Skip to content

Commit

Permalink
[GH-23] Add supertrend indicator. (#111)
Browse files Browse the repository at this point in the history 
As title.  Also fix some issues in readme.
  • Loading branch information
@jealous
jealous committed Jan 7, 2022
1 parent 64b6c66 commit 201aa0d
Show file tree
Hide file tree
Showing 3 changed files with 175 additions and 60 deletions.
136 changes: 77 additions & 59 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -45,14 +45,15 @@ Supported statistics/indicators are:
* ADXR: Smoothed Moving Average of ADX
* TRIX: Triple Exponential Moving Average
* TEMA: Another Triple Exponential Moving Average
* VR: Volatility Volume Ratio
* VR: Volume Variation Index
* MFI: Money Flow Index
* VWMA: Volume Weighted Moving Average
* CHOP: Choppiness Index
* KAMA: Kaufman's Adaptive Moving Average
* PPO: Percentage Price Oscillator
* StochRSI: Stochastic RSI
* WT: LazyBear's Wave Trend
* Supertrend: with the Upper Band and Lower Band

## Installation

Expand Down Expand Up @@ -232,22 +233,19 @@ date
[2813 rows x 3 columns]
```

#### RSI - Relative Strength Index
#### [RSI - Relative Strength Index](https://en.wikipedia.org/wiki/Relative_strength_index)

RSI stands
for [Relative Strength Index](https://en.wikipedia.org/wiki/Relative_strength_index)

It has a configurable window. The default window size is 14 which is
RSI has a configurable window. The default window size is 14 which is
configurable through `StockDataFrame.RSI`. e.g.

* `df['rsi']`: 14 periods RSI
* `df['rsi_6']`: 6 periods RSI

#### Log Return of the Close
#### [Log Return of the Close](https://en.wikipedia.org/wiki/Rate_of_return)

Logarithmic return = ln( close / last close)

From [wiki](https://en.wikipedia.org/wiki/Rate_of_return):
From wiki:

> For example, if a stock is priced at 3.570 USD per share at the close on
> one day, and at 3.575 USD per share at the close the next day, then the
Expand Down Expand Up @@ -327,10 +325,10 @@ Examples:
RSV is essential for calculating KDJ. It takes a window parameter.
Use `df['rsv']` or `df['rsv_6']` to access it.

#### RSI - Relative Strength Index
#### [RSI - Relative Strength Index](https://en.wikipedia.org/wiki/Relative_strength_index)

[RSI](https://en.wikipedia.org/wiki/Relative_strength_index) chart the current
and historical strength or weakness of a stock. It takes a window parameter.
RSI chart the current and historical strength or weakness of a stock. It takes
a window parameter.

The default window is 14. Use `StockDataFrame.RSI` to tune it.

Expand All @@ -339,11 +337,10 @@ Examples:
* `df['rsi']`: retrieve the RSI of 14 periods
* `df['rsi_6']`: retrieve the RSI of 6 periods

#### Stochastic RSI
#### [Stochastic RSI](https://www.investopedia.com/terms/s/stochrsi.asp)

[Stochastic RSI](https://www.investopedia.com/terms/s/stochrsi.asp) gives
traders an idea of whether the current RSI value is overbought or oversold. It
takes a window parameter.
Stochastic RSI gives traders an idea of whether the current RSI value is
overbought or oversold. It takes a window parameter.

The default window is 14. Use `StockDataFrame.RSI` to tune it.

Expand All @@ -352,11 +349,9 @@ Examples:
* `df['stochrsi']`: retrieve the Stochastic RSI of 14 periods
* `df['stochrsi_6']`: retrieve the Stochastic RSI of 6 periods

#### WT - Wave Trend
#### [WT - Wave Trend](https://medium.com/@samuel.mcculloch/lets-take-a-look-at-wavetrend-with-crosses-lazybear-s-indicator-2ece1737f72f)

Retrieve
the [LazyBear's Wave Trend](https://medium.com/@samuel.mcculloch/lets-take-a-look-at-wavetrend-with-crosses-lazybear-s-indicator-2ece1737f72f)
with `df['wt1']` and `df['wt2']`.
Retrieve the LazyBear's Wave Trend with `df['wt1']` and `df['wt2']`.

Wave trend uses two parameters. You can tune them with
`StockDataFrame.WAVE_TREND_1` and `StockDataFrame.WAVE_TREND_2`.
Expand All @@ -368,10 +363,10 @@ It takes two parameters, column and window.
For example, use `df['close_7_smma']` to retrieve the 7 periods smoothed moving
average of the close price.

#### TRIX - Triple Exponential Average
#### [TRIX - Triple Exponential Average](https://www.investopedia.com/articles/technical/02/092402.asp)

[Trix, the triple exponential average](https://www.investopedia.com/articles/technical/02/092402.asp)
, is used to identify oversold and overbought markets.
The triple exponential average is used to identify oversold and overbought
markets.

The algorithm is:

Expand All @@ -391,12 +386,9 @@ Examples:
* `df['trix']` stands for 12 periods Trix for the close price.
* `df['middle_10_trix']` stands for the 10 periods Trix for the typical price.

#### TEMA - Another Triple Exponential Average
#### [TEMA - Another Triple Exponential Average](https://www.forextraders.com/forex-education/forex-technical-analysis/triple-exponential-moving-average-the-tema-indicator/)

Tema is another implementation for the triple exponential moving average. You
can find the
algorithm [here](https://www.forextraders.com/forex-education/forex-technical-analysis/triple-exponential-moving-average-the-tema-indicator/)
.
Tema is another implementation for the triple exponential moving average.

