@inproceedings{69e5dbafb4424e309c6c12923f5cee25,
title = "Algorithmic daily trading based on experts{\textquoteright} recommendations",
abstract = "Trading financial products evolved from manual transactions, carried out on investors{\textquoteright} behalf by well informed market experts to automated software machines trading with millisecond latencies on continuous data feeds at computerised market exchanges. While high-frequency trading is dominated by the algorithmic robots, mid-frequency spectrum, around daily trading, seems left open for deep human intuition and complex knowledge acquired for years to make optimal trading decisions. Banks, brokerage houses and independent experts use these insights to make daily trading recommendations for individual and business customers. How good and reliable are they? This work explores the value of such expert recommendations for algorithmic trading util-ising various state of the art machine learning models in the context of ISMIS 2017 Data Mining Competition. We point at highly unstable nature of market sentiments and generally poor individual expert performances that limit the utility of their recommendations for successful trading. However, upon a thorough investigation of different competitive classification models applied to sparse features derived from experts{\textquoteright} recommendations, we identified several successful trading strategies that showed top performance in ISMIS 2017 Competition and retrospectively analysed how to prevent such models from over-fitting.",
keywords = "Algorithmic trading, Classification, Feature selection, Gradient boosting decision trees, K-nn, Sparse features",
author = "Andrzej Ruta and Dymitr Ruta and Ling Cen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 23rd International Symposium on Methodologies for Intelligent Systems, ISMIS 2017 ; Conference date: 26-06-2017 Through 29-06-2017",
year = "2017",
doi = "10.1007/978-3-319-60438-1_72",
language = "British English",
isbn = "9783319604374",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "736--744",
editor = "Marzena Kryszkiewicz and Henryk Rybinski and Ras, {Zbigniew W.} and Dominik Slezak and Andrzej Skowron and Annalisa Appice and Andrzej Skowron",
booktitle = "Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings",
address = "Germany",
}