Query A-share prices, backtest strategies, screen stocks, and get trading signals
A-Share Quant is a quantitative trading and analysis skill on EasyClaw that combines real-time A-share market data with strategy backtesting, technical screening, and trading signal generation. Built on the Tushare financial data infrastructure, it gives individual investors and quant researchers access to tools previously limited to institutional trading desks — without writing a single line of code.
The skill is designed for technically oriented retail investors, algorithmic trading enthusiasts, and financial analysts who want to test trading ideas, screen for momentum stocks, or generate systematic entry and exit signals for Chinese equities listed on the Shanghai and Shenzhen exchanges.
The expected outcome is a quantified view of any A-share stock or strategy: a backtest result showing historical returns for a specific strategy, a screened list of technically strong stocks ranked by composite score, or a live signal indicating whether a stock's technical indicators are bullish or bearish.
1. Connect via Tushare Token. The skill requires a Tushare API token for data access. Once configured, it connects to Tushare's A-share database covering prices, financials, and index data.
2. Natural language strategy input. Describe your strategy in plain language — "backtest a 20-day moving average crossover on Moutai for the past year" — and the skill interprets and executes it without requiring code.
3. Backtesting engine. The skill runs historical simulations for common technical strategies including MA crossover, MACD, KDJ, and Bollinger Bands. It calculates total return, maximum drawdown, Sharpe ratio, and win rate.
4. Technical screener. For stock screening, the skill scores A-share stocks across multiple technical indicators and returns a ranked list of the top candidates based on composite signal strength.
5. Signal output. For individual stocks, the skill generates a current signal summary — bullish, bearish, or neutral — based on the selected indicator set, along with the specific values driving the signal.
- Quote lookup: Real-time price, change, volume, and key metrics for any A-share stock by name or ticker.
- Strategy backtesting: Test MA, MACD, KDJ, and Bollinger Band strategies on any stock and time range with full performance metrics.
- Technical screener: Scan the entire A-share universe and return top-ranked stocks by composite technical score.
- Trading signals: Get current bullish/bearish/neutral signals for individual stocks based on selected indicators.
- Tushare integration: Powered by Tushare's comprehensive A-share database for reliable historical and real-time data.
- No-code interface: All quantitative operations are accessible through plain language queries — no Python or SQL required.
1. Backtesting a strategy idea before trading it
An investor has a hypothesis: buy Moutai when the 5-day MA crosses above the 20-day MA, sell when it crosses below. Instead of paper trading for months, they ask A-Share Quant to backtest this strategy on the past 2 years of data. The result shows annualized return, maximum drawdown, and win rate — letting them evaluate the idea with evidence before risking capital.
2. Finding technically strong stocks for swing trading
A trader wants a watchlist of A-shares showing strong technical momentum across multiple indicators. They ask the skill to screen for the top 10 technically strong stocks. The result is a ranked list with composite scores, ready to narrow down with fundamental checks.
3. Comparing strategy variants
A quant researcher wants to compare MACD and KDJ strategies on the same stock over the same period. They run both backtests in sequence within the same EasyClaw conversation and compare the performance metrics side by side.
4. Getting a quick signal check before entering a position
Before buying a ChiNext stock, an investor wants to know whether the current technical setup is favorable. They ask for a signal summary and receive a clear bullish/bearish/neutral verdict with the specific indicator values behind it.
5. Building a systematic watchlist
A fund researcher runs a weekly technical screen every Monday morning to identify which A-share stocks have the strongest momentum signals heading into the week, building a dynamic watchlist without manual chart review.
A retail investor wants to test whether a Bollinger Band mean-reversion strategy works on CATL (300750) before committing capital.
1. They open EasyClaw and activate A-Share Quant.
2. They type: *"Check the current quote for 300750."* — receive live price and volume.
3. They ask: *"Backtest a Bollinger Band strategy on 300750 for the past 18 months."* — the skill runs the simulation and returns total return, max drawdown, Sharpe ratio, and number of trades.
4. The result shows 23% return with a 12% max drawdown and 58% win rate — acceptable parameters for their risk tolerance.
5. They ask: *"What's the current signal for 300750 based on Bollinger Bands?"* — receive a current position signal to time entry.
