Can this be used for machine learning in finance?

Absolutely. It includes specific patterns for volatility-normalized returns and a differentiable Sharpe loss function designed for training Deep Momentum Networks.

What strategies can I implement with this skill?

You can implement a variety of trend-following strategies including Time-Series Momentum (TSMOM), MACD indicators, and multi-scale momentum models that combine different lookback periods.

Does it handle risk management and position sizing?

Yes, the skill focuses heavily on volatility targeting, using ex-ante volatility (typically 60-day EWMA) to ensure assets contribute equal risk to a portfolio regardless of their individual price swings.

How does it handle futures contract data?

It provides logic for creating continuous price series from individual futures contracts, specifically recommending ratio-adjusted methods to maintain consistent percentage returns for backtesting.

Financial Time-Series Momentum

Name: Financial Time-Series Momentum
Author: Donaldshen27

byDonaldshen27

0•

데이터 과학 및 ML

Implements professional-grade trend-following strategies, volatility targeting, and multi-scale momentum indicators for financial data analysis.

This skill provides a comprehensive framework for processing financial time-series data based on the X-Trend and Deep Momentum Networks models. It equips Claude with the specialized knowledge to calculate stationary returns, implement ex-ante volatility targeting using 60-day EWMA, and generate complex momentum signals like MACD and multi-scale TSMOM. Whether you are building quantitative trading systems or training deep learning models, this skill covers the entire pipeline from continuous futures contract handling to differentiable Sharpe ratio optimization and transaction cost modeling.

주요 기능

01Advanced volatility targeting for risk-normalized position sizing

02Portfolio construction frameworks with transaction cost modeling

03Continuous futures contract chaining with ratio-adjustment logic

04Multi-scale momentum factor calculation including MACD and TSMOM

05Differentiable Sharpe ratio loss functions for neural network training

060 GitHub stars

사용 사례

01Creating feature engineering pipelines for Deep Momentum Networks

02Developing and backtesting trend-following quantitative trading strategies

03Constructing equal-risk portfolios across multiple asset classes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add donaldshen27/xtrend-vanilla financial-time-series

For use in Claude.ai and ChatGPT

주요 기능

01Advanced volatility targeting for risk-normalized position sizing

02Portfolio construction frameworks with transaction cost modeling

03Continuous futures contract chaining with ratio-adjustment logic

04Multi-scale momentum factor calculation including MACD and TSMOM

05Differentiable Sharpe ratio loss functions for neural network training

060 GitHub stars

사용 사례

01Creating feature engineering pipelines for Deep Momentum Networks

02Developing and backtesting trend-following quantitative trading strategies

03Constructing equal-risk portfolios across multiple asset classes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add donaldshen27/xtrend-vanilla financial-time-series

For use in Claude.ai and ChatGPT