Danny munrow james preston (84 resultados)

Paperback. Condición: New.

Paperback. Condición: New.

Paperback. Condición: New.

Paperback. Condición: New.

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingAlgorithmic Trading Recipes in Python delivers practical, ready-to-implement code examples for developing systematic trading strategies across major financial markets.This book provides a collection of Python recipes covering core techniques used in algorithmic trading. Readers will find working code examples for data handling, strategy implementation, backtesting, and execution workflows tailored to stocks, forex, and cryptocurrency markets.Whether you are an intermediate Python developer exploring quantitative trading or a trader looking to automate your approaches, these recipes offer concrete starting points and modular building blocks.What's Inside: - Reproducible Python code examples for common trading tasks- Strategy frameworks for trend following, mean reversion, momentum, and more- Data acquisition, cleaning, and feature engineering techniques- Backtesting and performance evaluation methods- Market-specific considerations for equities, forex, and cryptoImportant Note: Trading involves substantial risk of loss and is not suitable for everyone. The strategies and code in this book are for educational and illustrative purposes only. Past performance does not guarantee future results. Readers should conduct their own research and testing before applying any trading approach with real capital.Ideal for developers, quantitative enthusiasts, and traders interested in building and testing systematic strategies in Python.…

Condición: New. Print on Demand.

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingStochastic Calculus for Modern Quantitative Finance and Algorithmic Trading offers a clear, practical, and rigorous introduction to stochastic calculus tailored specifically for quantitative finance professionals and algorithmic traders.This book bridges the gap between theoretical stochastic processes and real-world implementation in modern financial markets. Readers will learn how to apply core concepts, such as Itô's lemma, stochastic differential equations, martingales, and Brownian motion, directly to quantitative modeling and trading strategy development.What You'll Find Inside: - Python Implementation: Complete, ready-to-use code examples using Python (NumPy, SciPy, pandas, and QuantLib) that demonstrate how to simulate stochastic processes, price derivatives, and build trading models.- Modern Models: In-depth coverage of key models used in today's quantitative finance, including the Black-Scholes framework extensions, local volatility, stochastic volatility (Heston), jump-diffusion, and more.- Real-World Applications: Practical case studies on algorithmic trading strategies, risk management, option pricing, portfolio optimization, and Monte Carlo methods applied to live market data.Written with both clarity and technical depth, this book is designed for readers who want to move beyond abstract theory and develop production-grade skills in quantitative finance and algorithmic trading.Whether you are a quantitative analyst, aspiring quant developer, algorithmic trader, or finance graduate student looking to strengthen your technical toolkit, this book provides the mathematical foundation and practical coding guidance needed to succeed in today's data-driven financial markets.No prior stochastic calculus experience is assumed, but familiarity with basic probability, calculus, and Python programming is recommended.…

