Build and backtest your algorithmic trading strategies to gain a true advantage in the market Key FeaturesGet quality insights from market data, stock analysis, and create your own data visualisationsLearn how to navigate the different features in Python's data analysis librariesStart systematically approaching quantitative research and strategy generation/backtesting in algorithmic tradingBook Description Creating an effective system to automate your trading can help you achieve two of every trader's key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage. This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. As you progress, you'll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet. By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets. What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for If you're a financial trader or a data analyst who wants a hands-on introduction to designing algorithmic trading strategies, then this book is for you. You don't have to be a fully-fledged programmer to dive into this book, but knowing how to use Python's core libraries and a solid grasp on statistics will help you get the most out of this book.
Build and backtest your algorithmic trading strategies to gain a true advantage in the market Key FeaturesGet quality insights from market data, stock analysis, and create your own data visualisationsLearn how to navigate the different features in Python's data analysis librariesStart systematically approaching quantitative research and strategy generation/backtesting in algorithmic tradingBook Description Creating an effective system to automate your trading can help you achieve two of every trader's key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage. This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. As you progress, you'll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet. By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets. What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for If you're a financial trader or a data analyst who wants a hands-on introduction to designing algorithmic trading strategies, then this book is for you. You don't have to be a fully-fledged programmer to dive into this book, but knowing how to use Python's core libraries and a solid grasp on statistics will help you get the most out of this book.
It is essential that differently oriented specialists and students involved in image processing have a firm grasp of the necessary concepts and principles. A single-source reference that can provide this foundation, as well as a thorough explanation of the techniques involved, particularly those found in medical image processing, would be an
Self-Similarities and Invariant Densities for Model Sets.- Model Sets and Self-Similarities.- Averaging Operators and Invariant Densities.- Further Remarks.- Outlook.- References.- Symmetry Operations in the Brain: Music and Reasoning.- Trion Model.- Music Enhances Spatial-Temporal Reasoning.- References.- Lie Modules of Bounded Multiplicities.- Simple L Modules with Finite-Dimensional Weight Spaces.- Completely Pointed Modules.- Completely Pointed Modules Tensored with Finite-Dimensional Modules.- References.- Moving Frames and Coframes.- References.- The Fibonacci-Deformed Harmonic Oscillator.- About Strictly Increasing Sequences of Positive Numbers.- Quantum Algebra Associated with the Spectrum ? = xn.- The ?-Natural Spectrum.- The Fibonacci Deformation of Weyl Algebra.- Coherent States and Some Special Functions.- References.- Continuous and Discrete Linearizable Systems: The Riccati Saga.- Brief Review of the Continuous Gambier Equation.- Discrete Analog of the Gambier Equation, Revisited.- Discrete Projective and Matrix Riccati Equations.- Discrete Conformai Riccati Equations.- Conclusions and Outlook.- References.- Superintegrability on Two-Dimensional Complex Euclidean Space.- Potential V5.- Potential V6.- Potential V7.- References.- Hydrodynamic Systems and the Higher-Dimensional Laplace Transformations of Cartan Submanifolds.- Hydrodynamic Systems Rich in Conservation Laws.- Applications of the Higher-Dimensional Laplace Transformation to Hydrodynamic Systems that are Rich in Conservation Laws.- References.- Branching Rules and Weight Multiplicities for Simple and Affine Lie Algebras.- Simple and Affine Lie Algebras.- Branching Rules for Simple Lie Algebras.- Young Diagrams and Branching Rules.- Weight Multiplicities of Simple Lie Algebras.- Young Tableaux and Weight Multiplicities.- Branching Rule Multiplicities for the Restriction from Affine to Simple Lie Algebras.- Branching Rules Derived from Characters.- Weight Multiplicities of Affine Lie Algebras.- References.- Conditions for the Existence of Higher Symmetries and Nonlinear Evolutionary Equations on the Lattice.- Construction of the Classifying Conditions.- The Toda Lattice Class.- References.- Complete Description of the Voronoï Cell of the Lie Algebra An Weight Lattice. On the Bounds for the Number of d-Faces of the n-Dimensional Voronoï Cells.- The Expression of the Bounds Nd(n) Obtained by Voronoï.- Detailed Description of the Voronoï Cells of the A(TM) Lattices.- The New Explicit Expression of Bounds Nd(n).- Expression of Nd(n) as Multiple of a Stirling Number of Second Kind.- Final Remarks.- References.- The Relativistic Oscillator and the Mass Spectra of Baryons.- The System of Three Relativistic Scalar Particles with Oscillator Interactions.- An Approach to the Spinorial Relativistic Three-Body System.- References.- Seiberg-Witten Theory Without Tears.- N = 2 Supersymmetry.- N = 2 Superaction.- Textbook Properties.- Spontaneous Symmetry-Breaking.- Holomorphy and Duality.- Perturbative and Nonperturbative F (A).- Preliminaries.- Fuchsian Maps.- The Schwarzian Derivatives.- SW Choice.- Correctness.- Uniqueness.- References.- Bargmann Representation for Some Deformed Harmonic Oscillators with Non-Fock Representation.- Representations.- Toward a Bargmann Representation.- The "q-Oscillator".- Generalization of the Previous Example.- Deformed Algebra Associated to a Given Weight function.- Bargmann Representations Corresponding to Different ?.- The Case of an Annulus.- Conclusion.- References.- The Vector-Coherent-State Inducing Construction for Clebsch-Gordan Coefficients.- Induced Representations of su(4).- SU(4) Clebsch-Gordan Coefficients.- Summary.- References.- Highest-Weight Representations of Borcherds Algebras.- Borcherds Algebras.- Cartan Subalgebra of an Affine Kac-Moody Algebra.- Adding Energy and Number Operators to the Cartan Subalgebra.- Conclusions.- References.- Graded Contractions of Lie Algebras of Physical Interest.- Notion of Graded
The four-volume set comprising LNCS volumes 3021/3022/3023/3024 constitutes the refereed proceedings of the 8th European Conference on Computer Vision, ECCV 2004, held in Prague, Czech Republic, in May 2004. The 190 revised papers presented were carefully reviewed and selected from a total of 555 papers submitted. The four books span the entire range of current issues in computer vision. The papers are organized in topical sections on tracking; feature-based object detection and recognition; geometry; texture; learning and recognition; information-based image processing; scale space, flow, and restoration; 2D shape detection and recognition; and 3D shape representation and reconstruction.
This book presents methods of solving problems in three areas of elementary combinatorial mathematics: classical combinatorics, combinatorial arithmetic, and combinatorial geometry. Brief theoretical discussions are immediately followed by carefully worked-out examples of increasing degrees of difficulty and by exercises that range from routine to rather challenging. The book features approximately 310 examples and 650 exercises.
A detailed presentation is offered of the fundamental equations in solid mechanics focusing on constitutive equations including quasibrittle materials. Details are provided on individual numerical algorithms, with a heavier emphasis placed on the understanding of basic principles.
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