Alice preston (63 Ergebnisse)

Zustand: Very Good. Very Good condition. Volume 35. A copy that may have a few cosmetic defects. May also contain light spine creasing or a few markings such as an owner's name, short gifter's inscription or light stamp. Aliya Chen; Alexander Gustafson; Yingying Jiang; Sam Kemp; Qianjiao Ma; Allen Morris; Jennifer Ober; Josh Pemberton; Emerson Rabbit; Christine Rhee; Vytas Vasiliauskas; Alice Wang; David Furnal; Brian C. Hailes (illustrator).…

Paperback. Zustand: Very Good. Prompt Shipment, shipped in Boxes, Tracking PROVIDEDTravel. Vintage travel guide. Very good.

Zustand: New. pp. 428. Aliya Chen; Alexander Gustafson; Yingying Jiang; Sam Kemp; Qianjiao Ma; Allen Morris; Jennifer Ober; Josh Pemberton; Emerson Rabbit; Christine Rhee; Vytas Vasiliauskas; Alice Wang; David Furnal; Brian C. Hailes (illustrator).

Zustand: New. In English.

Zustand: New. In English.

paperback. Zustand: Very Good. No Dust Jacket. First Edition. Numerous tables. Tiny chip to tail of spine, text is clean, bright and tight throughout. Clean Copy.

Half Cloth. Zustand: Fair. First Edition. All Six color plates are present. Cover is edge chipped with scuffiing. Free front end paper is missing, rear end paper is cracked at the hinge with some breaking to the netting. Gift inscription on the half title page, otherwise clean. A12. Preston, Alice Bolam (illustrator).…

Zustand: New. In English.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Neuware - 'Peggy in Her Blue Frock' by Eliza Orne White offers a heartwarming glimpse into family life, particularly the challenges and triumphs of fatherless families. This classic children's story explores themes of friendship and resilience through the eyes of young Peggy. This tale of childhood navigates the emotional landscape of growing up, emphasizing the importance of connection and the enduring bonds of family. A touching portrayal of childhood experiences, 'Peggy in Her Blue Frock' provides a gentle exploration of social themes and the everyday emotions of young girls.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingFinancial markets are driven by complex relationships that traditional correlation measures often fail to capture. Many trading strategies rely on linear assumptions, yet real market dynamics frequently involve nonlinear dependencies that remain hidden when using standard statistical tools.Mutual Information in Trading Systems introduces a rigorous framework for identifying and analyzing nonlinear relationships in financial data using information theory. The book explains how mutual information can reveal structural dependencies between variables such as price movements, volatility regimes, and macro signals that conventional methods overlook.Through practical Python implementations, readers learn how to estimate mutual information, apply it to market datasets, and incorporate information-theoretic metrics into systematic trading research. The techniques presented are useful for analyzing feature relationships, improving signal selection, and understanding the informational structure of financial time series.Topics covered include: - Foundations of information theory and entropy- Mutual information estimation techniques- Nonlinear dependency analysis in market data- Feature selection for trading models- Python implementations for quantitative research- Applications in systematic trading and financial data analysisDesigned for quantitative researchers, data scientists, and traders working with Python, this book provides a structured introduction to applying information-theoretic methods within modern trading systems.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingUnlock the essential building blocks of modern finance with Financial Derivatives Fundamentals.This clear and practical guide delivers a solid foundation in the core derivative instruments that drive today's global markets: options, futures, and forwards. Written for students, early-career professionals, and self-directed investors, the book walks you through the mechanics, real-world applications, and basic pricing models of these powerful financial tools, without unnecessary complexity or heavy mathematics.What You'll Learn: - The fundamental differences between options, futures, and forwards - and when each is used in practice- How derivatives are priced using foundational models (including intuitive explanations of the binomial model and Black-Scholes framework)- Key concepts such as hedging, speculation, arbitrage, margin requirements, and contract specifications- Practical examples drawn from equities, commodities, and interest rates- Risk management principles and the role derivatives play in institutional portfoliosWhether you're preparing for finance exams, starting a career in trading or risk management, or simply want to understand the instruments behind the headlines, this book gives you the confidence to navigate derivatives with clarity and precision.Perfect for: - Finance students and MBA candidates- Junior analysts and traders- Individual investors seeking a deeper market edge- Professionals transitioning into quantitative or risk rolesClear. Practical. Focused on fundamentals.Start mastering the language of derivatives today. …

