Hands On Deep Learning For Finance

Hands On Deep Learning for Finance PDF
Author: Luigi Troiano
Publisher: Packt Publishing Ltd
ISBN: 1789615348
Size: 54.29 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 442
View: 1323

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Hands On Deep Learning For Finance

by Luigi Troiano, Hands On Deep Learning For Finance Books available in PDF, EPUB, Mobi Format. Download Hands On Deep Learning For Finance books, Take your quantitative strategies to the next level by exploring nine examples that make use of cutting-edge deep learning technologies, including CNNs, LSTMs, GANs, reinforcement learning, and CapsNets Key Features Implement deep learning techniques and algorithms to build financial models Apply modern AI techniques in quantitative market modeling and investment decision making Leverage Python libraries for rapid development and prototyping Book Description Quantitative methods are the vanguard of the investment management industry. This book shows how to enhance trading strategies and investments in financial markets using deep learning algorithms. This book is an excellent reference to understand how deep learning models can be leveraged to capture insights from financial data. You will implement deep learning models using Python libraries such as TensorFlow and Keras. You will learn various deep learning algorithms to build models for understanding financial market dynamics and exploiting them in a systematic manner. This book takes a pragmatic approach to address various aspects of asset management. The information content in non-structured data like news flow is crystalized using BLSTM. Autoencoders for efficient index replication is discussed in detail. You will use CNN to develop a trading signal with simple technical indicators, and improvements offered by more complex techniques such as CapsNets. Volatility is given due emphasis by demonstrating the superiority of forecasts employing LSTM, and Monte Carlo simulations using GAN for value at risk computations. These are then brought together by implementing deep reinforcement learning for automated trading. This book will serve as a continuing reference for implementing deep learning models to build investment strategies. What you will learn Implement quantitative financial models using the various building blocks of a deep neural network Build, train, and optimize deep networks from scratch Use LSTMs to process data sequences such as time series and news feeds Implement convolutional neural networks (CNNs), CapsNets, and other models to create trading strategies Adapt popular neural networks for pattern recognition in finance using transfer learning Automate investment decisions by using reinforcement learning Discover how a risk model can be constructed using D-GAN Who this book is for If you're a finance or investment professional who wants to lead the development of quantitative strategies, this book is for you. With this practical guide, you'll be able to use deep learning methods for building financial models and incorporating them in your investment process. Anyone who wants to enter the fascinating domain of quantitative finance using the power of deep learning algorithms and techniques will also find this book useful. Basic knowledge of machine learning and Python programming is required.


Ai And Financial Markets

AI and Financial Markets PDF
Author: Shigeyuki Hamori
Publisher: MDPI
ISBN: 3039362240
Size: 17.43 MB
Format: PDF, Kindle
Category : Business & Economics
Languages : en
Pages : 230
View: 1705

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Ai And Financial Markets

by Shigeyuki Hamori, Ai And Financial Markets Books available in PDF, EPUB, Mobi Format. Download Ai And Financial Markets books, Artificial intelligence (AI) is regarded as the science and technology for producing an intelligent machine, particularly, an intelligent computer program. Machine learning is an approach to realizing AI comprising a collection of statistical algorithms, of which deep learning is one such example. Due to the rapid development of computer technology, AI has been actively explored for a variety of academic and practical purposes in the context of financial markets. This book focuses on the broad topic of “AI and Financial Markets”, and includes novel research associated with this topic. The book includes contributions on the application of machine learning, agent-based artificial market simulation, and other related skills to the analysis of various aspects of financial markets.


