[PDF] Robo-Advisors: Investing Through Machines | Semantic Scholar (2024)

A novel framework in which a robo-advisor interacts with a client to solve an adaptive mean-variance portfolio optimization problem is introduced and it is argued that the optimal portfolio’s Sharpe ratio and return distribution improve if the robos counters the clients’ tendency to reduce market exposure during economic contractions when the market risk-return tradeoff is more favorable.

How robo-advice could potentially address some fundamental problems in investors’ decision making as well as in traditional financial advice and how new forms of AI applied to financial services would benefit from importing insights from economics and psychology to design effective human/robot interaction.

Analysis of the development of robo-advisory on a global scale from an evolutionary point of view, focusing on the variety of methods applied by the advisors and the factors influencing their performance between 2018 and 2021 by regression analysis, shows that modern portfolio theory remains the primary framework used by roba-advisors.

The study proposes a theoretical framework that combines the divergence of opinion hypothesis with consumer behavior insights and information technology diffusion research and results show that in a pre-chasm market, overconfident investors have a significantly higher propensity of adopting robo-advice.

The results indicate that the number of robo-advisor users, assets under management amount, and the penetration rate increased even in 2020, as covered by the Covid-19 pandemic, and assets under Management amount per person decreased.

The concept of digital twin (DT) as the next frontier of robo-advisor as a new wave of intelligent financial advisors in supporting the personalisation and customisation of financial technology (FinTech) services and management is assessed.

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The predominant robo-advisor model is investigated, uncovering that however novel this solution might be, it also relies religiously on imperative contributions to modern portfolio theory that have been made in the past half a century.

The postulation that RAs have an edge over traditional wealth managers is examined, which is expected to respond by providing new and improved customized and integrated services at competitive fees.

The view is that the emergence of digital entrants into the wealth management space will indeed change the industry in several ways and ultimately benefit new and existing investors alike by providing better and more affordable products and services through an improved client experience.

The possibilities offered by computer power for increasing the choices available to people and communities are overshadowed by the economically and socially divisive effects of computers where they are introduced into a competitive world.

This book applies modern techniques of analysis and computation to find combinations of securities that best meet the needs of private or institutional investors.

The challenges and opportunities that financial technology innovations present for banks in emerging market economies are explored, and a viable digital alternative to traditional banks is offered.

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