or sell any securities.
All trading involves substantial risk of loss. Past performance of strategies does not guarantee future results. Always consult with qualified financial professionals before making investment decisions.
Our research transforms data into knowledge and knowledge into trading success. Explore our findings and join the systematic trading revolution.