Recent client work using classification algorithms showcases software development firm’s aptitude for advanced financial use cases

DEMIR HISAR, MACEDONIA, February 3, 2021 /EINPresswire.com/ -- Quant Coding, one of the world’s foremost software development firms for Machine Learning (ML), today announced that it has completed several ML projects related to classification on imbalanced data sets for clients. The projects and their attendant models, which leverage classification algorithms, represent a tour de force of data science-driven coding. They effectively demonstrate Quant Coding’s proficiency in ML, which is now attracting interest from clients in the financial sector.

“These recently completed projects comprise a proof point for our abilities with data science and Machine Learning,” explained Tomislav Najdovski, CEO of Quant Coding. “It’s time to apply these technologies more completely to financial markets. Though ML and NLP are not new in finance, it seems clear that financial markets have not yet fully benefited from the latest advances in Data Science. We are pivoting the firm to address this unmet need.” Najdovski has more than five years of experience in managing IT Consultancies. He is also a financial expert who has passed Level 1 of the Chartered Financial Analyst exams.

Quant Coding has experience creating trading bots, along with solutions for backtesting and investment analytics using interactive brokers and Application Programming Interfaces (APIs) for Trader Workstations (TWS). The firm’s deeply experienced team has proven itself in investment analytics as well as the broader disciplines of data analytics, data science and data management. Quant Coding is capable of developing software for the web, mobile devices and desktop computing environments—working across multiple platforms, including the Windows stack, Linux and a variety of database solutions.

“Using NLP and ML for improved trading outcomes is a win-win,” Najdovski added. “It’s good for the trading house, but it also benefits society by improving the allocative efficiency of capital markets.”

To learn more, visit https://quantcoding.com/

END
# # #

Media Relations
Quant Coding
email us here

Legal Disclaimer:

EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.