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingRetail traders obsess over indicators, models, and backtests, but the traders who survive and scale are the ones who master execution. In modern markets, your fill quality, order logic, latency, and routing decisions matter as much as your strategy itself. Execution Intelligence is the first book that teaches retail algo traders how to build smart, adaptive order engines that actually work in live trading environments.James Preston breaks down the execution techniques used by prop firms, systematic funds, and high-efficiency quant desks, and translates them into powerful, Python-based frameworks that retail traders can use today.This book doesn't teach signals.It teaches how to turn signals into money.Inside, You'll Learn How To: - Decode market microstructureLiquidity, order books, slippage mechanics, spreads, volatility expansion, and how real markets 'behave' underneath the chart.- Build adaptive order enginesExecution logic that adjusts dynamically to volatility, liquidity conditions, time of day, and structural order flow changes.- Design smarter order typesFrom simple market/limit workflows to pegged, discretionary, post-only, smart-limit, and hybrid order logic.- Minimize slippage & execution dragHow to reduce hidden costs that destroy retail performance and distort backtest expectations.- Develop real-time execution intelligenceOrder-state management, midpoint logic, partial fills, re-routing, and dynamic sizing based on execution quality.- Integrate execution into your trading systemsHow to connect signal models to an execution layer that respects risk, latency, and state conditions.- Build a full Python execution stackIncluding brokers, exchanges, APIs, wrappers, retry systems, error handling, and live monitoring.Who This Book Is ForThis book is built for: - Retail algo traders- System designers- Prop-firm traders- Quantitative developers- Anyone serious about closing the gap between backtests and live resultsIf you've ever built a strategy that looked great in testing but fell apart in the real market, this book explains exactly why, and gives you the tools to fix it.Execution is the silent engine of every profitable system.This book teaches you how to build it.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingQuantitative Risk Management with Python is a practical guide to measuring, modeling, and analyzing financial risk using modern Python workflows.Designed for analysts, traders, students, and quantitative finance practitioners, this book explains how core risk measures are built, interpreted, and applied across real-world portfolios. Readers will learn how to calculate Value at Risk, estimate Expected Shortfall, run portfolio stress tests, analyze return distributions, and evaluate risk under changing market conditions.The book emphasizes clear implementation, practical interpretation, and reusable Python techniques. Instead of treating risk metrics as isolated formulas, it shows how they fit into a broader risk management workflow involving data preparation, volatility estimation, scenario analysis, backtesting, and portfolio-level reporting.Inside, readers will explore: Value at Risk using historical, parametric, and simulation-based methodsExpected Shortfall and downside risk measurementStress testing and scenario analysis for portfolio exposuresVolatility, correlation, and distributional assumptionsBacktesting risk models and interpreting model limitationsPython workflows for repeatable financial risk analysisThis book is written for readers who want a structured, applied approach to quantitative risk management without unnecessary theory or promotional trading claims. It provides the tools and context needed to understand risk models, implement them in Python, and use them responsibly in financial analysis.…

Taschenbuch. Condición: Neu. Neuware.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingVolatility is no longer a side-note in quant trading. It is the engine. Volatility Trading Systems with Python takes you inside the architecture of real, deployable vol-driven strategies, from building arbitrage-free surfaces to constructing gamma-scalping engines, dynamic hedging models, and automated risk responses. This is a hands-on, Python-first guide designed for traders, quants, and system designers who want to master the mechanics of volatility as a tradeable asset.Inside, you'll build full pipelines: implied vol surface construction, intraday vol metrics, vega-neutral and gamma-positive systems, automated hedge adjusters, microstructure-aware risk triggers, and real-market backtests. Every chapter focuses on production-ready frameworks that translate directly into deployable edge, giving you a complete view of volatility as both a model and a profit-center.If you trade options, run quant strategies, or design automated systems, this book becomes a cornerstone - the bridge between volatility theory and live execution.…

