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Trend Indicators

Trend indicators measure the direction and strength of a trend.

Absolute Price Oscillator (APO)

The AbsolutePriceOscillator function calculates a technical indicator that is used to follow trends. APO crossing above zero indicates bullish, while crossing below zero indicates bearish. Positive value is upward trend, while negative value is downward trend.

Fast = Ema(fastPeriod, values)
Slow = Ema(slowPeriod, values)
APO = Fast - Slow

apo := indicator.AbsolutePriceOscillator(fastPeriod, slowPeriod, values)

Most frequently used fast and short periods are 14 and 30. The DefaultAbsoluePriceOscillator function calculates APO with those periods.

Aroon Indicator

The Aroon function calculates a technical indicator that is used to identify trend changes in the price of a stock, as well as the strength of that trend. It consists of two lines, Aroon Up, and Aroon Down. The Aroon Up line measures measures the strength of the uptrend, and the Aroon Down measures the strength of the downtrend. When Aroon Up is above Aroon Down, it indicates bullish price, and when Aroon Down is above Aroon Up, it indicates bearish price.

Aroon Up = ((25 - Period Since Last 25 Period High) / 25) * 100
Aroon Down = ((25 - Period Since Last 25 Period Low) / 25) * 100

aroonUp, aroonDown := indicator.Aroon(high, low)

Balance of Power (BOP)

The BalanceOfPower function calculates the strength of buying and selling pressure. Positive value indicates an upward trend, and negative value indicates a downward trend. Zero indicates a balance between the two.

BOP = (Closing - Opening) / (High - Low)

bop := indicator.BalanceOfPower(opening, high, low, closing)

Chande Forecast Oscillator (CFO)

The ChandeForecastOscillator developed by Tushar Chande The Forecast Oscillator plots the percentage difference between the closing price and the n-period linear regression forecasted price. The oscillator is above zero when the forecast price is greater than the closing price and less than zero if it is below.

R = Linreg(Closing)
CFO = ((Closing - R) / Closing) * 100

Based on Chande Forecast Oscillator Formula, Strategy, Forecast Oscillator , and Least Squares Regression.

cfo := indicator.ChandeForecastOscillator(closing)

Community Channel Index (CMI)

The CommunityChannelIndex is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold.

Moving Average = Sma(Period, Typical Price)
Mean Deviation = Sma(Period, Abs(Typical Price - Moving Average))
CMI = (Typical Price - Moving Average) / (0.015 * Mean Deviation)

result := indicator.CommunityChannelIndex(period, high, low, closing)

The DefaultCommunityChannelIndex calculates with the period of 20.

result := indicator.DefaultCommunityChannelIndex(high, low, closing)

Double Exponential Moving Average (DEMA)

The Dema function calculates the Double Exponential Moving Average (DEMA) for a given period.

The double exponential moving average (DEMA) is a technical indicator introduced by Patrick Mulloy. The purpose is to reduce the amount of noise present in price charts used by technical traders. The DEMA uses two exponential moving averages (EMAs) to eliminate lag. It helps confirm uptrends when the price is above the average, and helps confirm downtrends when the price is below the average. When the price crosses the average that may signal a trend change.

DEMA = (2 * EMA(values)) - EMA(EMA(values))

dema := indicator.Dema(period, values)

Based on Double Exponential Moving Average (DEMA).

Exponential Moving Average (EMA)

The Ema function calculates the exponential moving average for a given period.

result := indicator.Ema(2, []float64{2, 4, 6, 8, 12, 14, 16, 18, 20})

Mass Index (MI)

The MassIndex uses the high-low range to identify trend reversals based on range expansions.

Singe EMA = EMA(9, Highs - Lows)
Double EMA = EMA(9, Single EMA)
Ratio = Single EMA / Double EMA
MI = Sum(25, Ratio)

result := indicator.MassIndex(high, low)

Moving Average Convergence Divergence (MACD)

The Macd function calculates a trend-following momentum indicator that shows the relationship between two moving averages of price.

MACD = 12-Period EMA - 26-Period EMA.
Signal = 9-Period EMA of MACD.

macd, signal := indicator.Macd(closing)

Moving Max

The Max function gives the maximum value within the given moving period. It can be used to get the moving maximum closing price and other values.

max := indicator.Max(period, values)

Moving Min

The Min function gives the minimum value within the given moving period. It can be used to get the moving minimum closing price and other values.

max := indicator.Min(period, values)

Moving Sum

The Sum function gives the sum value within the given moving period.

sum := indicator.Sum(period, values)

Parabolic SAR

The ParabolicSar function calculates an identifier for the trend and the trailing stop.

PSAR = PSAR[i - 1] - ((PSAR[i - 1] - EP) * AF)

If the trend is Falling:

  • PSAR is the maximum of PSAR or the previous two high values.
  • If the current high is greather than or equals to PSAR, use EP.

If the trend is Rising:

  • PSAR is the minimum of PSAR or the previous two low values.
  • If the current low is less than or equials to PSAR, use EP.

If PSAR is greather than the closing, trend is falling, and the EP is set to the minimum of EP or the low.

