Example Indicators¶
Custom Average Directional Index - ADX https://www.investopedia.com/terms/a/adx.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.adx.
IndicatorADX
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.adx import IndicatorADX ind = IndicatorADX(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.adx.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Average True Range - ATR
https://www.investopedia.com/terms/a/atr.asp
Volatility
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.atr.
IndicatorATR
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.atr import IndicatorATR ind = IndicatorATR(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.atr.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom BollingerBands
https://www.investopedia.com/terms/b/bollingerbands.asp
Overlap
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.bollinger_bands.
IndicatorBollingerBands
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.bollinger_bands import IndicatorBollingerBands ind = IndicatorBollingerBands(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.bollinger_bands.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Chaikin Oscillator
https://www.investopedia.com/terms/c/chaikinoscillator.asp https://www.investopedia.com/articles/active-trading/ 031914/understanding-chaikin-oscillator.asp
Volume
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.chaikin_osc.
IndicatorChaikinOSC
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.chaikin_osc import IndicatorChaikinOSC ind = IndicatorChaikinOSC(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.chaikin_osc.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Chaikin
https://www.investopedia.com/terms/c/chaikinoscillator.asp https://www.investopedia.com/articles/active-trading/ 031914/understanding-chaikin-oscillator.asp
Volume
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.chaikin.
IndicatorChaikin
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.chaikin import IndicatorChaikin ind = IndicatorChaikin(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.chaikin.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Exponential Moving Average
https://www.investopedia.com/terms/e/ema.asp
Overlap
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.ema.
IndicatorEMA
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.ema import IndicatorEMA ind = IndicatorEMA(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.ema.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Moving Average Convergence Divergence - MACD
https://www.investopedia.com/terms/a/adx.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.macd.
IndicatorMACD
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.macd import IndicatorMACD ind = IndicatorMACD(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.macd.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Money Flow Index - MFI
https://www.investopedia.com/terms/m/mfi.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.mfi.
IndicatorMFI
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.mfi import IndicatorMFI ind = IndicatorMFI(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.mfi.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Momentum - MOM
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.mom.
IndicatorMOM
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.mom import IndicatorMOM ind = IndicatorMOM(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.mom.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Normalized Average True Range - NATR
https://www.investopedia.com/terms/a/atr.asp
Volatility
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.natr.
IndicatorNATR
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.natr import IndicatorNATR ind = IndicatorNATR(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.natr.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom On Balance Volume
https://www.investopedia.com/terms/o/onbalancevolume.asp
Volume
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.obv.
IndicatorOnBalanceVolume
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.obv import IndicatorOnBalanceVolume ind = IndicatorOnBalanceVolume(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.obv.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Price of Rate of Change - ROC
https://www.investopedia.com/terms/p/pricerateofchange.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.roc.
IndicatorROC
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.roc import IndicatorROC ind = IndicatorROC(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.roc.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Relative Strength Index - RSI
https://www.investopedia.com/terms/r/rsi.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.rsi.
IndicatorRSI
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.rsi import IndicatorRSI ind = IndicatorRSI(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.rsi.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Stochastics - STOCHF
https://www.investopedia.com/terms/s/stochasticoscillator.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.stochf.
IndicatorSTOCHF
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.stochf import IndicatorSTOCHF ind = IndicatorSTOCHF(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.stochf.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Stochastics - STOCH
https://www.investopedia.com/terms/a/adx.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.stoch.
IndicatorSTOCH
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.stoch import IndicatorSTOCH ind = IndicatorSTOCH(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.stoch.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom True Range - TRANGE
https://www.investopedia.com/terms/a/atr.asp
Volatility
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.trange.
IndicatorTRANGE
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.trange import IndicatorTRANGE ind = IndicatorTRANGE(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.trange.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Williams Percent R Indicator that uses Open instead of Close
https://www.investopedia.com/terms/w/williamsr.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.williamsr_open.
IndicatorWilliamsROpen
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.williamsr_open import IndicatorWilliamsROpen ind = IndicatorWilliamsROpen(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.williamsr_open.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Williams Percent R Indicator
https://www.investopedia.com/terms/w/williamsr.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.williamsr.
IndicatorWilliamsR
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.williamsr import IndicatorWilliamsR ind = IndicatorWilliamsR(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.williamsr.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Weighted Moving Average
https://www.investopedia.com/articles/technical/060401.asp
Overlap
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.indicators.wma.
IndicatorWMA
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.indicators.wma import IndicatorWMA ind = IndicatorWMA(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.indicators.wma.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
V1 Indicator Examples¶
Custom Williams Percent R Indicator
https://www.investopedia.com/terms/w/williamsr.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.mocks.example_indicator_williamsr.