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingNonlinear Risk Systems is a practitioner's field manual for the risks that do not scale nicely. The ones that hide in the tails, compound through feedback loops, and only reveal themselves when your portfolio, your leverage, and the market's microstructure interact in the wrong sequence. This book explains why 'normal' risk models break precisely when you need them most, and how to think in convexity, regime shifts, and stress propagation instead of smooth vol and stable correlations.You will learn how tail events emerge from seemingly reasonable assumptions, how path dependency turns small differences in timing into radically different outcomes, and how convex exposures (options, leverage, stop mechanics, liquidity constraints) can either protect you or accelerate losses. Using real-world trading system logic rather than ivory-tower math, James Preston shows how stress travels across instruments, venues, and constraints, creating cascades: margin calls, liquidity gaps, execution slippage, correlation spikes, and forced de-risking that feeds back into price impact.Inside, you'll build an intuition for nonlinear risk surfaces, identify hidden convexities, map dependency networks, and design stress tests that actually break systems in simulation before markets break them in production. You'll also learn how to architect portfolios and execution workflows for robustness: volatility-aware sizing, convex hedging frameworks, kill-switch logic, drawdown governors, and scenario libraries that reflect discontinuities, gaps, and clustered volatility.If you trade systematic strategies, options, leveraged portfolios, or multi-asset books, Nonlinear Risk Systems gives you the mental models and tools to stop treating tails as rounding errors and start designing trading systems that survive the regimes that end careers.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingNavigate the regulatory and operational complexities of AI-driven underwriting.As algorithmic models increasingly dictate credit decisions, the regulatory scrutiny on automated underwriting architectures has intensified. Institutions must balance the efficiency of machine learning with the strict compliance requirements of model risk management.AI Governance in Credit Scoring provides a structured, technical framework for aligning automated lending models with rigorous regulatory standards, including SR 11-7 guidelines. Designed for risk managers, systems architects, and compliance officers, this text breaks down the mechanics of auditing complex models for fairness, stability, and explainability without sacrificing performance.Core topics include: - Model Risk Management: Frameworks for testing, validating, and monitoring algorithmic scoring systems.- Regulatory Alignment: Translating SR 11-7 and current financial regulations into operational parameters for AI architectures.- Explainability in Underwriting: Techniques to ensure automated credit decisions remain transparent and auditable by third parties.- Governance Protocols: Establishing clear oversight and lifecycle management for financial machine learning models.Bridge the gap between quantitative innovation and regulatory compliance to build robust, secure, and auditable credit scoring systems.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingDiscover how to make your trading models transparent, trustworthy, and regulator-ready.In the fast-moving world of quantitative trading, black-box machine learning models present serious challenges. Regulators demand transparency, risk managers require explanations, and successful deployment depends on understanding exactly why a model makes its predictions.This book provides a clear, practical guide to explainable AI and interpretable machine learning techniques specifically for trading applications. You'll learn how to implement and apply key methods such as SHAP, LIME, attention mechanisms, and model auditing to build more transparent quant strategies.What You'll Find Inside: - Core concepts of explainable AI and interpretable models- Step-by-step implementation of SHAP and LIME for financial models- Using attention mechanisms to improve model transparency- Techniques for model auditing and regulatory compliance- Real-world examples from production quant trading environments- Best practices for balancing performance with explainabilityWritten for quantitative traders, data scientists, and financial professionals, this book bridges the gap between advanced machine learning and the practical requirements of trading desks and compliance teams.Whether you're developing new strategies or working to meet evolving regulatory standards, this guide offers the technical foundation needed to create models that are both powerful and explainable.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingMaster the mathematical and computational tools required to price and risk-manage complex derivative structures.Applied Stochastic Calculus for Exotic Options provides a rigorous, application-focused treatment of continuous-time financial mathematics tailored specifically to path-dependent and exotic options. Designed for quantitative analysts, financial engineers, and advanced graduate students, this text bridges the gap between pure probability theory and practical implementation in modern trading environments.Inside, you will find detailed coverage of: - Stochastic Foundations: Ito calculus, change of measure, Girsanov's theorem, and risk-neutral valuation frameworks.- Advanced Diffusion Models: Jump-diffusion processes, Lévy models, and local-stochastic volatility dynamics.- Path-Dependent Structures: Precise valuation methodologies for Asian, barrier, lookback, and cliquet options.- Numerical Methods: PDE solving techniques, finite difference schemes, and Monte Carlo simulation design for path-dependent payoff structures.Whether you are implementing quantitative pricing models in production or deepening your theoretical understanding of financial math, this book delivers the essential mathematical mechanics without sacrificing clarity or rigor.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingAre you ready to move beyond manual trading and build your own algorithmic trading system 'Building Your First Algorithmic Trading System in Python' takes you through the complete process of creating, testing, and deploying your first automated trading system, from initial concept to live market execution.This practical guide is designed for Python developers, aspiring quantitative traders, and programmers with little to no prior experience in algorithmic trading. You will follow a clear, sequential path that mirrors real-world development: - Turning trading ideas into testable strategies- Working with market data and key Python libraries- Building backtesting frameworks to evaluate performance- Implementing risk management and position sizing rules- Moving from simulation to paper trading- Transitioning to live trading with proper execution and monitoringEach chapter builds directly on the previous one, providing working code examples, clear explanations, and practical considerations at every stage. You'll learn how to avoid common pitfalls that trip up new algo traders and how to maintain and improve your system once it's live.Whether you're looking to systematize your existing trading approach or explore algorithmic trading for the first time, this book offers a structured, hands-on foundation in Python.Note: Algorithmic trading involves significant risk of loss. Past performance does not guarantee future results. This book is for educational purposes and does not constitute financial advice.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingBridge the gap between financial theory and quantitative execution with this practical guide to fixed-income modeling using Python.Modern fixed-income markets demand a rigorous approach to valuation, risk management, and derivative pricing. Fixed Income Quantitative Analytics provides a comprehensive framework for software architects, data scientists, and financial engineers looking to build robust, production-ready valuation engines from scratch.This book strips away the mathematical abstraction to deliver clear, step-by-step implementations of core quantitative concepts. By combining advanced financial engineering principles with clean, object-oriented Python code, you will learn how to design flexible architecture capable of handling complex market data and volatile rate environments.Inside, you will explore the core pillars of fixed-income engineering: - Foundations of Analytics: Master the mechanics of bootstrapping yield curves, constructing discount factors, and handling day-count conventions with precision.- Term Structure Modeling: Implement and calibrate industry-standard frameworks, including the Vasicek, Cox-Ingersoll-Ross (CIR), and Hull-White models.- Interest Rate Derivatives: Code pricing engines for vanilla instruments, swaps, swaptions, caps, and floors using both analytical formulas and numerical methods.- Numerical Methods and Simulation: Deploy Monte Carlo simulations and finite difference methods to price path-dependent structures and measure risk sensitivities (the Greeks).Whether you are looking to refine your quantitative development skills or transition traditional financial models into scalable code, this book serves as an engineering blueprint for modern interest rate analytics. …

