1# Library to Find Best eBook for Read
Author : Donald A. Bradley
Release : 1948
Genre : Astrology
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Stock Market Prediction by : Donald A. Bradley
Download or read book Stock Market Prediction written by Donald A. Bradley. This book was released on 1948. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dr.N.Srinivasan
Release :
Genre : Business & Economics
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Stock price Prediction a referential approach on how to predict the stock price using simple time series... by : Dr.N.Srinivasan
Download or read book Stock price Prediction a referential approach on how to predict the stock price using simple time series... written by Dr.N.Srinivasan. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt: This book is about the various techniques involved in the stock price prediction. Even the people who are new to this book, after completion they can do stock trading individually with more profit.
Author : Azhar Ul Haque Sario
Release : 2023-07-13
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Stock Price Predictions by : Azhar Ul Haque Sario
Download or read book Stock Price Predictions written by Azhar Ul Haque Sario. This book was released on 2023-07-13. Available in PDF, EPUB and Kindle. Book excerpt: "Stock Price Predictions: An Introduction to Probabilistic Models" is a comprehensive guide that delves into the intricate world of stock market prediction models. This book is a treasure trove of knowledge for both novice and seasoned investors, providing detailed explanations of traditional and modern approaches used to predict stock prices. In the first part of the book, "Traditional Approaches, " the author examines the most commonly used techniques for estimating share prices, such as Fundamental Analysis, Technical Analysis, and Quantitative Analysis. It also delves into more specific methods like Sentiment Analysis, Time Series Analysis, and Machine Learning Algorithms, among others. Each method is meticulously explained, providing readers with a sound understanding of the strengths and limitations of each approach. The second part, "Understanding the World of Probability-Based Models," introduces readers to the realm of probability models, explaining their role and different types. It covers a wide range of models like ARIMA, GARCH, VAR, MGARCH, Stochastic Volatility Models, and many more. Each model is discussed in depth, with explanations of how they can be used to estimate future share prices. This section serves as an excellent resource for those seeking to expand their knowledge and skills in using probability-based models for stock price prediction. The final section, "Instances of Successful Forecasts Using Probability-Based Models," provides real-world examples of successful forecasts using these models. It includes well-known models like the Black-Scholes Model, Monte Carlo Simulations, Brownian Motion Model, ARIMA, and GARCH Model. The book concludes with a discussion on the success of more contemporary models like LSTM and Facebook's Prophet.
Author : Paul Barry
Release : 2016-11-21
Genre : Computers
Kind : eBook
Book Rating : 493/5 ( reviews)
Book Synopsis Head First Python by : Paul Barry
Download or read book Head First Python written by Paul Barry. This book was released on 2016-11-21. Available in PDF, EPUB and Kindle. Book excerpt: Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.
Author : Joish Bosco
Release : 2018-09-18
Genre : Computers
Kind : eBook
Book Rating : 456/5 ( reviews)
Book Synopsis Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network by : Joish Bosco
Download or read book Stock Market Prediction and Efficiency Analysis using Recurrent Neural Network written by Joish Bosco. This book was released on 2018-09-18. Available in PDF, EPUB and Kindle. Book excerpt: Project Report from the year 2018 in the subject Computer Science - Technical Computer Science, , course: Computer Science, language: English, abstract: Modeling and Forecasting of the financial market have been an attractive topic to scholars and researchers from various academic fields. The financial market is an abstract concept where financial commodities such as stocks, bonds, and precious metals transactions happen between buyers and sellers. In the present scenario of the financial market world, especially in the stock market, forecasting the trend or the price of stocks using machine learning techniques and artificial neural networks are the most attractive issue to be investigated. As Giles explained, financial forecasting is an instance of signal processing problem which is difficult because of high noise, small sample size, non-stationary, and non-linearity. The noisy characteristics mean the incomplete information gap between past stock trading price and volume with a future price. The stock market is sensitive with the political and macroeconomic environment. However, these two kinds of information are too complex and unstable to gather. The above information that cannot be included in features are considered as noise. The sample size of financial data is determined by real-world transaction records. On one hand, a larger sample size refers a longer period of transaction records; on the other hand, large sample size increases the uncertainty of financial environment during the 2 sample period. In this project, we use stock data instead of daily data in order to reduce the probability of uncertain noise, and relatively increase the sample size within a certain period of time. By non-stationarity, one means that the distribution of stock data is various during time changing. Non-linearity implies that feature correlation of different individual stocks is various. Efficient Market Hypothesis was developed by Burton G. Malkiel in 1991.
