A typical Anselme Capital portfolio has two parts. One is broad, systematic, and built from decades of data. The other is small, deliberate, and long-held. Together they describe the same firm doing two complementary things.
Most of a portfolio sits in passive asset classes. Their choice and composition come out of our mean-variance optimization, which puts the portfolio on the efficient frontier. We know the monthly performance of every asset class we use since June 1998 — twenty-eight years of data, and the same year the firm was founded. That allocation shifts about twice a year.
We lean passive for two reasons. It tends to be more tax efficient, and our clients tend to be in high tax brackets. And that long record of asset-class behavior lets us design portfolios with controlled volatility. Anselme Capital focuses on volatility as much as on return.
We’re in a time of rapid and profound technological change. To capture it, a smaller part of the portfolio — 20% or less, depending on the model — goes to a dozen or so individual stocks that capitalize on those shifts, mainly in artificial intelligence and infrastructure. We look for sustainable strategic advantage, and we intend to hold them for some time. This is stock picking with tax efficiency in mind.
Our most efficient portfolio family is produced by a mean-variance optimization over monthly market data going back to June 1998, with modest leverage treated as an asset class. It’s named after the giboulées — the sudden spring storms of the Alps — and designed, in back-testing, for relative calm through chaotic markets.
We use leverage modestly and deliberately. Rather than viewing it simply as a way to increase investment exposure, we often use it as a low-cost source of liquidity within the portfolio.
That flexibility can make it easier to trade efficiently, manage taxable gains, and cover large or unexpected expenses without being forced to sell appreciated investments and potentially trigger substantial capital gains taxes.
Leverage still carries risk and can amplify losses as well as gains, which is why we use it conservatively and as part of the broader portfolio strategy rather than as a standalone return-seeking tool.