5 citations · 5 across the 3 of their papers we have counts for
3 papers
q-fin.MF2026
Efficient Multivariate Kelly Optimization Reveals Sigmoidal Scaling Laws
Ruslan Tepelyan, Daniel Lam
For a sequence of binary bets, the Kelly criterion provides a closed-form solution that maximizes the expected growth rate of wealth. In contrast, when multiple bets are placed sim…
q-fin.ST2025
Enhancing OHLC Data with Timing Features: A Machine Learning Evaluation
Ruslan Tepelyan
OHLC bar data is a widely used format for representing financial asset prices over time due to its balance of simplicity and informativeness. Bloomberg has recently introduced a ne…
q-fin.ST2023★ 5 cited
Generative Machine Learning for Multivariate Equity Returns
Ruslan Tepelyan, Achintya Gopal
The use of machine learning to generate synthetic data has grown in popularity with the proliferation of text-to-image models and especially large language models. The core methodo…