Search results for "Python Arithmetic"
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Python for Algorithmic Trading
Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading.You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field.Set up a proper Python environment for algorithmic tradingLearn how to retrieve financial data from public and proprietary data sourcesExplore vectorization for financial analytics with NumPy and pandasMaster vectorized backtesting of different algorithmic trading strategiesGenerate market predictions by using machine learning and deep learningTackle real-time processing of streaming data with socket programming toolsImplement automated algorithmic trading strategies with the OANDA and FXCM trading platforms
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Algorithmic Decision Making with Python Resources
This book describes Python3 programming resources for implementing decision aiding algorithms in the context of a bipolar-valued outranking approach. These computing resources, made available under the name Digraph3, are useful in the field of Algorithmic Decision Theory and more specifically in outranking-based Multiple-Criteria Decision Aiding (MCDA).The first part of the book presents a set of tutorials introducing the Digraph3 collection of Python3 modules and its main objects, such as bipolar-valued digraphs and outranking digraphs. In eight methodological chapters, the second part illustrates multiple-criteria evaluation models and decision algorithms. These chapters are largely problem-oriented and demonstrate how to edit a new multiple-criteria performance tableau, how to build a best choice recommendation, how to compute the winner of an election and how to make rankings or ratings using incommensurable criteria. The book’s third part presents three real-world decision case studies, while the fourth part addresses more advanced topics, such as computing ordinal correlations between bipolar-valued outranking digraphs, computing kernels in bipolar-valued digraphs, testing for confidence or stability of outranking statements when facing uncertain or solely ordinal criteria significance weights, and tempering plurality tyranny effects in social choice problems. The fifth and last part is more specifically focused on working with undirected graphs, tree graphs and forests. The closing chapter explores comparability, split, interval and permutation graphs.The book is primarily intended for graduate students in management sciences, computational statistics and operations research. The chapters presenting algorithms for ranking multicriteria performance records will be of computational interest for designers of web recommender systems. Similarly, the relative and absolute quantile-rating algorithms, discussed and illustrated in several chapters, will be of practical interest to public and private performance auditors.
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Arithmetic and Algebraic Circuits
This book presents a complete and accurate study of arithmetic and algebraic circuits. The first part offers a review of all important basic concepts: it describes simple circuits for the implementation of some basic arithmetic operations; it introduces theoretical basis for residue number systems; and describes some fundamental circuits for implementing the main modular operations that will be used in the text. Moreover, the book discusses floating-point representation of real numbers and the IEEE 754 standard. The second and core part of the book offers a deep study of arithmetic circuits and specific algorithms for their implementation. It covers the CORDIC algorithm, and optimized arithmetic circuits recently developed by the authors for adders and subtractors, as well as multipliers, dividers and special functions. It describes the implementation of basic algebraic circuits, such as LFSRs and cellular automata. Finally, it offers a complete study of Galois fields, showing some exemplary applications and discussing the advantages in comparison to other methods. This dense, self-contained text provides students, researchers and engineers, with extensive knowledge on and a deep understanding of arithmetic and algebraic circuits and their implementation.
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Python for Asset Management
The asset management industry is undergoing a paradigm shift toward automation, transparency, and data-driven decision-making. Traditional tools (Excel, Bloomberg) are being replaced by programmable, scalable solutions. Yet, most finance professionals lack accessible, practical training in applying Python to real portfolio problems.Python For Asset Management fills that gap. The book empowers non-programmers—portfolio managers, risk analysts, and students—to implement advanced models themselves. It responds to the growing demand for quantitative literacy in finance, especially in sustainable investing and smart beta strategies, areas of active research for both of the authors.Features31 hands-on Python exercises with real data and executable code.Complete GitHub repository (MIT License) with all scripts, data pipelines, and results.Step-by-step implementation of VaR (historical, parametric, Monte Carlo), bond immunization, and factor models.Real-world decision tools — e.g., build a bullet/barbell/ladder bond portfolio, run Brinson-Fachler attribution, or backtest smart beta vs. index.Immediate applicability — every exercise produces a deliverable (e.g., optimal weights, risk report, attribution table) ready for client meetings.Focus on practical asset management workflows, not just theory.
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Joseph J's Basic Arithmetic
Joseph J's Basic Arithmetic book focuses solely on addition, subtraction, multiplication, and division. It offers a convenient way to practice 1,600 questions. To maintain simplicity, the number operations are in whole numbers only.
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Python Basics
This book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in industry. The book has been divided into four sections. The first section deals with the language fundamentals, primarily the procedural part of the language, the second introduces the object-oriented paradigms, the third section deals with data structures, and the last is devoted to advanced topics like handling multi-dimensional arrays using NumPy and visualization using Matplotlib. Regular expressions and multi-threading have been introduced in the appendices.Features:Includes sections dedicated to data structures Offers in-depth treatment of topics such as classes, inheritance, BST, andNumPyIntroduces topics like Matplotlib and PILContains exercises for practice and a review of essential programming concepts
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