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technical-basic

Combine EMA, ADX, BB, RSI, and OBV into long, short, or neutral trading signals.

Updated Apr 14, 2026
Search Tags:#signals#pandas#trading#ema#ohlcv#technical-indicators#obv
One-click install
npx skills add https://github.com/Liangwei-zhang/six-stock --skill technical-basic-liangwei-zhang
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: technical-basic
Source: https://github.com/Liangwei-zhang/six-stock/tree/main/Vibe-Trading/agent/src/skills/technical-basic
Command: npx skills add https://github.com/Liangwei-zhang/six-stock --skill technical-basic-liangwei-zhang

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Core technical indicators are fused into a single signal engine to reduce manual analysis and decision-making on OHLCV data.

Core Features & Use Cases

  • Three-dimensional voting combines Trend (EMA/ADX), Mean Reversion (BB/RSI), and Volume-Price (OBV) into a unified long/short/neutral signal.
  • Pure pandas implementation works with any OHLCV data, no external dependencies beyond standard data science stack.
  • Use cases include backtesting trading strategies, real-time signal generation, and scenario analysis across multiple assets.

Quick Start

Provide a composite buy/hold/sell signal for your OHLCV dataset by applying the three-dimensional voting engine.

Frequently Asked Questions about technical-basic

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate trading signals from OHLCV data using pandas?▼

Generate trading signals from OHLCV data by applying a three-dimensional voting scheme across trend, mean-reversion, and volume-price indicators, outputting long, short, or neutral results using pure pandas.

What is the best way to combine EMA, RSI, and OBV indicators into a single signal?▼

Combine EMA, RSI, and OBV indicators into a single signal via a three-dimensional voting engine that fuses trend, mean-reversion, and volume-price dimensions into deterministic long, short, or neutral outputs.

Can I use this technical indicator voting engine for backtesting strategies?▼

Yes, you can use this technical indicator voting engine for backtesting strategies because it enforces deterministic, parameterized behavior and outputs OHLCV signals suitable for both backtests and live trading.

Does the signal engine require external libraries beyond the standard data science stack?▼

No, the signal engine requires no external libraries beyond the standard data science stack, utilizing a pure pandas implementation to process OHLCV time series and compute trading signals.

How does the three-dimensional voting scheme determine long or short signals?▼

The three-dimensional voting scheme determines long or short signals by evaluating EMA/ADX for trend, BB/RSI for mean-reversion, and OBV for volume-price, combining the results into a cohesive trading signal.

When should I use a multi-indicator voting scheme instead of individual technical indicators?▼

Use a multi-indicator voting scheme instead of individual technical indicators when you need to reduce manual analysis and produce a cohesive, deterministic trading signal across any compatible OHLCV time series.

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