```
TEMA=(3 x EMA) - (3 x EMA of EMA) + (EMA of EMA of EMA)
Expand All @@ -412,9 +404,19 @@ Examples:
* `df['tema']` stands for 12 periods TEMA for the close price.
* `df['middle_10_tema']` stands for the 10 periods TEMA for the typical price.

#### WR - Williams Overbought/Oversold Index
#### [VR - Volume Variation Index](https://help.eaglesmarkets.com/hc/en-us/articles/900002867026-Summary-of-volume-variation-index)

It is the strength index of trading volume.

It has a default window of 26. Change it with `StockDataFrame.VR`.

Examples:
* `df['vr']` retrieves the 26 periods VR.
* `df['vr_6']` retrieves the 6 periods VR.

#### [WR - Williams Overbought/Oversold Index](https://www.investopedia.com/terms/w/williamsr.asp)

[Williams Overbought/Oversold index](https://www.investopedia.com/terms/w/williamsr.asp)
Williams Overbought/Oversold index
is a type of momentum indicator that moves between 0 and -100 and measures
overbought and oversold levels.

Expand All @@ -426,11 +428,9 @@ Examples:
* `df['wr']` retrieves the 14 periods WR.
* `df['wr_6']` retrieves the 6 periods WR.

#### CCI - Commodity Channel Index
#### [CCI - Commodity Channel Index](https://www.investopedia.com/terms/c/commoditychannelindex.asp)

CCI stands
for [Commodity Channel Index](https://www.investopedia.com/terms/c/commoditychannelindex.asp)
.
CCI stands for Commodity Channel Index.

It requires a window parameter. The default window is 14. Use
`StockDataFrame.CCI` to change it.
Expand All @@ -445,9 +445,9 @@ Examples:
TR is a measure of volatility of a High-Low-Close series. It is used for
calculating the ATR.

#### ATR - Average True Range
#### [ATR - Average True Range](https://en.wikipedia.org/wiki/Average_true_range)

The [Average True Range](https://en.wikipedia.org/wiki/Average_true_range) is an
The Average True Range is an
N-period smoothed moving average (SMMA) of the true range value.
Default to 14 periods.

Expand All @@ -458,14 +458,27 @@ Example:
* `df['atr']` retrieves the 14 periods ATR.
* `df['atr_5']` retrieves the 5 periods ATR.

#### [Supertrend](https://economictimes.indiatimes.com/markets/stocks/news/how-to-use-supertrend-indicator-to-find-buying-and-selling-opportunities-in-market/articleshow/54492970.cms)

Supertrend indicates the current trend.
We use the [algorithm described here](https://medium.com/codex/step-by-step-implementation-of-the-supertrend-indicator-in-python-656aa678c111).
It includes 3 lines:
* `df['supertrend']` is the trend line.
* `df['supertrend_ub']` is the upper band of the trend
* `df['supertrend_lb']` is the lower band of the trend

It has 2 parameters:
* `StockDataFrame.SUPERTREND_MUL` is the multiplier of the band, default to 3.
* `StockDataFrame.SUPERTREND_WINDOW` is the window size, default to 14.

#### DMA - Difference of Moving Average

`df['dma']` retreives the difference of 10 periods SMA of the close price and
the 50 periods SMA of the close price.

#### DMI - Directional Movement Index
#### [DMI - Directional Movement Index](https://www.investopedia.com/terms/d/dmi.asp)

The [directional movement index (DMI)](https://www.investopedia.com/terms/d/dmi.asp)
The directional movement index (DMI)
identifies in which direction the price of an asset is moving.

It has several lines:
Expand All @@ -484,9 +497,12 @@ It has several parameters.
* `StockDataFrame.ADX_EMA` - window for ADX
* `StockDataFrame.ADXR_EMA` - window for ADXR

#### KDJ Indicator
#### [KDJ Indicator](https://en.wikipedia.org/wiki/Stochastic_oscillator)

It consists of three lines:
The stochastic oscillator is a momentum indicator that uses support and
resistance levels.

