Chande Forecast Oscillator (CFO)

Parameters:

Source: allows the selection of the data source for the oscillator calculation. The options available in the dropdown menu are:
- Open Price: Uses the opening price of each period for calculation.
- High Price: Uses the highest price of each period.
- Low Price: Uses the lowest price of each period.
- Close Price: Uses the closing price of each period (currently selected).
- Volume: Uses the trading volume of each period.
- Weighted: Typically a weighted price calculated as (High + Low + Close + Close) / 4.
- Typical: Calculated as (High + Low + Close) / 3.
- Median: Calculated as (High + Low) / 2.
Periods: The number of periods used to calculate the oscillator, affecting its sensitivity to price changes and the smoothness of the indicator.
Forecasting Method: Specifies the statistical method used for forecasting (e.g., linear regression), impacting how future prices are projected and the oscillator's responsiveness.

Style

Customizable options for visual representation (line color, style, etc.)

The Chande Forecast Oscillator (CFO) is the technical analysis tool developed by Tushar Chande to gauge the deviation of a security's price from its predicted price as calculated by a linear regression model over a specific time period. Essentially, the CFO is an oscillator that fluctuates around the zero line, indicating the direction and magnitude of the deviation.

How CFO Works: The Chande Forecast Oscillator is calculated by subtracting the asset's actual price from the forecasted price, which is determined through linear regression, and then dividing this difference by the forecasted price. Then, the result is multiplied by 100 to convert it into a percentage. The formula can be expressed as follows:

CFO = (Forecast Price - Actual Price) / Forecast Price * 100

Linear Regression Analysis: This statistical method predicts future prices based on past price data. It fits a straight line to the selected data points to determine the best fit that represents the trend of the data.
Forecast Price: This is the price predicted by the linear regression model for the current period.
Actual Price: This is the current closing price of the asset.

Key Aspects of CFO:

Zero Line Crossover: The CFO's movement around the zero line is crucial. A move above zero indicates that the actual price is higher than the forecast price, suggesting bullish momentum. Conversely, a move below zero indicates bearish momentum, where the actual price is lower than the forecast price.

Strength of Trend: The further away the CFO is from zero, the stronger the current trend's momentum. This can signal continuation if aligned with the broader trend or warn of potential reversals if contrary to the prevailing trend.

Divergence: As with many oscillators, the divergence between the CFO and the price action is a key signal. If the CFO is making higher highs while the price makes lower highs, or vice versa, a potential reversal in the trend can be indicated.

Application of CFO: The CFO is versatile and can be used in various market conditions and trading strategies. It is especially useful in identifying entry and exit points based on momentum shifts indicated by the oscillator crossing the zero line.

Trend Confirmation: Traders can use the CFO to confirm the strength of a trend. For example, in a bullish trend, the CFO remaining above zero would confirm intense buying pressure.
Reversal Signals: Significant divergences between the CFO and price action can signal potential price reversals.
Overbought/Oversold Conditions: While primarily not designed to indicate overbought or oversold levels, extreme readings may suggest such conditions.

Limitations:

Lagging Indicator: As with most indicators based on past price data, the CFO can lag real-time events. The reliance on linear regression also assumes that past patterns and trends will continue, which may not always be the case.

Sensitivity to Outliers: Based on linear regression, the CFO can be overly sensitive to outliers or sharp price movements, distorting the regression line and, thus, the oscillator readings.

Conclusion: The Chande Forecast Oscillator offers traders an insightful tool for measuring the deviation of current prices from statistically expected prices based on trend analysis. By clearly measuring how far prices have deviated from expected values, the CFO helps traders make informed decisions regarding potential trend continuations or reversals. However, as with all indicators, it is most effective when used in conjunction with other technical tools and within the context of a comprehensive trading strategy.