Analysis of ‘Time Series Forecasting with Yahoo Stock Price ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/arashnic/time-series-forecasting-with-yahoo-stock-price on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

Stocks and financial instrument trading is a lucrative proposition. Stock markets across the world facilitate such trades and thus wealth exchanges hands. Stock prices move up and down all the time and having ability to predict its movement has immense potential to make one rich. Stock price prediction has kept people interested from a long time. There are hypothesis like the Efficient Market Hypothesis, which says that it is almost impossible to beat the market consistently and there are others which disagree with it.

There are a number of known approaches and new research going on to find the magic formula to make you rich. One of the traditional methods is the time series forecasting. Fundamental analysis is another method where numerous performance ratios are analyzed to assess a given stock. On the emerging front, there are neural networks, genetic algorithms, and ensembling techniques.

Another challenging problem in stock price prediction is Black Swan Event, unpredictable events that cause stock market turbulence. These are events that occur from time to time, are unpredictable and often come with little or no warning.

A black swan event is an event that is completely unexpected and cannot be predicted. Unexpected events are generally referred to as black swans when they have significant consequences, though an event with few consequences might also be a black swan event. It may or may not be possible to provide explanations for the occurrence after the fact – but not before. In complex systems, like economies, markets and weather systems, there are often several causes. After such an event, many of the explanations for its occurrence will be overly simplistic.

#
#

https://www.visualcapitalist.com/wp-content/uploads/2020/03/mm3_black_swan_events_shareable.jpg"> #
#
New bleeding age state-of-the-art deep learning models stock predictions is overcoming such obstacles e.g. "Transformer and Time Embeddings". An objectives are to apply these novel models to forecast stock price.

Content

Stock price prediction is the task of forecasting the future value of a given stock. Given the historical daily close price for S&P 500 Index, prepare and compare forecasting solutions. S&P 500 or Standard and Poor's 500 index is an index comprising of 500 stocks from different sectors of US economy and is an indicator of US equities. Other such indices are the Dow 30, NIFTY 50, Nikkei 225, etc. For the purpose of understanding, we are utilizing S&P500 index, concepts, and knowledge can be applied to other stocks as well.

Dataset

The historical stock price information is also publicly available. For our current use case, we will utilize the pandas_datareader library to get the required S&P 500 index history using Yahoo Finance databases. We utilize the closing price information from the dataset available though other information such as opening price, adjusted closing price, etc., are also available. We prepare a utility function get_raw_data() to extract required information in a pandas dataframe. The function takes index ticker name as input. For S&P 500 index, the ticker name is ^GSPC. The following snippet uses the utility function to get the required data.(See Simple LSTM Regression)

Features and Terminology: In stock trading, the high and low refer to the maximum and minimum prices in a given time period. Open and close are the prices at which a stock began and ended trading in the same period. Volume is the total amount of trading activity. Adjusted values factor in corporate actions such as dividends, stock splits, and new share issuance.

Starter Kernel(s)

• Simple LSTM Regression

Acknowledgements

Mining and updating of this dateset will depend upon Yahoo Finance .

Inspiration

Sort of variation of sequence modeling and bleeding age e.g. attention can be applied for research and forecasting

Some Readings

• Applications of deep learning in stock market prediction: recent progress
• Stock predictions with state-of-the-art Transformer and Time Embeddings
• https://arxiv.org/pdf/1712.02136.pdf
• https://catanacapital.com/blog/unpredictable-black-swan-event-stock-market/
• https://par.nsf.gov/servlets/purl/10149715
• https://arxiv.org/pdf/1712.02136.pdf

*If you download and find the data useful your upvote is an explicit feedback for future works*

--- Original source retains full ownership of the source dataset ---

TADMALTA - Collection of sea temperature (TEMP) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=14.5589 ep_parameter_group=Water Temperature featureType=TimeSeries geometryType=Point geospatial_lat_max=36.0249 geospatial_lat_min=35.818083 geospatial_lat_units=degrees_north geospatial_lon_max=14.5589 geospatial_lon_min=14.3018 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=TADMALTA keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'TEMP'."&integrator_id="tadmalta" Northernmost_Northing=36.0249 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::TEMPPR01 sourceUrl=(local files) Southernmost_Northing=35.818083 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2024-06-25T07:14:00Z time_coverage_start=2021-05-28T13:32:55Z Westernmost_Easting=14.3018

INGV - Collection of electrical conductivity (CNDC) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=15.393117 ep_parameter_group=Water conductivity/ BioGeoChemical featureType=TimeSeries geometryType=Point geospatial_lat_max=39.488333 geospatial_lat_min=36.352917 geospatial_lat_units=degrees_north geospatial_lon_max=15.393117 geospatial_lon_min=-9.518245 geospatial_lon_units=degrees_east geospatial_vertical_max=3320.0 geospatial_vertical_min=2036.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=INGV keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'CNDC'."&integrator_id="ingv" Northernmost_Northing=39.488333 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::CNDCZZ01 sourceUrl=(local files) Southernmost_Northing=36.352917 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2013-06-12T19:00:00Z time_coverage_start=2003-12-14T08:00:00Z Westernmost_Easting=-9.518245

