"""Curated longlist of candidate funds for the alpha search.

Universe rationale: we cannot meaningfully screen all ~10k registered
funds (most are small, illiquid or strategy-unstable and would not
deserve portfolio consideration anyway). So the UNIVERSE is curated by
reputation — large, liquid, long-tracked funds in the buckets where
idiosyncratic alpha lives (market-neutral/quant, multi-strategy, global
macro, dynamic TA, dynamic credit/convertibles) — and the SELECTION is
data-driven (fundlab/search.py). Tickers are resolved from the fund NAME
via Yahoo search with a precision gate; a candidate that cannot be
resolved cleanly is dropped, never guessed.

The 13-fund shortlist already in funds.json is screened with the same
code so the ranking is consistent (qspnx/pmaix are the user's current
holdings and act as controls).
"""
from __future__ import annotations

# (fund name as searched, strategy bucket, ticker guess or None)
LONGLIST: list[tuple[str, str, str | None]] = [
    # --- market-neutral / quant / pure alpha / event-driven ------------
    ("AQR Diversified Event-Driven Fund", "event_driven", None),
    ("Bridgewater Pure Alpha II Fund", "pure_alpha", None),
    ("Winton Global Quantitative Fund", "cta_quant", None),
    ("Two Sigma Dynamic Strategy Fund", "systematic", None),
    ("Brevan Howard Dymon Asia Fund", "macro_relative_value", None),
    ("Marshall Wace Global Opportunities Fund", "macro_relative_value",
     None),
    # --- multi-strategy -------------------------------------------------
    ("ExodusPoint Diversified Fund", "multi_strategy", None),
    ("Verition Dynamic Risk Fund", "multi_strategy", None),
    ("Millennium Focus Fund", "multi_strategy", None),
    ("Balyasny Absolute Return Multi-Strategy Fund", "multi_strategy", None),
    ("Schonfeld Strategic Opportunities Fund", "multi_strategy", None),
    # --- global macro / risk parity ------------------------------------
    # (T. Rowe Price New Global Opportunity: fund terminated - no data)
    ("Bridgewater All Weather Fund", "risk_parity", None),
    ("Oak Hill Tactical Allocation Fund", "tactical_allocation", None),
    # --- multi-asset / dynamic TA open-ends (the accessible alpha pool) -
    ("Fidelity Multi-Asset Income Fund", "tactical_allocation", None),
    ("Janus Henderson Global Dynamic Dividend Fund", "dynamic_equity", None),
    ("Wellington Dynamic Global Diversified Fund", "tactical_allocation", None),
    ("Lord Abbett Global Opportunities Fund", "tactical_allocation", None),
    ("BlackRock Multi-Asset Income Fund", "tactical_allocation", None),
    ("PIMCO Income Strategy Fund", "tactical_allocation", None),
    ("JPMorgan Diversified Return Fund", "tactical_allocation", None),
    ("Invesco Diversified Equity and Income Fund", "tactical_allocation", None),
    ("T. Rowe Price Global Allocation Fund", "tactical_allocation", None),
    ("Morgan Stanley Global Multi Asset Fund", "tactical_allocation", None),
    ("Fidelity Diversified Multi-Asset Fund", "tactical_allocation", None),
    # --- controls: credit (expected to classify as sleeve mix)
    # (Calamos Dynamic Convertible CCD is a CEF - excluded)
    ("PIMCO Dynamic Income Fund", "dynamic_credit", None),
]

# the 13 unique shortlist funds (share classes resolved once)
SHORTLIST = ["atesx", "atrfx", "cvsix", "jlpsx", "pmaix", "pmorx", "qspnx",
             "svarx", "cosix", "mbxix", "eagmx", "lcorx", "lamhx"]

# broad sleeve set used by the screen (same 21 axes for every fund -
# nothing is tuned to a specific fund, so selection is comparable)
BROAD_SLEEVES = ["qqq", "ivv", "iwm", "vea", "efa", "vwo", "vnq", "bil",
                 "shv", "ief", "tlt", "vblix", "agg", "vweax", "vmbix",
                 "finux", "djp", "gsg", "gld", "fxe", "fxy"]

# the user's current portfolio + benchmark mix (settings.json)
PORTFOLIO = {"qspnx": 0.5, "pmaix": 0.5}
BENCHMARKS = {"spy": 1 / 3, "agg": 1 / 3, "tlt": 1 / 3}