96 citations · 408 across the 7 of their papers we have counts for
8 papers
Identical Runs, Different Results: Benchmarking AI Coding Agents on Open-Weight Models
Eduardo Ariño de la Rubia, Szilard Pafka
Repeated runs of the same coding agent are known to give different benchmark scores. We ask what that variation means for a team running an agent on its own task, by intensive repl…
Noise sensitivity of portfolio selection under various risk measures
Imre Kondor, Szilard Pafka, Gabor Nagy
We study the sensitivity to estimation error of portfolios optimized under various risk measures, including variance, absolute deviation, expected shortfall and maximal loss. We in…
Random Matrix Filtering in Portfolio Optimization
Gabor Papp, Szilard Pafka, Maciej A. Nowak +1
We study empirical covariance matrices in finance. Due to the limited amount of available input information, these objects incorporate a huge amount of noise, so their naive use in…
Exponential Weighting and Random-Matrix-Theory-Based Filtering of Financial Covariance Matrices for Portfolio Optimization
Szilard Pafka, Marc Potters, Imre Kondor
We introduce a covariance matrix estimator that both takes into account the heteroskedasticity of financial returns (by using an exponentially weighted moving average) and reduces…
Estimated Correlation Matrices and Portfolio Optimization
Szilard Pafka, Imre Kondor
Financial correlations play a central role in financial theory and also in many practical applications. From theoretical point of view, the key interest is in a proper description…
Noisy Covariance Matrices and Portfolio Optimization II
Szilard Pafka, Imre Kondor
Recent studies inspired by results from random matrix theory [1,2,3] found that covariance matrices determined from empirical financial time series appear to contain such a high am…