STS Glossary
Here you can find important terms and definitions, explained the sentient way.
These definitions have been layered in order of importance.
Market logic is a falsifiable explanation tied to how auctions operate fundamentally, and what constraints create repeatable setups, not “because my backtest said so”.
STS repeatedly pushes the question: what verifiable mechanism would make this edge persist? and we stress if traders have to rely on narrative instead of facts that they drop it.
It is the “why” that must come before backtesting, otherwise traders are often adjusting to noise that the market is unlikely to repeat.
Market logic
Markets continuously match buyers and sellers as orders arrive, rather than clearing at fixed moments. Price moves because liquidity at the best bid/ask gets consumed and the auction must search for the next level where trade can occur.
Continuous auction
The mechanics of how price is actually formed and how aggressive orders interact with resting liquidity. Understanding market microstructure is understanding the potential causation behind movement which is important for logical strategy development.
Market microstructure
Constraints are the hard limits within which your strategy must operate on such as leverage, trading times and maximum drawdown. Designing with constraints first stops you from building idealistic systems that cannot be traded as intended.
Constraints
A measurable condition that meaningfully shifts expectancy in your favour, beyond what randomness and costs would explain. This results in entries. To us, a signal is not “something looks nice”, it is something that “is likely to provide a return based on data” and can be expressed as mechanical rules which are tested and shown to survive robustness checks.
Signal
Edges are the small, repeatable advantages your strategy has over random trading after all costs, often confined to particular markets and regimes. Each strategy component adds to it, one weak link enough to shatter it.
Edges
Expectancy is the average profit or loss per trade you can expect over a large number of trades, after all costs, we measure it in multiples of the unit of Risk (R) taken per trade.
Example: 1% could be 1R. A strategy takes a trade losing 1R (-1R), followed by a gain of 2% (+2R). Expectancy: (2R - 1R) / 2 trades = +0.5R average per trade (good).
Expectancy
Edge decay is the gradual weakening of an edge over time as markets adapt, liquidity changes, or more traders crowd into the same pattern. When decay sets in, a once strong system can become flat or negative, so clinging to it out of habit is how traders slowly give back many months or years’ worth of gains.
Imagine it like harvesting a fresh crop, a profitable strategy. When the strategy loses its edge, it has expired.
Edge Decay
Alpha decay is the loss of a strategy’s excess return after its logic or rules become widely known and copied, so the edge no longer exists.
Think of it like this: a business does something unique that brings in lots of customers (an edge), then competitors copy it and the business no longer has an advantage. The same happens in trading, the move gets priced in before regular traders can take benefit from it.
Alpha Decay
The baseline upward bias in financial markets such as the S&P 500 over long horizons, largely due to structured incentives, market participation and macroeconomics (reinvestment, pensions, passive allocation). It makes certain long-biased behaviours more viable over larger samples.
Positive drift can be tied to a single event such as good news too.
Positive drift
A repeatable tendency for returns or behaviour to cluster around particular calendar windows (monthly, quarterly, turn-of-month, session-based), driven by predictable market participant activities and constraints rather than chart patterns. Seasonality is only useful if it's grounded in something fundamental which is likely to persist, it survives costs and remains stable across tests.
Seasonality
Variance is how much your returns fluctuate around their average, creating inevitable streaks of wins and losses even on breakeven systems. Variance often makes traders abandon robust edges after a small losing streak, or mistake a lucky profitable run for skill and blow up when adverse conditions present themselves.
Variance
Return Distributions describe how results such as trade outcomes, daily returns or drawdowns are spread out, not just the average.
Think of it like this: distributions show you the speed at which your profits accumulate, and how your losses potentially can add up. It's a volatility measure.
Distributions
The path-dependent nature of trading is where each decision builds upon the last. Variation in outcomes, when understood and used effectively, helps you use the correct position sizing, so you can succeed when your strategy performs well while also surviving the bad runs.
Trading success is path dependent
A market regime is the market behaviour over a period of time, defined by factors like volatility, trend direction, and liquidity. It describes how price discovers new value over a given time horizon, and how that behaviour differs from other periods.
A strategy that works well in one regime (for example, low volatility grind up with positive drift) can fail badly in another (for example, high volatility ranging) which is why STS treats regime as more important than the exact entry pattern.
Market regime
Overfitting is when a strategy is adjusted to fit, complement or ‘predict’ unique events of past data rather than a real market behaviour (effect) grounded in a logical mechanism (cause). Most people who backtest make this mistake.
This is dangerous because it looks great in backtests and then collapses when conditions change, costs are applied, or you extend the sample. The consequence is usually impressive performance with little integrity: small rule tweaks or different dates often break it.
Overfitting
Instruments are the specific products you trade, such as CFDs, Futures, FX pairs or individual equities. Every instrument has its own liquidity, cost structures.
Instrument
Timeframes are the lengths of the bars you look at, for example 1 minute, 15 minutes or 4 hours.
Timeframe
To us, trade windows are the specific hours or sessions during which your system is allowed to open new trades, often aligned with liquid and volatile periods like London session or New York open.
Trade windows
Drawdowns are the drops from a peak in your equity curve to a subsequent trough before a new high is made. Knowing your typical and worst historical drawdowns makes it easier to sit through normal pain.
If you have seen 10 losing trades in a backtest, when you experience it in real time it can be dismissed as, “I have seen this before.” Stoicism is earned through data.
Drawdowns
A baseline model where price changes are largely unpredictable from past price alone, because next moves are dominated by new information and randomness. This is not our belief system but STS treats this as the default assumption you try to disprove locally with evidence (from testing).
Random walk
A theoretical extreme where prices instantly and perfectly incorporate all information, leaving no exploitable edge after costs. In that world, trading returns beyond noise are not realistically achievable.
We use this as a baseline to exploit market inefficiencies and understand what they are fundamentally.
100% efficient
OHLC data is the set of Open, High, Low and Close prices that define each bar or candle on your chart for a chosen timeframe. It is a compressed view of the underlying tick-by-tick data. Can be useful, but not on its own.
OHLC data
Backtests are individual runs of a strategy we perform on historical data using a set of rules and parameters, to measure returns, drawdowns and other statistics.
Backtests
A mental shortcut that helps you make a decision or solve a problem quickly, without needing a full, perfect analysis every time. A rule of thumb.
Heuristic
Licensed people in prop desks, investment banks and other institutions who actually deploy risk in the real market, with real constraints and real execution costs as a profession, not just commentators. Practitioners think in mechanisms, costs, and repeatability, not narratives which is where STS aligns.
Practitioners
Journal of Financial and Quantitative Analysis. An accredited peer-reviewed academic journal that we have cited where you should expect empirical finance research, asset pricing work, market microstructure papers, and statistical studies relevant to trading claims.
JFQA
The Quarterly Journal of Economics. An accredited peer-reviewed economics journal, typically broader than trading, but still a source for rigorous work on incentives, behaviour, institutions, and economic mechanisms that can matter for how markets function, we also cite this journal in our work.