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingExchange-traded funds are built on a market structure that connects fund shares, underlying baskets, authorized participants, liquidity providers, and intraday pricing relationships. ETF Arbitrage with Python provides a practical technical guide to understanding how these relationships work and how they can be modeled with Python.This book explains the core mechanics behind ETF creation and redemption, basket pricing, market making, liquidity behavior, and arbitrage relationships. Rather than focusing on trading claims or simplified profit formulas, it approaches ETF arbitrage as a market-structure problem involving data, pricing logic, execution constraints, and portfolio relationships.Readers will learn how to examine ETF premiums and discounts, compare fund prices against underlying basket values, model liquidity conditions, and build Python workflows for research, analysis, and simulation. The book is designed for quantitative finance readers, analysts, developers, traders, and students who want a clearer technical understanding of ETF pricing systems.Inside, the book covers: Creation-redemption mechanics and ETF primary-market structureAuthorized participants and liquidity provider workflowsBasket pricing and net asset value relationshipsPremium and discount analysisETF liquidity modeling and spread behaviorMarket making concepts for ETF productsPython-based research workflows for ETF dataHedging logic across ETF shares and underlying basketsPractical modeling examples for pricing and arbitrage analysisETF Arbitrage with Python is a structured guide for readers who want to understand how ETF arbitrage works beneath the surface and how Python can be used to study ETF market behavior with greater precision.…

Taschenbuch. Zustand: Neu. Neuware - Reactive Publishing \*\*AI for Algorithmic Trading: Master the Fundamentals in 2025\*\* Unlock the Secrets of the Future of Trading! In the ever-evolving world of finance, algorithmic trading has surged to the forefront, and artificial intelligence is redefining the rules of the game. If you've already embraced the basics, it's time to elevate your skills and delve into sophisticated strategies that can set you apart in the competitive landscape of trading. \*\*AI for Algorithmic Trading: Master the Fundamentals in 2025\*\* is your comprehensive guide to harnessing the power of AI and machine learning in the financial markets. This book is designed for enthusiasts and traders who are ready to transcend foundational concepts and embark on a journey to master advanced techniques that drive results. Within these pages, you will: - \*\*Dive Deep into AI Techniques\*\*: Discover the cutting-edge AI methods that are revolutionizing trading strategies. From neural networks to reinforcement learning, equip yourself with the knowledge to leverage these technologies for predictive analysis and enhanced decision-making. - \*\*Explore Real-World Applications\*\*: Benefit from case studies and practical examples that illustrate how top traders and firms utilize AI to outperform the market. Learn from real scenarios to strategically apply your newfound knowledge. - \*\*Master Data Analysis\*\*: Gain insights into effectively sourcing, processing, and analyzing vast datasets. Understand the intricacies of big data and how it influences trading decisions, risk assessment, and profitability. - \*\*Build and Optimize Your Trading Models\*\*: Step-by-step guidance will walk you through the process of designing, testing, and refining your own algorithmic trading strategies that are robust and adaptable to market shifts. - \*\*Stay Ahead of the Curve\*\*: Get a forward-looking perspective on trends, regulatory considerations, and the future of AI in trading. Equip yourself with the tools to not only navigate but thrive in the dynamic landscape of finance through 2025 and beyond. Whether you are a seasoned trader aiming to sharpen your competitive edge, or an ambitious newcomer excited to embrace AI's potential, \*\*AI for Algorithmic Trading\*\* is your key to mastering the future of trading. Transform your approach and unlock new opportunities with the sophisticated insights found in this essential tome! Prepare to elevate your trading strategy and secure your place at the forefront of the AI revolution. Are you ready to master the fundamentals and transform your trading journey The future awaits.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingMaster the mathematical foundations that power modern trading with Financial Mathematics for Traders: Essential Probability, Statistics, and Stochastic Processes.This clear and practical guide bridges the gap between theory and trading application. Designed specifically for traders, quants, and finance professionals, it delivers a focused treatment of the core mathematical tools used in quantitative finance and algorithmic trading strategies.What You'll Learn: - Probability Theory - Master random variables, distributions, expectations, and conditional probability as they apply to market behavior and risk assessment.- Statistical Methods - Build competence in estimation, hypothesis testing, regression analysis, and time-series modeling essential for backtesting and strategy validation.