Our team
Anufriiev
Oleg is finance professional and tech entrepreneur who launched multiple successful businesses. He possesses 15+ years experience as financial advisor and trader, holds MS in mathematics and financial law. Oleg obtained Certified Project Management associate degree from IPMA.
Rizvanov
Mr. Rizvanov is an extraordinary AI/ML specialist who created a face recognition system at Viewdle (acquired by Google). He also led the team that created the face-tracking technology of Snap lenses. Roman won a Bronze medal at the International Olympiad in Informatics and participated at the ACM ICPC World Finals. He holds Masters degree in Applied Mathematics from Taras Shevchenko National University of Kyiv.
Monastyrshyn
Yurii is a serial entrepreneur and investor. Co-founder of Looksery Inc that was acquired by Snap for 150M$. Ex Sr. Director of Engineering at Snap where he was leading the development of Snap AR platform from its inception. Yurii got Applied Mathematics degree at Odessa National University and is a prize winner of multiple programming contests.
Bilyi
Roman Bilyi is the well-recognized specialist in ML and AI, who worked as a key researcher in several AI startups. Roman won Bronze medal in ACM ICPC World Finals. Also he reached the 11th place at Facebook hackers Cup finals, 2018 among 8216 participants. Roman held Legendary Grandmaster title at Codeforces (7th rank among 56000). He holds Masters degree in Applied Mathematics from Lviv National University.
Maksym Kovalchuk is a remarkable programmer and researcher with a foundation in mathematics, competitive programming, and ML. Maksym achieved high ranking in the Ukrainian Olympiad in Informatics and in competitions organized by the Minor Academy of Sciences of Ukraine. During university years, he has consistently secured top10 placements in various optimization contests, most notably achieving 1st place in the Bioinformatics Contest 2021 and 2nd place in the ICPC Challenge 2020. Maksym holds Bachelor’s degree in Computer Science, Taras Shevchenko National University of Kyiv.
Rizvanov
Rinat Rizvanov is a leading Machine Learning Engineer who specializes in trading model’s optimization and opinion mining of social networks, e.g. Twitter. He was the Participant of III stage of Ukrainian Olympiad in Informatics and programming contest held by Minor Academy of Sciences of Ukraine. Rinat holds Bachelor’s degree in Reprography, NTUU “KPI".
Orlov
Anton Orlov is a software engineer with a wide experience. He worked as System Administrator, Software Engineer, Team Leader and taught his own course about Software Engineering. As a student he has authored multiple scientific papers in Software Engineering and Information Retrieval sphere. Anton holds Masters degree in Applied Mathematics from Saint-Petersburg State University. He also set a Guinness Book record as a "strongest boy" in his childhood.
Vitaliy is a talented software engineer who has participated in the ICPC and other contests, demonstrating his skills in algorithmic problem-solving and competitive programming. He has worked on projects involving distributed systems and network communication, specializing in improving system performance and reliability. He is currently pursuing his Bachelor’s degree in Applied Mathematics at Odessa I.I. Mechnikov National University.
Research Timeline
A multi-currency trading model has been implemented
A new volatility-adaptable model has been implemented
New live model parameter optimization was implemented
Probabilistic risk model of the fund's assets allocation was developed
A new update that significantly improves the handling of market liquidity has been implemented
Market maker algorithm implemented
Updated bot version now includes new position size optimisation
Release of live parameters optimization bot
Testing of live parameters optimization bot
Updated version of Trading algo which normalize trading volume is deployed
Testing of models ensemble to fine tune the results of Trading bot
Advanced statistics tracking liquidity issues is implemented
Launch of Private Fund
New version of trading algo is deployed
Parallel backtesting which traces algo performance in real-time is implemented
Advanced market making algorithm is developed
Launch of cutting-edge new AI long/short algo on cyryptomarkets
Algo backtesting and bug fixing
Advanced Backtester with Algo parameters optimization feature is developed
Based on internal research pivot to cryptomarkets is done due to much higher risk/reward ratio
New advanced neural network architectures are implemented
Liquidity issues fixed
Proprietary algo ranking system is developed
Series of practical experiments were hold in Tesoro (more details in Research section)
Testing of VIX trading algorithm using VX futures combos
1st working neural network architecture implemented
Testing of different approaches to trading on futures and stock markets
Start of the development of brand new AI trading algo
Top AI/ML researchers joined Tesoro Management
Extended deep research of VIX and VIX term structure
VIX research using statistical methods
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