Untangle
the market.

Begin with the Market Explanation

Every session starts here. The Market Explanation card sits at the top of Market Intel and synthesises everything the model sees into plain English. It tells you what the current bias is, which indicators are driving it, what is confirming it, and what is conflicting. Read it before looking at any numbers. It is your executive summary for the current market condition.

The Conviction percentage tells you how strongly the three models agree. 90% conviction means all three models are aligned. 55% means they are split and the picture is unclear. The lower the conviction, the more cautious your interpretation should be.

Pay close attention to the sparkline beneath the signal gauge. This small line chart shows how the model's conviction has been trending across recent refreshes — whether the reading is strengthening, weakening, or holding steady. A conviction reading that is rising toward the current bias is a very different picture from one that has just reversed sharply from the other direction. If the sparkline shows the model shifting against its current reading, head to the Advanced tab for the full probabilistic picture before forming any view.

Cross-reference Key Drivers with Indicator Health

The Key Drivers card shows which indicators the model weighted most heavily in its current analysis. These are not just any indicators — they are the ones that historically showed the strongest relationship with future price direction for this specific asset. The Indicator Health card shows the current reading of every indicator on the platform.

The rows highlighted in gold inside Indicator Health are the exact key drivers. This is where the real analysis happens. If the model reads Bullish and the top key driver also reads Bullish in Indicator Health, that is meaningful confirmation. If the key driver reads Bearish while the overall bias is Bullish, that is a contradiction worth noting before forming any view.

Read the Context card and Model Votes

The Context card shows two things: the current Market Regime (Bull, Bear or Sideways as detected by the multi-factor regime model) and the News Sentiment (live deep learning sentiment analysis of recent headlines). Both show an alignment tag. "Aligned" means the regime or news supports the current bias. "Contradicts" means the broader environment is pushing in the opposite direction.

The Model Votes card shows how each of the three individual models voted. When all three agree, the ensemble is strong. When one model disagrees, look at which one and at what confidence. A single model at 92% voting against the other two is more significant than a model at 51% dissenting.

Understand the statistical environment

The Probability tab gives you the full statistical picture of the asset. Start with the Market Regime section to confirm the regime reading and see the factor breakdown — trend, momentum, volatility and skewness all scored individually. The composite score tells you how strong the regime reading is.

The Descriptive Statistics section tells you how this asset typically behaves. Annualised volatility shows how much the price moves on average. Skewness tells you whether gains or losses tend to be more extreme. Kurtosis tells you how often extreme moves happen. A kurtosis above 9 means extreme events occur far more frequently than a normal distribution would predict.

The Bayesian Update section is particularly useful after major news events. It shows how the model updated its regime belief after incorporating live news sentiment. A large shift in the posterior (shown by the pp change numbers) means the news had a meaningful impact on the probabilistic view of the market.

Verify with Monte Carlo and scenario probabilities

The Advanced tab is where the probabilistic future comes into view. The Monte Carlo fan chart shows 1,000 simulated price paths over the next 30 bars. The blue band in the middle is the most likely zone. The wider the fan, the more uncertain the model is about future direction. A narrow fan with a clear upward slope is a very different reading from a wide fan with paths going in both directions.

The Scenario Analysis card breaks those 1,000 paths into three groups. The Bull Case shows the average outcome of the top 20% of paths. The Bear Case shows the worst 20%. The probabilities show how many paths ended above or below the current price. Compare these probabilities with the Market Intel bias. If Market Intel reads Bullish but 60% of Monte Carlo paths end below current price, the statistical evidence is mixed and worth noting.

The Price Distribution histogram shows exactly where the simulated prices clustered at the end of 30 bars. A heavily right-skewed distribution (bars piling up on the right) suggests statistically more upside paths. A left-skewed distribution suggests downside paths dominated the simulation.

The Fear and Greed gauge combines regime, momentum, trend, news sentiment and volatility into a single score. Extreme Greed readings historically appear near market tops. Extreme Fear readings often appear near bottoms. Neither guarantees a reversal but both are meaningful context for interpreting other data.

Use Kelly Criterion for position sizing context

The Kelly Criterion section in the Probability tab computes the mathematically optimal position size as a percentage of capital based on the asset's historical win rate and average win-to-loss ratio. This is not a recommendation on what to do. It is a data reference point that quantifies how the historical statistics of this asset translate into a sizing framework.

The Half-Kelly figure is what most quantitative practitioners use as a reference. Full Kelly is mathematically optimal for long-run growth but produces large drawdowns in practice. The Mathematical Edge figure tells you whether this asset has historically had a positive expected value per bar. A negative edge means the asset has historically lost more than it gained per bar on average.

Understand cross-asset relationships

If you hold positions across multiple assets, the Hedging tab shows you how the available assets are correlated in the current market. When two assets are highly correlated, holding both does not meaningfully reduce your risk. The hedging engine computes the minimum variance hedge ratio — how much of one asset you would need to hold relative to another to theoretically reduce portfolio volatility.

This is particularly useful during periods of macro stress when asset correlations tend to spike. Assets that sometimes behave as uncorrelated can temporarily move together during risk-off events. The live correlation reading tells you whether the normal relationship is holding or whether it has broken down.

Enrich your view with the community

The Community tab is a real-time feed of other Enodara users sharing their analysis, observations and questions. Filter by asset to see what others are noticing about the same market. Look for Analysis posts that reference specific data points from the platform. A well-reasoned Analysis post from another data-driven user can surface context you may have missed or frame the data from a different angle.

The community is not a signals service and should not be treated as one. It is a place to compare observations, ask questions and share what the data is showing from different perspectives. Enodara gives everyone the same underlying data. What differs is interpretation, experience and the specific question each user is trying to answer.