Practical investment with the long-short game

Najim Al-Baghdadi, David Lindsay, Yuri Kalnishkan, Sian Lindsay
Proceedings of the Ninth Symposium on Conformal and Probabilistic Prediction and Applications, PMLR 128:209-228, 2020.

Abstract

In this paper we apply the aggregating algorithm, an on-line prediction with expert advice algorithm, to real-world foreign exchange trading data with the aim of finding investment strategies with optimal returns. We consider the Long-Short game first introduced in Vovk and Watkins (1998) and it’s implementation, including the derivation of expert predictions from model trading data. Furthermore, we propose modifications to improve the practical performance of the game with respect to well-known portfolio performance indicators.

Cite this Paper

BibTeX
@InProceedings{pmlr-v128-al-baghdadi20a, title = {Practical investment with the long-short game}, author = {Al-Baghdadi, Najim and Lindsay, David and Kalnishkan, Yuri and Lindsay, Sian}, booktitle = {Proceedings of the Ninth Symposium on Conformal and Probabilistic Prediction and Applications}, pages = {209--228}, year = {2020}, editor = {Gammerman, Alexander and Vovk, Vladimir and Luo, Zhiyuan and Smirnov, Evgueni and Cherubin, Giovanni}, volume = {128}, series = {Proceedings of Machine Learning Research}, month = {09--11 Sep}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v128/al-baghdadi20a/al-baghdadi20a.pdf}, url = {https://proceedings.mlr.press/v128/al-baghdadi20a.html}, abstract = {In this paper we apply the aggregating algorithm, an on-line prediction with expert advice algorithm, to real-world foreign exchange trading data with the aim of finding investment strategies with optimal returns. We consider the Long-Short game first introduced in Vovk and Watkins (1998) and it’s implementation, including the derivation of expert predictions from model trading data. Furthermore, we propose modifications to improve the practical performance of the game with respect to well-known portfolio performance indicators.} }
Endnote
%0 Conference Paper %T Practical investment with the long-short game %A Najim Al-Baghdadi %A David Lindsay %A Yuri Kalnishkan %A Sian Lindsay %B Proceedings of the Ninth Symposium on Conformal and Probabilistic Prediction and Applications %C Proceedings of Machine Learning Research %D 2020 %E Alexander Gammerman %E Vladimir Vovk %E Zhiyuan Luo %E Evgueni Smirnov %E Giovanni Cherubin %F pmlr-v128-al-baghdadi20a %I PMLR %P 209--228 %U https://proceedings.mlr.press/v128/al-baghdadi20a.html %V 128 %X In this paper we apply the aggregating algorithm, an on-line prediction with expert advice algorithm, to real-world foreign exchange trading data with the aim of finding investment strategies with optimal returns. We consider the Long-Short game first introduced in Vovk and Watkins (1998) and it’s implementation, including the derivation of expert predictions from model trading data. Furthermore, we propose modifications to improve the practical performance of the game with respect to well-known portfolio performance indicators.
APA
Al-Baghdadi, N., Lindsay, D., Kalnishkan, Y. & Lindsay, S.. (2020). Practical investment with the long-short game. Proceedings of the Ninth Symposium on Conformal and Probabilistic Prediction and Applications, in Proceedings of Machine Learning Research 128:209-228 Available from https://proceedings.mlr.press/v128/al-baghdadi20a.html.

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