# Future Work No work here is blocking — we're in a good state. Items below are ordered roughly by priority within each section. Priority labels (`HIGH` / `MEDIUM` / `LOW`) mark items that deserve explicit ranking; unlabeled items are "someday, if the mood strikes." **Next up:** configurable benchmark symbols (low-effort win) and the manual-check accounts mechanism (medium effort, real user value). ## Projections: future enhancements - **Configurable benchmark symbols — priority MEDIUM.** Currently hardcoded SPY + AGG. Route through `projections.srf` as a `type::config,benchmark::SYMBOL` record (or similar). Low effort. - **Configurable return cap per position — priority MEDIUM.** Default: none; cap outliers like NVDA. Should route through `projections.srf` cleanly. - **"Not Retired Yet" accumulation-phase mode — priority HIGH.** Accumulation phase with contributions before retirement. Separate from life events — the simulation has two distinct phases: accumulation (base spending = 0, contributions applied) and distribution (searched-for withdrawal + spending model). Config: `retirement_age::60` or `retirement_in::10`, plus `annual_contribution::100000`. Safe withdrawal search only applies to the distribution phase. Chart shows portfolio growing during accumulation, peaking at retirement, then drawing down. - Configurable MIN period selection (currently 3Y/5Y/10Y, exclude 1Y) - Multiple spending models: flat (current), decreasing (1-2% real annual decrease, Blanchett "spending smile"). Late-life healthcare better modeled as a life event. - Unclassified position handling in allocation split (warn user) - Historical projection comparison: re-run projections from any past snapshot date, overlay actual portfolio trajectory from subsequent snapshots onto the projected percentile bands. Shows how reality tracked against the model. Data is already available in history/*.srf snapshots — just need to load a historical portfolio value and re-run `computePercentileBands` with that starting point, then plot actual values from later snapshots as a line overlaid on the bands. `zfin projections --as-of ` already reruns the simulation against a past snapshot (the prerequisite for this overlay). What's missing is the overlay itself — loading multiple downstream snapshots and plotting their net-worth trajectory on the same chart. **Deferred to ~2027.** Needs a practical volume of real snapshots (currently building up; meaningful backtest requires 12+ months). Backfilling from git history is not viable — the lot-level state on portfolio.srf at a past commit is insufficient to reconstruct the full transaction+contribution picture. Revisit once there are 12+ months of continuous snapshot data. Also consider: `metadata.srf` and `projections.srf` classifications / assumptions drift over time. For back-dated runs we currently use the current versions of both; historical git-tracked versions could be checked out and loaded instead. Edge case for now. ## Audit: manual-check accounts mechanism (NYL, Kelly's ESPP, etc.) — priority HIGH Some accounts/positions can't be reconciled from broker CSVs and need a human-in-the-loop reminder at the audit step. Examples: - **NY Life** — no CSV export at all. Values only live in periodic statements. - **Kelly's ESPP** — accrued payroll-deduction cash doesn't appear in the Fidelity positions CSV until the purchase date hits (typically every 6 months). Between purchases the cash is a real contribution that `zfin audit` can't see. - Future: treat as an open category. The existing `update_cadence::weekly|monthly|quarterly|none` field already sort-of covers this, but has two gaps: 1. It fires off the last *git-detected change*, not the last *human review*. For NYL, the value sometimes hasn't changed in months — so git never fires, cadence never trips. 2. ESPP needs weekly-ish attention while accumulating cash between purchases, but the accrued balance is invisible to the CSV audit. ### Options A. **New `update_cadence::manual` variant** — always fires every audit run until silenced. Blunt but zero design work. B. **`last_refreshed::YYYY-MM-DD` field on `accounts.srf`** — explicit human-review timestamp, decoupled from git-detected changes. Audit compares `today - last_refreshed` against the cadence. User bumps the field when they check the statement. Probably the most correct fit for NYL. C. **Sticky TODO list** — a `todos.srf` or `todo::` field on accounts that audit always surfaces until cleared. General-purpose; also covers "remember to rebalance on 5/15". ### ESPP-specific follow-through ESPP is also a contribution-attribution blind spot. If Kelly's paystub deducts $X/week but the cash lot doesn't reach `portfolio.srf` until the purchase date, the attribution math is under-counting contributions and over-counting the purchase-week gain. Possible fixes are discussed in the "Contributions diff" TODO below — option C there (per-account `cash_is_contribution`) would make manually-entered ESPP cash additions count correctly. ## In-kind transfer support (`type::in_kind`) — priority MEDIUM `transaction_log.srf` parses `type::in_kind` records but the contributions matcher always rejects them with "in-kind transfers not yet supported in v1." In-kind movements need per-symbol matching across accounts: an in-kind transfer of 100 VTI shares from Acct A to Acct B shows up as `lot_removed` on A + `new_stock` on B (or a `rollup_delta` share increase if B already had a VTI lot), neither of which can be matched by the current amount-based cash matcher. Proposed: a second pass in `matchTransfers` that iterates `type::in_kind` records and looks for same-symbol matches across `lot_removed` on `from` + `new_stock`/`rollup_delta` on `to` within the window. Gated on share-count and open_price sanity so a partial transfer doesn't false-positive against an unrelated edit. Driver: when the user starts moving positions between accounts directly (e.g. Roth conversion of already-held shares, 401k → rollover IRA in-kind) rather than liquidating and re-buying. ## Torn SRF files from server sync (root cause unknown) **Status:** Root cause still unidentified. We have mitigations and diagnostics in place that keep torn responses from corrupting the cache, but we don't yet know *why* responses arrive torn. Until we have a root cause, this is not resolved — it's mitigated. Mitigations landed so far: - `syncFromServer` (`src/service.zig`) validates responses via `cache.Store.looksCompleteSrf` before `writeRaw`. Torn HTTP bodies (empty, missing `#!srfv1` header, or no trailing newline) are rejected with a warn-level log and NOT written to cache. - HTTP responses are checked for an `ETag` sha256 header; on mismatch we retry the request once before giving up and falling back to the provider. - Read-path self-heal: on SRF parse failure during read, the cache entry is invalidated so a subsequent refresh can repair without user intervention. - Diagnostics: richer error capture around the sync path. So far, HTTP transit is the dominant source of torn responses — but that's an observation, not a root cause. **Remaining work:** - Identify root cause. Candidates to investigate: proxy/load-balancer behavior, HTTP keepalive reuse, partial reads on the server side, client-side buffer handling. The etag retry tells us whether the problem is per-request or persistent; dig into the diagnostics output when the next occurrence is captured. - Once root cause is known, decide whether the current mitigations are sufficient or whether a targeted fix is needed. The mitigations may end up being the whole answer, but we can't conclude that without understanding the underlying cause. (Content-Length validation was considered and rejected: once the server starts compressing response bodies, Content-Length reflects the compressed byte count, not the decoded payload, so it's not a reliable integrity check.) ## Market-aware cache TTL for daily candles Daily candle TTL is currently 23h45m, but candle data only becomes meaningful after the market close. Investigate keying the cache freshness to ~4:30 PM Eastern rather than a rolling window. This would avoid unnecessary refetches during the trading day and ensure a fetch shortly after close gets fresh data. Probably alleviated by the cron job approach. ## On-demand server-side fetch for new symbols Currently the server's SRF endpoints (`/candles`, `/dividends`, etc.) are pure cache reads — they 404 if the data isn't already on disk. New symbols only get populated when added to the portfolio and picked up by the next cron refresh. Consider: on a cache miss, instead of blocking the HTTP response with a multi-second provider fetch, kick off an async background fetch (or just auto-add the symbol to the portfolio) and return 404 as usual. The next request — or the next cron run — would then have the data. This gives "instant-ish gratification" for new symbols without the downsides of synchronous fetch-on-miss (latency, rate limit contention, unbounded cache growth from arbitrary tickers). Note that this process doesn't do anything to eliminate all the API keys that are necessary for a fully functioning system. A more aggressive view would be to treat ZFIN_SERVER as a 100% source of record, but that would introduce some opacity to the process as we wait for candles (for example) to populate. This could be solved on the server by spawning a thread to fetch the data, then returning 202 Accepted, which could then be polled client side. Maybe this is a better long term approach? ## Low-priority items The following items are acknowledged but not prioritized. Listed here so they don't get lost; pick up opportunistically. ### UX - **CLI options command UX.