Xiaohan Meiquant · data viz

Alpha signal research

From signal to portfolio

Systematic alpha research on US equities and China A-shares. Signals are discovered and validated on a self-built platform, then combined into market-neutral portfolios. Signals and implementation stay private; results are published per portfolio.

Market
Portfolio

In developmentResearch status →

    02

    Training, validation and test periods, month by month

    The three periods are split by time. Green months are gains and red months are losses; darker means larger.

    Monthly return, %

    03

    Rolling 12-month Sharpe

    Annualised Sharpe over the past 252 trading days. A flat, positive line means performance is not concentrated in one episode.

    04

    What happens with more capital

    The same signals, re-run with market impact for each fund size.

    05

    From thousands of candidate signals to a small library

    Very few candidates survive the tests. Signals appear here only as anonymous aggregates.

    Pairwise correlation between library signals

    Library growth, portfolio Sharpe after costs

    06

    One platform covers the whole research loop

    Every stage, from data to publishing, is written in-house and shared across markets. Research, testing, backtesting and publishing all run automatically.

    ADataOne store, checked for quality on load
    BSignal researchExpress and evaluate an idea in seconds
    CAutomated screeningGenerate candidates in bulk, test them strictly
    DPortfolio constructionCombine signals into a market-neutral book
    EBacktestingDaily holdings, full trading costs, capacity
    FPublishingThis page refreshes after each research round

    Research principles

    • No look-ahead. Every signal and portfolio is checked automatically so a backtest never uses information that wasn't known at the time.
    • No survivorship bias. On each historical day a portfolio only picks from stocks that actually existed that day.
    • Out-of-sample testing. Results are split by time, and the most recent stretch is held out from all research for a final test.
    • Control for data mining. The more candidates a round tests, the higher the bar; redundant or decayed signals are retired.