Investment philosophy

A draft, written in public. Iterated as the model portfolio and research stack mature.

1. Two lenses, one decision

The CMT taught me to read the tape — trend, breadth, rotation, relative strength. The CFA program teaches what something is worth. Most analysts pick a side; I work both. Fundamental gives me the what and why; technical gives me the when and how much.

2. Top-down, then bottom-up

Macro sets the opportunity set. Sector and factor rotation say which areas of the market are being rewarded right now. Bottom-up security work happens inside that frame — not in spite of it. Starting bottom-up alone means under-pricing regime risk.

3. Technicals as risk management, not prediction

Technical signals are most useful for one job: telling me when something I've fundamentally underwritten is being rejected by the market — and conversely, when a thesis is starting to be confirmed. Rotation, trend, and breadth are inputs to sizing and timing, not substitutes for valuation work.

4. Process > outcomes (over any single quarter)

Outcomes are a noisy signal of process quality at short horizons. The fix is to make the process inspectable: written theses, dated entries, attribution, and an honest review when names disappoint. The portfolio publishes its dirty laundry.

5. Concentration with discipline

Diversify by factor, not by ticker count. A 20-25 name book of high-conviction ideas across uncorrelated drivers beats a 60-name book where the marginal positions exist out of fear of being wrong.

6. Valuation matters — eventually

The market spends years not caring about valuation and then a quarter caring about nothing else. Sizing should reflect the gap between intrinsic value and price; technicals reflect whether the path to closing that gap has begun.

7. Wealth advisory respects sequence risk

For client capital, the right portfolio depends on the path, not just the destination. Mean-variance is a starting point; risk parity, drawdown sensitivity, and goals-based bucketing all live downstream.

8. Models are accountability

Every model behind this research is open math I built myself. If a thesis depends on a margin assumption I can't justify with a sensitivity table, or a setup that doesn't survive a different lookback window, the thesis is weaker than I think.

Last revised — draft v0.2. Some of these will change with experience. The site will reflect that.