- Stochastic Processes - Develop a solid understanding of Brownian motion, martingales, Itô calculus, and diffusion processes that underpin option pricing, risk management, and simulation-based trading models.Each concept is presented with trading-relevant examples, intuitive explanations, and minimal jargon, making complex topics accessible without sacrificing technical rigor. Whether you are developing quantitative models, evaluating trading systems, or seeking a stronger mathematical edge in the markets, this book provides the essential toolkit.Ideal for intermediate to advanced traders, self-taught quants, and finance students looking to move beyond surface-level technical analysis into mathematically grounded decision-making.Financial Mathematics for Traders equips you with the probabilistic and statistical foundation required to think like a professional quant, clearly, confidently, and with precision.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingMaster the hidden mechanics driving modern crypto and DeFi markets.This technical guide dives deep into market microstructure, the real-time plumbing of centralized and decentralized digital asset trading. Learn how to design and implement latency-optimized trading strategies using Python, with a focus on practical systems architecture rather than theoretical hype.What You'll Explore: - CEX Order Book Dynamics: Advanced modeling of order flow, depth, and liquidity on centralized exchanges- DEX AMMs: Mechanics of automated market makers, liquidity provision, impermanent loss, and arbitrage opportunities- MEV Bot Architecture: Extraction strategies, searchers, and the technical infrastructure behind maximal extractable value on blockchain networks- Python implementations for low-latency data processing, simulation frameworks, and production-ready strategy deploymentDesigned for quantitative developers, algorithmic traders, and blockchain engineers who want to move beyond surface-level trading knowledge into the actual systems and code powering high-performance crypto strategies.Prerequisites: Intermediate Python programming experience and basic familiarity with crypto markets.Whether you're building production trading systems or researching DeFi protocols, this book provides the technical foundation for understanding and engineering in today's digital asset markets.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingMaster the Mathematical and Structural Mechanics of Institutional Risk ControlAdvanced Quantitative Risk Management provides a rigorous, unified treatment of the quantitative frameworks used to measure, model, and mitigate extreme market outcomes. Designed for quantitative analysts, portfolio managers, and financial engineers, this text bridges the gap between theoretical risk metrics and practical tail risk management.Moving beyond standard variance-based models, this book details the advanced statistical tools necessary to capture non-normal distributions, systemic shocks, and complex asset dependencies.Inside, you will find: - Volatility Modeling: Practical applications of stochastic volatility models, GARCH variants, and high-frequency volatility estimation in stressed market regimes.- Copula Theory & Dependency Structures: Step-by-step methodologies for applying Archimedean and Elliptical copulas to capture joint tail dependency and non-linear asset correlations.- Tail Risk Frameworks: Advanced application of Extreme Value Theory (EVT), including Generalized Pareto Distributions (GPD) for accurate Value-at-Risk (VaR) and Expected Shortfall (ES) estimation.- Hedging Strategies: Quantitative approaches to designing and executing asymmetric downside protection, convex payoff structures, and dynamic tail risk overlay strategies.Whether you are designing institutional risk systems or refining options overlays, this volume serves as a comprehensive reference for modern quantitative risk control and tail risk engineering.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingThis book is your definitive guide to building, training, and deploying deep reinforcement learning systems for modern futures markets. Designed for quantitative analysts, systematic traders, and advanced practitioners, it bridges cutting-edge academic research with real-world execution logic.The futures market is a shifting landscape of volatility, liquidity, and structural regime changes. Traditional models fail when conditions move too quickly. Reinforcement learning thrives in this environment. By learning directly from reward structures, market transitions, and agent-environment feedback loops, RL becomes a powerful engine for signal discovery and autonomous strategy optimization.This book delivers a complete, end-to-end framework for RL-powered trading: - How to design an RL environment that reflects market reality- State representation: volatility tensors, price transforms, microstructure features- Reward engineering that aligns the agent with real P&L- Policy networks, deep Q-learning, PPO, and actor-critic architectures- Training pipelines that prevent overfitting and mode collapse- Detecting and adapting to structural market regimes- Execution-aware RL: slippage, latency, and position sizing- Building an RL trading engine that can operate in productionYou also receive practical blueprints, including walkthrough Python examples, environment templates, and agent-training workflows tailored for futures contracts across equities, commodities, FX, and rates.James Preston presents a direct, technical, and actionable guide built for traders who demand measurable edge. If you are ready to integrate reinforcement learning into your systematic futures strategies, this book gives you the tools, architecture, and methodology required to compete at the frontier of AI-driven markets.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingBayesian Decision Making for Traders & CFOs delivers a practical, code-first framework for applying Bayesian inference to real-world financial problems. You'll move beyond basic probability to build and deploy hierarchical models that capture complex market dynamics, investor behavior, and organizational risk.What You'll Discover Inside: - How to apply Bayesian thinking to trading strategies, portfolio construction, and risk management- Building hierarchical models that account for varying market regimes and individual heterogeneity- Real-world applications in volatility forecasting, credit risk, option pricing, and capital allocation- Full Python implementations using Stan (CmdStanPy) for efficient Bayesian computation- Techniques for model checking, posterior predictive checks, and decision analysis under uncertainty- Practical workflows for integrating Bayesian outputs into trading systems and executive dashboardsWritten for quantitative traders, risk managers, and forward-thinking CFOs, this book bridges theory and practice with clear explanations, complete code examples, and reproducible case studies. Whether you're refining high-frequency signals or making multi-million-dollar capital decisions, you'll gain the probabilistic tools needed to navigate uncertainty with confidence.Perfect for practitioners who want to move past black-box models and develop transparent, adaptable decision frameworks.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingRisk measurement sits at the core of modern finance, yet traditional metrics often lag behind the complexity of today's markets. Machine Learning for Risk Measurement with Python bridges that gap.This book takes you from classical risk measures, Value-at-Risk, Expected Shortfall, volatility modeling, and stress testing, into the next generation of predictive risk signals powered by machine learning. You will learn how to move beyond static, backward-looking calculations and build models that anticipate risk rather than merely report it.Using clear Python implementations, the book covers: - Core classical risk metrics and their practical limitations- Feature engineering for risk-sensitive data- Supervised and unsupervised approaches for detecting emerging risk patterns- Model validation, backtesting, and stability under changing market regimes- Interpretable machine learning techniques that keep risk models transparent and defensibleWritten for quantitative analysts, risk managers, data scientists in finance, and Python-fluent practitioners, the material emphasizes practical application over abstract theory. Every major concept is grounded in code you can adapt, extend, and deploy.Whether you are modernizing an existing risk framework or building predictive capabilities from the ground up, this book provides a structured path from established metrics to forward-looking risk signals.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingTime series data in quantitative finance is noisy, non-stationary, and full of regime shifts. Extracting reliable signals from this data is one of the core technical challenges in systematic trading and research.This book provides a practical treatment of time series filtering and regime detection methods tailored for quantitative finance applications. It focuses on techniques for signal extraction and denoising that practitioners can implement and evaluate directly.Topics covered include: - Classical and modern filtering approaches for financial time series- Methods for identifying market regimes and state changes- Practical signal extraction and noise reduction techniques- Implementation considerations for real-world quant workflowsThe material is written for quantitative researchers, systematic traders, and developers who work with financial time series and need clear, implementable methods rather than purely theoretical treatments.No prior expertise in advanced signal processing is assumed, but readers should be comfortable with basic time series concepts and Python or a similar quantitative programming environment.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingAn enterprise-grade guide to building, validating, and deploying quantitative risk models in Python.Applied Quantitative Risk Analytics provides a rigorous, hands-on framework for measuring and managing market risk using modern Python libraries. Designed for quantitative analysts, risk managers, and financial engineers, this practical manual bridges the gap between theoretical risk metrics and operational code execution.Moving beyond basic statistical concepts, the book covers the full lifecycle of quantitative risk measurement. You will learn how to construct historical, parametric, and Monte Carlo Value at Risk (VaR) models, implement Expected Shortfall (ES) to capture tail risk, and design regulatory-compliant stress testing scenarios.Key Topics Covered: - Market Risk Metrics: Mathematical foundations and code implementations for standard and parametric Value at Risk (VaR).