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01_​Stocks

Stock Analysis: Automatic value prediction and alertingThe input to this workflow is a list of stock symbols from Yahoo Finance. After some preprocessing to determine the date range, this information is sent to the pandas webreader library (through the Python Source node) to collect (near) realtime stock information.The information is sent to the modeling workflow (through the Call Workflow node) where feature creation, model estimation, and prediction takes place for each stock symbol. This workflow collects the predictions and the reliability of the model, and visually displays the results - the expected percentagechange in value for each stock symbol.Note: To use this workflow you need to have Python and the following libraries installed on your machine:-pandas as pd-pandas-datareader-datetime This section creates the workflow variables that are sent to the Python Source node The workflow variables are sent to the Python Source node, which gathers historical data for each symbol. It can occur that data for a specific symbol is (temporarily) unavailable, in which case a value of -99 is returned. These cases are sent to the bottom port of theIf Switch node and are filtered out after the Loop End node. The predicted increased in stock value is sorted and exported to a plot and .csv files.When deployed on KNIME server, the Send Email node can be used to alert traders of potential interesting stock developments on a dailybasis. Authentication is supported via workflow or node level credentials; connection security via STARTTLS and SSL are both supported. Extract today's dateDeduct one dayCollect stockdata from Yahoo FinanceConvert to workflow variablesDecompose date to day, month and yearExtract date field from RowIDInitiate a loop for each stock symbolMerge date variableswith stock symbolAttach .csv file andplot of stock predictions to an e-mailSort symbols by expected% increaseGather all predictionsFilter unavailablesymbolsWrite daily predictions to a .csvCall modelling workflowExport plot to a fileUnavailable Symbolsare set to -99Add predictionsto history fileInsert a list of stock symbolsCollect stockdata from Yahoo Financepandaspandas-datareaderNode 268 Create Date&TimeRange Date&Time Shift Python Source Table Row to Variable(deprecated) Extract Date&TimeFields (deprecated) RowID Table Row To VariableLoop Start (deprecated) Merge Variables(deprecated) Send Email Sorter IF Switch End IF Loop End(deprecated) Rule-basedRow Filter CSV Writer(deprecated) Call Workflow (TableBased) (deprecated) Image Writer (Port)(deprecated) Set format forunavailable stocks CSV Writer(deprecated) Determine stockavailability Table Creator Bar Chart Python Script(Labs) Conda EnvironmentPropagation Line Plot Stock Analysis: Automatic value prediction and alertingThe input to this workflow is a list of stock symbols from Yahoo Finance. After some preprocessing to determine the date range, this information is sent to the pandas webreader library (through the Python Source node) to collect (near) realtime stock information.The information is sent to the modeling workflow (through the Call Workflow node) where feature creation, model estimation, and prediction takes place for each stock symbol. This workflow collects the predictions and the reliability of the model, and visually displays the results - the expected percentagechange in value for each stock symbol.Note: To use this workflow you need to have Python and the following libraries installed on your machine:-pandas as pd-pandas-datareader-datetime This section creates the workflow variables that are sent to the Python Source node The workflow variables are sent to the Python Source node, which gathers historical data for each symbol. It can occur that data for a specific symbol is (temporarily) unavailable, in which case a value of -99 is returned. These cases are sent to the bottom port of theIf Switch node and are filtered out after the Loop End node. The predicted increased in stock value is sorted and exported to a plot and .csv files.When deployed on KNIME server, the Send Email node can be used to alert traders of potential interesting stock developments on a dailybasis. Authentication is supported via workflow or node level credentials; connection security via STARTTLS and SSL are both supported. Extract today's dateDeduct one dayCollect stockdata from Yahoo FinanceConvert to workflow variablesDecompose date to day, month and yearExtract date field from RowIDInitiate a loop for each stock symbolMerge date variableswith stock symbolAttach .csv file andplot of stock predictions to an e-mailSort symbols by expected% increaseGather all predictionsFilter unavailablesymbolsWrite daily predictions to a .csvCall modelling workflowExport plot to a fileUnavailable Symbolsare set to -99Add predictionsto history fileInsert a list of stock symbolsCollect stockdata from Yahoo Financepandaspandas-datareaderNode 268 Create Date&TimeRange Date&Time Shift Python Source Table Row to Variable(deprecated) Extract Date&TimeFields (deprecated) RowID Table Row To VariableLoop Start (deprecated) Merge Variables(deprecated) Send Email Sorter IF Switch End IF Loop End(deprecated) Rule-basedRow Filter CSV Writer(deprecated) Call Workflow (TableBased) (deprecated) Image Writer (Port)(deprecated) Set format forunavailable stocks CSV Writer(deprecated) Determine stockavailability Table Creator Bar Chart Python Script(Labs) Conda EnvironmentPropagation Line Plot

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: maartenm
Created at: 2019-03-25
On NodePit since: 2022-10-14
Last update: 2024-11-21
Created with KNIME version: v4.6.1

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