** The `options` command auto-expands only the nearest monthly expiration and lists others collapsed. Reconsider the interaction model — e.g. allow specifying an expiration date, showing all monthlies expanded by default, or filtering by strategy (covered calls, spreads). - **TUI: toggle to last symbol keybind.** A single-key toggle that flips between the current symbol and the previously selected one (like `cd -` in bash or `Ctrl+^` in vim). Store `last_symbol` on `App`; on symbol change, stash the previous. Useful for eyeball-comparing performance/risk data between two symbols. ### Data quality - **Fix `enrich` command for international funds.** `deriveMetadata` in `src/commands/enrich.zig` misclassifies international ETFs: 1. `geo` uses Alpha Vantage's `Country` field, which is the *fund issuer's* domicile (USA for all US-listed ETFs), not the fund's investment geography. Every US-domiciled international fund gets `geo::US`. 2. `asset_class` short-circuits to `"ETF"` when `asset_type == "ETF"`, or falls through to a US-market-cap heuristic that always produces `"US Large Cap"` / `"US Mid Cap"` / `"US Small Cap"`. Known misclassified tickers (all came back as `geo::US, asset_class::US Large Cap`): - **FRDM** — Freedom 100 Emerging Markets ETF → should be `geo::Emerging Markets, asset_class::Emerging Markets` - **HFXI** — NYLI FTSE International Equity Currency Neutral ETF → should be `geo::International Developed, asset_class::International Developed` - **IDMO** — Invesco S&P International Developed Momentum ETF → should be `geo::International Developed, asset_class::International Developed` - **IVLU** — iShares MSCI International Developed Value Factor ETF → should be `geo::International Developed, asset_class::International Developed` The Alpha Vantage OVERVIEW endpoint doesn't provide fund geography data. Options: use the ETF_PROFILE holdings/country data to infer geography, parse the fund name for keywords ("International", "Emerging", "ex-US"), or accept that `enrich` is a scaffold and emit a `# TODO` comment for ETFs instead of silently misclassifying. ### Options / valuation - **Per-account covered call adjustment.** `adjustForCoveredCalls` in `valuation.zig` operates on portfolio-wide aggregated allocations. It matches sold calls against total underlying shares across all accounts. This is wrong — calls in one account can only cover shares in that same account. Fixing means restructuring `portfolioSummary`, since `Allocation` is currently account-agnostic. Low priority — naked calls are rare, and calls are typically in the same account as the underlying. - **Covered call adjustment O(N*M) loop.** `adjustForCoveredCalls` has a nested loop — for each allocation, it iterates all lots to find matching option contracts. Fine for personal portfolios (<1000 lots). Pre-indexing options by underlying would help if someone had a very large options-heavy portfolio. ### Analysis / correctness - **Analysis account/asset-class total mismatch.** The "By Account" and "By Tax Type" sections in the analysis command sum to slightly more than "Asset Class" (~0.6% error). Likely a discrepancy between how the lot-level account loop values cash, CDs, or options vs how the asset-class section computes them via `portfolio.totalCash()` / `totalCdFaceValue()`. Per-account values themselves are correct after the price_ratio fix. ### Audit - **Audit large-lot threshold tuning.** `src/commands/audit.zig` uses `audit_large_lot_threshold: f64 = 10_000.0` as the cutoff for "surface this new lot for confirmation." Revisit if $10k proves too aggressive (ESPP accruals spam the report) or too permissive (large DRIP confirmations slip past). If runtime tuning becomes necessary, a `--large-lot ` flag or a global `audit_large_lot_threshold` field on `accounts.srf` would be reasonable extensions. ### Infra / performance - **HTTP connection pooling.** Parallel server sync in `loadAllPrices` spawns up to 8 threads, each with its own HTTP connection. Could reuse connections to reduce TCP handshake overhead. Only matters with very large portfolios (100+ symbols) hitting ZFIN_SERVER. - **Streaming cache deserialization.** Cache store reads entire files into memory (`readFileAlloc` with 50MB limit). For portfolios with 10+ years of daily candles, this could use significant memory. Keep current approach unless memory becomes a real problem.