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Momentum


Awesome Oscillator

This indicator attempts to identify momentum with the intention to affirm trends or anticipate possible reversals.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
fast int

Fast period. Default: 5

None
slow int

Slow period. Default: 34

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Absolute Price Oscillator

This indicator attempts to quantify momentum.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
fast int

Fast period. Default: 12

None
slow int

Slow period. Default: 26

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Note
  • Simply the difference of two different EMAs.
  • APO and MACD lines are equivalent.




Bias

This indicator computes the Rate of Change between the source and a moving average.

Sources
  • Few internet resources on definitive definition.

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 26

None
mamode str

See help(ta.ma). Default: "sma"

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Balance of Power

This indicator attempts to quantify the market strength of buyers versus sellers.

Sources

Parameters:

Name Type Description Default
open_ Series

open Series

required
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
scalar float

Scalar. Default: 1

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column


NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated! 🙏

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!




BRAR

BR and AR

Sources
  • No internet resources on definitive definition.

Parameters:

Name Type Description Default
open_ Series

open Series

required
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 26

None
scalar float

Scalar. Default: 100

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns




Commodity Channel Index

This indicator attempts to identify "overbought" and "oversold" levels relative to a mean.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 14

None
c float

Scaling Constant. Default: 0.015

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Chande Forcast Oscillator

This indicator attempts to calculate the percentage difference between the actual price and the Time Series Forecast (the endpoint of a linear regression line).

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 9

None
scalar float

Scalar. Default: 100

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Center of Gravity

This indicator, by John Ehlers, attempts to identify turning points with minimal to zero lag and smoothing.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 10

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Chande Momentum Oscillator

This indicator attempts to capture momentum.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
scalar float

Scalar. Default: 100

None
talib bool

If installed, use TA Lib. Uses EMA if False. Default: True

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Note
  • Overbought around 50
  • Oversold around -50.




Coppock Curve

This indicator, by Edwin Coppock 1962, was originally called the "Trendex Model", attempts to identify major upturns and downturns.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

WMA period. Default: 10

None
fast int

Fast ROC period. Default: 11

None
slow int

Slow ROC period. Default: 14

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Note

Although designed for monthly use, a daily calculation over the same period length can be made, converting the periods to 294-day and 231-day rate of changes, and a 210-day WMA.


NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated! 🙏

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!




Connors Relative Strength Index

This indicator attempts to identify momentum and potential reversals at "overbought" or "oversold" conditions.

Sources
  • alvarezquanttrading
  • tradingview
  • An Introduction to ConnorsRSI. Connors Research Trading Strategy Series. Connors, L., Alvarez, C., & Radtke, M. (2012). ISBN 978-0-9853072-9-5.

Parameters:

Name Type Description Default
close Series

close Series

required
rsi_length int

The RSI period. Default: 3

None
streak_length int

Streak RSI period. Default: 2

None
rank_length int

Percent Rank length. Default: 100

None
scalar float

Scalar. Default: 100

None
talib bool

If installed, use TA Lib. Default: True

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Correlation Trend Indicator

This oscillator, by John Ehlers' in 2020, attempts to identify the magnitude and direction of a trend using linear regession.

Note

This is a wrapper for ta.linreg(close, r=True).

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 12

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Directional Movement

This indicator, by J. Welles Wilder in 1978, attempts to determine direction.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
mamode str

See help(ta.ma). Default: "rma"

None
talib bool

If installed, use TA Lib. Default: True

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns




Efficiency Ratio

This indicator, by Perry J. Kaufman, attempts to identify market noise or volatility.

Sources
  • "New Trading Systems and Methods", Perry J. Kaufman
  • tc2000

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Note

It is calculated by dividing the net change in price movement over n periods by the sum of the absolute net changes over the same n periods.




Elder Ray Index

This indicator, by Dr Alexander Elder, attempts to identify market strength.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 14

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns

Note
  • Possible entry signals when used in combination with a trend,
  • Bear Power attempts to quantify lower value appeal.
  • Bull Power attempts the to quantify higher value appeal.




Exhaustion Count

This indicator attempts to identify rising/falling exhaustion.

