Chaikin Money Flow
Chaikin Money Flow (CMF) is a volume-weighted average of the Accumulation/Distribution values over a specified lookback period, developed by Marc Chaikin, that produces a bounded oscillator reflecting the degree to which volume has historically been concentrated on days when the close was near the high versus near the low of the day's range.
Marc Chaikin developed the Chaikin Money Flow indicator as a time-windowed, bounded version of the Accumulation/Distribution Line he had previously created. While the A/D Line is a cumulative running total with an unbounded range, the CMF is calculated by summing the money flow volume (volume multiplied by the Close Location Value) over a defined lookback period — typically 20 or 21 days — and dividing by total volume over the same period. The result is an oscillator that fluctuates between -1 and +1, though in practice most readings fall between -0.5 and +0.5.
The CMF's construction means that its value reflects the proportion of volume that has historically occurred on days when prices closed in the upper versus lower portion of the daily range, over the chosen lookback window. Technical analysts have historically observed that in periods where a stock's CMF was consistently positive, the historical record showed more volume on days when prices closed near the high of the day's range. As with all technical analysis indicators, these observations reflect patterns in historical price and volume data and are not assertions about future price movement.
Chaikin Money Flow is used in the technical analysis community as a companion to price-based trend indicators. Its combination of both price position (where the close fell in the day's range) and volume data distinguishes it from pure price-based oscillators like the stochastic or Williams %R. The CMF is available on charting platforms used in U.S. equity analysis including Bloomberg Terminal, FactSet, and retail brokerage tools.
Academic research on volume-price indicators in U.S. equity markets has produced mixed conclusions about the consistency and statistical significance of signals derived from CMF and similar tools. Studies have found that apparent relationships between volume-price indicators and subsequent price behavior may be sensitive to the time period examined, the universe of stocks analyzed, and the transaction cost assumptions used.
The lookback period selection for CMF has a meaningful effect on its sensitivity. A shorter lookback — such as 10 days — produces a more reactive oscillator that responds quickly to recent changes in volume-price patterns but generates more variability. A longer period — such as 21 days — smooths out short-term fluctuations but responds more slowly to changes in volume distribution. Technical analysts using CMF in U.S. equity analysis typically choose the period based on their investment time horizon and the typical holding period of the securities they analyze, recognizing that no single parameter is universally optimal across different stocks and market environments.