Isbn: 9798274427647 - reinforcement learning for live market execution: building rl agents with action penalties, slippage modelling, market impact.: 2 (algorithmic alpha: next-gen trading systems for the modern market) (5 resultados)

Idioma: Inglés
Editorial: Independently Published, 2025
Serie: Libro 2 de 6 - Algorithmic Alpha: Next-Gen Trading Systems for the Modern Market
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 43,56
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Idioma: Inglés
Editorial: Independently Published, 2025
Serie: Libro 2 de 6 - Algorithmic Alpha: Next-Gen Trading Systems for the Modern Market
- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 39,16
Envío por EUR 5,92Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Idioma: Inglés
Editorial: Independently published, 2025
Serie: Libro 2 de 6 - Algorithmic Alpha: Next-Gen Trading Systems for the Modern Market
- Tapa blanda
- Impresión bajo demanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 38,62
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Condición: New. Print on Demand.

Idioma: Inglés
Editorial: Independently Published, 2025
Serie: Libro 2 de 6 - Algorithmic Alpha: Next-Gen Trading Systems for the Modern Market
- Tapa blanda
- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 43,58
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Paperback. Condición: new. Paperback. Reactive PublishingExecution is where theories die and real trading begins.In today's markets, microseconds matter, order books shift without warning, and liquidity evaporates the moment a trader hesitates. Reinforcement learning, built on adaptive decision-making and continuous reward optimization, has become the most powerful framework for navigating this environment.Reinforcement Learning for Live Market Execution reveals how modern quant desks design agents that learn, react, and evolve inside real-time market conditions. This is not a theoretical tour. It is a practical, institutional-grade manual for building RL-driven execution systems capable of surviving and thriving in live markets.Inside, you'll learn how to: Construct RL agents that optimize entries, exits, sizing, and timing in dynamic environmentsModel slippage, spread, queue position, and market impact as penalties and rewardsTrain policies using volatility shocks, liquidity droughts, and regime shiftsIntegrate RL with microstructure signals: order flow imbalance, volatility bursts, and quote dynamicsBuild execution engines for futures, options, and crypto using constrained decision workflowsRun walk-forward simulations that mirror real-world stress conditionsDeploy agents to live trading while maintaining risk controls and fail-safe overridesEach chapter focuses on durability, how to engineer models that not only backtest well, but perform reliably when the market becomes chaotic, thin, or structurally hostile.For quantitative traders, algorithm designers, and researchers seeking an advanced but accessible pathway into reinforcement learning, this book offers a complete blueprint for turning RL into a true execution edge. This is the future of live market execution, built one decision at a time. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Idioma: Inglés
Editorial: Independently Published, 2025
Serie: Libro 2 de 6 - Algorithmic Alpha: Next-Gen Trading Systems for the Modern Market
- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 43,73
Envío por EUR 43,65Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponible
Paperback. Condición: new. Paperback. Reactive PublishingExecution is where theories die and real trading begins.In today's markets, microseconds matter, order books shift without warning, and liquidity evaporates the moment a trader hesitates. Reinforcement learning, built on adaptive decision-making and continuous reward optimization, has become the most powerful framework for navigating this environment.Reinforcement Learning for Live Market Execution reveals how modern quant desks design agents that learn, react, and evolve inside real-time market conditions. This is not a theoretical tour. It is a practical, institutional-grade manual for building RL-driven execution systems capable of surviving and thriving in live markets.Inside, you'll learn how to: Construct RL agents that optimize entries, exits, sizing, and timing in dynamic environmentsModel slippage, spread, queue position, and market impact as penalties and rewardsTrain policies using volatility shocks, liquidity droughts, and regime shiftsIntegrate RL with microstructure signals: order flow imbalance, volatility bursts, and quote dynamicsBuild execution engines for futures, options, and crypto using constrained decision workflowsRun walk-forward simulations that mirror real-world stress conditionsDeploy agents to live trading while maintaining risk controls and fail-safe overridesEach chapter focuses on durability, how to engineer models that not only backtest well, but perform reliably when the market becomes chaotic, thin, or structurally hostile.For quantitative traders, algorithm designers, and researchers seeking an advanced but accessible pathway into reinforcement learning, this book offers a complete blueprint for turning RL into a true execution edge. This is the future of live market execution, built one decision at a time. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…