- Extreme Value & Tail Risk: Advanced estimation of Expected Shortfall (CVaR) to address non-normal return distributions and fat-tailed asset behavior.- Simulation Techniques: Building Monte Carlo and historical simulation engines using NumPy, Pandas, and SciPy.- Stress Testing & Scenario Analysis: Designing historical crisis scenarios, hypotheticals, and reverse stress tests for complex portfolios.- Model Validation & Backtesting: Evaluating model coverage using Kupiec's POF test, Christoffersen's independence test, and failure rate tracking.Whether you are upgrading legacy risk infrastructure or implementing modern quantitative models from scratch, this resource provides the production-ready code and structural methodology required for modern financial engineering.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingThe NumPy Quant Handbook is the ultimate practical guide to mastering numerical computing with NumPy in the world of finance. Written for quants, traders, portfolio managers, and Python-savvy finance professionals, this book bridges the gap between theoretical finance and real-world implementation.What You'll Master: - High-performance array computing - vectorization, broadcasting, and memory-efficient code that runs at lightning speed- Financial data wrangling - working with tick data, order books, and massive time series- Trading strategies - backtesting, signal generation, and execution logic using pure NumPy- Risk management - Value-at-Risk (VaR), Expected Shortfall, Monte Carlo simulations, and stress testing- Portfolio optimization - Markowitz, Black-Litterman, and advanced numerical solvers- Derivatives & quantitative models - option pricing, Greeks, and finite difference methods- Production-grade techniques - performance optimization, numerical stability, and integration with pandas, Numba, and CythonWith hands-on code examples, real market data applications, and battle-tested patterns used by top quant funds, this handbook transforms NumPy from a basic library into your most powerful competitive advantage.Perfect for: - Quantitative analysts and researchers- Algorithmic traders and developers- Risk managers and portfolio analysts- Finance students and self-taught quants ready to level upTurn data into decisions. Turn Python into profit.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingBitcoin has moved beyond speculation. It is now a global asset held by hedge funds, family offices, corporations, and high-net-worth investors who recognize its asymmetric potential, and the catastrophic risks of mishandling it. This book is a complete, institutional-grade framework for anyone who wants to hold Bitcoin safely, strategically, and in a way that preserves wealth across decades.You'll learn how sophisticated investors structure their positions, where they store their keys, and how they minimize exposure to theft, loss, and regulatory pressure. You'll understand the custody spectrum from cold storage to multisig and distributed key management, and you'll see how wealth managers evaluate counterparty risk, jurisdictional stability, and long-horizon security. Beyond the technical mechanics, this book explains how to blend Bitcoin into a broader portfolio while maintaining liquidity, managing volatility, and protecting family wealth through trusts, offshore entities, and inheritance design.This is not a hype book or a beginner's guide. It is a strategic manual for serious investors who need clarity, discipline, and a defensible plan. Whether you manage your own capital or oversee family assets, you'll gain the tools to build a robust Bitcoin position, one that survives market cycles, regulatory shifts, and geopolitical instability.For high-net-worth individuals navigating a volatile world, this book provides what the industry has failed to deliver: a sober, actionable, expert-level approach to owning Bitcoin with confidence.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingRisk-Asymmetric Trading is a practical guide to designing derivative trades where risk is strictly defined and upside remains structurally open.Most traders fail not because they are wrong about direction, but because their risk is poorly shaped. This book focuses on trade architecture rather than prediction, showing how to structure options and futures positions so losses are capped, probability is controlled, and favorable convexity does the heavy lifting over time.James Preston breaks down how asymmetry actually emerges in real markets: through volatility dynamics, payoff curvature, time decay, and positioning relative to market structure-not through oversized bets or heroic forecasts. You'll learn how professional traders think about downside first, then build exposure where gains can compound non-linearly when conditions align.Inside, you'll learn how to: - Structure derivative trades