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International Workshop on Enterprise Applications, Markets and Services in the Finance Industry

FinanceCom 2020: Enterprise Applications, Markets and Services in the Finance Industry pp 92–108Cite as

What Do Robo-Advisors Recommend? - An Analysis of Portfolio Structure, Performance and Risk

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 401))

Abstract

Robo-Advisors guide investors through an automated investment advisory process, recommend personalized portfolio assignments based on their individual risk-affinity as well as investment goals and rebalance the portfolio automatically over time. Giving basic investment advice to customers, it can provide a useful way to reduce risk by diversifying and mitigating biases, while keeping a certain degree of performance at low costs. To verify these claims we conduct a sophisticated analysis of recommended portfolios of 36 Robo-Advisors, based on six distinct model customers with different risk-affinities and investment horizons, resulting in 216 recommended portfolios. We find that the analyzed Robo-Advisors provide distinct recommended portfolios for the different risk/investment horizon combinations, while sharing similarities in used products for portfolio allocation. We also find issues within the recommended portfolios, e.g. a low degree of distinctiveness between different investment horizons and a high amount of equities even in the short-term investment horizon.

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Author information

Authors and Affiliations

  1. Chair of Electronic Finance and Digital Markets, University of Goettingen, Goettingen, Germany

    Albert Torno & Sören Schildmann

Authors
  1. Albert Torno
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  2. Sören Schildmann
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Corresponding author

Correspondence to Albert Torno .

Editor information

Editors and Affiliations

  1. Goethe University Frankfurt, Frankfurt, Germany

    Benjamin Clapham

  2. Goethe University Frankfurt, Frankfurt, Germany

    Jascha-Alexander Koch

Appendix

Appendix

Table 4. Exemplary static characteristics of model customer
Full size table
Table 5. Exemplary questions concerning dynamic characteristics of model customer
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Table 6. Analyzed Robo-Advisors
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Torno, A., Schildmann, S. (2020). What Do Robo-Advisors Recommend? - An Analysis of Portfolio Structure, Performance and Risk. In: Clapham, B., Koch, JA. (eds) Enterprise Applications, Markets and Services in the Finance Industry. FinanceCom 2020. Lecture Notes in Business Information Processing, vol 401. Springer, Cham. https://doi.org/10.1007/978-3-030-64466-6_6

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  • DOI: https://doi.org/10.1007/978-3-030-64466-6_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64465-9

  • Online ISBN: 978-3-030-64466-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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