data-quality
Data Quality
Purpose
Guide the design and operation of data quality management programs for financial services firms. Covers the six dimensions of data quality (accuracy, completeness, timeliness, consistency, validity, uniqueness) applied to financial data domains, golden source architecture and master data management, data lineage and provenance tracking, validation rule design for security prices, client data, transaction data, and position data, data profiling and anomaly detection, exception management workflows, data quality governance frameworks, and regulatory requirements for data accuracy including BCBS 239, MiFID II, GIPS, and SEC recordkeeping obligations. Enables building or evaluating data quality infrastructure that ensures downstream systems — portfolio management, trading, compliance, reporting, and billing — operate on trustworthy data.
Layer
13 — Data Integration (Reference Data & Integration)
Direction
both
When to Use
- Designing a data quality monitoring framework for a wealth management or asset management platform
- Building validation rules for security pricing, client data, transaction data, or position data pipelines
- Conducting a data quality assessment for regulatory reporting readiness (SEC filings, GIPS, AML/KYC)
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Analyze commodity markets including futures curve dynamics, roll yield, and supply/demand fundamentals. Use when the user asks about commodity investing, commodity ETFs, contango, backwardation, roll yield, commodity indices (GSCI, BCOM), or commodities as an inflation hedge. Also trigger when users mention 'oil prices', 'gold as a safe haven', 'agricultural futures', 'convenience yield', 'storage costs', 'natural gas', 'copper demand', or ask why commodity ETF returns differ from spot price changes.
179statistics-fundamentals
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
174quantitative-valuation
Estimate intrinsic value of stocks and companies using DCF, dividend discount models, comparable multiples, and residual income. Use when the user asks about discounted cash flow, DCF models, WACC, terminal value, dividend discount models, comparable multiples, or sum-of-the-parts valuation. Also trigger when users mention 'what is this stock worth', 'fair value estimate', 'Gordon growth model', 'free cash flow valuation', 'cost of equity', 'sensitivity analysis', 'exit multiple', or ask whether a stock is overvalued or undervalued.
156asset-allocation
Determine how to distribute capital across asset classes using strategic and tactical allocation frameworks. Use when the user asks about portfolio allocation, mean-variance optimization, Black-Litterman, risk parity, glide paths, or target-date strategies. Also trigger when users mention 'how much in stocks vs bonds', '60/40 portfolio', 'policy portfolio', 'core-satellite', 'liability-driven investing', 'asset-liability matching', or ask how to split their money across investments.
150trade-execution
Guide the design, evaluation, and monitoring of trade execution quality and best execution practices. Use when assessing best execution obligations under FINRA Rule 5310 or RIA fiduciary duty, designing smart order routing across exchanges and dark pools, selecting execution algorithms (VWAP, TWAP, implementation shortfall, POV), building transaction cost analysis (TCA) for pre-trade estimation or post-trade measurement, analyzing bid-ask spread decomposition or market impact or information leakage, conducting best execution committee reviews, evaluating payment for order flow (PFOF) arrangements, interpreting Rule 605/606 reports, or handling fixed income or ETF execution via RFQ protocols. Also covers Reg NMS Order Protection Rule and venue fee structures.
146finance-psychology
Recognize and mitigate cognitive biases that impair financial decisions, and coach clients toward values-driven financial lives. Use when the user asks about behavioral finance, money psychology, loss aversion, overconfidence, herd behavior, or emotional investing. Also trigger when users mention 'why do I panic sell', 'money fights with my spouse', 'I can never save enough', 'fear of investing', 'lifestyle creep', 'keeping up with the Joneses', 'Rich Life', 'money scripts', or ask how emotions affect financial decisions.
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