2 citations · 3 across the 9 of their papers we have counts for
10 papers
Evolution-Bootstrapped Simulation: Artificial or Human Intelligence: Which Came First?
Paul Alexander Bilokon
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,…
From Deep Filtering to Deep Econometrics
Robert Stok, Paul Bilokon
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 p…
Applying Deep Learning to Calibrate Stochastic Volatility Models
Abir Sridi, Paul Bilokon
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…
Derivatives Sensitivities Computation under Heston Model on GPU
Pierre-Antoine Arsaguet, Paul Bilokon
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 simulat…
Real-time VaR Calculations for Crypto Derivatives in kdb+/q
Yutong Chen, Paul Bilokon, Conan Hales +1
Cryptocurrency market is known for exhibiting significantly higher volatility than traditional asset classes. Efficient and adequate risk calculation is vital for managing risk exp…
C++ Design Patterns for Low-latency Applications Including High-frequency Trading
Paul Bilokon, Burak Gunduz
This work aims to bridge the existing knowledge gap in the optimisation of latency-critical code, specifically focusing on high-frequency trading (HFT) systems. The research culmin…
Semi-static Conditions in Low-latency C++ for High Frequency Trading: Better than Branch Prediction Hints
Paul Alexander Bilokon, Maximilian Lucuta, Erez Shermer
Conditional branches pose a challenge for code optimisation, particularly in low latency settings. For better performance, processors leverage dedicated hardware to predict the out…
Benchmarking Specialized Databases for High-frequency Data
Fazl Barez, Paul Bilokon, Ruijie Xiong
This paper presents a benchmarking suite designed for the evaluation and comparison of time series databases for high-frequency data, with a focus on financial applications. The pr…
Quasi-Monte Carlo methods for calculating derivatives sensitivities on the GPU
Paul Bilokon, Sergei Kucherenko, Casey Williams
The calculation of option Greeks is vital for risk management. Traditional pathwise and finite-difference methods work poorly for higher-order Greeks and options with discontinuous…
Iterated and exponentially weighted moving principal component analysis
Paul Bilokon, David Finkelstein
The principal component analysis (PCA) is a staple statistical and unsupervised machine learning technique in finance. The application of PCA in a financial setting is associated w…