https://christianmacion.github.io/portfolio/ Client engagements and shipped deliverables. Newest first. en Sun, 09 Aug 2026 03:08:15 GMT christianmacion26@gmail.com (Christian T. Macion) https://christianmacion.github.io/portfolio/solutions/#11-agent-eval-platform tag:christianmacion26.github.io,2026:solution:11-agent-eval-platform Sun, 09 Aug 2026 03:08:15 GMT A small systematic-trading desk needed an AI workflow that could keep pace with the research pipeline *without* shipping hallucinated or unverifiable analysis. The naive path : a single agent with one prompt : produced plausible but unfalsifiable outputs. The desk needed something closer to a research organization than a chatbot. multi-agent eval-harness MCP model-routing walk-forward deflated-sharpe https://christianmacion.github.io/portfolio/solutions/#7-agent-venture-pipeline tag:christianmacion26.github.io,2026:solution:7-agent-venture-pipeline Sun, 09 Aug 2026 03:08:15 GMT An operator-led venture incubation arm needed a repeatable way to triage, brief, and ledger new business ideas : without one human bottleneck, and without the agent that proposes a decision being the same one that approves it. multi-agent governance venture prompts separation-of-duties https://christianmacion.github.io/portfolio/solutions/#8-agent-editorial-pipeline tag:christianmacion26.github.io,2026:solution:8-agent-editorial-pipeline Sun, 09 Aug 2026 03:08:15 GMT A high-volume editorial workflow was generating content with a measurable "slop index" : generic, templated, easily-detected text. Quality gate was after-the-fact and manual. Production scaled faster than the editorial team could review. multi-agent content eval-gate slop-scanner https://christianmacion.github.io/portfolio/solutions/#9-project-quant-library tag:christianmacion26.github.io,2026:solution:9-project-quant-library Sun, 09 Aug 2026 03:08:15 GMT Most online quant research demos are not reproducible: closed datasets, undisclosed parameters, un-reported multiple-testing bias, and no OOS discipline. A hiring-grade research portfolio needs every one of those addressed explicitly. deflated-sharpe PBO CSCV walk-forward block-bootstrap multiple-testing https://christianmacion.github.io/portfolio/solutions/#crypto-stat-arb-funding tag:christianmacion26.github.io,2026:solution:crypto-stat-arb-funding Sun, 09 Aug 2026 03:08:15 GMT Crypto perps run funding payments every 8h. A naive long-short book ignores funding carry and bleeds slowly when the spread is inverted. A working stat-arb needs the funding cost added back to P&L *before* sizing. crypto stat-arb funding-carry cointegration half-life https://christianmacion.github.io/portfolio/solutions/#cta-curriculum-public tag:christianmacion26.github.io,2026:solution:cta-curriculum-public Sun, 09 Aug 2026 03:08:15 GMT The Philippines has limited access to rigorous CTA-grade technical analysis training. Most curriculum is either imported (US/UK, expensive) or shallow (TA-by-rote). There's a gap for affordable, rigorous, evidence-based technical analysis education. education STA CTA public-curriculum open-source https://christianmacion.github.io/portfolio/solutions/#deflated-sharpe-gate tag:christianmacion26.github.io,2026:solution:deflated-sharpe-gate Sun, 09 Aug 2026 03:08:15 GMT Naive Sharpe ratios ignore the search effort : if you try 100 variants of an idea, the best-looking one will overstate the true edge. The desk needed this multiple-testing correction built into the validation pipeline, not stapled on at the end. deflated-sharpe PBO MinBTL multiple-testing scipy-free https://christianmacion.github.io/portfolio/solutions/#eval-mcp-server tag:christianmacion26.github.io,2026:solution:eval-mcp-server Sun, 09 Aug 2026 03:08:15 GMT LLM eval harnesses live in code or in spreadsheets : neither is a clean integration target for multi-agent pipelines. A multi-agent system needs the eval gates exposed as **tools**, not as Python imports. MCP eval-harness multi-agent contract-first https://christianmacion.github.io/portfolio/solutions/#lookahead-bias-audit tag:christianmacion26.github.io,2026:solution:lookahead-bias-audit Sun, 09 Aug 2026 03:08:15 GMT Look-ahead bias is silent: a backtest that uses future data looks great until you deploy it. A serious research portfolio needs an **explicit audit suite** : a checklist of failure modes with mechanical tests. lookahead-bias point-in-time survivorship frozen-spec https://christianmacion.github.io/portfolio/solutions/#txn-cost-aware-backtest tag:christianmacion26.github.io,2026:solution:txn-cost-aware-backtest Sun, 09 Aug 2026 03:08:15 GMT Backtests that ignore transaction costs, slippage, and latency are the most common source of overfit research. A backtest engine needs all three treated as first-class inputs, not as after-the-fact deductions. txn-costs slippage capacity walk-forward