The Options Contract Pricing Project is designed to provide advanced tools and analytics for options traders. It integrates market sentiment analysis, options pricing models, and volatility evaluation, offering a comprehensive suite of functionalities.
get_option_chain(ticker): Retrieves the options chain for a given stock ticker.last_price_contract(contract_name): Gets the last traded price of a specific options contract.get_risk_free_rate(): Fetches the current risk-free interest rate.get_ticker_from_contract(contract_name): Extracts the stock ticker from an options contract name.get_expiry(contract_name): Determines the expiration date of an options contract.get_historical_options_data(ticker, start_date, end_date): Gathers historical options data for a given ticker within a specified date range.get_data(ticker): General function to obtain data for a given ticker.time_to_maturity(contract_name): Calculates the time to maturity for an options contract.strike_price(contract_name): Extracts the strike price from an options contract name.get_underlying_price(contract_name): Retrieves the current price of the underlying asset for an options contract.extract_option_type(contract_name): Determines whether an options contract is a call or put.get_nearest_expiry_and_strike_filtered_options(ticker): Fetches options contracts for a ticker with the nearest expiration and filters them based on certain criteria.get_combined_option_chain(ticker, dividend_yield, option_type, start_date, end_date, risk_free_rate): Combines various options data for a comprehensive analysis.
black_scholes(S, K, T, r, sigma, option_type): Implements the Black-Scholes pricing model for options.future_black_scholes_price(contract_name, future_price): Estimates future Black-Scholes price for an options contract.black_scholes_vectorized(...): Vectorized version of the Black-Scholes formula for batch processing.monte_carlo_simulation(...): Conducts a Monte Carlo simulation for stock price paths.monte_carlo_option_price(...): Estimates the price of an option using Monte Carlo simulations.mle_gbm(ticker): Performs Maximum Likelihood Estimation for Geometric Brownian Motion parameters.estimate_jump_parameters(ticker): Estimates parameters for the Jump Diffusion model.jump_diffusion_simulation(...): Simulates stock price paths using the Merton Jump Diffusion model.jump_diffusion_option_price(...): Calculates option price using Jump Diffusion simulations.price_my_option(contract_name, model): Prices an option using specified pricing models.
get_implied_volatility(contract_name): Calculates the implied volatility for an options contract.historical_volatility(ticker): Computes historical volatility for a given stock ticker.sabr_volatility(...): Implements the SABR volatility model.get_historical_volatility_of_contract(contract_name): Fetches historical volatility specifically for an options contract.derived_implied_volatility(...): Derives the implied volatility based on market data.vega(...): Calculates the vega of an option.get_ticker_volatility(ticker): Retrieves volatility metrics for a specific stock ticker.
visualize_net_institutional_trading_5_days(): Visualizes net institutional trading over the past five days.visualize_net_institutional_trading_today(): Displays net institutional trading for the current day.calculate_net_institutional_trading(...): Calculates net institutional trading based on block trades.weighted_volume_sentiment_analysis(...): Analyzes sentiment based on trading volume and price impact.detect_volume_anomalies(...): Identifies significant deviations in trading volume.highlight_key_info(...): Extracts and highlights key information from data.weighted_reddit_sentiment_analysis(subreddit, ticker): Performs sentiment analysis based on Reddit posts and comments.aggregate_subreddit_sentiment(...): Aggregates sentiment scores from multiple subreddits.alpha_extract_and_calculate_sentiment(...): Extracts and calculates sentiment from Alphavantage news feeds.alpha_get_top_gainers_losers(): Retrieves top gainers and losers from the stock market.alpha_get_news_sentiment(...): Fetches news sentiment for specified tickers or topics.
over_under_priced_contracts_by_volatility(contract_name): Determines if contracts are overpriced or underpriced based on volatility.derive_implied_volatility_contract(contract_name): Derives implied volatility for a specific contract.max_profit_contract(...): Identifies the contract with the maximum potential profit based on future expectations.avg_contract_price_with_all_models(contract_name): Averages the contract price using different pricing models.profitability_range(...): Calculates profitability ranges for contracts within expected price fluctuations.profitability_heatmap(...): Generates a heatmap visualization for contract profitability.evaluate_contracts(tickers): Evaluates contracts for a list of tickers to determine pricing status.market_mispriced_contracts_finder(): Identifies mispriced contracts in the market.