Some algo trading strategies are geared towards the speed of execution, enabling the so-called high-frequency trading algos to access and act on information much faster than human traders. Many algorithmic trading servers are now located near major exchanges and data sources. It is a highly competitive segment of the global financial markets since the marginal profit per trade is narrow and the potential for profit is high. However, it is not sufficient to find a working algorithm once. There is a constant arms race for speed and accuracy in the high-frequency trading world, and HFT algorithms must be modified constantly to keep ahead of the competition. Having a great technology that can keep up with the pace of innovation is as important in this industry as having a great algorithm or a fast connection to the exchanges.
At the same time, many other algo strategies are not as sensitive to the latency of trading. The bulk of quant investment firms are actually focused on much longer time horizons than intraday trading, even though they care a lot about efficient execution which happens intraday. There are many hundreds of billions of dollars of capital invested with quant strategies that have typical holding horizons measured in weeks and months. But even on such longer time frames, it is critical that the corresponding algorithms are well tested, and that portfolio managers can estimate their ongoing profitability and risk characteristics.
With their solutions, SmartQuant provides emerging and midsize quant managers with an industrial strength strategy development, backtesting, optimization, and automation platform that fits their budgets, and scales up with the growth of their business and the complexity of their strategies while retaining the reliable modular architecture and not compromising on quality. SmartQuant algo solutions allow managers to focus on the development of investment strategies and benefit from a reliable framework to implement and deploy them in the market using a distributed trading environment. SmartQuant fills the gap between expensive high-end institutional systems and the lower-end systems, which do not have the requisite features and robustness necessary for professional investment managers. Tailored solutions are offered to clients, which comprises the set of products for each stage of their development.
SmartQuant Distributed Trading Platform™ consists of OpenQuant integrated development environment (IDE), QuantTrader, a production deployment engine for automated trading strategies developed in OpenQuant, QuantBroker,an algo execution server with feed replication, consolidation, aggregation, and smart order routing, QuantBase, a data server with real-time feed capture and optimized time series management capabilities, and QuantController, a central command and control module for the distributed trading environment.
We believe in the importance of flexibility of customer solutions, coupled with the reliability of the underlying framework and affordability of the complete infrastructure
Given their focus on emerging managers who often start very small and then rapidly scale up, SmartQuant offers license subscriptions starting from a single OpenQuant IDE, and allow additions of any combination of Platform components for the most flexible client growth option. A popular license bundle hems together several OpenQuant and QuantTrader licenses and adds QuantBroker, QuantBase, and QuantController server licenses for a complete trading system capable of supporting a small hedge fund or a quant prop desk.
The company's other solution, QuantWeb, is a cloud-based version of the SmartQuant Distributed Trading Platform™. SmartQuant is working with institutional data providers to integrate real-time and historical market data within its cloud services and to enable its clients to have access to fully managed cloud-based data services complementing the strengths of the SmartQuant software.
"The main difference between the quantitative and the discretionary trading style is the systematic nature of the quant approach"
All this provides clients with the liberty of working with their in-house database or choose externally managed data, and still use the same software for strategy development. “We believe in the importance of flexibility of customer solutions, coupled with the reliability of the underlying framework and affordability of the complete infrastructure”, said Anton Fokin, CEO and Co- Founder. “Emerging and midsize firms represent an underserved segment of the financial industry, and we are focused on providing them with the best technology on par with their much larger competitors”, added Arthur M. Berd.
Since its inception, SmartQuant has partnered with various companies based in the U.S., Europe, Australia, and Asia to expand their business. Partnerships include service affiliates such as Cerberus Trading in Israel, which specializes in custom development and support of strategies using SmartQuant software. Among the largest such partnerships is SmartQuant’s collaboration with Tianfeng Securities, a fast-growing brokerage in Shanghai, which commenced in 2017 and through which SmartQuant products are finding a growing adoption in China. SmartQuant’s future plans continue to revolve around collaborations with a network of brokers and service providers as well as select larger organizations together with whom it can provide more comprehensive service to a larger number of buy-side clients.