Reactive Publishing
In the world of finance, trading, and risk management, understanding probability and statistics is essential. Whether you're analyzing market trends, pricing options, or optimizing portfolios, quantitative finance relies on a strong foundation in statistical methods.
This comprehensive guide bridges the gap between theory and application, helping you develop the skills needed to succeed in financial markets.
What You’ll Learn:Core Probability Concepts – Random variables, expected value, and probability distributions (Normal, Lognormal, Poisson)
Statistical Methods for Finance – Hypothesis testing, regression analysis, and Bayesian inference
Risk Management & Portfolio Optimization – Value at Risk (VaR), Monte Carlo simulations, and correlation analysis
Machine Learning in Finance – Predictive analytics, time series forecasting, and statistical arbitrage
Practical Python Applications – Code examples for data analysis, risk modeling, and backtesting strategies
Traders & Investors – Improve your trading strategies with statistical insights
Financial Analysts & Risk Managers – Master probability-based risk assessment
Students & Quantitative Finance Professionals – Strengthen your mathematical foundation for real-world applications
With clear explanations, real-world case studies, and Python implementations, this book is designed to turn complex math into actionable financial insights.
Take your finance skills to the next level—get your copy today!
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
EUR 4,62 expédition depuis Royaume-Uni vers France
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Vendeur : California Books, Miami, FL, Etats-Unis
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Paperback. Etat : new. Paperback. Reactive PublishingMaster Probability & Statistics for Smarter Financial Decision-MakingIn the world of finance, trading, and risk management, understanding probability and statistics is essential. Whether you're analyzing market trends, pricing options, or optimizing portfolios, quantitative finance relies on a strong foundation in statistical methods.This comprehensive guide bridges the gap between theory and application, helping you develop the skills needed to succeed in financial markets.What You'll Learn: Core Probability Concepts - Random variables, expected value, and probability distributions (Normal, Lognormal, Poisson)Statistical Methods for Finance - Hypothesis testing, regression analysis, and Bayesian inferenceRisk Management & Portfolio Optimization - Value at Risk (VaR), Monte Carlo simulations, and correlation analysisMachine Learning in Finance - Predictive analytics, time series forecasting, and statistical arbitragePractical Python Applications - Code examples for data analysis, risk modeling, and backtesting strategiesWho This Book is For: Traders & Investors - Improve your trading strategies with statistical insightsFinancial Analysts & Risk Managers - Master probability-based risk assessmentStudents & Quantitative Finance Professionals - Strengthen your mathematical foundation for real-world applicationsWith clear explanations, real-world case studies, and Python implementations, this book is designed to turn complex math into actionable financial insights.Take your finance skills to the next level-get your copy today! Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798312079890
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Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
Paperback. Etat : new. Paperback. Reactive PublishingMaster Probability & Statistics for Smarter Financial Decision-MakingIn the world of finance, trading, and risk management, understanding probability and statistics is essential. Whether you're analyzing market trends, pricing options, or optimizing portfolios, quantitative finance relies on a strong foundation in statistical methods.This comprehensive guide bridges the gap between theory and application, helping you develop the skills needed to succeed in financial markets.What You'll Learn: Core Probability Concepts - Random variables, expected value, and probability distributions (Normal, Lognormal, Poisson)Statistical Methods for Finance - Hypothesis testing, regression analysis, and Bayesian inferenceRisk Management & Portfolio Optimization - Value at Risk (VaR), Monte Carlo simulations, and correlation analysisMachine Learning in Finance - Predictive analytics, time series forecasting, and statistical arbitragePractical Python Applications - Code examples for data analysis, risk modeling, and backtesting strategiesWho This Book is For: Traders & Investors - Improve your trading strategies with statistical insightsFinancial Analysts & Risk Managers - Master probability-based risk assessmentStudents & Quantitative Finance Professionals - Strengthen your mathematical foundation for real-world applicationsWith clear explanations, real-world case studies, and Python implementations, this book is designed to turn complex math into actionable financial insights.Take your finance skills to the next level-get your copy today! Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798312079890
Quantité disponible : 1 disponible(s)