Dr. Terry Benzschawel – Natural Language Processing in Trading

Dr. Terry Benzschawel – Natural Language Processing in TradingIf you are looking to trade based on the sentiments and opinions expressed in the news headline through cutting edge natural language processing techniques, this is the right course for you. Learn to quantify the news headline and add an edge to your trading using powerful models such as Word2Vec, BERT and XGBoost.Train a machine learning model to calculate a sentiment from a news headlineImplement and compare the word embeddings methods such as Bag of Words (BoW), TF-IDF, Word2Vec and BERTPredict the stock returns and bond returns from the news headlinesDescribe the applications of natural language processingAutomate and paper trade the strategies covered in the courseFetch the recent news headline dataImplement strategies in the live markets and analyze the performanceSKILLS COVEREDPredictive ModellingSupervised LearningXGBoost ModelTrain and Test DatasetsCorporate Bonds returnsStock Returns, Sharpe ratioWord EmbeddingsBag of WordsTF-IDFWord2VecBERTPythonNumpyPandasXGBoostMatplotlibCountVectorizerPREREQUISITES Basic familiarity with machine learning concepts such as training, testing, features and target variables is required. Exposure to programming concepts is required to interpret the codes covered in the course. However, experience with Python coding knowledge is optional. If you want to be able to code and implement the strategies in Python, you should be able to work with ‘Pandas Data frames’. All the required skill sets are covered in the foundation courses available in the learning track.SYLLABUSNatural Language Processing in Trading by Dr. Terry Benzschawel, what is it included (Content proof: Watch here!)Section 1: Introduction to the CourseSection 2: Applications of Natural Language ProcessingSection 3: Sources of News Headline DataSection 4: Sentiment Score and Strategy LogicSection 5: Sentiment Strategy on StocksSection 6: Sentiment Strategy on BondsSection 7: Introduction to Word EmbeddingsSection 8: Bag of WordsSection 9: Predicting Sentiment Score Using XGBoostSection 10: Sentiment Class of News HeadlinesSection 11: TF-IDFSection 12: WordVecSection 13: BERTSection 14: BERT Model AdaptationSection 15: Result AnalysisSection 16 (Optional): Python InstallationSection 17: (Optional): Live Trading on IBridgePySection 18: Paper and Live TradingSection 19: Capstone ProjectSection 20: Course SummaryABOUT AUTHORDr. Terry BenzschawelDr. Terry Benzschawel is the founder and Principal at Benzschawel Scientific, LLC. Before that, Terry had worked with Citigroup’s Institutional Clients Business, as a Managing Director, heading the Quantitative Credit Trading group. In Citi’s Fixed Income Strategy department, Terry has worked as a credit strategist with a focus on client-oriented solutions across all credit markets. Before that, he had worked in Chase Manhattan and Citi to build algorithms to predict corporate bankruptcy and to detect credit fraud on card transactions. He has authored two books on Credit Modeling.Sale Page: https://quantra.quantinsti.com/course/natural-language-processing-tradingArchive: https://archive.ph/wip/klXGcDelivery Method– After your purchase, you’ll see a View your orders link which goes to the Downloads page. Here, you can download all the files associated with your order.– Downloads are available once your payment is confirmed, we’ll also send you a download notification email separate from any transaction notification emails you receive from esy[GB].– Since it is a digital copy, our suggestion is to download and save it to your hard drive. In case the link is broken for any reason, please contact us and we will resend the new download link.– If you cannot find the download link, please don’t worry about that. We will update and notify you as soon as possible at 8:00 AM – 8:00 PM (UTC+8).Thank You For Shopping With Us!