01
Market context
A rolling 60-day standard deviation provides a measure of recent volatility. The model evaluates the last three sessions relative to that distribution to assess potential reversion opportunities in the next session.
Approach
A systematic, automated investment program
Gates Mills Technologies employs systematic, automated trading strategies across the U.S. equity markets.
Thesis
Short-term price dislocations can create opportunity.
Our research is based on the view that behavioral responses to information can create recurring short-term price dislocations. We seek to identify conditions in which those moves may reverse, using a systematic process grounded in market data.
Investment focus
Quantitative signals
Trading decisions are based on proprietary quantitative data. The process does not interpret headlines or rely on discretionary narratives.
Intraday opportunities
The program detects price consolidation to materialize as price dislocations in the form of mean reversion over a horizon of several hours, with a focus on asymmetric risk and reward. It does not rely on estimates of intrinsic value.
Process
From signal to exit
02
Signal confirmation
An initial signal is evaluated alongside corroborating evidence across a broad set of equities and indexes. Capital is committed when the program's entry criteria are met.
03
Exit discipline
The system reassesses open positions as market data updates. Predefined exit rules govern when to close a position and seek to limit downside throughout the trade.
04
Portfolio positioning
Trades are held for one to six hours, and the program holds short-term treasuries overnight. It takes both long and short positions, with approximately 40–50% of trades on the short side.
Our framework
Price behavior in context
GMT transforms open, high, low, and closing prices into a proprietary set of standardized measures. These describe direction, ranges, gaps, and dislocations within and across recent sessions, allowing comparison across price levels and market environments. The resulting framework evaluates each price move in the context of the market structure that preceded it.
01
Parameter robustness
Research emphasizes consistent behavior across a range of parameter settings. We look for signals whose usefulness extends beyond a single optimized configuration.
02
Consistent execution
Entry, exit, position sizing, and exposure follow predefined algorithmic rules. This structure supports a repeatable process and limits discretionary intervention.
03
Risk in context
Position sizing and exit levels are informed by the market's current structure. This allows risk controls to respond to the characteristics of each opportunity.
GMT has developed a family of related strategies around a common set of signal-generation principles, with more than a dozen variants deployed using real capital.
Philosophy
Signal and noise
01
Selective participation
Our research seeks to distinguish routine price fluctuations from conditions that may precede larger moves in either direction.
02
Explainable signals
We favor signals that are simple to explain and evaluate. Research examines how they behave across a range of market environments.
03
Defined limitations
A signal's limitations are central to its evaluation, including the conditions in which it may become unreliable.
Interpreting the framework
The diagram illustrates the distinction between routine price variation and larger directional moves. The central band represents moves within one standard deviation of the average. Our research seeks signals that may precede moves outside that range.
Past performance of these strategies is not necessarily indicative of future results. There is the possibility of loss, and all investment involves risk including the loss of principal. See Important Information.
Contact
Connect with our team
Contact our team to learn more about the firm and its investment approach.