with predefined maximum loss- Identify setups where payoff distribution is skewed in your favor- Use volatility, skew, and term structure to create convex exposure- Combine probability, payoff, and risk sizing into a coherent framework- Avoid hidden tail risk embedded in 'high-probability' strategies- Think in distributions instead of outcomesThis book is not about signals, indicators, or overfitted strategies. It is about engineering trades, understanding how options, futures, and volatility interact so you can participate in markets without exposing your capital to catastrophic risk.Whether you trade options, futures, or complex derivatives, Risk-Asymmetric Trading gives you a durable mental model for surviving uncertainty while positioning for outsized gains when the market moves.If your goal is longevity, capital preservation, and asymmetric upside, this is the framework that makes that possible.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingCrypto Quant Strategies teaches you how to design, backtest, and implement automated trading strategies specifically for Bitcoin, Ethereum, DeFi protocols, and other digital assets. You'll move beyond simple indicators and learn how to construct robust quantitative systems that can operate with discipline in 24/7 markets.What You'll Learn: - Core principles of quantitative trading applied to crypto markets- How to collect, clean, and analyze cryptocurrency market data- Building backtesting engines tailored for crypto-specific challenges (funding rates, slippage, 24/7 trading)- Developing systematic strategies including momentum, mean reversion, arbitrage, and DeFi yield opportunities- Risk management techniques designed for high-volatility digital assets- Python implementation using libraries such as pandas, NumPy, TA-Lib, CCXT, and backtrader- Strategy optimization, walk-forward analysis, and avoiding common overfitting pitfalls- Deployment considerations for live trading systemsWritten for traders, developers, and analysts with basic Python knowledge, this book bridges the gap between traditional quant methods and the unique characteristics of cryptocurrency markets. Each chapter includes working code examples and practical implementation guidance.Whether you're looking to professionalize your crypto trading or develop algorithmic systems for Bitcoin, Ethereum, and decentralized finance, Crypto Quant Strategies offers a clear, technical pathway to building trading systems based on data and logic rather than emotion.Perfect for: - Python developers interested in finance- Experienced traders moving into systematic crypto strategies- Quantitative analysts exploring digital asset marketsThis book is for educational and informational purposes only. Trading cryptocurrencies involves substantial risk of loss.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingIn today's volatile global markets, supply chain and operations professionals face unprecedented uncertainty. From demand fluctuations and supplier disruptions to price volatility and geopolitical risks, traditional deterministic models often fall short. This practical guide shows you how to build robust, data-driven risk models using Monte Carlo simulation, one of the most powerful techniques for quantifying uncertainty and making better decisions under risk.You will learn how to: - Construct Monte Carlo simulations from the ground up in both Excel and Python- Model key supply chain and operations risks including demand variability, lead time uncertainty, price fluctuations, and inventory risk- Translate complex real-world problems into probabilistic models- Analyze simulation outputs to generate actionable insights and risk metrics- Compare deterministic vs. stochastic approaches and understand when Monte Carlo adds the most value- Build reusable, professional-grade models suitable for both quick analysis and enterprise environmentsWritten for supply chain analysts, operations managers, risk professionals, and data-savvy practitioners, this book bridges the gap between theory and hands-on implementation. Whether you work in manufacturing, logistics, retail, or procurement, you'll gain concrete skills to stress-test your supply chain and improve resilience.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingProtect your trading capital and make smarter decisions with practical risk management techniques.In today's volatile markets, effective risk management separates successful traders from those who quickly blow up their accounts. This hands-on guide walks you through the foundational tools every trader needs: position sizing to control exposure, stop losses to limit downside, portfolio diversification strategies to reduce overall risk, and an introduction to Value at Risk (VaR) calculations.Using clear explanations and real-world examples, you'll learn how to implement these methods in both Python and Excel. Whether you're a beginner looking to build strong habits or an experienced trader refining your approach, these practical frameworks will help you manage uncertainty and trade with greater confidence.What You'll Find Inside: - Step-by-step guidance on calculating and applying position sizes- Techniques for setting effective stop losses- Diversification methods for building resilient portfolios- Basic VaR modeling to quantify potential losses- Ready-to-use code examples in Python and Excel spreadsheetsNo prior programming experience required. Focus on building sustainable trading practices that prioritize capital preservation alongside growth.Ideal for independent traders, quantitative enthusiasts, and anyone serious about long-term success in the markets.