Sources

Parameters:

Name Type Description Default
close Series

Series of close's

required
length int

The period. Default: 4

None
cap int

Count cap. For no cap, set to 0. Default: 13

None
show_all bool

Counts 1 - 13. For 6 - 9, set to False. Default: True

None
asint bool

Returns as Int. Default: False

None
nozeros bool

Replace zeros with np.nan. Default: False

None
offset int

Post shift. Default: 0

None

Returns:

Type Description
DataFrame

2 columns

Note

Similar to TD Sequential




Fisher Transform

This indicator attempts to identify significant reversals through normalization.

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
length int

The period. Default: 9

None
signal int

Signal period. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns

Reversal Signal

When the two lines cross.




Inertia

This indicator, by Donald Dorsey, is the rvi smoothed by the Least Squares MA.

Sources

Parameters:

Name Type Description Default
high Series

high Series

None
low Series

low Series

None
close Series

close Series

required
length int

The period. Default: 20

None
rvi_length int

RVI period. Default: 14

None
refined bool

Use 'refined' calculation. Default: False

None
thirds bool

Use 'thirds' calculation. Default: False

None
mamode str

See help(ta.ma). Default: "ema"

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Note
  • Negative Inertia when less than 50.
  • Positive Inertia when greater than 50.


NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated! 🙏

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!




KDJ

This indicator, derived from the Slow Stochastic, includes an extra signal named the J line. The J line represents the divergence of the %D value from the %K.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 9

None
signal int

Signal period. Default: 3

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns

Note

The J can go beyond [0, 100] for %K and %D lines when charted.




'Know Sure Thing'

This indicator, by Martin Pring, attempts to capture trends using a smoothed indicator of four different smoothed ROCs.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
roc1 int

ROC 1 period. Default: 10

None
roc2 int

ROC 2 period. Default: 15

None
roc3 int

ROC 3 period. Default: 20

None
roc4 int

ROC 4 period. Default: 30

None
sma1 int

SMA 1 period. Default: 10

None
sma2 int

SMA 2 period. Default: 10

None
sma3 int

SMA 3 period. Default: 10

None
sma4 int

SMA 4 period. Default: 15

None
signal int

Signal period. Default: 9

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns




Moving Average Convergence Divergence

This indicator attempts to identify trends.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
fast int

Fast MA period. Default: 12

None
slow int

Slow MA period. Default: 26

None
signal int

Signal period. Default: 9

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
asmode value

Enable AS version of MACD. Default: False

fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns




Momentum

This indicator attempts to quantify speed by using the differences over a bar length.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 1

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Pretty Good Oscillator

This indicator, by Mark Johnson, attempts to identify breakouts for longer time periods based on the distance of the current bar to its N-day SMA, expressed in terms of an ATR over a similar length.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 14

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Entry
  • Long when greater than 3.
  • Short when less than -3.




Percentage Price Oscillator

Similar to MACD.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
fast int

Fast MA period. Default: 12

None
slow int

Slow MA period. Default: 26

None
signal int

Signal period. Default: 9

None
scalar float

Scalar. Default: 100

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns




Psychological Line

This indicator compares the number of the rising bars to the total number of bars. In other words, it is the percentage of bars that are above the previous bar over a given length.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
open_ Series

open Series

None
length int

The period. Default: 12

None
scalar float

Scalar. Default: 100

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Quantitative Qualitative Estimation

This indicator is similar to SuperTrend but uses a Smoothed rsi with upper and lower bands.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

RSI period. Default: 14

None
smooth int

RSI smoothing period. Default: 5

None
factor float

QQE Factor. Default: 4.236

None
mamode str

See help(ta.ma). Default: "ema"

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

4 columns

Trend
  • Long: When the Smoothed RSI crosses the previous upperband.
  • Short: When the Smoothed RSI crosses the previous lowerband.
See also
  • QQE.mq5 by EarnForex Copyright © 2010
  • Tim Hyder (2008) version
  • Roman Ignatov (2006) version




Rate of Change

This indicator, also (confusingly) known as Momentum, is a pure oscillator that quantifies the percent change.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 10

None
scalar float

Scalar. Default: 100

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Relative Strength Index

This oscillator used to attempts to quantify "velocity" and "magnitude".