If PSAR is lower than or equals to the closing, trend is rising, and the EP is set to the maximum of EP or the high.

If the trend is the same, and AF is less than 0.20, increment it by 0.02. If the trend is not the same, set AF to 0.02.

Based on video How to Calculate the PSAR Using Excel - Revised Version.

psar, trend := indicator.ParabolicSar(high, low, closing)

Qstick

The Qstick function calculates the ratio of recent up and down bars.

QS = Sma(Closing - Opening)

qs := indicator.Qstick(period, closing, opening)

Random Index (KDJ)

The Kdj function calculates the KDJ indicator, also known as the Random Index. KDJ is calculated similar to the Stochastic Oscillator with the difference of having the J line. It is used to analyze the trend and entry points.

The K and D lines show if the asset is overbought when they crosses above 80%, and oversold when they crosses below 20%. The J line represents the divergence.

RSV = ((Closing - Min(Low, rPeriod)) / (Max(High, rPeriod) - Min(Low, rPeriod))) * 100
K = Sma(RSV, kPeriod)
D = Sma(K, dPeriod)
J = (3 * K) - (2 * D)

k, d, j := indicator.Kdj(rPeriod, kPeriod, dPeriod, high, low, closing)

By default, rPeriod of 9, kPeriod of 3, and dPeriod of 3 are used. The DefaultKdj function can be used with those periods.

k, d, j := indicator.DefaultKdj(high, low, closing)

Rolling Moving Average (RMA)

The Rma function calculates the rolling moving average for a given period.

R[0] to R[p-1] is SMA(values)
R[p] and after is R[i] = ((R[i-1]*(p-1)) + v[i]) / p

result := indicator.Rma(2, []float64{2, 4, 6, 8, 10, 12})

Simple Moving Average (SMA)

The Sma function calculates the simple moving average for a given period.

result := indicator.Sma(2, []float64{2, 4, 6, 8, 10})

Since Change

The Since function provides the number values since the last change.

changes := indicator.Since(values)

Triple Exponential Moving Average (TEMA)

The Tema function calculates the Triple Exponential Moving Average (TEMA) for a given period.

The triple exponential moving average (TEMA) was designed to smooth value fluctuations, thereby making it easier to identify trends without the lag associated with traditional moving averages. It does this by taking multiple exponential moving averages (EMA) of the original EMA and subtracting out some of the lag.

TEMA = (3 * EMA1) - (3 * EMA2) + EMA3
EMA1 = EMA(values)
EMA2 = EMA(EMA1)
EMA3 = EMA(EMA2)

tema := indicator.Tema(period, values)

Based on Triple Exponential Moving Average (TEMA).

Triangular Moving Average (TRIMA)

The Trima function calculates the Triangular Moving Average (TRIMA) for a given period.

The Triangular Moving Average (TRIMA) is a weighted moving average putting more weight to the middle values.

If period is even:
   TRIMA = SMA(period / 2, SMA((period / 2) + 1, values))
If period is odd:
   TRIMA = SMA((period + 1) / 2, SMA((period + 1) / 2, values))

trima := indicator.Trima(period, values)

Based on Triangular Moving Average.

Triple Exponential Average (TRIX)

The Trix indicator is an oscillator used to identify oversold and overbought markets, and it can also be used as a momentum indicator. Like many oscillators, TRIX oscillates around a zero line.

EMA1 = EMA(period, values)
EMA2 = EMA(period, EMA1)
EMA3 = EMA(period, EMA2)
TRIX = (EMA3 - Previous EMA3) / Previous EMA3

trix := indicator.Trix(period, values)

Typical Price

The TypicalPrice function calculates another approximation of average price for each period and can be used as a filter for moving average systems.

Typical Price = (High + Low + Closing) / 3

ta, sma20 := indicator.TypicalPrice(high, low, closing)

Volume Weighted Moving Average (VWMA)

The Vwma function calculates the Volume Weighted Moving Average (VWMA) averaging the price data with an emphasis on volume, meaning areas with higher volume will have a greater weight.

VWMA = Sum(Price * Volume) / Sum(Volume) for a given Period.

vwma := indicator.Vwma(period, closing, volume)

Vortex Indicator

The Vortex function provides two oscillators that capture positive and negative trend movement. A bullish signal triggers when the positive trend indicator crosses above the negative trend indicator or a key level. A bearish signal triggers when the negative trend indicator crosses above the positive trend indicator or a key level.

+VM = Abs(Current High - Prior Low)
-VM = Abs(Current Low - Prior High)

+VM14 = 14-Period Sum of +VM
-VM14 = 14-Period Sum of -VM

TR = Max((High[i]-Low[i]), Abs(High[i]-Closing[i-1]), Abs(Low[i]-Closing[i-1]))
TR14 = 14-Period Sum of TR

+VI14 = +VM14 / TR14
-VI14 = -VM14 / TR14

Based on Vortex Indicator

plusVi, minusVi := indicator.Vortex(high, low, closing)

Disclaimer

The information provided on this project is strictly for informational purposes and is not to be construed as advice or solicitation to buy or sell any security.

License

Copyright (c) 2021 Onur Cinar. All Rights Reserved.

The source code is provided under MIT License.