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  • John Snow Labs
  • Jan 19, 2023

Mapping Companies to NASDAQ Stock Screener by Ticker

  • en
  • finance
  • licensed
  • nasdaq
  • ticker

Description

This model allows you to, given a Ticker, get the following information about a company at Nasdaq Stock Screener:

  • Country
  • IPO_Year
  • Industry
  • Last_Sale
  • Market_Cap
  • Name
  • Net_Change
  • Percent_Change
  • Sector
  • Ticker
  • Volume

Firstly, you should get the TICKER symbol from the finance text with the finner_ticker model, then you can get detailed information about the company with the ChunkMapper model.

Predicted Entities

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How to use

document_assembler = nlp.DocumentAssembler()\
    .setInputCol('text')\
    .setOutputCol('document')

tokenizer = nlp.Tokenizer()\
    .setInputCols("document")\
    .setOutputCol("token")

embeddings = nlp.BertEmbeddings.pretrained("bert_embeddings_sec_bert_base","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings")

ner_model = finance.NerModel.pretrained("finner_ticker", "en", "finance/models")\
    .setInputCols(["document", "token", "embeddings"])\
    .setOutputCol("ner")

ner_converter = nlp.NerConverter()\
    .setInputCols(["document", "token", "ner"])\
    .setOutputCol("ner_chunk")

CM = finance.ChunkMapperModel.pretrained('finmapper_nasdaq_ticker_stock_screener', 'en', 'finance/models')\
    .setInputCols(["ner_chunk"])\
    .setOutputCol("mappings")

pipeline = nlp.Pipeline().setStages([document_assembler,
                                 tokenizer, 
                                 embeddings,
                                 ner_model, 
                                 ner_converter, 
                                 CM])
                                 
text = ["""There are some serious purchases and sales of AMZN stock today."""]

test_data = spark.createDataFrame([text]).toDF("text")

model = pipeline.fit(test_data)

result = model.transform(test_data).select('mappings').collect()

Results

"Country": "United States",
"IPO_Year": "1997",
"Industry": "Catalog/Specialty Distribution",
"Last_Sale": "$98.12",
"Market_Cap": "9.98556270184E11",
"Name": "Amazon.com Inc. Common Stock",
"Net_Change": "2.85",
"Percent_Change": "2.991%",
"Sector": "Consumer Discretionary",
"Ticker": "AMZN",
"Volume": "85412563"

Model Information

Model Name: finmapper_nasdaq_ticker_stock_screener
Compatibility: Finance NLP 1.0.0+
License: Licensed
Edition: Official
Input Labels: [ner_chunk]
Output Labels: [mappings]
Language: en
Size: 584.5 KB

References

https://www.nasdaq.com/market-activity/stocks/screener