Research & Methodology
Every trading decision is backed by rigorous quantitative analysis. We combine academic research, advanced analytics, and real-world trading experience.
Our Edge: Data-Driven Precision
All trading decisions are guided by our proprietary analytics engine, the Option Sentiment Score (OSS), and a suite of quantitative tools.
Option Chain Analysis
Open interest, volume, bid-ask spreads
Implied Volatility
IV percentile, IV rank, term structure
Option Flow Analysis
Large institutional trades and positioning
Greeks Analysis
Delta, Theta, Vega, Gamma optimization
Option Sentiment Score (OSS)
Our proprietary scoring system that synthesizes multiple data streams into a single, actionable signal for each potential trade opportunity.
Probability Assessment
OSS evaluates the statistical probability of profit based on historical patterns and volatility.
Risk Quantification
Every trade is scored for downside risk, helping avoid unfavorable risk-reward profiles.
Optimal Execution
OSS guides strike selection, expiration timing, and entry points for maximum efficiency.
Risk Management Framework
Capital preservation is our first priority. Our risk framework protects capital while capturing opportunities.
Position Sizing
No single position exceeds defined capital limits. Diversification across instruments and expiration dates.
Diversification
Spread across indices and large-cap instruments to avoid concentrated single-stock risk.
Liquidity Focus
Trade only in highly liquid options markets to ensure efficient execution and tight spreads.
Tools & Technology
Our analytics infrastructure is built on modern, reliable technology designed for speed, accuracy, and scalability.
Python Analytics
Custom scripts for data processing and signal generation.
Real-Time Dashboards
Tableau and custom visualizations for market monitoring.
Automated Pipelines
Continuous data ingestion for real-time decision support.
# OSS Signal Generation
def calculate_oss(symbol, expiry):
"""
Compute Option Sentiment Score
"""
iv_score = analyze_volatility(symbol)
flow_score = analyze_option_flow(symbol)
oi_score = analyze_open_interest(symbol)
# Weighted composite score
oss = (
iv_score * 0.35 +
flow_score * 0.35 +
oi_score * 0.30
)
return normalize(oss, 0, 100)