CoSupport AI
What is KloudTrader?
KloudTrader provides products and tools engineered to offer users a competitive advantage in the financial markets. Its offerings feature Narwhal, a comprehensive platform for the development, deployment, and monitoring of trading algorithms. Narwhal supports over 100 cryptocurrency exchanges and includes an integrated flat-rate broker for commission-free trading of U.S. Securities.
Additionally, KloudTrader offers Libkloudtrader, an in-house trading framework optimized for computational finance. This framework provides intuitive trading and data APIs designed to facilitate the implementation of various trading models. The company is also developing a next-generation trading platform equipped with live analytics, advanced charting features, and integrated Machine Learning technology, aiming to enable automated order placement via plain English commands and deliver high-speed access to daily market feeds.
Features
- Narwhal Platform: Develop, deploy, and monitor trading algorithms.
- Multi-Asset Support: Trade across 100+ crypto exchanges and US securities.
- Commission-Free Trading: Integrated flat-rate broker for US Securities.
- Libkloudtrader Framework: In-house trading framework optimized for computational finance.
- Intuitive APIs: Trading and data APIs for model implementation.
- Machine Learning Integration: Built-in ML for analytics and automation (upcoming platform).
- Natural Language Orders: Place automated orders using plain English commands (upcoming platform).
- Live Analytics & Charting: Advanced features for market analysis (upcoming platform).
Use Cases
- Developing custom algorithmic trading strategies.
- Deploying trading bots across multiple cryptocurrency exchanges.
- Automating stock trading based on predefined algorithms.
- Monitoring the performance of automated trading systems.
- Utilizing machine learning for predictive trading analytics.
- Backtesting trading models.
Related Queries
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KloudTrader Uptime Monitor
Average Uptime
100%
Average Response Time
236.93 ms
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