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingIn the next frontier of quantitative finance, markets are no longer driven solely by human intuition, they are shaped by autonomous, adaptive agents operating at scale. Advanced Market Architectures is your comprehensive guide to designing and deploying multi-agent trading systems that learn, evolve, and compete in real time.Inside, you'll explore: - Multi-Agent Frameworks: How to engineer systems where agents interact, cooperate, and compete to simulate true market dynamics.- Deep Reinforcement Learning: Practical strategies for training agents to adapt to volatility, liquidity shocks, and evolving market structures.- Real-Time Data Integration: Techniques for connecting live feeds, high-frequency data streams, and distributed environments for robust execution.- System Architecture & Optimization: Building scalable infrastructures that balance complexity, performance, and risk management.- Case Studies & Simulations: Walkthroughs that connect theory with practice, showing how advanced agent-based environments can reveal hidden edges.Whether you are a quant trader, AI researcher, or financial engineer, this book equips you with the tools to move beyond single-model trading systems into a world of adaptive, autonomous architectures that mirror the complexity of global markets.If you want to stay ahead of the curve in quant finance, algorithmic trading, and AI-driven market design, this book is your blueprint.…

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingGlobal markets are connected, and the best opportunities are hidden in the cracks between them. Systematic Macro & Cross-Asset AI Strategies is your complete playbook for designing robust, adaptive strategies that trade currencies, interest rates, and commodities with confidence.This book bridges AI, data science, and macro trading, showing you how to engineer models that thrive in complex, interconnected markets. Learn to detect global regime shifts, model cross-asset relationships, and deploy systematic strategies that capture alpha across the macro landscape.Inside, you'll master: - AI-Driven Macro Signals, Extract predictive features from macroeconomic data, yield curves, and geopolitical events.- Cross-Asset Models, Build correlations and co-integration strategies that link FX, rates, and commodities.- Systematic Global Macro Frameworks, Design event-driven, seasonal, and factor-based systems with automated execution.- Volatility and Risk Modeling, Hedge cross-asset exposures with regime-aware position sizing.- Python Implementation, End-to-end code for backtesting, portfolio construction, and live signal generation.Whether you are a quant researcher, portfolio manager, or independent macro trader, this guide will help you create scalable, data-driven strategies that uncover hidden opportunities across asset classes-transforming global complexity into systematic profit.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingBuild robust, production-grade automated trading infrastructure from the ground up using Python.Systematic Python Trading Systems provides a comprehensive, engineering-focused blueprint for designing, testing, and deploying automated trading strategies. Moving beyond simple scripts and isolated backtests, this book focuses on building clean, modular architecture capable of handling the entire systematic life cycle, from high-throughput market data processing to real-time order execution and dynamic risk management.Designed for quantitative developers, systematic traders, and software engineers, this guide delivers clear, actionable implementations without relying on black-box frameworks. You will learn how to write efficient, vectorized code, construct realistic simulation engines, and implement robust risk controls that protect capital in live market environments.What You Will Learn: - System Architecture: Design modular, maintainable Python frameworks for signal generation, portfolio allocation, and order routing.- Vectorized Backtesting: Build high-performance backtesting engines using NumPy and pandas, accounting for slippage, commission models, and execution delays.- Data Pipelines: Ingest, clean, and structure time-series market data for accurate historical analysis and real-time processing.- Execution Controls: Connect to broker APIs, manage live order state, and implement dynamic position-sizing algorithms.- Risk Management: Integrate automated stop-loss mechanisms, drawdown monitors, and system-level kill switches to prevent catastrophic failures.- Performance Optimization: Identify and eliminate bottlenecks in signal computation and data handling to ensure low-latency execution.Equip yourself with the tools and architectural clarity needed to transition your trading ideas from research to execution with confidence.…

Paperback. Condición: New.

Paperback. Condición: New.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingFinancial markets don't fail when the models say they should, they fail when the models say they can't. Risk Engineering for Quant Finance gives you the tools to survive and profit when the unexpected becomes reality.This comprehensive guide goes beyond basic VaR and volatility estimates, showing you how to build crisis-resilient trading systems that thrive under extreme market stress. Learn to model fat-tailed distributions, detect regime shifts before they break your strategy, and design robust hedges that protect capital during black swan events.Inside, you'll discover: - Advanced Monte Carlo Stress Testing, Simulate extreme drawdowns, liquidity shocks, and tail-risk events with realistic scenarios.- Fat-Tail & Black Swan Modeling, Go beyond normality assumptions using EVT, power-law distributions, and Bayesian methods.- Crisis-Ready Hedging Frameworks, Deploy convex tail hedges with VIX, CDS, and volatility options to protect portfolios when correlations go to 1.- Regime-Switching Models, Build machine-learning classifiers to detect volatility regime changes before they impact PnL.- Practical Implementation, Step-by-step Python code for stress tests, risk metrics, and hedging strategies you can deploy today.Whether you are a quant developer, risk manager, or independent trader, this book will show you how to turn catastrophic risk into predictable, manageable exposure-and build a portfolio that survives the next systemic shock.…

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingIn modern markets, speed is alpha. Market Microstructure & High-Frequency Trading is your step-by-step guide to understanding how liquidity really works, and how to exploit it with precision.This book takes you beyond academic theory, giving you a practitioner's view of market microstructure, order book dynamics, and latency-optimized strategy design. Learn to engineer systems that operate at the speed of modern markets, from smart order routing to high-frequency execution algorithms.Inside, you'll master: - Order Book Analytics, Model depth-of-book data, bid-ask dynamics, and hidden liquidity.- Market Impact & Slippage Control, Minimize footprint with optimal execution algorithms and liquidity-aware sizing.- Smart Order Routing, Navigate fragmented exchanges with routing logic that optimizes fills and minimizes cost.- Latency Engineering, Design systems that achieve microsecond response times using co-location, low-latency networking, and efficient data pipelines.- Backtesting & Simulation, Build realistic market simulators to stress-test strategies before live deployment.With hands-on Python examples and a clear focus on real-world application, this book is ideal for quant developers, traders, and researchers who want to compete at the cutting edge of electronic trading.If your goal is to capture alpha before the rest of the market reacts, this is the blueprint.…

Paperback. Condición: New.