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 14

None
scalar float

Scalar. Default: 100

None
mamode str

See help(ta.ma). Default: "rma"

None
talib bool

If installed, use TA Lib. Default: True

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column

Warning

TA-Lib Correlation: np.float64(0.9289853267851295)

Tip

Corrective contributions welcome!


NOTICE

Thanks to all those that have sponsored and dontated to the library in the past! Your support has been greatly appreciated! 🙏

However, future releases are on definite hold until 100+ donations of $150+ have been received via Buy Me a Coffee.

Help keep this library and application the best in it's class!




Relative Strength Xtra

This indicator, by Jurik Research, is an enhanced version of the RSI which attemps to reduce noise and provide a clearer, though slightly delayed, signal.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 14

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Relative Vigor Index

This indicator attempts to quantify the strength of a trend relative to its trading range.

Sources

Parameters:

Name Type Description Default
open_ Series

open Series

required
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 14

None
swma_length int

SWMA period. Default: 4

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Slope

Calculates a rolling slope.

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 1

None
as_angle bool

Converts slope to an angle in radians per np.arctan(). Default: False

None
to_degrees value

If as_angle=True, converts radians to degrees. Default: False

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




Smart Money Concept

This indicator combines several techniques in an attempt to identify significant movements that might indicate "smart money" actions. It uses candlestick patterns, moving averages, and imbalance calculations.

Sources

Parameters:

Name Type Description Default
abr_length int

ABR length. Default: 14

None
close_length int

The close MA period. Default: 50

None
vol_length int

Volatility period. Default: 20

None
percent int

Percent of wick that exceeds the body. Default: 5

None
vol_ratio float

Volatility ratio (high) limit. Default: 1.5

None
asint bool

Returns as Int. Default: True

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Returns:

Type Description
DataFrame

7 columns




SMI Ergodic Indicator

This indicator, by William Blau, is the same as the TSI except the SMI includes a signal line. A trend is considered bullish when crossing above zero and bearish when crossing below zero. This implementation includes both the SMI Ergodic Indicator and SMI Ergodic Oscillator.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
fast int

The short period. Default: 5

None
slow int

The long period. Default: 20

None
signal int

Signal period. Default: 5

None
scalar float

Scalar. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns




Squeeze

This indicator, based on John Carter's "TTM Squeeze" indicator, attempts identify momentum using volatility.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
bb_length int

BB period. Default: 20

None
bb_std float

BB Std. Dev. Default: 2

None
kc_length int

KC period. Default: 20

None
kc_scalar float

KC scalar. Default: 1.5

None
mom_length int

Momentum Period. Default: 12

None
mom_smooth int

Momentum Smoothing period. Default: 6

None
mamode str

One of: "ema" or "sma". Default: "sma"

None
prenan bool

Apply prenans. Default: False

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
tr value

Use True Range for Keltner Channels. Default: True

asint bool

Returns as Int. Default: True

lazybear value

LazyBear's TradingView. Default: False

detailed value

Extra detailed. Default: False

fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame
  • Default: 4 columns
  • Detailed: 10 columns
Volatility
  • Increasing: kc and bbands difference increases
  • Decreasing: kc and bbands difference decreases




Squeeze Pro

This indicator, based on John Carter's "TTM Squeeze" indicator, attempts identify momentum using volatility with additional details.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
bb_length int

BB period. Default: 20

None
bb_std float

BB Std. Dev. Default: 2

None
kc_length int

KC period. Default: 20

None
kc_scalar_normal float

Keltner Channel scalar for normal channel. Default: 1.5

None
kc_scalar_narrow float

Narrow channel KC scalar. Default: 1

None
kc_scalar_wide float

Wide channel KC scalar. Default: 2

None
mom_length int

Momentum Period. Default: 12

None
mom_smooth int

Momentum Smoothing period. Default: 6

None
mamode str

One of: "ema" or "sma". Default: "sma"

None
prenan bool

Apply prenans. Default: False

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
tr value

Use True Range for Keltner Channels. Default: True

asint bool

Returns as Int. Default: True

mamode value

Which MA to use. Default: "sma"

detailed value

Extra detailed. Default: False

fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

6 columns (default) or 12 columns if detailed=True

Warning

May be depreciated in the future and combined with squeeze.




