Technical Analysis with a Quantitative Edge




Patterns and Indicators

Here is the current list of patterns and indicators used by QuantForecast:


  • Up/Down Trends: Based on whether moving averages are trending up or down, where slope of moving average is used as a measure for trend. WingCharts uses moving averages of different time frames for short-term, medium-term and long-term trends.
  • Positive/Negative Divergence: Divergence is defined as price moving higher/lower while a technical indicator is moving in the opposite direction, which usually signal that current trend is losing momentum and about to turn. We use RSI, MACD, Stochastics and OBV as the indicators to detect divergences.
  • Candlestick Patterns: Analyze high - close, close - low and close - open differentials for any signs of intraday selling/buying pressure
  • Volatility: Detect periods of quiet and choppy markets based on historical volatility measures.
  • Statistical Rarity: Extremely high or low values in oscillator indicators which may indicate overbought or oversold conditions. For example, if current value is more than 90% of the time higher relative to its history, it is considered a statistical rarity.

  • Indicators

    Definition Source: Investopedia

    • Relative Strength Index (RSI): The relative strength index (RSI) is a momentum indicator developed by noted technical analyst Welles Wilder, that compares the magnitude of recent gains and losses over a specified time period to measure speed and change of price movements of a security. It is primarily used to attempt to identify overbought or oversold conditions in the trading of an asset.

      The relative strength index is calculated using the following formula:

      RSI = 100 - 100 / (1 + RS)

      Where RS = Average gain of up periods during the specified time frame / Average loss of down periods during the specified time frame
    • Moving Average Convergence Divergence (MACD): Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of prices. The MACD is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA. A nine-day EMA of the MACD, called the "signal line", is then plotted on top of the MACD, functioning as a trigger for buy and sell signals.
    • Stochastic Oscillator: The stochastic oscillator is a momentum indicator comparing the closing price of a security to the range of its prices over a certain period of time. The sensitivity of the oscillator to market movements is reducible by adjusting that time period or by taking a moving average of the result.

      The stochastic oscillator is calculated using the following formula:
      %K = 100(C - L14)/(H14 - L14)


      C = the most recent closing price

      L14 = the low of the 14 previous trading sessions

      H14 = the highest price traded during the same 14-day period

      %K= the current market rate for the currency pair

      %D = 3-period moving average of %K

      The general theory serving as the foundation for this indicator is that in a market trending upward, prices will close near the high, and in a market trending downward, prices close near the low. Transaction signals are created when the %K crosses through a three-period moving average, which is called the %D.

      The Fast Stochastic Oscillator is essentially the above methodology, while Slow Stochastic Oscillator is a smoother variation with %K being the the 3DMA while the %D being the 3DMA of the 3DMA.
    • Bollinger Band®: A Bollinger Band, developed by famous technical trader John Bollinger, is plotted two standard deviations away from a simple moving average. Because standard deviation is a measure of volatility, when the markets become more volatile, the bands widen; during less volatile periods, the bands contract.Bollinger Bands® are a highly popular technical analysis technique. Many traders believe the closer the prices move to the upper band, the more overbought the market, and the closer the prices move to the lower band, the more oversold the market.
    • On-Balance Volume: On-balance volume (OBV) is a momentum indicator that uses volume flow to predict changes in stock price. The theory behind OBV is based on the distinction between smart money – namely, institutional investors – and less sophisticated retail investors. As mutual funds and pension funds begin to buy into an issue that retail investors are selling, volume may increase even as the price remains relatively level. Eventually, volume drives the price upward. At that point, larger investors begin to sell, and smaller investors begin buying.

      The OBV is a running total of volume (positive and negative). There are three rules implemented when calculating the OBV. They are:

      1. If today's closing price is higher than yesterday's closing price, then: Current OBV = Previous OBV + today's volume

      2. If today's closing price is lower than yesterday's closing price, then: Current OBV = Previous OBV - today's volume

      3. If today's closing price equals yesterday's closing price, then: Current OBV = Previous OBV




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