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Blaque Baux Bossy

The 3rd-place capstone — conviction. Concentrate on the winners, or lever up. It buys return, not risk-adjusted return. For the bold, not the best.

Bossy is one of the three capstone allocators of the Blaque Baux family (the bold one, alongside breakthrough and brilliant). Same keeper set, same engine — an allocation rule that takes charge.

Not investment advice. Educational/research software. Nothing here is validated to a live-money bar. See LICENSE.

git clone --recursive https://github.com/blaquebaux/bossy.git
julia --project=engine -e 'using Pkg; Pkg.instantiate()'   # one-time engine setup

The thesis

Three ways to assemble the keepers, three philosophies: humility (breakthrough — risk parity), cleverness (brilliant — optimize), and aggression (bossy — concentrate). Bossy takes charge: tilt hard toward the strongest sleeves (Sharpe-weighted conviction, top-2 concentration) or lever the humble book up. The honest question: does boldness beat humility, or does it just trade drawdown for headline return? The family's whole record says the latter — this proves it at the allocation layer.

The test — and the verdict: 3rd place, honestly

research/bossy_1_conviction.py — same keepers as breakthrough, causal, monthly, net of cost, long-only (Alpaca SIP 2016–2026):

allocator Sharpe CAGR vol maxDD M² exc
risk-parity (breakthrough) +1.16 +11% 9.3% −17% +5.1%
conviction (Sharpe-weighted) +0.68 +8% 13.3% −29% −3.5%
top-2 concentration +0.72 +10% 14.5% −33% −2.7%
1.5× levered risk-parity +1.16 +16% 13.9% −25% +5.1%
SPY (Bogle hurdle) +0.87 +15% 18.0% −34%

Boldness does not beat humility risk-adjusted. Chasing the winners — Sharpe-weighted conviction and top-2 concentration — lowers the Sharpe (+0.68 / +0.72) and deepens the drawdown, because concentration throws away the very diversification that made breakthrough work. The one bold move that "works" is just leverage: 1.5× the humble risk-parity book delivers +16% CAGR (finally beating the index on headline return) — but at the same Sharpe (+1.16) and M² (+5.1%), and a deeper −25% drawdown. Leverage buys return, not risk-adjusted return; it doesn't create edge, it magnifies it (and the drawdown with it).

So bossy is the honest 3rd-place capstone: concentration is a step down, and the only way boldness earns its shine is levered risk-parity — breakthrough with the volume turned up, for the allocator who wants the double-digit headline and will wear the deeper drawdown. Same edge, more of it, both ways.

Status

Research validated — the 3rd-place capstone. Conviction/concentration under-performs humble risk parity risk-adjusted (concentration sheds diversification → lower Sharpe, deeper drawdown); the only bold variant that pays is 1.5× levered risk-parity — same Sharpe/M², +16% CAGR, −25% DD. Return for the bold, not a better edge. Ranked 3rd. The governed version is breakthrough's allocator with a leverage dial.

About Blaque Baux

Blaque Baux is a quantitative research initiative and a subsidiary of Carter Warrens. BlaqueBaux.com is the home for the work; the code lives here on GitHub — open to study, test, and build bespoke strategies on top of.

Anyone can point an AI at a market. The edge is understanding what the data actually says — and turning it into something you can act on. We test relentlessly and put most of it on the record as rejected, with the reason; what survives is built, governed, and validated before it is ever called real. That combination — honest research, reproducible evidence, and execution you can trust — is why Carter Warrens leads on strategy and implementation, not merely uses the tools everyone now has.

The Blaque Baux family

This repo is one sleeve of the Blaque Baux family — a single governed engine steered in many directions. The core repo is the base/blueprint and holds the full family roster.

Layout

engine/     the Blaque Baux platform (git submodule -> blaquebaux/base; incl. PortfolioOpt)
research/   _bossy_common.py + bossy_1_conviction.py (the conviction/leverage bake-off) + scorecard
live/       (rides on breakthrough's governed allocator, with a leverage dial)

License

MIT. (c) 2026 Carter Warrens.

Governed rail (live)

This capstone is wired to its own governed rail — 1.5x levered risk-parity (aggression). live/bossy_allocator.py emits today's target book (as of the last settled close); live/bossy_live.jl routes it through the engine's Layer-3 safety gate (preflight, idempotency, reconciliation, HWM, kill switch) — no LLM in the order path. Dry-run by default (live/run_bossy_daily.sh), graduates to paper once ~/.config/blaquebaux/alpaca_bossy.env exists. Capstones are alternatives, not additions — stacking them is net-negative (see breakthrough's capstone_of_capstones); run the one whose objective fits. Dry-run PASSES the gate.

About

The 3rd-place capstone allocator: CONVICTION / concentration / leverage over the keepers. Concentration underperforms risk parity risk-adjusted (+0.68/+0.72, deeper DD); only 1.5x levered risk-parity pays -- +16% CAGR but same Sharpe/M2 at -25% DD. Leverage buys return, not edge. For the bold, not the best. [Research]

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