Data

A-Share Data queries A股实时行情、历史数据、技术指标、事件、板块热力图和行业信息. Use it when you need stock quotes, market movers, or analysis for a listed Chinese stock or sector.

MACD Trend Resonance Stock Picker combines moving averages and MACD to screen A-share stocks and build trading plans. It is used for trend-following picks, pullback entries, golden-cross confirmation, divergence reduction, and risk rules.

Ad Budget Allocation optimizes spend across multiple campaigns using marginal returns analysis. Use it to split a fixed ad budget, rebalance after performance changes, or maximize ROAS under budget constraints.

ARIMA Time Series Model builds ARIMA or SARIMA forecasts from univariate historical data. Use it to test stationarity, choose parameters, and produce predictions with confidence intervals.

Compensation Benchmarking compares internal pay to market survey data using compa-ratios and percentile positioning. Use it to assess market competitiveness, build salary bands, and check pay equity.

Cpk Process Capability calculates Cp and Cpk to check whether a stable process can meet specification limits. Use it to compare process capability, estimate defect rates, and assess centering against target values.

Design Of Experiments designs and analyzes factorial experiments to find significant process factors and interactions. Use it to screen variables, optimize settings, or confirm which inputs affect quality or yield.

Ensemble Forecasting combines predictions from multiple models to improve forecast reliability and reduce error. Use it when several ARIMA, Prophet, ETS, or ML forecasts are available and you need a robust combined prediction.

Exponential Smoothing applies SES, Holt, or Holt-Winters methods to forecast time series with level, trend, and seasonality. Use it for simple short-horizon forecasts and lightweight smoothing when a full model is unnecessary.

LDA Topic Modeling discovers latent topics in document collections and assigns documents to themes. Use it when you need exploratory topic extraction, document clustering by theme, or a summary of the main topics in a corpus.

Louvain Community Detection finds densely connected groups in weighted graphs by optimizing modularity. Use it to segment social, organizational, or customer networks and to analyze network structure.

Network Centrality calculates degree, betweenness, closeness, and eigenvector scores for nodes in a graph. Use it to identify key influencers, bridge nodes, and critical infrastructure in network data.