Machine Learning In Finance

Machine Learning in Finance PDF
Author: Bob Mather
Publisher:
ISBN: 9781922300058
Size: 29.83 MB
Format: PDF, Docs
Category : Business & Economics
Languages : en
Pages : 90
View: 2119

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Machine Learning In Finance

by Bob Mather, Machine Learning In Finance Books available in PDF, EPUB, Mobi Format. Download Machine Learning In Finance books, Are you a machine learning enthusiast looking for a practical day to day application? Or are you just trying to incorporate machine learning software in your trading decisions? This book is your answer. While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day trading scenario, or to determine the long term value of a stock; financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine learning algorithms like clustering and regression? When would be the best time to use these? While machine learning and finance have generally been seen as separate entities, this book looks at several applications of machine learning in the financial world. Whether it is predicting the best time to buy a stock in a day trading scenario, or to determine the long term value of a stock; financial ratios and common sense have always been used as reliable indicators. But how do these compare about advanced machine learning algorithms like clustering and regression? When would be the best time to use these? What's Included In This Book: What is Financial Machine Learning Developing a Trading Strategy for Stocks Machine Learning to Determine Current Value of Stocks Optimal Time to Buy Stocks Machine Learning Algorithm to Predict When to Sell a Stock Determine Value of a Penny Stock Trading Automation Software Conclusion


Machine Learning For Financial Engineering

Machine Learning for Financial Engineering PDF
Author: László Györfi
Publisher: World Scientific
ISBN: 1908977663
Size: 35.55 MB
Format: PDF, ePub, Docs
Category : Business & Economics
Languages : en
Pages : 260
View: 7075

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Machine Learning For Financial Engineering

by László Györfi, Machine Learning For Financial Engineering Books available in PDF, EPUB, Mobi Format. Download Machine Learning For Financial Engineering books, This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. Such sequential investment strategies use information collected from the market's past and determine, at the beginning of a trading period, a portfolio; that is, a way to invest the currently available capital among the assets that are available for purchase or investment. The aim is to produce a self-contained text intended for a wide audience, including researchers and graduate students in computer science, finance, statistics, mathematics, and engineering. Contents:On the History of the Growth-Optimal Portfolio (M M Christensen)Empirical Log-Optimal Portfolio Selections: A Survey (L Györfi, Gy Ottucsák & A Urbán)Log-Optimal Portfolio-Selection Strategies with Proportional Transaction Costs (L Györfi & H Walk)Growth-Optimal Portfolio Selection with Short Selling and Leverage (M Horváth & A Urbán)Nonparametric Sequential Prediction of Stationary Time Series (L Györfi & G Ottuscák)Empirical Pricing American Put Options (L Györfi & A Telcs) Readership: Researchers, academics and graduate students in artificial intelligence/machine learning, and mathematical finance/quantitative finance. Keywords:Log-Optimal Portfolio;Growth-Optimal Portfolio;Sequential Investment Strategies for Financial MarketsKey Features:Covers machine learning algorithms for the aggregation of elementary investment strategiesHighlights multi-period and multi-asset tradingFocuses on nonparametric estimation of the underlying distributions in the market process


Machine Learning And Ai In Finance

Machine Learning and AI in Finance PDF
Author: German Creamer
Publisher: Routledge
ISBN: 1000372049
Size: 19.24 MB
Format: PDF, Kindle
Category : Business & Economics
Languages : en
Pages : 120
View: 6260

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Machine Learning And Ai In Finance

by German Creamer, Machine Learning And Ai In Finance Books available in PDF, EPUB, Mobi Format. Download Machine Learning And Ai In Finance books, The significant amount of information available in any field requires a systematic and analytical approach to select the most critical information and anticipate major events. During the last decade, the world has witnessed a rapid expansion of applications of artificial intelligence (AI) and machine learning (ML) algorithms to an increasingly broad range of financial markets and problems. Machine learning and AI algorithms facilitate this process understanding, modelling and forecasting the behaviour of the most relevant financial variables. The main contribution of this book is the presentation of new theoretical and applied AI perspectives to find solutions to unsolved finance questions. This volume proposes an optimal model for the volatility smile, for modelling high-frequency liquidity demand and supply and for the simulation of market microstructure features. Other new AI developments explored in this book includes building a universal model for a large number of stocks, developing predictive models based on the average price of the crowd, forecasting the stock price using the attention mechanism in a neural network, clustering multivariate time series into different market states, proposing a multivariate distance nonlinear causality test and filtering out false investment strategies with an unsupervised learning algorithm. Machine Learning and AI in Finance explores the most recent advances in the application of innovative machine learning and artificial intelligence models to predict financial time series, to simulate the structure of the financial markets, to explore nonlinear causality models, to test investment strategies and to price financial options. The chapters in this book were originally published as a special issue of the Quantitative Finance journal.


