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

2 citations · 2 across the 5 of their papers we have counts for

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5 papers

q-fin.PM2024

Construction and Hedging of Equity Index Options Portfolios

Maciej Wysocki, Robert Ślepaczuk

This research presents a comprehensive evaluation of systematic index option-writing strategies, focusing on S&P500 index options. We compare the performance of hedging strategies…

q-fin.TR2024

LSTM-ARIMA as a Hybrid Approach in Algorithmic Investment Strategies

Kamil Kashif, Robert Ślepaczuk

This study focuses on building an algorithmic investment strategy employing a hybrid approach that combines LSTM and ARIMA models referred to as LSTM-ARIMA. This unique algorithm u…

q-fin.PM2024

Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market

Adam Korniejczuk, Robert Ślepaczuk

The study seeks to develop an effective strategy based on the novel framework of statistical arbitrage based on graph clustering algorithms. Amalgamation of quantitative and machin…

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.CP20232 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…