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What is StockMock?

Backtesting provides an invaluable opportunity to evaluate your trading strategies against historical data, allowing you to gauge their effectiveness in past market conditions. As you transition to live trading, utilizing the Backtesting feature can confirm the viability of your methods and their likelihood of success. Stockmock offers data relevant to the same week and month, enabling efficient backtesting on any selected date, and also allows for the inclusion of subsequent week or month data for deeper insights. Our objective is to support you as best as we can, so please do not hesitate to share your thoughts or inquiries, as we are committed to assisting you. You can customize your strategy with a variety of parameters, such as Nifty/Banknifty, futures/options, call/put options, buy/sell decisions, strike prices, premium ranges, lot sizes, stop loss/target profit levels, and specific entry/exit timings. Embark on your backtesting journey today, and keep in mind that any issues can be reported via email for prompt resolution. Our platform allows users to access every feature using free credits, which provides ample opportunities to enhance your trading strategies. We invite you to thoroughly explore all the available tools, as doing so will help you unlock your full potential in the trading arena. Furthermore, regular engagement with our support team can lead to a more enriched trading experience.

What is QuantRocket?

QuantRocket is a versatile platform that utilizes Python for the research, backtesting, and execution of quantitative trading strategies. Designed with Docker, it can be conveniently deployed on local machines or cloud environments, showcasing an open architecture that allows for significant customization and expansion. The platform features a JupyterLab interface and includes a comprehensive set of data integrations, along with support for various backtesting frameworks, such as Zipline—originally the backbone of Quantopian; Alphalens for alpha factor analysis; Moonshot, a backtester leveraging pandas; and MoonshotML, which focuses on walk-forward machine learning backtesting. Additionally, users can benefit from its flexibility to adapt to diverse trading needs and strategies as they evolve.

Media

Media

Integrations Supported

Alpaca
Amazon Web Services (AWS)
DigitalOcean
Docker
Google Cloud Platform
Microsoft Azure
Moonshot
NGINX
PostgreSQL
SQLite
Zipline

Integrations Supported

Alpaca
Amazon Web Services (AWS)
DigitalOcean
Docker
Google Cloud Platform
Microsoft Azure
Moonshot
NGINX
PostgreSQL
SQLite
Zipline

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

StockMock

Company Location

India

Company Website

www.stockmock.in/

Company Facts

Organization Name

QuantRocket

Date Founded

2018

Company Location

United States

Company Website

www.quantrocket.com

Categories and Features

Categories and Features

Algorithmic Trading

2-Click Trading
Analyst on Demand
Auto Fibs
Auto Trend Lines
Backtesting
Basket Trading
Drawing Tools
Pattern Tools
Stock Screener
Trading From Charts

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