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pro vyhledávání: '"Bilokon, Paul"'
AIAltMed is a cutting-edge platform designed for drug discovery and repurposing. It utilizes Tanimoto similarity to identify structurally similar non-medicinal compounds to known medicinal ones. This preprint introduces AIAltMed, discusses the concep
Externí odkaz:
http://arxiv.org/abs/2407.02126
Autor:
Bilokon, Paul Alexander
Humans have created artificial intelligence (AI), not the other way around. This statement is deceptively obvious. In this note, we decided to challenge this statement as a small, lighthearted Gedankenexperiment. We ask a simple question: in a world
Externí odkaz:
http://arxiv.org/abs/2402.00030
Autor:
Jaddu, Koti S., Bilokon, Paul A.
High-frequency trading is prevalent, where automated decisions must be made quickly to take advantage of price imbalances and patterns in price action that forecast near-future movements. While many algorithms have been explored and tested, analytica
Externí odkaz:
http://arxiv.org/abs/2311.02088
Autor:
Bilokon, Paul Alexander
In academic literature portfolio risk management and hedging are often versed in the language of stochastic control and Hamilton--Jacobi--Bellman~(HJB) equations in continuous time. In practice the continuous-time framework of stochastic control may
Externí odkaz:
http://arxiv.org/abs/2309.15767
Autor:
Bilokon, Paul, Qiu, Yitao
With the rapid development of artificial intelligence, long short term memory (LSTM), one kind of recurrent neural network (RNN), has been widely applied in time series prediction. Like RNN, Transformer is designed to handle the sequential data. As T
Externí odkaz:
http://arxiv.org/abs/2309.11400
This report investigates the computation of option Greeks for European and Asian options under the Heston stochastic volatility model on GPU. We first implemented the exact simulation method proposed by Broadie and Kaya and used it as a baseline for
Externí odkaz:
http://arxiv.org/abs/2309.10477
Autor:
Sridi, Abir, Bilokon, Paul
Stochastic volatility models, where the volatility is a stochastic process, can capture most of the essential stylized facts of implied volatility surfaces and give more realistic dynamics of the volatility smile/skew. However, they come with the sig
Externí odkaz:
http://arxiv.org/abs/2309.07843
Autor:
Stok, Robert, Bilokon, Paul
Calculating true volatility is an essential task for option pricing and risk management. However, it is made difficult by market microstructure noise. Particle filtering has been proposed to solve this problem as it favorable statistical properties,
Externí odkaz:
http://arxiv.org/abs/2311.06256
Cryptocurrency market is known for exhibiting significantly higher volatility than traditional asset classes. Efficient and adequate risk calculation is vital for managing risk exposures in such market environments where extreme price fluctuations oc
Externí odkaz:
http://arxiv.org/abs/2309.06393
Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed by such models. While data sources are application-spec
Externí odkaz:
http://arxiv.org/abs/2309.05682