Systematic multi-assets arbitrage strategies and use of heterogeneous data

Financial markets evolve more or less rapidly and strongly to all kind of information depending on time period of study. In this context, we intend to measure a broad set of information influence on systematic multi-assets classes “euro neutral” arbitrage portfolios either for “naive” diversification and optimal diversification. Our research focuses on systematic tactical asset allocation and we group these information under the name of heterogeneous data (market data and “other market information”). Market data are “end of day” asset closing prices and “other market information” gather economic cycle, sentiment and volatility indicators. We assess the influence of a heterogeneous data combination on our arbitrage portfolios for a time period including the subprimes crisis period and thanks to data analysis and quantization algorithms. The impact of a heterogeneous data combination on our arbitrage portfolio is materialized by increasing return, increasing return/volatility ratio for the post subprimes crisis period, decreasing volatility and asset class correlations. These empirical findings suggest that “other market information” presence could be an element of arbitrage portfolio risk diversification. Furthermore, we investigate and bring empirical results to Blitz and Vliet (2008) issue on global tactical asset allocation (GTAA) by considering “predictive” variables with a systematic market timing process integrating heterogeneous data thanks to a quantitative data processing.

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Source https://theses.hal.science/tel-00987635
Author Fereres, Yohan
Maintainer CCSD
Last Updated May 5, 2026, 12:02 (UTC)
Created May 5, 2026, 12:02 (UTC)
Identifier NNT: 2013PEST0075
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Institut de Recherche en Gestion (IRG) ; Université Paris-Est Marne-la-Vallée (UPEM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)
creator Fereres, Yohan
date 2013-12-10T00:00:00
harvest_object_id 825e2dbc-0b4c-4126-b833-dee417b40ec9
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE