Prices are the visible surface of stocks and flows, feedback loops, and thousands of interacting participants. We pair fundamental macro research with system dynamics and agent-based models to see where a trend is likely to reinforce itself, and where it is likely to break.
Every model we build starts from the same principles. Open them below, then explore two toy models built on them: one about feedback loops, one about crowds.
Economies accumulate: capital, inventories, debt, sentiment. We model those stocks and the flows that fill and drain them, then trace the reinforcing and balancing loops that decide whether a trend accelerates or reverses.
Markets are made of participants with rules, limits and incentives. Agent-based models let us simulate how they interact, and how crowding can turn a small shock into a cascade.
Models show where a small change can have an outsized effect. That is where expectations are most likely to become unanchored, and where we focus our research.
We hold our views to the discipline of a model: explicit assumptions, delays and limits. Then we stress-test them against data, against history and against each other.
What happens when investment races ahead of returns?
When does a small shock become a cascade?
Forty simulated pods run long/short books, and part of every book sits in the same crowded trades. Each pod halves its risk at its drawdown limit and is stopped out a little further down. Their selling moves prices, which hits everyone else holding the same names.
Illustrative toy models with simplified, hypothetical parameters, shown to explain how we think about systems. They are not forecasts, and they do not represent any Goose Hollow strategy, portfolio or performance.
We utilize a disciplined and process-driven methodology to seek out opportunities while keeping a low correlation to the broader markets in our alpha strategies — combining fundamental analysis with quantitative tools to identify them.
We seek global investment opportunities in Equities, Fixed Income, Commodities, and Currencies. Investment decisions are made using a process-driven approach that draws insights from data on macro fundamentals, valuations, and sentiment.
We make extensive use of custom quantitative tools and alternative data sets to identify and measure opportunities. These tools continue to change as more data becomes available and computational power increases.
Risk management and portfolio management cannot be separated — we are all risk managers. Positions are optimally structured to produce attractive risk-reward opportunities, and our systems have been tested during periods of turbulence. We assess and monitor market, credit, and geopolitical risk.