Institutions Option Database Trading Part-4Advanced traders use machine learning to forecast:
Option price movement
Volatility changes
IV spikes before events
Popular Models:
Random Forest → Trend direction.
LSTM (Deep Learning) → Predict future IV.
Logistic Regression → Probability of ITM expiry.
These are trained on millions of past trades using structured databases.
Tec
Database Trading Introduction to Database Option Trading
Database Option Trading is an advanced strategy where traders use massive historical and real-time market data stored in structured databases to identify profitable option trades. Unlike conventional trading, this approach focuses on data-driven decision-making—leveraging algorithms, statistics, and pattern recognition rather than pure technical/fundamental analysis.
2. The Role of Data in Option Trading
Types of Data Used:
Option Chain Data: Strike prices, premiums, LTP, OI, IV, volume.
Historical Data: Past price action, volatility, Greeks, PCR.
Sentiment Data: FII/DII positions, news sentiment.
Real-Time Market Feeds: Tick-by-tick updates.
Macroeconomic Data: Interest rates, inflation, events.
Advanced Institutions Option Trading - Part 7Time Decay (Theta) Strategies
Options lose value over time due to Theta Decay.
Strategies to Take Advantage of Theta:
Selling options (Covered Calls, Naked Puts)
Calendar Spreads
Iron Butterflies
Caution:
Theta decay accelerates as expiry nears. Option sellers must hedge their deltas to stay safe.
Risk Management in Options
Institutions and pro traders always focus on capital protection.
🔐 Techniques:
Position sizing (no more than 2-3% risk per trade)
Hedging with opposite legs or underlying
Stop-loss on premium or delta exposure
Use of Greeks for real-time adjustment
Risk management > Strategy in the long run.