Results for “volatility-smile”

Builds a 3D volatility surface for any optionable ticker, mapping implied volatility across strike price and time to expiration to identify cheap, expensive, or anomalous options.

Calculates a per-ticker panic index (0-100) from six weighted signals including VIX, IV Rank, RSI-14, volume anomaly, put/call ratio, and consecutive down days, triggering Bull Put Spread entry signals at scores ≥60.

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path.

Acquires Linux memory using the LiME kernel module and analyzes the image with Volatility 3 to extract processes, network connections, bash history, kernel modules, and injected code for incident response.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.

Delivers a daily DeFi regime verdict (RISK-ON/NEUTRAL/RISK-OFF) from five named inputs, top TVL movers with causal reasoning, and a sustainable-vs-incentive yield split to distinguish real product-market fit from emissions-pumped APY.

Pythonic wrapper around RDKit for cheminformatics, simplifying SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing while returning native rdkit.Chem.Mol objects.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning, covering 100+ featurizers including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa, with support for QSAR modeling and virtual screening.