Schaff Trend Cycle

This indicator is an evolved MACD with additional smoothing.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
tc_length int

TC period. (Adjust to the half of cycle) Default: 10

None
fast int

Fast MA period. Default: 12

None
slow int

Slow MA period. Default: 26

None
factor float

Smoothing factor for last stoch. calculation. Default: 0.5

None
offset int

How many bars to shift the results. Default: `0

None

Other Parameters:

Name Type Description
ma1 Series

User chosen MA. Default: False

ma2 Series

User chosen MA. Default: False

osc Series

User chosen oscillator. Default: False

fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns

Note

Can also seed STC with two MAs, ma1 and ma2, or an oscillator osc.

  • ma1 and ma2 are both required if this option is used.




Stochastic

This indicator, by George Lane in the 1950's, attempts to identify and quantify momentum; it assumes that momentum precedes value change.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
k int

The Fast %K period. Default: 14

None
d int

The Slow %D period. Default: 3

None
smooth_k int

The Slow %K period. Default: 3

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

3 columns




Fast Stochastic

This indicator, by George Lane in the 1950's, attempts to identify and quantify momentum like STOCH, but is more volatile.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
k int

The Fast %K period. Default: 14

None
d int

The Slow %D period. Default: 3

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns




Stochastic RSI

This indicator attempts to quantify RSI relative to its High-Low range.

Sources
  • "Stochastic RSI and Dynamic Momentum Index", Tushar Chande and Stanley Kroll, Stock & Commodities V.11:5 (189-199)
  • tradingview

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 14

None
rsi_length int

RSI period. Default: 14

None
k int

The Fast %K period. Default: 3

None
d int

The Slow %K period. Default: 3

None
mamode str

See help(ta.ma). Default: "sma"

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns

Note

May be more sensitive to RSI and thus identify potential "overbought" or "oversold" signals.




True Momentum Oscillator

This indicator attempts to quantify momentum.

Sources

Parameters:

Name Type Description Default
open_ Series

open Series

required
close Series

close Series

required
tmo_length int

TMO period. Default: 14

None
calc_length int

Initial MA period. Default: 5

None
smooth_length int

Main and smooth signal MA period. Default: 3

None
mamode str

See help(ta.ma). Default: "ema"

None
momentum bool

Compute main and smooth momentum. Default: False

None
normalize bool

Normalize. Default: False

None
exclusive bool

Exclusive period over n bars, or inclusively over n-1 bars. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

DataFrame.fillna(value)

Returns:

Type Description
DataFrame

4 columns


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Trix

This indicator attempts to identify divergences as an oscillator.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
length int

The period. Default: 18

None
signal int

Signal period. Default: 9

None
scalar float

Scalar. Default: 100

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




True Strength Index

This indicator attempts to identify short-term swings in trend direction as well as identifying possible "overbought" and "oversold" signals.

Sources

Parameters:

Name Type Description Default
close Series

close Series

required
fast int

Fast MA period. Default: 13

None
slow int

Slow MA period. Default: 25

None
signal int

Signal period. Default: 13

None
scalar float

Scalar. Default: 100

None
mamode str

Signal MA. See help(ta.ma). Default: "ema"

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
DataFrame

2 columns




Ultimate Oscillator

This indicator, by Larry Williams, attempts to identify momentum.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
fast int

The Fast %K period. Default: 7

None
medium int

The Slow %K period. Default: 14

None
slow int

The Slow %D period. Default: 28

None
fast_w float

The Fast %K period. Default: 4.0

None
medium_w float

The Slow %K period. Default: 2.0

None
slow_w float

The Slow %D period. Default: 1.0

None
talib bool

If installed, use TA Lib. Default: True

None
drift int

Difference amount. Default: 1

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column




William's Percent R

This indicator attempts to identify "overbought" and "oversold" conditions similar to the RSI.

Sources

Parameters:

Name Type Description Default
high Series

high Series

required
low Series

low Series

required
close Series

close Series

required
length int

The period. Default: 14

None
talib bool

If installed, use TA Lib. Default: True

None
offset int

Post shift. Default: 0

None

Other Parameters:

Name Type Description
fillna value

pd.DataFrame.fillna(value)

Returns:

Type Description
Series

1 column


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