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20232025
most citedMean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

q-fin.CP2025

Alternative Loss Function in Evaluation of Transformer Models

Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk

The proper design and architecture of testing machine learning models, especially in their application to quantitative finance problems, is crucial. The most important aspect of th…

q-fin.CP2024

Generalized Mean Absolute Directional Loss for Machine Learning Trading Models

Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk

The article presents and evaluates a custom loss function designed specifically for machine learning models used in algorithmic trading. Regardless of the selected asset class and…

q-fin.PM2023

Hedging Properties of Algorithmic Investment Strategies using Long Short-Term Memory and Time Series models for Equity Indices

Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk

This paper proposes a novel approach to hedging portfolios of risky assets when financial markets are affected by financial turmoils. We introduce a completely novel approach to di…

q-fin.CP2023★ 2 cited

Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies

Jakub Michańków, Paweł Sakowski, Robert Ślepaczuk

This paper investigates the issue of an adequate loss function in the optimization of machine learning models used in the forecasting of financial time series for the purpose of al…

q-fin.RM2023★ 1 cited

Systemic risk indicator based on implied and realized volatility

Paweł Sakowski, Rafał Sieradzki, Robert Ślepaczuk

We propose a new measure of systemic risk to analyze the impact of the major financial market turmoils in the stock markets from 2000 to 2023 in the USA, Europe, Brazil, and Japan.…