TADMALTA - Collection of water surface height above a specific datum (SLEV) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=14.549409 ep_parameter_group=Sea Level featureType=TimeSeries geometryType=Point geospatial_lat_max=35.92111 geospatial_lat_min=35.818083 geospatial_lat_units=degrees_north geospatial_lon_max=14.549409 geospatial_lon_min=14.49417 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=TADMALTA keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'SLEV'."&integrator_id="tadmalta" Northernmost_Northing=35.92111 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::ASLVZZ01 sourceUrl=(local files) Southernmost_Northing=35.818083 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2023-02-09T12:15:45Z time_coverage_start=2019-11-07T11:50:00Z Westernmost_Easting=14.49417

INGV - Collection of sea temperature (TEMP) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=15.393117 ep_parameter_group=Water Temperature featureType=TimeSeries geometryType=Point geospatial_lat_max=39.488333 geospatial_lat_min=36.352917 geospatial_lat_units=degrees_north geospatial_lon_max=15.393117 geospatial_lon_min=-9.518245 geospatial_lon_units=degrees_east geospatial_vertical_max=3320.0 geospatial_vertical_min=2036.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=INGV keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'TEMP'."&integrator_id="ingv" Northernmost_Northing=39.488333 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::TEMPPR01 sourceUrl=(local files) Southernmost_Northing=36.352917 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2013-06-12T19:00:00Z time_coverage_start=2003-12-14T08:00:00Z Westernmost_Easting=-9.518245

TADMALTA - Collection of wind direction, wind speed (WDIR_WSPD) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=14.5589 ep_parameter_group=Winds featureType=TimeSeries geometryType=Point geospatial_lat_max=36.0249 geospatial_lat_min=35.8217 geospatial_lat_units=degrees_north geospatial_lon_max=14.5589 geospatial_lon_min=14.3018 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=TADMALTA keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'WDIR_WSPD'."&integrator_id="tadmalta" Northernmost_Northing=36.0249 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::EWDAZZ01, SDN:P01::EWSBZZ01 sourceUrl=(local files) Southernmost_Northing=35.8217 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2024-06-25T07:14:00Z time_coverage_start=2022-09-28T15:54:00Z Westernmost_Easting=14.3018

TADMALTA - Collection of gust wind speed (GSPD) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=14.5589 ep_parameter_group=Winds featureType=TimeSeries geometryType=Point geospatial_lat_max=36.0249 geospatial_lat_min=35.818083 geospatial_lat_units=degrees_north geospatial_lon_max=14.5589 geospatial_lon_min=14.3018 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=TADMALTA keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'GSPD'."&integrator_id="tadmalta" Northernmost_Northing=36.0249 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::EGTSZZ01 sourceUrl=(local files) Southernmost_Northing=35.818083 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2024-06-25T07:14:00Z time_coverage_start=2021-05-28T13:32:55Z Westernmost_Easting=14.3018

TADMALTA - Collection of atmospheric pressure at sea level (ATMS) TimeSeries - IN SITU MultiPointTimeSeriesObservation cdm_data_type=TimeSeries cdm_timeseries_variables=PLATFORMCODE,SOURCE,latitude,longitude citation=Data are the property of the producer/owner distributed through EMODnet Physics. EMODnet Physics and the partners are not responsible for improper use contact=contacts@emodnet-physics.eu Conventions=CF-1.6 OceanSITES-Manual-1.2 Copernicus-InSituTAC-SRD-1.3 Copernicus-InSituTAC-ParametersList-3.0.0, COARDS, ACDD-1.3 Easternmost_Easting=14.5589 ep_parameter_group=Atmospheric featureType=TimeSeries geometryType=Point geospatial_lat_max=36.0249 geospatial_lat_min=35.8181 geospatial_lat_units=degrees_north geospatial_lon_max=14.5589 geospatial_lon_min=14.3018 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=http://www.emodnet-physics.eu institution=TADMALTA keywords_vocabulary=GCMD Science Keywords metadata_dataset=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.html metadata_document=https://ercompwebapps.emodnet-physics.eu/erddap/tabledap/EP_PLATFORMS_METADATA.csv?&parameters=~".*'ATMS'."&integrator_id="tadmalta" Northernmost_Northing=36.0249 platformType_best_practices_DOI=https://atlantos-h2020.eu/download/7.2-QC-Report.pdf platformType_dataFeatureType=timeseries platformType_description=mooring time series platformType_trajectory=False qc_reference_table=https://er2webapps.emodnet-physics.eu/erddap/tabledap/qc_reference_table.html SDN=SDN:P01::CAPAZZ01 sourceUrl=(local files) Southernmost_Northing=35.8181 standard_name_vocabulary=CF Standard Name Table v70 subsetVariables=PLATFORMCODE,SOURCE testOutOfDate=now-7days time_coverage_end=2024-06-25T07:14:00Z time_coverage_start=2022-09-28T15:54:00Z Westernmost_Easting=14.3018