Quantifying Bias in Trading: A Smarter Approach

Developing a clear market bias at the start of each futures trading session can help bring structure to your strategy. But when that bias is based purely on instinct or news headlines, it can lead to inconsistent results. A more reliable approach is to quantify your bias using objective data—turning market tendencies into measurable probabilities that support more informed trading decisions. 

Let’s explore how tools like gap-fill studies and breakout data can help you quantify bias and build a smarter, data-driven trading plan. 

Why it pays to quantify your trading bias 

You probably start the day with a perspective, often shaped by what you’ve read, seen, or heard. But personal opinions can be unreliable in fast-moving markets. Traders who seek consistency often turn to quantifiable signals. 

By using historical price data, market tendencies, and statistical probabilities, you can frame each session with objective insights. This approach can help support better trade selection, identify realistic targets, and minimize emotional decision-making. 

Gap-fill analysis: A simple framework for market direction 

A gap-fill analysis is a common method to quantifying bias in trading. This concept looks at how often prices “fill the gap” between a new session’s open and the previous session’s close. 

In equity markets, gaps are more apparent. In futures markets, due to extended trading hours, gaps are typically measured from the 4:00 pm ET close of the New York session to the following day’s open. Here’s how the analysis works: 

• If price opens above the previous close, traders may adopt a bearish bias targeting a move back to that close. 
• If price opens below the previous close, a bullish bias may be more appropriate. 

Historical data reveals how often these gaps tend to fill. Over a six-month period, for instance, gap-downs may have filled back to the previous session’s close about 66% of the time, while gap-ups have filled approximately 59% of the time. These insights provide a repeatable method for you to establish a directional bias and identify a realistic price target. 

Adjusting for partial moves and different conditions 

Full gap fills don’t always occur, so tracking how often price retraces partway—such as 50% or 75% of the gap—can help you adjust your expectations. This approach is especially useful in lower volatility conditions or when taking a more conservative stance on risk. For example, historical data may show a 78% probability of reaching the halfway point on a gap-down and a 73% probability on a gap-up. With this information, you can fine-tune your entry and exit strategies without relying on full gap completions. 

Using opening range breakout data to reinforce direction 

Another valuable technique for quantifying bias in trading involves analyzing opening range breakouts. The opening range is typically defined as the high and low during the first 15 minutes of the trading session. You can measure: 

• How often price breaks above or below this range 
• How often both sides are broken in the same session 

Over time, trends may shift. For instance, in some months, breakouts might lean heavily in one direction. If recent data shows that breakouts have only occurred to the upside, traders may adjust their intraday bias accordingly. 

This analysis doesn't provide trade signals on its own, but it can support or challenge other indicators, creating confluence for more confident decisions. 

Power hour probabilities and trade management 

The last hour of the trading session—often called the “power hour”—is another area where data can inform trading behavior. Despite its name, this window isn’t always marked by high volatility or dramatic moves. 

Historical analysis may show that a new low of day occurs during the final hour just 19% of the time, while a new high is made only 28% of the time. This insight can be valuable for managing your trades. 

For example, if you're holding a long position late in the session, it may make sense to take profits before expecting a breakout to new highs. The same reasoning applies if you’re short and approaching the day’s low. Instead of assuming heightened volatility in the final hour, you can base your decisions on how the market has actually behaved in recent sessions. 

Adapting to current market conditions 

Market dynamics change. Whether due to economic events, earnings cycles, or seasonality, patterns evolve over time. That’s why it’s important to analyze data in different time frames—weekly, monthly, or even across several years. 

A strategy that worked during one stretch of volatility may not be as effective in calmer conditions. Reviewing recent probabilities allows you to update your expectations in real time and avoid relying on outdated assumptions. Design note: Build the below into a 50/50 CTA module as on other blogs.