Artificial Intelligence In Financial Services And Banking Industry

Artificial Intelligence in Financial Services and Banking Industry PDF
Author: Dr. V.V.L.N. Sastry
Publisher: Idea Publishing
ISBN:
Size: 34.89 MB
Format: PDF, Mobi
Category : Business & Economics
Languages : en
Pages : 87
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Artificial Intelligence In Financial Services And Banking Industry

by Dr. V.V.L.N. Sastry, Artificial Intelligence In Financial Services And Banking Industry Books available in PDF, EPUB, Mobi Format. Download Artificial Intelligence In Financial Services And Banking Industry books, In the last couple of years, the finance and banking sectors have increasingly deployed and implemented Artificial Intelligence (AI) technologies. AI and machine learning are being rapidly adopted for a range of applications for front-end and back end processes to both business and financial management operations. Thus, it is quite significant to consider the financial stability repercussions of such uses. Since AI is relatively new, the data on the usage is largely unavailable, any analysis may be necessarily considered Preliminary1 . Some of the current and potential use cases of AI and machine learning in the finance sector include the following.  Institutions use AI and machine learning methods to optimize scarce capital, back-test models, and analyze the market impact of trading large positions.  Financial institutions and vendors use AI and machine learning techniques to evaluate credit quality for market and price insurance contracts, and to automate client interaction.  Brokers, hedge funds, and other firms are using AI and machine learning to find pointers for higher (and uncorrelated) returns to optimize trading execution.  Private and public sector institutions use these technologies for data quality assessment, surveillance, regulatory compliance, and fraud detection. This book seeks to map the use of AI in current state of affairs in the banking and financial sector. By doing so, it explores:  The present uses of AI in banking and finance and its narrative across the globe.


Machine Learning And Metaheuristics Algorithms And Applications

Machine Learning and Metaheuristics Algorithms  and Applications PDF
Author: Sabu M. Thampi
Publisher: Springer Nature
ISBN: 9811543011
Size: 79.86 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 265
View: 3800

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Machine Learning And Metaheuristics Algorithms And Applications

by Sabu M. Thampi, Machine Learning And Metaheuristics Algorithms And Applications Books available in PDF, EPUB, Mobi Format. Download Machine Learning And Metaheuristics Algorithms And Applications books, This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, held in Trivandrum, India, in December 2019. The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.


Advances In Financial Machine Learning

Advances in Financial Machine Learning PDF
Author: Marcos Lopez de Prado
Publisher: John Wiley & Sons
ISBN: 1119482089
Size: 27.21 MB
Format: PDF, ePub, Mobi
Category : Business & Economics
Languages : en
Pages : 400
View: 6840

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Advances In Financial Machine Learning

by Marcos Lopez de Prado, Advances In Financial Machine Learning Books available in PDF, EPUB, Mobi Format. Download Advances In Financial Machine Learning books, Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.


Big Data And Machine Learning In Quantitative Investment

Big Data and Machine Learning in Quantitative Investment PDF
Author: Tony Guida
Publisher: John Wiley & Sons
ISBN: 1119522196
Size: 57.53 MB
Format: PDF
Category : Business & Economics
Languages : en
Pages : 296
View: 1041

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Big Data And Machine Learning In Quantitative Investment

by Tony Guida, Big Data And Machine Learning In Quantitative Investment Books available in PDF, EPUB, Mobi Format. Download Big Data And Machine Learning In Quantitative Investment books, Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. • Gain a solid reason to use machine learning • Frame your question using financial markets laws • Know your data • Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.