RSI Overbought/Oversold Multi-Market Screener

Batch-scan A-share and Hong Kong equity universes for RSI signals, and output a ranked list of overbought and oversold candidates.

Factor Analysis
✓ 71 reported success·v1.0.0·Updated 2026-04-16

Overview

## Overview This crystal runs a full RSI(14) sweep across an entire market universe, automatically surfaces tickers in overbought territory (RSI > 70) and oversold territory (RSI < 30), and cross-references those signals with unusual volume activity to produce actionable trading candidates. ## Features - Covers A-shares, Hong Kong stocks, and US equities - Fully configurable RSI period and threshold parameters - Volume surge filter to separate high-conviction signals from noise - Output sorted by signal strength in a clean Markdown table, ready to copy into your research notebook

Blueprint Source

finance-bp-001

freqtrade/freqtrade3a7623534 source files

Constraints

117total
36fatal
36 must-not-violate

Evidence Quality

Confidence90%

High confidence — strong evidence base

36 non-negotiable constraints

FATALRCfinance-C-001可自动验证

WHEN实现 OHLCV 数据转换函数时

ACTION将 date 列设为普通列（非 DatetimeIndex），类型为 datetime64[ns, UTC]

CONSEQUENCE下游 groupby(by='date', as_index=False) 和 shift(1) 操作依赖 date 为普通列，设为索引会导致 KeyError 或静默数据错位

converter.py:46 — df['date'] = to_datetime(df['date'], unit='ms', utc=True); converter.py:82 — groupby(by='date', as_index=False)
FATALRCfinance-C-002可自动验证

WHEN实现 OHLCV DataFrame 构造时

ACTION列名固定为 ['date', 'open', 'high', 'low', 'close', 'volume']，与 DEFAULT_DATAFRAME_COLUMNS 一致

CONSEQUENCE策略引擎和回测引擎通过硬编码列名索引数据，列名不一致会导致 KeyError 使整个流程崩溃

constants.py:84 — DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
FATALRCfinance-C-007可自动验证

WHEN实现策略基类时

ACTION将 populate_indicators 标记为 @abstractmethod，强制子类实现

CONSEQUENCEpopulate_indicators 是策略核心计算入口，如不强制实现，子类可能遗漏导致 DataFrame 无任何指标列，信号全为 0

interface.py:228-229 — @abstractmethod def populate_indicators(...)

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Changelog

v1.0.02026-04-10·Contributors: @doramagic-team

Initial release.