plugins/advisory-practice/skills/portfolio-management-systems/SKILL.md
Select, configure, and operate portfolio management systems for advisory firms, covering model portfolios, UMA/sleeve management, drift monitoring, rebalancing, and custodian data feeds. Use when the user asks about choosing a PMS platform, building or distributing model portfolios, implementing UMA or sleeve-based management, setting drift monitoring thresholds, aggregating held-away assets, reconciling PMS with custodian records, configuring PMS-based billing, or troubleshooting custodian feed issues. Also trigger when users mention 'portfolio management system', 'Orion', 'Black Diamond', 'Tamarac', 'Addepar', 'Advent APX', 'model portfolio', 'sleeve management', 'rebalancing engine', 'custodian feed', or 'PMS migration'.
npx skillsauth add joellewis/finance_skills portfolio-management-systemsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Expanded detail for each numbered section below lives in references/platform-details.md. Load it when the task needs: §1 the platform comparison table or IBOR/OBOR reconciliation dimensions; §2 full model specification, governance steps, or marketplace detail; §3 UMA cash-waterfall rules or the UMA/SMA/wrap comparison table; §4 drift measurement formulas, threshold configurations, or tax-aware rebalancing logic; §5 aggregation data sources and data-quality failure modes; §6 break-resolution workflow, corporate-action types, or cost basis methods; §8 daily vs. monthly calculation and benchmark tracking detail; §10 the custodian data-flow table, integration methods, and feed timing. (Reference §7 trading and §9 billing are pointers to the order-management-advisor and fee-billing skills — load those skills directly instead.)
The PMS is the operational nerve center of an advisory practice, orchestrating data flow between custodians, trading platforms, reporting engines, CRM, and planning tools. Core functions include portfolio construction, model management, rebalancing, trading, performance reporting, and billing. Major platforms: Orion, Black Diamond, Tamarac, Addepar, Morningstar Direct, Advent/APX. The PMS serves as the firm's Investment Book of Record (IBOR), which must be reconciled daily against the custodian's Official Book of Record (OBOR).
Model portfolios define target allocations (asset classes, securities, weights) applied consistently across client accounts. Types include strategic (SAA), tactical (TAA overlays), and specialty models (income, ESG, tax-managed). Firms typically use a two-tier hierarchy (firm-level + advisor-customized). Model changes trigger versioning, account identification, trade proposal generation, and tax-aware transition. Third-party model marketplaces (BlackRock, DFA, Vanguard, PIMCO) allow smaller firms to access institutional-quality investment management.
Unified Managed Accounts (UMAs) divide a single custodial account into virtual sub-accounts (sleeves), each following its own strategy or manager. Benefits: cross-sleeve tax optimization, simplified reporting, reduced account proliferation, and unified cash management. Cash waterfall rules govern deposits, withdrawals, and income allocation across sleeves. UMAs differ from SMAs (single-strategy, one manager) and mutual fund wraps (indirect ownership, limited customization). Typical minimums: $250K-$1M+.
Drift is the divergence of actual weights from targets caused by differential returns and cash flows. Measured as absolute drift (percentage-point difference) or relative drift (percentage of target). Threshold configurations range from conservative (3%/15%) to permissive (7%/30%). Rebalancing approaches: calendar-based, threshold-based, opportunistic (cash-flow-directed), and hybrid. Tax-aware rebalancing incorporates capital gains minimization, loss harvesting, wash sale avoidance, and gain budgets.
A complete client picture requires visibility into all assets, including employer plans, stock options, RSUs, bank accounts, and accounts at other custodians. Data sources: aggregation services (Plaid, Yodlee, MX, ByAllAccounts), custodian feeds, manual entry, and employer plan integrations. Challenges include data staleness, categorization errors, and broken connections. The PMS should provide both managed-only and total-household reporting views.
Portfolio accounting tracks positions, transactions, cost basis, cash flows, and accrued income. Daily reconciliation compares PMS against custodian across three dimensions: positions, transactions, and cash. Breaks require classification, root-cause diagnosis, correction, and documentation. Common break sources: corporate actions (splits, mergers, spin-offs, DRIP), trade settlement timing, and data feed issues. Cost basis methods: specific identification, FIFO, and average cost.
The PMS generates trade proposals from model changes, rebalancing triggers, cash flows, and ad-hoc instructions. In larger firms, trades flow through a separate OMS for compliance checks, block aggregation, and execution routing. Block trading aggregates orders across accounts for best execution with pro-rata allocation. Pre-trade checks cover restricted securities, concentration limits, client restrictions, regulatory limits, and cash minimums. Implementation methods: direct custodian trading, third-party EMS, and mutual fund trading platforms.
The PMS computes returns at multiple levels: security, sleeve, account, household, model, composite, and firm. TWR (time-weighted) eliminates cash flow impact for manager evaluation and GIPS compliance. MWR (money-weighted/IRR) reflects the investor's actual experience. Daily performance provides the most precise TWR; monthly uses approximations like Modified Dietz. Benchmarks (primary, blended, custom) must be tracked at the same frequency as portfolio returns.