It includes three lines:
* `df['kdfk']` - K series
* `df['kdfd']` - D series
* `df['kdfj']` - J series
Expand All @@ -497,9 +513,9 @@ Use `df['kdjk_6']` to retrieve the K series of 6 periods.
KDJ also has two configurable parameter named `StockDataFrame.KDJ_PARAM`.
The default value is `(2.0/3.0, 1.0/3.0)`

#### CR - Energy Index
#### [CR - Energy Index](https://support.futunn.com/en/topic167/?lang=en-us)

The [Energy Index (Intermediate Willingness Index)](https://support.futunn.com/en/topic167/?lang=en-us)
The Energy Index (Intermediate Willingness Index)
uses the relationship between the highest price, the lowest price and
yesterday's middle price to reflect the market's willingness to buy
and sell.
Expand All @@ -510,12 +526,12 @@ It contains 4 lines:
* `df['cr-ma2']` - `StockDataFrame.CR_MA2` periods of the CR moving average
* `df['cr-ma3']` - `StockDataFrame.CR_MA3` periods of the CR moving average

#### Typical Price
#### [Typical Price](https://en.wikipedia.org/wiki/Typical_price)

It's the average of `high`, `low` and `close`.
Use `df['middle']` to access this value.

#### Bollinger Bands
#### [Bollinger Bands](https://en.wikipedia.org/wiki/Bollinger_Bands)

The Bollinger bands includes three lines
* `df['boll']` is the baseline
Expand All @@ -526,7 +542,7 @@ The default period of the Bollinger Band can be changed with
`StockDataFrame.BOLL_PERIOD`. The width of the bands can be turned with
`StockDataFrame.BOLL_STD_TIMES`. The default value is 2.

#### MACD - Moving Average Convergence Divergence
#### [MACD - Moving Average Convergence Divergence](https://en.wikipedia.org/wiki/MACD)

We use the close price to calculate the MACD lines.
* `df['macd']` is the difference between two exponential moving average.
Expand All @@ -540,10 +556,9 @@ value are 12 and 26
The period of the signal line can be tuned with
`StockDataFrame.MACD_EMA_SIGNAL`. The default value is 9.

#### PPO - Percentage Price Oscillator
#### [PPO - Percentage Price Oscillator](https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:price_oscillators_ppo)

The [Percentage Price Oscillator](https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:price_oscillators_ppo)
includes three lines.
The Percentage Price Oscillator includes three lines.

* `df['ppo']` derives from the difference of 2 exponential moving average.
* `df['ppos]` is the signal line.
Expand All @@ -556,17 +571,21 @@ value are 12 and 26
The period of the signal line can be tuned with
`StockDataFrame.PPO_EMA_SIGNAL`. The default value is 9.

#### Moving Standard Deviation
#### [Simple Moving Average](https://www.investopedia.com/terms/m/mean.asp)

Follow the pattern `<columnName>_<window>_sma` to retrieve simple moving average.

#### [Moving Standard Deviation](https://www.investopedia.com/terms/s/standarddeviation.asp)

Follow the pattern `<columnName>_<window>_mstd` to retrieve the moving STD.

#### Moving Variance
#### [Moving Variance](https://www.investopedia.com/terms/v/variance.asp)

Follow the pattern `<columnName>_<window>_mvar` to retrieve the moving VAR.

#### Volume Weighted Moving Average
#### [Volume Weighted Moving Average](https://www.investopedia.com/articles/trading/11/trading-with-vwap-mvwap.asp)

It's the [moving average weighted by volume](https://www.investopedia.com/articles/trading/11/trading-with-vwap-mvwap.asp).
It's the moving average weighted by volume.

It has a parameter for window size. The default window is 14. Change it with
`StockDataFrame.VWMA`.
Expand All @@ -575,10 +594,9 @@ Examples:
* `df['vwma']` retrieves the 14 periods VWMA
* `df['vwma_6']` retrieves the 6 periods VWMA

#### CHOP - Choppiness Index
#### [CHOP - Choppiness Index](https://www.tradingview.com/education/choppinessindex/)

The [Choppiness Index](https://www.tradingview.com/education/choppinessindex/)
determines if the market is choppy.
The Choppiness Index determines if the market is choppy.

It has a parameter for window size. The default window is 14. Change it with
`StockDataFrame.CHOP`.
Expand All @@ -587,9 +605,9 @@ Examples:
* `df['chop']` retrieves the 14 periods CHOP
* `df['chop_6']` retrieves the 6 periods CHOP

#### MFI - Money Flow Index
#### [MFI - Money Flow Index](https://www.investopedia.com/terms/m/mfi.asp)

The [Money Flow Index](https://www.investopedia.com/terms/m/mfi.asp)
The Money Flow Index
identifies overbought or oversold signals in an asset.

It has a parameter for window size. The default window is 14. Change it with
Expand All @@ -599,10 +617,10 @@ Examples:
* `df['mfi']` retrieves the 14 periods MFI
* `df['mfi_6']` retrieves the 6 periods MFI

#### KAMA - Kaufman's Adaptive Moving Average
#### [KAMA - Kaufman's Adaptive Moving Average](https://school.stockcharts.com/doku.php?id=technical_indicators:kaufman_s_adaptive_moving_average)

[Kaufman's Adaptive Moving Average](https://school.stockcharts.com/doku.php?id=technical_indicators:kaufman_s_adaptive_moving_average)
is designed to account for market noise or volatility.
Kaufman's Adaptive Moving Average is designed to account for market noise or
volatility.

It has 2 optional parameter and 2 required parameter
* fast - optional, the parameter for fast EMA smoothing, default to 5
Expand Down
Loading

0 comments on commit 201aa0d

Please sign in to comment.