Lacma Scores
In the world of forex trading, standard metrics have long served as the bedrock of performance analysis. The Sharpe Ratio, Jensen’s Alpha, and Calmar Ratio have helped traders and investors quantify risk and return for decades. But for Liquid Markets AI mentoring , risk management and support system, with multiple broker trading, cross-platform accounts, and increasingly complex market dynamics, static formulas alone are no longer enough.
With Lacma, we’ve developed a new framework. One that doesn’t discard traditional metrics but instead vectorises them—layering comparative intelligence and continuous AI refinement on top of established financial science. The result is a suite of proprietary scores designed to give traders, partners, and risk managers a clearer window into account behaviour, risk exposure, and performance sustainability.
This article introduces the four core Lacma scores: Risk Score, Trend Score, Event Trading Score, and Mean Reversion Score. These scores are available to traders in the free AI Trader App and to managers in the AI Risk Dashboard
The Lacma Philosophy: Context Is Everything
Before diving into the individual scores, it’s worth understanding what makes the Lacma approach different.
Traditional metrics evaluate an account in isolation. They ask: How has this account performed relative to the risk it took? It’s a valid question, but it misses something crucial—context.
If every account in a platform is posting strong returns during a bullish trend, how much of that performance is genuine skill versus simply being carried by the market? Conversely, if an account underperforms during a volatile event, is it a flawed strategy or just a reflection of impossible trading conditions?
Lacma’s methodology solves for this through comparative market context. By analysing each account’s performance against all other active accounts operating under identical market conditions, we can isolate signal from noise, skill from luck, and genuine risk from temporary turbulence.
This comparative layer, combined with our proprietary AI engine that continuously back-tests and refines its weightings, forms the foundation of every Lacma score.
The Lacma Risk Score: Quantifying Capital at Risk
Definition
The Lacma Risk Score is a dynamic classification metric, expressed on a scale of 1 to 100, designed to vectorise the risk profile of individual trading accounts across different platforms. Its primary function is to indicate the statistical probability of an account suffering a proprietary-defined percentage loss of capital.
Methodology
The Risk Score is generated through a multi-layered analysis:
Absolute Risk Metrics: The foundation incorporates Lacma-derived financial data, including but not limited to the Sharpe Ratio, Jensen’s Alpha, Calmar Ratio, and Risk of Ruin. These established metrics provide a baseline understanding of risk-adjusted returns.
Comparative Market Context: Lacma analyzes the performance of each account against all other active accounts within the platform. Because every account operates under identical market conditions, this comparative analysis helps distinguish genuine trading skill from market luck, making outlier risk exposure immediately visible.
Proprietary AI Adjustment: The weighting, interpretation, and vectorisation of these data points are governed by a proprietary algorithm within the Lacma consensus engine. This algorithm is continuously refined, back-testing the score’s accuracy against actual account performance to enhance its predictive power regarding the probability of capital loss.
What It Tells You
A high Risk Score (closer to 100) suggests elevated probability of significant drawdown based on historical behaviour, comparative underperformance during stressed periods, and metrics that signal instability. A low Risk Score (closer to 1) suggests relative stability, consistent risk management, and resilience compared to platform peers.
The Lacma Trend Score: Measuring Directional Strength
Definition
The Lacma Trend Score is a dynamic classification metric, expressed on a scale of 1 to 100, that vectorises the strength and sustainability of an account’s directional trading performance. It indicates the statistical likelihood that current profit or loss trajectories will persist, based on historical consistency and market alignment.
Methodology
Trend Consistency Metrics: The score evaluates the account’s performance over time, analysing factors such as consecutive winning or losing periods, average hold times, and the correlation of trades to broader market movements.
Comparative Market Context: Lacma compares the account’s trend behaviour against all other active accounts within the platform. This isolates whether a trend is unique to the account’s strategy or merely reflective of a broader market move affecting everyone.
Proprietary AI Adjustment: The weighting and vectorisation of these data points are governed by a proprietary algorithm, continuously refined through back-testing against actual account outcomes to improve its ability to predict trend sustainability.
What It Tells You
A high Trend Score indicates strong directional consistency that persists even when compared to peers—suggesting genuine trend-following skill rather than market beta. A low Trend Score may signal erratic performance, trend inconsistency, or an account that is simply mirroring broader market movements without adding independent value.
The Lacma Event Trading Score: Resilience Under Pressure
Definition
The Lacma Event Trading Score is a dynamic classification metric, expressed on a scale of 1 to 100, that vectorises an account’s performance and risk exposure around significant market events. It indicates the statistical probability of an account experiencing amplified volatility or drawdown during periods of high-impact news or economic releases.
