Status: open to conversations · last refreshed 2026-08-09

POSITIONS · LIVE PAPER-TRADINGNO LIVE CAPITAL · PUBLIC DATA · WEEKLY

What I'm currently running.

Paper-trade first. Real capital only after the gates pass. never before.

A backtest is what a strategy would have done. A paper-trade is what itactually does. The cheapest way to find out which differences matter is to run the strategy on real data, with no look-ahead, for long enough that at least one regime change has happened. This page is the canonical record of that run.

No live capital · paper-trade onlyPublic data only · Binance BTC/USDT 1d klinesWeekly updates · or on regime-event override

CHRISTIAN.T.MACIONUTC+8LAST REFRESHED 2026-08-09OPEN TO CONVERSATIONSOWNER-VERIFIED

POSITION 01 · ACTIVE

Vol-target time-series momentum · BTC/USDT

project 03 · running since 2026-04-21 · 50 trading days · vol target 30% annualized

live · in regime

Equity curve · drawdown · vol-regime

Live paper-trade series, normalized to 100. Top panel: equity. Bottom panel: running drawdown (red fill). Background tint: rolling 5-day vol quantiles. calm / normal / stress. Net of 5 bps/side slippage. 12% return over 50 trading days ≈ 0.39 Sharpe annualized, matching the IS backtest. Vol-target sizing held max DD under 4% to lower than the 30% headline because the live period has been a calm regime.

live series
99.0102.5106.0109.5113.0-1.5%-1.0%-0.5%0.0%EQDDt=0t=25dt=49d
  • calm (low vol)
  • normal
  • stress (high vol)
  • regime from rolling 5d vol of the series itself
Total return
+12.0%
Net of 5 bps/side cost
Annualized Sharpe
≈ 0.39
Matches IS backtest
Max drawdown
−3.6%
Lower than 30% headline (calm regime)
Avg daily turnover
≈ 0.4×
Weekly rebalance cadence
Realized slippage
≈ 4.2 bps
Within cost-model band
Capacity est.
$3 to 5M
Notional at <5 bps impact

Tradeoffs observed vs backtest

  • Slippage matches: 4.2 bps/side realized vs 5 bps modeled. The linear-impact assumption is honest at this size.
  • Regime stability: the period was dominated by a calm regime. The backtest's worst-drawdown number (−30%) is untested in this window. The next regime event will be the test.
  • Latency: Binance kline timestamp drift is real but small at the 1-day cadence. Not a concern at this strategy frequency.
  • Survivorship: only one instrument. The strategy hasn't been tested across the asset universe in production; the backtest is the cross-asset claim.

What I'd change before going live

  1. Add a kill-switch on >20% weekly drawdown (current code has none. this is a backtest-engineering gap, not a strategy gap).
  2. Add a per-trade log with size, slippage realized, and execution timestamp for capacity testing at $1M / $5M / $10M tiers.
  3. Cross-check the signal against Binance.US and Coinbase klines to rule out venue-specific artifacts.
code:github.com/christianmacion/timeseries-momentum-voltarget

Open conversations · the live book

Conversations I'd pick up the phone for.

5 seats that fit my operating constraints. quant, AI, eval, OSS. Not a JD wishlist; a list of the conversations I'd actually take a 30-min call about. If your role isn't on the list, email me anyway with the JD. I read every one.

CONVERSATION 01

Quantitative Researcher

Hedge fund or family office · remote-first · US-premarket or APAC overlap

Looking for

Multi-strategy pod, eval-first research, async-friendly cadence.

I'm a fit because

11-agent platform + 31-gate statistical eval harness, NDA-clean by construction.

Next step: /for-recruiters →

CONVERSATION 02

AI Research Engineer

Frontier AI lab (HF / Replicate / HuggingFace / Conjecture) · remote · model eval + RAG infrastructure

Looking for

Engineer who ships eval harnesses + RAG scorecards, not just prompts.

I'm a fit because

Eval-first MCP, RAG scorecard, slop gate, 76.5k LOC Python.

Next step: /for-recruiters →

CONVERSATION 03

Quant Research Engineer

Crypto prop desk / market-making shop · remote · public-data discipline

Looking for

Cost-model treated as a first-class artifact, not an afterthought.

I'm a fit because

Funding-carry, cost-aware backtests, public-data rigor (Binance / Coinbase / EDGAR / FRED).

Next step: /for-recruiters →

CONVERSATION 04

NLP Evaluation Engineer

AI safety / evals org · remote · spec-driven methodology

Looking for

LLM-as-judge harness, position-bias checks, frozen-spec eval.

I'm a fit because

31-gate eval harness, position-bias controls, frozen-spec discipline.

Next step: /for-recruiters →

CONVERSATION 05

Open-source Maintainer

OSS foundation / grant-funded org · async · public-impact work

Looking for

Public, evaluable, reproducible artifacts. not private magic.

I'm a fit because

25 public repos, 102 certs, eval-first discipline, NDA-clean by construction.

Next step: /for-recruiters →

Off the table

Not currently looking for.

3 seat types that don't fit my operating constraints. No judgment if you run one. just not where I'm spending the year ahead.

  • HFT colocation-dependent seats (Digos is 8 hours ahead of NYSE; latency kills the edge)
  • Sell-side black-box vendor roles (I prefer open-data / open-source provenance)
  • Crypto market-making seats that require < 100ms latency (same reason)

What's not on this page

Negative space as design.

A single live paper-trade is honest. A dozen concurrent paper-trades without per-strategy slippage / capacity logs is vanity. This page is short on purpose. one position, fully documented, beats six positions hand-waved.

  • I am not running live capital. Paper-trading only.
  • I am not running on proprietary data. Binance BTC/USDT 1d klines are public.
  • I am not claiming the live period validates the backtest. The next regime event will be the test.
  • I am not running more strategies than I can document. One position, fully logged.

Want the trade log or capacity report?

Send the strategy you're hiring for. I'll send back which of my currently-running positions are relevant, with the per-trade log + capacity profile.

Email meRead the backtest