SigTech
SigTech offers quant technologies for global investors and data owners. Cloud-hosted and Python-based, SigTech accelerates the data-driven investment process, from research to live trading. The platform integrates an industry leading backtesting engine with clean, validated data across asset classes. SigTech eliminates the expensive upfront costs of infrastructure build-out, giving clients an edge in alpha generation from day one. The SigTech platform was originally built over eight years ago to manage systematic investments at Brevan Howard, which remains a SigTech client today. After the spinoff into an independent company in early 2019, the team has grown substantially and established SigTech as the leading provider of quant technologies.
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Financial Services
84 Employees
Found
Founded 2019
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SigTech Technology Stack
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Frequently asked questions about SigTech
Who is the CEO of SigTech?
Alex Sandro R is the CEO of SigTech.
Who are the decision makers in SigTech?
The decision makers in SigTech are Alex Sandro R, Sophia Li, Emma P, etc. Click to Find SigTech decision makers emails.
What types of investors can benefit from SigTech's platform?
SigTech's platform is designed for a wide range of investors, including hedge funds, asset managers, and institutional investors. By providing cloud-hosted, Python-based quantitative technologies, SigTech enables these investors to streamline their data-driven investment processes, from research and strategy development to backtesting and live trading.
How does SigTech support the backtesting of trading strategies?
SigTech offers a robust backtesting framework that allows users to test their trading strategies against historical data. The platform provides access to a wide array of data vendors and integrates seamlessly with various data sources. Users can easily simulate their strategies in a controlled environment, analyze performance metrics, and refine their approaches before deploying them in live markets.
Can SigTech's platform handle large datasets from multiple sources?
Yes, SigTech's platform is specifically designed to handle large datasets from various sources, making it ideal for quantitative investing. The cloud-hosted architecture allows for scalable data storage and processing, enabling users to integrate and analyze data from multiple vendors efficiently. This capability is crucial for macro trading and systematic investing, where diverse data inputs can significantly impact strategy performance.
What programming languages does SigTech support for developing investment strategies?
SigTech primarily supports Python for developing investment strategies. Python is widely used in the quantitative finance community due to its versatility and the rich ecosystem of libraries available for data analysis, machine learning, and statistical modeling. This makes it easier for users to implement complex algorithms and leverage advanced analytical techniques within the SigTech platform.
Is SigTech suitable for both systematic and discretionary trading strategies?
While SigTech excels in supporting systematic trading strategies through its quantitative technologies and backtesting capabilities, it can also accommodate discretionary trading approaches. The platform's flexibility allows users to analyze data, generate insights, and develop models that can inform discretionary decisions, making it a valuable tool for a variety of trading styles.
What industries does SigTech serve, and how do they benefit from the platform?
SigTech serves a variety of industries, including finance, investment management, and data analytics. Hedge funds and asset managers benefit from the platform's ability to enhance their quantitative research and trading capabilities, while asset owners can leverage the technology to optimize their investment strategies. By providing a comprehensive suite of tools for data analysis and strategy development, SigTech helps these industries improve their investment outcomes and operational efficiency.