We believe that the IPO pricing context offers greater value than the more common stock price prediction studied in the literature, for two compelling reasons. First, the IPO context is less susceptible to self-fulfilling prophecies, making it a robust setting for assessing causality. This implies...
(0,1,1)to make predictions about the stock price during the pandemic,then we train the Prophet model using the stock price before January 1,2021,and predict the stock price after January 1,2021,to present.We also make a comparison of the prediction graphs of the two models.The empirical ...
A Deep Learning-based Long Short-Term Memory Technique for Google Stock Price Prediction Stock market is also an important economic factor today- the purchasing curve and its variations strongly influence the market and a significant portion of... Arshleen Kaur,Vinay Kukreja,Deepak Upadhyay,... ...
The impact of investor sentiment on the German stock market This paper develops a broad-based sentiment indicator for Germany and investigates whether investor sentiment can explain stock returns on the German stock... Philipp,Finter,Alexandra,... - 《Zeitschrift Für Betriebswirtschaft》 被引量: 66...
may face a shortfall in earnings due to their employee stock options programs. Expanding its workforce, Google has given out 498,000 performance-based stock units, which represents an expenditure of $8.9 million. The company plans to give out around a million of these stock units per year. ...
microsoft tensorflow machine-learning-algorithms googlecollab stockprice-prediction Updated Aug 18, 2024 Jupyter Notebook sanjanahombal / Study-on-Sentiment-Analysis Star 0 Code Issues Pull requests This project explores the optimal combination of Bag-of-Words and TF-IDF vectorization with Naive...
Stock index forecasting by hidden Markov models with trends recognition CUI Xiaoning, W Shang, F Jiang, W Shouyang 2019 IEEE International Conference on Big Data (Big Data), 5292-5297 102019 Reservation price reporting mechanisms for online negotiations ...
Multi-step-ahead time series prediction using multiple-output support vector regression Y Bao, T Xiong, Z Hu Neurocomputing 129, 482-493 243 2013 Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting T Xiong, Y Bao, Z Hu Knowledge-...
A small observation here: “Glitch” seems to be doing a lot of work in this headline: “Berkshire Stock Glitch at NYSE Cost Interactive Brokers $48 Million.” Interactive Brokers is also in the news because they are planning to launch a binary prediction market in early July with economy ...
2021, Journal of Economic Behavior and Organization Show abstract Fear of the coronavirus and the stock markets 2020, Finance Research Letters Citation Excerpt : The observation that Google searches for coronavirus are correlated with price variation is perhaps unsurprising. The research linking stock ma...