Balancing trading volume reveals market participant strategies

Although looking at volume can help investors determine where the price trend is likely to go, balancing volume will generate clearer signals to help investors take trading actions. Volume shows crowd sentiment, because price bars form patterns that predict bullish or bearish outcomes.

Volumes that support price action will converge and increase the reliability of directional signals. Opposing actions will create divergence, warn that market forces are in conflict, and will ultimately be controlled by one party. The transaction volume explained by the cumulative distribution indicator clarifies this process and provides a reliable signal that affects position selection and transaction management.

The Balanced Volume (OBV) was developed by Joseph Granville in the 1960s to pack a large number of uses into a simple cumulative distribution tool that can calculate the upper and lower transaction volume and add or subtract the result to the continuous subtotal.This formula generates a smooth indicator line that can draw highs, lows and trend lines similar to price bars. Comparing the relative behavior between price bars and OBV will generate more actionable signals than the usual green or red volume histograms at the bottom of price charts.

Key points

  • Balanced trading volume (OBV) is a simple cumulative distribution tool that can record the rise and fall of trading volume and create a smooth indicator line to predict when major market fluctuations may occur based on changes in relative trading volume.
  • OBV works best when testing around major highs and lows to gauge possible breakouts and collapses.
  • Investors can use OBV to provide many key predictions, such as a bullish divergence that predicts that the price will break through resistance or a bearish divergence that predicts that a rebound will stagnate or reverse.

OBV feedback system

OBV provides the most reliable feedback around major highs and lows testing, making it the perfect tool for measuring the potential for breakthroughs and collapses. This is a simple process that compares the progress of the indicator with price action and pays attention to the relationship of convergence or divergence. This gives way to many key predictions:

  • OBV hits a new high, while the price tests resistance: a bullish divergence, predicts that the price will break through the resistance and soar to higher, catching up.
  • The price hits a new high, and OBV is hovering at or below the previous resistance level: a bearish divergence, predicting that the upward trend will stagnate or reverse.
  • OBV hit a new low, price test support: bearish divergence, predict that the price will break through the support and fall sharply to catch up.
  • The price hits a new low, and OBV is hovering at or above the previous support level: a bullish divergence, predicting that the selling will stagnate or reverse.
  • OBV matches the price trend, higher or lower: bullish or bearish convergence, depending on the direction.

Limit OBV analysis to the main test area on the daily chart. In the process of horizontal markets, the conflicting relationship between price and transaction volume naturally develops, thereby reducing the reliability of indicators between disputed levels. It also does not scale well, and intraday and weekly OBV cannot generate a consistent and reliable signal.

In order to get the most benefit from OBV, limit your analysis to tests that have been in existence for several months. This will increase your chances of getting more relevant results, thereby improving your bottom line.

OBV example

Let’s look at two common OBV scenarios:

CME Group (CME) rose to 80 in June (1), setting a high OBV volatility. It fell back and exceeded that high in November, but OBV failed to reach the previous high (2), indicating a bearish divergence. The rally failed, giving way to a sell-off that reached an 11-month low in April. Then the stock entered the accumulation phase, and the OBV and price went up consistently within seven months. OBV rose to a multi-year high in September (3), while the price was still lower than the previous year’s high, triggering a bullish divergence and predicting a strong breakthrough in December.

Celgene Corporation reached its peak in early 2014, just below 90 (1) and entered a correction showing a wide distribution. It started to recover in April and made progress in a steady rise, pushing prices to the previous high in June, and OBV failed to reach that level.

The stock traded sideways in a symmetrical triangle for two months and broke (2) to rise to 100, but the OBV continued to lag, well below the high set earlier this year. This divergence forced the upward trend to stall and weakened the breakthrough level, shaking up promising buyers, while OBV recovered slowly and steadily, finally adding a new price high in November (3).

When the OBV lags behind the price action, the stock is easy to break through or collapse, but the divergence behavior will send a red flag to predict the wash until the price turns to meet the OBV or the OBV turns to meet the price. This test activity tracks the second phase of the operation or reaction resolution cycle. This is why traders should look for OBV to match the lead price before taking the risk of a new breakout or breakout position.

Bottom line

The balance volume shows the intentions of market participants, usually before the price action generates a buy or sell signal. Therefore, investors can use OBV to provide insights that can help them make trading decisions. Specifically, it is most useful as an entry filter whenever a security tests a major support or resistance level.

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