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingThe volatility surface is broken. Rough volatility explains why.This book delivers the most accessible, practical, and comprehensive guide to rough volatility, fractional Brownian motion (fBM), and Hurst-driven modeling ever written for quantitative traders and financial engineers.If you have struggled to understand why standard stochastic volatility models fail, or why modern markets behave with 'memory' and microstructure-induced roughness, this book gives you the complete framework, intuition, and Python workflows to build the next generation of volatility models and trading systems.What This Book Teaches You- The core intuition behind rough volatilityWhy volatility is not smooth, why it cannot be modeled with classical Brownian motion, and how fractional processes capture long-memory behavior in real markets.- Fractional Brownian motion (fBM) from zero to masteryStep-by-step construction, parameterization, simulation, and calibration. Learn Hurst exponents the right way - intuitively first, then rigorously.- Full rough volatility model implementations in PythonIncluding: - The Rough Bergomi Model- Fractional Stochastic Volatility (fSV)- Multi-factor fractional models- Hybrid neural/fractional architecturesAll presented with clean, reusable code templates.- How rough volatility transforms tradingUse fractional features to detect volatility clustering, regime shifts, option mispricings, and structural breaks that traditional models miss.- Complete volatility trading systemsConcrete, plug-and-play strategies built from fractional features: - Hurst-driven volatility filters- fBM momentum/anti-momentum signals- Rough volatility mean-reversion engines- Volatility-of-volatility predictorsIncludes full Python implementations.Why Rough Volatility MattersClassical models assume volatility is smooth, Markovian, and memoryless. Modern markets are the opposite. They are rough, self-similar, and exhibit long-range dependence - and this book shows how to model that structure directly.Rough volatility is not an academic curiosity. It is the new foundation of volatility modeling at banks, hedge funds, and derivatives desks worldwide.Who This Book Is ForQuant traders, systematic volatility researchers, derivatives professionals, financial engineers, and advanced Python quants who want to push beyond Black-Scholes-era assumptions and into the future of stochastic modeling.If you want to understand how volatility really behaves, and build trading systems that exploit it, this is the most practical, complete, and modern guide available.…

Taschenbuch. Zustand: Neu. Neuware - Reactive PublishingAlgorithmic trading has entered a new era where machine learning models can analyze vast streams of market data, detect subtle patterns, and adapt strategies faster than traditional rule-based systems. The challenge is not simply building models, it is integrating them into trading frameworks that operate reliably in real markets.Machine Learning for Algorithmic Trading with Python provides a structured guide to designing and implementing data-driven trading systems using modern machine learning techniques and Python-based tools.The book moves beyond theory and focuses on practical architecture: how predictive models translate into signals, how strategies are designed around those signals, and how automated systems execute them within real trading environments.Readers will explore how machine learning interacts with market structure, risk management, and portfolio construction while learning how to implement reproducible research pipelines and deploy algorithmic strategies.Inside the book you will learn how to: - Build predictive market models using supervised and unsupervised learning- Prepare financial datasets for machine learning workflows- Design signal pipelines and strategy logic- Integrate machine learning outputs into algorithmic trading frameworks- Evaluate models using walk-forward testing and robust validation techniques- Construct automated trading systems using Python- Manage execution, risk, and portfolio constraints within systematic strategiesThe book uses practical Python examples and focuses on real implementation challenges faced by quantitative traders and developers.It is designed for: - Quantitative traders and systematic investors- Developers building trading algorithms- Data scientists working with financial time series- Finance professionals interested in machine learning applicationsRather than presenting isolated models, the book emphasizes the complete lifecycle of algorithmic trading systems, from data preparation and model development to strategy deployment and automation.If you want to understand how machine learning integrates with modern algorithmic trading infrastructure, this guide provides a clear and practical roadmap.…