Methodology
Event Response Metrics: It examines historical account behaviour before, during, and after major market events, analysing factors such as trade frequency, average slippage, and the magnitude of gains or losses relative to normal market conditions.
Comparative Market Context: Lacma compares the account’s event-driven performance against all other active accounts within the platform. This helps distinguish accounts that are structurally vulnerable to volatility from those that are merely caught in a temporary market-wide shakeout.
Proprietary AI Adjustment: The weighting and vectorisation of these data points are governed by a proprietary algorithm, continuously refined to sharpen its predictive accuracy regarding an account’s resilience or fragility during future market events.
What It Tells You
A high Event Trading Score suggests an account that navigates volatility effectively—perhaps by reducing position size, hedging, or simply maintaining discipline when markets become chaotic. A low score may indicate vulnerability to news events, poor execution during slippage, or strategies that perform well only in calm conditions.
The Lacma Mean Reversion Score: Mastering Range-Bound Markets
Definition
The Lacma Mean Reversion Score is a dynamic classification metric, expressed on a scale of 1 to 100, that vectorises an account’s ability to operate profitably in ranging or sideways market conditions. It indicates the statistical likelihood that an account can generate returns when prices oscillate within a defined channel rather than trending directionally.
Methodology
Range-Bound Performance Metrics: The score evaluates how an account behaves when markets lack clear directional momentum, analysing factors such as profit generation during consolidation periods, frequency of mean-reversion style entries, and the account’s performance differential between trending and ranging market phases.
Comparative Market Context: Lacma compares the account’s range-bound trading characteristics against all other active accounts within the platform. This identifies whether an account genuinely possesses mean-reversion skill or simply benefits from broader conditions that temporarily favour counter-trend strategies.
Proprietary AI Adjustment: The weighting and vectorisation of these data points are governed by a proprietary algorithm, continuously refined through back-testing to enhance its ability to predict an account’s future performance in ranging market environments.
What It Tells You
A high Mean Reversion Score indicates an account that thrives when markets are range-bound—demonstrating the ability to buy dips and sell rallies within a channel, generating consistent returns even without directional movement. These accounts often provide valuable diversification for portfolios heavily weighted toward trend-following strategies. A low Mean Reversion Score may suggest that an account struggles in sideways markets, requiring strong directional trends to perform effectively.
How the Scores Work Together
Individually, each Lacma score provides a focused lens on a specific aspect of account behaviour. Together, they form a forensic profile.
Consider an account with:
- A low Risk Score (suggesting stability)
- A high Trend Score (suggesting strong directional consistency)
- A moderate Event Trading Score (suggesting reasonable resilience during volatility)
- A moderate Mean Reversion Score (suggesting some ability to operate in ranging markets)
This profile paints a picture of a stable, trend-following account that handles volatility reasonably well and can adapt when trends pause—potentially suitable for signals seeking steady directional exposure with built-in flexibility.
Conversely, an account with:
- A high Risk Score
- A low Trend Score
- A high Event Trading Score
- A low Mean Reversion Score
…might suggest a volatile, event-driven strategy that performs poorly in calm or range-bound conditions—potentially suitable only for signals with high risk tolerance who are betting on continued market disruption.
Customisation for Partners: The Lacma Consensus Engine
A crucial aspect of the Lacma framework is its adaptability. The proprietary algorithms, weightings, and vectorised datasets that drive trigger and signal generation are trained on each partner’s own trading datasets. The vectorised database is used for reference only and does not contribute to the consensus model itself.
This means the derived Lacma scores are designed to be customised for each new installation. These customised scores function essentially as new prompts—informed by the Lacma framework but with flexibility and optionality determined by the partner.
For investors and platform operators, this offers the best of both worlds: access to a sophisticated, AI-refined analytical framework that remains adaptable to specific datasets, strategies, and risk tolerances.
The Future of Performance Analytics
The Lacma scores represent a shift away from static, one-size-fits-all metrics toward dynamic, context-aware analytics. By combining established financial science with comparative intelligence and continuous AI refinement, we believe this framework offers a more nuanced and predictive view of trading account behaviour.
Whether you’re prop partner evaluating traders, a trader seeking to understand your own patterns, or a platform operator looking to offer sophisticated analytics to your users, the Lacma scores provide a LLM friendly language for discussing and quantifying risk and performance.
We continue to refine our algorithms, back-test our predictions, and expand our vectorised datasets. The scores you see today are already more sophisticated than those of six months ago—and the scores of six months from now will be more refined still.
To learn more about implementing Lacma scores for your platform or investment process, contact our team via contact form below.
About Lacma
Lacma provides proprietary analytics and consensus-driven intelligence for forex trading accounts and platforms. Our AI-refined metrics help traders, investors, and platform operators understand risk, performance, and behaviour with greater clarity and context.