The Signals Panel gives you access to detailed trade data for every signal Volensy generates. But raw numbers only become useful when you know how to read them. This guide teaches you how to interpret signal results — understanding entry and exit prices, calculating profit and loss, reading the win/loss/break-even classification, distinguishing open from closed positions, and using signal history to assess strategy performance and improve your own trading knowledge.

Entry Price vs. Exit Price

Every signal has an entry price: the exact price at which the position was opened. For Long signals, this is the price at which the buy was executed. For Short signals, this is the price at which the sell was initiated.

When the position closes, an exit price is recorded: the price at which the trade ended. The relationship between entry and exit price determines whether the trade was profitable.

For Long Positions

• Win: Exit price is higher than entry price. The asset was bought low and sold high.
• Loss: Exit price is lower than entry price. The asset was bought but the price dropped before exit.

For Short Positions

• Win: Exit price is lower than entry price. The asset was sold at a higher price and the position was closed after the price fell.
• Loss: Exit price is higher than entry price. The price moved up against the short position.

Example

Suppose you see a Long signal with an entry price of 42,500 and an exit price of 43,200. The price moved up by 700 points from where the position was opened, which means this trade was profitable.

Now consider a Short signal with an entry price of 42,500 and an exit price of 42,800. The price moved up by 300 points. Since this was a Short (expecting the price to fall), the upward move resulted in a loss.

Understanding PnL

PnL stands for Profit and Loss. In the Volensy signal database, PnL is expressed as a percentage representing the return on the trade relative to the entry price.

The basic calculation is:

• Long PnL: ((Exit Price – Entry Price) / Entry Price) x 100
• Short PnL: ((Entry Price – Exit Price) / Entry Price) x 100

A positive PnL means the trade was profitable. A negative PnL means the trade resulted in a loss. A PnL of zero (or very close to zero) indicates a break-even outcome.

Reading PnL in the Panel

The PnL value is not displayed as a standalone column in the current panel view. Instead, it is reflected through the Result column badge, which classifies the trade based on its PnL:

• Win (green badge): Positive PnL. The trade made money.
• Loss (red badge): Negative PnL. The trade lost money.
• Break-even (yellow badge): Zero or negligible PnL. The trade closed at approximately the same price it entered.

Win, Loss, and Break-even

These three outcome categories tell you the bottom line for every closed signal.

Win

A winning trade closed with a profit. The strategy correctly predicted the price direction. When you see a green Win badge, it means:

• For Long signals: the price rose after entry.
• For Short signals: the price fell after entry.

Winning trades are the foundation of strategy profitability. When reviewing signals, pay attention to what winning trades have in common — which markets they occur in, what timeframes produce the most wins, and how large the average winning PnL tends to be.

Loss

A losing trade closed at a worse price than the entry. The market moved against the strategy’s prediction. When you see a red Loss badge, it means:

• For Long signals: the price fell after entry.
• For Short signals: the price rose after entry.

Losses are a normal and expected part of any trading strategy. No algorithm wins 100% of the time. What matters is the relationship between wins and losses — how often the strategy wins versus how often it loses, and whether the average win is larger than the average loss.

Break-even

A break-even trade closed at approximately the same price it entered. Neither a meaningful profit nor a meaningful loss was recorded. Yellow Break-even badges typically occur when:

• The price moved slightly in the right direction but not enough to register a significant profit before the exit condition triggered.
• The strategy exited early due to changing conditions, with the price near the entry level.

Break-even trades are neutral. They neither help nor hurt overall performance, but they do consume the time and opportunity cost of holding a position.

Open vs. Closed Positions

Open Positions

An Open signal (yellow badge) represents a trade that is still active. The system has entered the position but has not yet detected an exit condition. For open positions:

• The Exit Price column is blank.
• The Exit Date column is blank.
• The Exit Reason column is blank.
• The Result column is blank.

Open positions are live trades. Their outcome is undetermined. You should not include open positions when calculating performance statistics like win rate or average PnL, because those numbers would be incomplete and misleading.

Closed Positions

A Closed signal (gray badge) represents a completed trade with full data. All 11 columns are populated, giving you a complete picture of what happened from entry to exit. Closed positions are the data points you use for performance analysis.

Exit Reasons

The Exit Reason column tells you why a position was closed. Understanding exit reasons helps you evaluate not just whether a trade won or lost, but how and why it ended.

Common exit reasons include:

• Take Profit — The price reached a predefined profit target set by the strategy. This is typically a positive outcome and results in a Win classification.
• Stop Loss — The price moved against the position and hit the protective stop level set by the strategy. This is a risk management exit and typically results in a Loss classification.
• Strategy Exit — The algorithm’s internal conditions triggered a close. This might happen when the strategy detects that its setup has invalidated, momentum has shifted, or a new conflicting signal appears. Strategy exits can result in Wins, Losses, or Break-evens depending on the price at the moment of exit.

Studying exit reasons across many signals reveals important strategy characteristics. A strategy that closes most trades via Take Profit has a disciplined profit-taking mechanism. A strategy with frequent Stop Loss exits might be operating in choppy market conditions or using tight stop levels.

Assessing Strategy Performance

Individual signals tell you about specific trades. But the real power of the Signals Panel comes from analyzing signals collectively to assess strategy performance. Here is how to approach performance analysis using the signal data.

Win Rate

The most basic performance metric is win rate: the percentage of closed trades that resulted in Wins. To estimate win rate from the panel, filter for Closed positions and note the proportion of green Win badges versus red Loss badges. A higher win rate generally indicates a more accurate strategy, but win rate alone does not tell the whole story.

Win/Loss Size Ratio

A strategy can have a low win rate and still be profitable if its average winning trade is significantly larger than its average losing trade. Compare the price difference (exit minus entry) on winning trades versus losing trades to understand this ratio.

Consistency Across Markets

Filter by different markets to see if the strategy performs well across multiple coins or if its results are concentrated in one or two assets. Broad consistency is a sign of a robust strategy.

Directional Strength

Filter by Long and Short separately to see if the strategy performs better in one direction. Some strategies naturally favor trending markets (Long in bull markets, Short in bear markets).

Time-Based Analysis

Use the Date Range filter to compare performance across different time periods. Does the strategy perform consistently, or does it have periods of strong results followed by drawdowns?

Using Signals for Learning

Volensy signals are not just trade alerts. They are a structured educational dataset. Here are ways to use signal results for learning:

1. Pattern recognition — Look for common characteristics among winning trades. Do wins cluster in specific markets or timeframes?
2. Risk awareness — Study losing trades to understand when and why the strategy fails. This builds realistic expectations about drawdown periods.
3. Market context — Cross-reference signal dates with market events. Did a losing streak coincide with a major news event or a sudden trend reversal?
4. Strategy evaluation — Before following any strategy with real money, review its complete signal history. The data is there for you to study, question, and learn from.

*See also: Trading Signals Overview*
*See also: Filtering & Sorting Signals*