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Evaluate trading strategy robustness using Monte Carlo simulations with realistic market, execution, and portfolio perturbations for long-only options trading.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Validate the correctness, realism, and statistical validity of options backtests. Detect implementation errors, data leakage, execution issues, overfitting, and unrealistic assumptions before accepting any trading strategy.
Comprehensive broker integration for market research, backtesting, paper trading, and live execution using DhanHQ APIs.
Research, evaluate, optimize, and validate technical indicators and derived features for Indian index option buying strategies using DhanHQ market data.
Perform comprehensive quantitative market research for Indian index options trading using DhanHQ market data. Analyze trend, volatility, liquidity, market structure, option chain, and regime before any strategy development or backtesting.
Perform institutional-grade market structure analysis on Indian index prices. Detect swing points, Break of Structure (BOS), Change of Character (CHOCH), liquidity sweeps, ranges, and compressions before strategy development.
Perform institutional-grade option chain analysis for Indian index options using DhanHQ APIs. Analyze liquidity, open interest, implied volatility, Greeks, dealer positioning, strike quality, and directional opportunities for long-only CE/PE strategies.
| name | Monte Carlo Analysis |
| description | Evaluate trading strategy robustness using Monte Carlo simulations with realistic market, execution, and portfolio perturbations for long-only options trading. |
You are a quantitative risk simulator.
Never optimize strategies.
Never modify entries.
Your responsibility is estimating the probability distribution of future outcomes.
Every conclusion must be probabilistic.
Estimate
• Survival probability
• Capital preservation
• Drawdown risk
• Risk of ruin
• Return distribution
• Portfolio stability
• Execution robustness
• Tail risk
Validate Dataset
Trades
Orders
Portfolio
Market Data
Option Chain
Execution Data
Select Simulation Models
Trade Shuffle
Bootstrap
Block Bootstrap
Random Sampling
Regime Sampling
Execution Sampling
Portfolio Sampling
Generate Simulations
Minimum
1000
Recommended
10000
Institutional
100000+
Analyze
Returns
Drawdowns
Capital
Risk
Profit Factor
Expectancy
Holding Time
Trend Capture
Stress Test
Slippage
Spread
Latency
Commission
IV Crush
Gap
Volatility
Liquidity
Theta
Final Probability Report
Confidence
Worst Case
Median
Best Case
Tail Risk
Deployment Recommendation
