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Applying Deep Learning to Financial Markets with News Data

Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

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Page 1: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

ApplyingDeepLearningtoFinancialMarketswithNewsData

Page 2: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

Largeamountsofnewsdata

Usedeepneuralnetworkstobuildpredictivemodels

Predictmarketdirectionof

relevantstocks

ExecutiveSummary

Page 3: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

DealingwithNewsOriginalWorkflow

Findinterestingarticles

Makeinvestmentdecision

Reactinthemarket

VerytimeconsumingLimitedscopeofarticles Missedopportunities

Deriveimplications

Page 4: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

DealingwithNewsFutureWorkflow

Streammanynewsarticles

Linkarticleswithappropriatestocks

Determinesentimentscores

Determineifmarketmoving

Reactinthemarket

Abletodeterminesentimentandimpactonthemarket

Abletoanalyzemorearticlesthananyhuman

Abletogetinandoutofmarketfaster

A+

Page 5: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

DeepLearning

ModelApproach- DeepLearning

NVIDIA

abc

Lotsofdata FeatureselectionUnstructureddata NLP

GPU cuDNN Library

Page 6: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

CurrentResults

76%

F1Score

News

4

21

3

EmbeddingInput

ModelArchitecture ModelResults FutureConsiderations

GloVe

A+

LSTM

BatchNormalization

Softmax

5

Output

Linktotickers

Sentiment

MarketMovers

ProprietaryEmbedding

TickersAccuracy FinancialData

$

PositiveNeutralNegative

Page 7: Applying Deep Learning to Financial Markets with News Data · A+ LSTM Batch Normalization Softmax 5 Output Link to tickers Sentiment Market Movers Proprietary Embedding Accuracy Tickers

ThankYou

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