ExampleIndicatorWilliamsR
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.mocks.example_indicator_williamsr import ExampleIndicatorWilliamsR ind = ExampleIndicatorWilliamsR(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.mocks.example_indicator_williamsr.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Custom Williams Percent R Indicator that uses Open instead of Close
https://www.investopedia.com/terms/w/williamsr.asp
Momentum
Supported environment variables
# to show debug, trace logging please export ``SHARED_LOG_CFG``
# to a debug logger json file. To turn on debugging for this
# library, you can export this variable to the repo's
# included file with the command:
export SHARED_LOG_CFG=/opt/sa/analysis_engine/log/debug-logging.json
-
class
analysis_engine.mocks.example_indicator_williamsr_open.
ExampleIndicatorWilliamsROpen
(**kwargs)[source]¶ -
get_configurables
(**kwargs)[source]¶ helper for setting up algorithm configs for this indicator and programmatically set the values based off the domain rules
from analysis_engine.mocks.example_indicator_williamsr_open import ExampleIndicatorWilliamsROpen ind = ExampleIndicatorWilliamsROpen(config_dict={ 'verbose': True }).get_configurables()
Parameters: kwargs – keyword args dictionary
-
process
(algo_id, ticker, dataset)[source]¶ Derive custom indicator processing to determine buy and sell conditions before placing orders. Just implement your own
process
method.Please refer to the TA Lib guides for details on building indicators:
- Overlap Studies https://mrjbq7.github.io/ta-lib/func_groups/overlap_studies.html
- Momentum Indicators https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html
- Volume Indicators https://mrjbq7.github.io/ta-lib/func_groups/volume_indicators.html
- Volatility Indicators https://mrjbq7.github.io/ta-lib/func_groups/volatility_indicators.html
- Price Transform https://mrjbq7.github.io/ta-lib/func_groups/price_transform.html
- Cycle Indicators https://mrjbq7.github.io/ta-lib/func_groups/cycle_indicators.html
- Pattern Recognition https://mrjbq7.github.io/ta-lib/func_groups/pattern_recognition.html
- Statistic Functions https://mrjbq7.github.io/ta-lib/func_groups/statistic_functions.html
- Math Transform https://mrjbq7.github.io/ta-lib/func_groups/math_transform.html
- Math Operators https://mrjbq7.github.io/ta-lib/func_groups/math_operators.html
Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – dictionary of
pandas.DataFrame(s)
to process
-
-
analysis_engine.mocks.example_indicator_williamsr_open.
get_indicator
(**kwargs)[source]¶ Make sure to define the
get_indicator
for your custom algorithms to work as a backup with thesa.py
tool… Not anticipating issues, but if we do with importlib this is the backup plan.Please file an issue if you see something weird and would like some help: https://github.com/AlgoTraders/stock-analysis-engine/issues
Parameters: kwargs – dictionary of keyword arguments
Indicator Utilities¶
Algo data helper for mapping indicator category to an integer label value for downstream dataset predictions
-
analysis_engine.indicators.get_category_as_int.
get_category_as_int
(node, label=None)[source]¶ Helper for converting feature labels to numeric values
Parameters: node – convert the dictionary’s category
string to the integer mapped value
Indicator Processor
- v1 Indicator type:
supported
- Binary decision support on buys and sells
This is like an alert threshold that is
on
oroff
- v1 Indicator type:
- v2 Indicator type:
not supported
- Support for buy or sell value range
This is like an alert threshold between a
lower
andupper
bound
- v2 Indicator type:
-
class
analysis_engine.indicators.indicator_processor.
IndicatorProcessor
(config_dict, config_file=None, ticker=None, label=None, verbose=False, verbose_indicators=False)[source]¶ -
build_indicators_for_config
(config_dict)[source]¶ Convert the dictionary into an internal dictionary for quickly processing results
Parameters: config_dict – initailized algorithm config dictionary
-
get_latest_report
(algo_id=None, ticker=None, dataset=None)[source]¶ Return the latest report as a method that can be customized by a derived class from the
IndicatorProcessor
Parameters: - algo_id – optional - string - algo identifier label for debugging datasets during specific dates
- ticker – optional - string - ticker
- dataset – optional - a dictionary of
identifiers (for debugging) and
multiple pandas
pd.DataFrame
objects. Dictionary where keys represent a label from one of the data sources (IEX
,Yahoo
,FinViz
or other). Here is the supported dataset structure for the process method:
-
process
(algo_id, ticker, dataset)[source]¶ Parameters: - algo_id – string - algo identifier label for debugging datasets during specific dates
- ticker – string - ticker
- dataset – a dictionary of identifiers (for debugging) and
multiple pandas
pd.DataFrame
objects. Dictionary where keys represent a label from one of the data sources (IEX
,Yahoo
,FinViz
or other). Here is the supported dataset structure for the process method:
-