From idea to evidence-backed decision in under 5 minutes.
Quantitative rigor without coding. Backtesting in Python with Tushare typically requires 50–100 lines of code per strategy. This skill handles the entire workflow through natural language, making quantitative analysis accessible to investors without programming backgrounds.
Faster strategy validation. Testing a strategy idea manually — pulling data, calculating indicators, tracking trades — takes hours. Backtesting through this skill takes seconds, allowing more ideas to be evaluated before capital is committed.
Systematic screening at scale. Manually reviewing technical charts for hundreds of stocks is impractical. The screener evaluates the entire A-share universe against multiple indicators simultaneously and surfaces only the strongest setups.
Consistent signal interpretation. Human chart reading introduces subjectivity. The skill applies indicator calculations consistently using the same parameters every time, removing interpretation variability from the screening process.
Integrated workflow. Quote lookup, backtesting, screening, and signal generation are all available in one EasyClaw conversation — no switching between a data terminal, a backtesting platform, and a charting tool.
- Set up your Tushare token first. The skill requires a valid Tushare API token. Register at tushare.pro and configure the token in EasyClaw before running any queries.
- Specify strategy parameters clearly. "Backtest a 20/60-day MA crossover on 600519 for 2 years" produces better results than "backtest MA on Moutai." Include the stock, strategy variant, parameter values, and time range.
- Evaluate drawdown alongside return. A strategy showing 40% annual return with 35% max drawdown is harder to hold through in practice than one showing 25% return with 10% drawdown. Always check both metrics.
- Use screening as a first filter, not a final decision. Technical scores identify candidates with momentum. Follow up with fundamental checks — valuation, earnings trajectory, sector context — before entering a position.
- Rerun screens weekly, not daily. Technical momentum signals at the daily level generate excessive noise. Weekly screening produces more stable, actionable candidate lists for swing trading timeframes.
Tushare is a professional financial data provider for Chinese markets. The skill uses Tushare's API to access accurate, comprehensive A-share data. You need to register at tushare.pro to obtain a token. Basic tokens are free; higher data access levels require Tushare points earned through community contribution or purchase.
Currently supported strategies include: Moving Average (MA) crossover, MACD (Moving Average Convergence Divergence), KDJ stochastic oscillator, and Bollinger Bands. You can specify parameters for each — for example, the fast and slow period for MA crossover, or the band width multiplier for Bollinger Bands.
Backtest results include: total return percentage, annualized return, maximum drawdown, Sharpe ratio, win rate (percentage of trades that were profitable), and total number of trades executed during the period.
The screener covers all A-share stocks on the SSE and SZSE main boards, ChiNext, and STAR Market — approximately 5,000 stocks. It returns the top 10 by default, but you can request a larger set or filter by sector, market cap, or exchange.
Currently, backtesting runs on one stock per query. To compare strategies across multiple stocks, run sequential queries in the same EasyClaw conversation. A batch backtesting feature across multiple tickers is most efficiently handled by exporting data and running in a Python environment.
Historical daily data covers the full listing history for most stocks — typically 10–20 years for established companies. For recently listed stocks (less than 2 years), backtesting periods are limited to available data.
The skill generates signals based on mathematical indicator calculations, which are mechanical and consistent. However, no technical indicator system has a 100% win rate. Signals should be used as one input in a broader decision process that includes fundamental analysis, position sizing, and risk management — not as standalone trade triggers.
The skill is focused on A-share equities. While some ETF data may be available through Tushare, futures and derivatives are not currently in scope. For equity-focused quantitative analysis, the skill covers the full A-share universe.
A-Share Market Data focuses on data retrieval — live quotes, K-line history, financial metrics, sector fund flows. A-Share Quant adds the analytical layer: backtesting, composite technical scoring, and signal generation. Use Market Data for information lookup; use Quant for strategy testing and systematic screening.
Yes. You can specify which indicators the screener should weight or prioritize. For example, "screen for stocks with strong MACD momentum and trading above the 20-day MA" will apply those specific criteria rather than the default composite score.
Browse more in General Tools or all skills.
Get EasyClaw, add this skill, and start building AI agent workflows in minutes.
Get EasyClaw Free →