✔ 100% Money-Back Guarantee on Eligible Items
✔ Prices Displayed in Your Local Currency
✔ Final Price = No Surprise Import Fees
✔ Complimentary Insured Worldwide Shipping on Qualifying Orders
✔ Select Collector & Specialty Pieces May Require Secured Delivery Handling
by Chris Conlan (Author)
Learn to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage's API, and the source code is plug-and-play.
Automated Trading with R explains automated trading, starting with its mathematics and moving to its computation and execution. You will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform.
The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage. This book will:
- Provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders
- Offer an understanding of the internal mechanisms of an automated trading system
- Standardize discussion and notation of real-world strategy optimization problems
What You Will Learn
- Understand machine-learning criteria for statistical validity in the context of time-series
- Optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library
- Best simulate strategy performance in its specific use case to derive accurate performance estimates
- Understand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital
Who This Book Is For
Traders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students
Back Jacket
All the tools you need are provided in this book to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage's API, and the source code is plug-and-play.
Automated Trading with R explains the broad topic of automated trading, starting with its mathematics and moving to its computation and execution. Readers will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform.
The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage. This book will:
- Provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders Offer an understanding of the internal mechanisms of an automated trading system
- Standardize discussion and notation of real-world strategy optimization problems
What You'll Learn:
- To optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library
- How to best simulate strategy performance in its specific use case to derive accurate performance estimates
- Important optimization criteria for statistical validity in the context of a time series An understanding of critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital
Author Biography
Chris Conlan began his career as an independent data scientist specializing in trading algorithms. He attended the University of Virginia where he completed his undergraduate statistics coursework in three semesters. During his time at UVA, he secured initial fundraising for a privately held high-frequency forex group as president and chief trading strategist. He is currently managing the development of private technology companies in high-frequency forex, machine vision, and dynamic reporting.
- In stock, ready to ship
- ✔ Authenticity Guaranteed — Verified Designer Goods
- ✔ Sourced from Authorized European/U.S. Luxury Distributors
- ✔ Secure Checkout — SSL Encrypted Payments
- ✔ Fast Global Delivery — 3–11 Business Days
- ✔ Easy Returns on Eligible Items
- ✔ 100% Money-Back Guarantee — Full Refund if Not Satisfied
AUTHENTICITY GUARANTEED
Reserved for you — complete your purchase to secure this piece.
OFFICIALLY AUTHORIZED RESELLER
Discover Officially Authorized Authentic Items at STORE7994.com - Certificates Available on Request!
Independently verified for store quality and customer safety.
Trust score: 91/100
All designer items offered by STORE 7994 are sourced from trusted luxury distributors and verified through independent authentication services.
Learn how STORE 7994 authenticates luxury items
Guaranteed Authentic — Includes Brand Documentation & Third-Party Verification Options.
Shipping information
- Free Shipping* on all orders over $300 USD to most countries* Estimated delivery: 2-5 business days Mon-Sat to U.S., CA, EU etc.
- Tracking available: DHL Express
- Store 7994 Shipping policy
- Global delivery in 3–9 business days (location dependent).
- Free Worldwide Shipping $300+. International duties & VAT are calculated by destination country and may be collected upon delivery. UK orders are subject to 20% import VAT upon delivery.
Our innovation isn’t just in the brands we carry — it’s in the way we connect them. From our automation engine that keeps collections globally updated to our commitment to authenticity-first presentation, STORE 7994 exists where timeless design meets modern precision.
Every product we offer is:
Elevated · Intentional · Exclusive · Authentic
STORE 7994 is an authorized reseller of luxury fashion houses. Certificates and proof of authenticity are available to brand owners and partners upon request.
Returns & Refunds
We want you to shop with confidence at STORE 7994. If your purchase does not meet expectations, eligible items may be returned under the conditions below.
Return Eligibility
Items must be unused, unworn, and in original condition with all tags, packaging, and accessories included. Items showing any signs of wear or damage will not be accepted.
Return Window
Return requests must be made within 14 days of delivery.
Return Shipping
Customers are responsible for return shipping costs unless the item is defective, damaged, or incorrect.
Luxury Items
Items valued over $1,000 may be subject to a 7% restocking fee upon approved return.
Non-Returnable Items
For hygiene and product integrity reasons, the following items are final sale once opened or used:
• Underwear
• Fragrances
• Any worn or used items
Made-to-Order Items
Custom-designed products, including STORE 7994 hoodies, are made exclusively for each customer and are final sale. These items are not eligible for return or exchange unless defective or incorrect.
If you receive a defective or incorrect item, please contact us and we will make it right.
International Shipping & Duties
Many of our products ship directly from trusted international partners. Any applicable customs duties or import taxes are calculated at checkout and are non-refundable, even if the item is returned.
Returns & Associated Fees
All approved returns are subject to a $24 return processing fee. For international orders, duties, taxes, and return fees will be deducted from the original payment.
Shipping Policy
Complimentary shipping is offered on orders over $300. Orders below this threshold are subject to standard shipping rates at checkout.
