Data & Analytics

Structures ESG and impact reporting for fund investors with metric collection, framework alignment, and progress communication. Use when preparing ESG reports, collecting impact data, or aligning with reporting frameworks.

Builds cap table models with round-by-round dilution, ESOP expansion, convertible note conversion, and exit waterfall analysis. Use when modeling cap tables, projecting ownership dilution, or calculating exit proceeds distribution.

Prices variance and volatility swaps with replication methodology, convexity adjustment, and discrete monitoring analysis. Use when pricing vol products, modeling variance swaps, or evaluating volatility strategies.

Builds TCA frameworks with implementation shortfall, VWAP comparison, and market impact estimation across asset classes. Use when conducting TCA, measuring execution quality, or analyzing trading costs.

Builds strip and tail-end fund models with remaining portfolio analysis, unfunded obligation treatment, and duration-adjusted pricing. Use when modeling strip deals, evaluating tail-end portfolios, or analyzing remaining value.

Analyzes buyback program design with timing optimization, price sensitivity, and EPS accretion impact modeling. Use when optimizing buybacks, modeling repurchase economics, or comparing return-of-capital alternatives.

Analyzes securities lending market with borrow cost, short interest dynamics, and fail-to-deliver monitoring. Use when analyzing lending markets, tracking borrow costs, or evaluating short selling dynamics.

Analyzes rights offering dynamics with theoretical ex-rights price, subscription premium, and nil-paid value calculation. Use when evaluating rights offerings, modeling TERP, or analyzing subscription arbitrage.

Builds regime detection models with hidden Markov, threshold, and Bayesian change-point methodologies for strategy adaptation. Use when modeling regime changes, detecting market shifts, or adapting strategies to market conditions.

Designs rebalancing triggers with calendar-based, threshold-based, and hybrid approaches with tax and cost optimization. Use when designing rebalancing rules, optimizing rebalancing frequency, or modeling turnover impact.

Analyzes intraday volatility dynamics with open/close effects, lunch-time patterns, and event-driven volatility estimation. Use when modeling intraday volatility, timing order execution, or analyzing time-of-day effects.

Builds growth equity return models with minority/majority economics, participation rights, and preference stack analysis. Use when modeling growth equity returns, projecting minority investment outcomes, or analyzing preference structures.

Builds default probability and recovery rate models with industry data, structural analysis, and loss-given-default estimation. Use when modeling credit losses, estimating recovery values, or analyzing default scenarios.

Builds recovery waterfall models with absolute priority, secured vs unsecured claims, and plan of reorganization distribution analysis. Use when modeling bankruptcy recoveries, analyzing claim priorities, or estimating creditor distributions.

Builds carry waterfall models with preferred return hurdles, catch-up provisions, and clawback mechanics across deal-by-deal and whole-fund structures. Use when modeling carry economics, comparing waterfall structures, or analyzing GP incentive alignment.

Runs Monte Carlo simulations for portfolio analysis with return distribution, tail risk, and path-dependent scenario evaluation. Use when running portfolio simulations, estimating tail risk, or analyzing return distributions.

Constructs fund-level performance reporting with IRR, MOIC, DPI, RVPI, PME, and vintage year benchmarking. Use when building fund reports, calculating performance metrics, or preparing LP reporting packages.

Evaluates local currency government and corporate bond markets with yield analysis, inflation dynamics, and FX carry assessment. Use when analyzing local currency debt, evaluating EM bond opportunities, or assessing carry strategies.

Evaluates factor timing strategies with macro regime indicators, valuation spreads, and momentum signals for factor rotation. Use when analyzing factor timing, evaluating rotation signals, or designing tactical factor allocation.

Evaluates alternative trading systems with fill rate analysis, information leakage assessment, and venue toxicity measurement. Use when analyzing dark pools, evaluating ATS venues, or assessing execution venue quality.

Evaluates factor crowding with positioning analysis, valuation spread monitoring, and unwind risk assessment. Use when analyzing factor crowding, assessing unwind risk, or monitoring factor valuation extremes.

Monitors cross-asset correlation patterns with regime-dependent analysis and diversification effectiveness assessment. Use when analyzing correlations, assessing diversification, or evaluating cross-asset relationships.

Use when connecting any agent to data and external capabilities. Covers Databricks managed MCP servers (Vector Search, Genie, SQL, UC Functions), the databricks-mcp client library, _meta parameters, external MCP servers, code interpreter, non-MCP connections, resource grants, custom retriever schemas, tool cookbook (web search, SQL, file generation, HTTP), runtime guardrails, and end-to-end external MCP examples. Foundation Step 3. Consumed by all agent tracks (A, B, C).

Generate synthetic data with Faker for Bronze layer testing with configurable data corruption. Use when creating test data for data quality validation, testing DLT expectations, or simulating production-like datasets. Supports realistic data generation with intentional corruption patterns mapped to specific DQ expectations.