Fee structures: AUM-based (flat or tiered/breakpoint), flat/retainer, performance-based (qualified clients only), and blended. Billing frequency: quarterly (most common), monthly, or annual. Advance billing requires proration; arrears billing delays revenue recognition. Billable AUM determination requires clear policies on included/excluded assets and household aggregation. Fee deduction via direct debit (most common) or invoice. Revenue tracking covers client, advisor, model, and strategy dimensions.
Custodian integration provides the data backbone: positions, transactions, cash, cost basis, corporate actions, and new accounts flow from custodian to PMS; trade instructions and fee invoices flow from PMS to custodian. Integration methods: proprietary batch feeds (CSV/XML), FIX protocol, APIs, and third-party aggregators. Feed timing: EOD batch (most common), intraday updates, and real-time streaming. Multi-custodian management requires data normalization, consolidated views, custodian-specific trade routing, and separate reconciliation. Custodian transitions (e.g., TD Ameritrade to Schwab) require account mapping, feed migration, and historical data transfer.
See references/examples.md for three end-to-end worked examples — a PMS migration for a growing RIA, a UMA/sleeve implementation for HNW clients, and a reconciliation break investigation. Load it when the user needs a full scenario walkthrough.
Treating the PMS as the official record. The custodian, not the PMS, maintains the legally authoritative record of client assets. When discrepancies exist, the custodian record governs. Firms that rely solely on PMS data without reconciliation risk reporting incorrect positions and performance.
Neglecting daily reconciliation. Firms that reconcile weekly or monthly allow breaks to compound, making root-cause diagnosis much harder. A corporate action missed on Monday may cause cascading errors in performance, billing, and rebalancing throughout the week.
Over-engineering drift thresholds. Setting drift bands too tight (e.g., 1% absolute) generates excessive trading, increasing costs and tax drag. Setting bands too loose (e.g., 10% absolute) allows portfolios to deviate significantly from the intended risk profile. Calibrate thresholds based on asset class volatility and client tax sensitivity.
Ignoring wash sale rules across accounts. Tax-loss harvesting in one account while purchasing substantially identical securities in another account with the same tax ID disallows the loss. The PMS must monitor wash sale windows across all accounts for a client or household.
Stale held-away data. Aggregated held-away data that has not refreshed in weeks or months can lead to materially incorrect total-household allocation views and flawed planning recommendations. Implement alerts for stale connections and establish a process for client re-authentication.
Inconsistent model governance. Allowing advisors to freely modify firm models without oversight creates style drift and compliance risk. Establish clear policies on which model elements advisors can customize and require documentation of deviations.
Cost basis discrepancies between PMS and custodian. The PMS and custodian may calculate cost basis differently, especially after corporate actions, transfers, or wash sale adjustments. If the firm relies on PMS cost basis for tax-loss harvesting decisions but the custodian reports different basis to the IRS (Form 1099-B), clients may face unexpected tax consequences.
Billing on stale or unreconciled data. Calculating fees on PMS positions that have not been reconciled against the custodian may result in over- or under-billing. Always reconcile before running billing.
Failing to test custodian feed changes. Custodians periodically update their data feed formats. Firms that do not monitor for format changes or test in a staging environment before production risk silent data-import failures.
Overlooking performance calculation methodology. Reporting MWR when TWR is appropriate (or vice versa) can mislead clients or violate GIPS standards. Understand when each methodology is appropriate and clearly label which method is used in client-facing reports.
testing
Model, forecast, and interpret volatility using time-series models and options-implied measures. Use when the user asks about EWMA, GARCH models, implied volatility, volatility surfaces, volatility term structure, or the VIX. Also trigger when users mention 'volatility smile', 'volatility skew', 'realized vs implied vol', 'volatility risk premium', 'vol clustering', 'mean-reverting volatility', 'options pricing inputs', 'RiskMetrics', 'decay factor', or ask how to forecast future volatility for risk management.
testing
Execute a complete tax-loss harvesting workflow from candidate identification through post-harvest monitoring. Use when the user asks about finding TLH candidates, gain/loss budgeting, replacement security selection, wash-sale compliance, or harvest execution planning. Also trigger when users mention 'unrealized losses in my portfolio', 'swap ETFs for tax purposes', 'harvest losses before year-end', 'substantially identical security', 'wash-sale window', 'NIIT offset', 'loss carryforward', or ask how much tax they can save by harvesting.
testing
Maximizes after-tax returns through strategic asset location, gain/loss management, and withdrawal sequencing. Use when the user asks about asset location, Roth conversions, tax-efficient withdrawals, tax lot selection, or charitable giving with appreciated securities. Also trigger when users mention 'which account should I hold bonds in', 'tax drag', 'Roth vs Traditional', 'RMD planning', 'bracket stuffing', 'HIFO vs FIFO', or ask how to minimize taxes on investments. For tax-loss harvesting execution and wash-sale mechanics, see the tax-loss-harvesting skill.
development
Plan and track savings for specific financial goals including retirement, education, and home purchase. Use when the user asks about required savings rates, 529 plans, retirement accumulation targets, down payment planning, or goal prioritization. Also trigger when users mention 'how much do I need to save each month', 'am I on track for retirement', 'college savings', 'safe withdrawal rate', '4% rule', 'FIRE savings rate', 'catch-up contributions', 'employer match', or ask how to balance competing savings goals.