Robo Advisers and Mutual Fund Stickiness

Reher, Michael; Sun, Celine

doi:10.2139/ssrn.2872134

Cited by 4 publications

(3 citation statements)

References 25 publications

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“…Having parallel pretrends is important in order to conclude that any observed performance changes during market downturn is not merely a continuation of preexisting differences. Similar to the common practice in the literature (e.g., Cui, 2022; Kumar & Telang, 2012; Reher & Sokolinski, 2023), we use a relative time model where

RoboUse{r_i}

is interacted with a series of weekly dummy indicators both before and after the market crash (with one week prior to the crash as the baseline). All other variables are kept the same.…”

Section: Resultsmentioning

confidence: 99%

Judge me on my losers: Do robo‐advisors outperform human investors during the COVID‐19 financial market crash?

Liu

Yang

Wen

2023

Production and Operations Management

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As financial institutions increasingly offer robo‐advisors (RAs) as a service, the empirical evidence on their performance, particularly during market downturns, remains limited. We study the impact of using RAs on investment performance during the 2020 financial crisis caused by the COVID‐19 global pandemic. We obtain daily portfolio and transaction data of investors on an online investment platform. Besides making investment decisions by themselves, investors can also leverage an RA system offered by the platform. We match RA users with other investors who did not use the RA with similar investor and portfolio characteristics before the market crash, then compare their portfolio returns after the crash. We find that RA users experienced significantly fewer losses during the market downturn, and this performance advantage came from the RA‐managed assets (rather than assets managed by RA users themselves). We further show that the RA system adjusted its portfolios to hold less risky funds, whereas human investors stayed with their status quo and did not reduce the risk of their portfolios, which partly accounted for the performance discrepancy. Importantly, the RA’s superior performance was not simply a continuation of its performance in a normal market; in fact, we find RA users to have similar portfolio returns as non‐RA investors during normal markets, and the benefits of RA's risk‐reduction trading strategy only manifested during the financial crisis. Our work offers an empirical assessment of RAs’ performance under different market conditions and advances the understanding of algorithmic decision making in financial markets.

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RoboUse{r_i}

is interacted with a series of weekly dummy indicators both before and after the market crash (with one week prior to the crash as the baseline). All other variables are kept the same.…”

Section: Resultsmentioning

confidence: 99%

Judge me on my losers: Do robo‐advisors outperform human investors during the COVID‐19 financial market crash?

Liu

Yang

Wen

2023

Production and Operations Management

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“…The results effected by such a use of systems is clearly visible when the efficiency of Robo-Advice platforms is scrutinised. A research conducted by Reher & Sun [2016] shows that the platforms outmatch both portfolios of self-managed funds and mutual investment funds (risk adjusted). This advocates for modern theory of portfolio, as well as for passive investment strategy of Robo-Advice platforms.…”

Section: Strengths Of Robo-advicementioning

confidence: 99%

Robo-advisors as Automated Personal Financial Planners – SWOT Analysis

Waliszewski¹,

Zięba-Szklarska²

2020

FiPF

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Automatic financial consulting (robo-advice) is a financial innovation in the area of personal financial planning, and in particular investment consulting classified as fin-tech (financial technology). The main disadvantage of traditional investment advice is limited availability due to the required amount of assets and high management costs. These disadvantages are answered by robo-advice, using artificial intelligence and algorithms without the participation of a physical adviser, thereby reducing or abolishing minimal assets and reducing costs [Kocianski 2016]. The purpose of the article is to analyze strengths and weaknesses as well as opportunities and threats of robo-advisors, especially when compared to traditional financial advisors. This paper is an analysis of a history, regulations, application, functionality and development of Robo-Advice. The concept of Robo-Advice was critically analysed, with presentation of current strength and weaknesses, as well as opportunities and threats. We aimed showing that Robo-Advice should be innovative, feature a new approach, and should transform the current financial consulting. There are still, however, many opportunities and challenges in this field, which await discovering. The article uses the SWOT analysis method, analysis of the literature and reports. As indicated by the analysis, robo-advisors are not a threat to traditional financial advisors, but their complement, which makes the hybrid model connecting a physical advisor assisted by technological solutions (robo-advisors) most likely. This thesis is also confirmed by the small scale of robo-advisors’ activity compared to traditional advisors measured by the market penetration rate (in 2023 about 2% assets under management).

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“…Scholars have studied the design of robo-advisors [3,4,19], as well as their ability to improve diversification and performance [20], eliminate behavioral biases [7] and assess risk preferences [21]. In the legal domain, potential conflicts of interest and liability issues have been discussed [22,23].…”

Section: (Digital) Investment Managementmentioning

confidence: 99%

A Classification of Decision Automation and Delegation in Digital Investment Management Systems

Rühr¹,

Streich²,

Berger³

et al. 2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Digital investment management systems, commonly known as robo-advisors, provide new alternatives to traditional human services, offering competitive investment returns at lower cost and customer effort. However, users must give up control over their investments and rely on automated decision-making. Because humans display aversion to high levels of automation and delegation, it is important to understand the interplay of these two aspects. This study proposes a taxonomy of digital investment management systems based on their levels of decision automation and delegation along the investment management process. We find that the degree of automation depends on the frequency and urgency of decisions as well as the accuracy of algorithms. Notably, most providers only invest in a subset of funds pre-selected by humans, potentially limiting efficiency gains. Based on our taxonomy, we identify archetypical system designs, which facilitate further research on perception and adoption of digital investment management systems.

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Robo Advisers and Mutual Fund Stickiness

Cited by 4 publications

References 25 publications

Judge me on my losers: Do robo‐advisors outperform human investors during the COVID‐19 financial market crash?

Judge me on my losers: Do robo‐advisors outperform human investors during the COVID‐19 financial market crash?

Robo-advisors as Automated Personal Financial Planners – SWOT Analysis

A Classification of Decision Automation and Delegation in Digital Investment Management Systems

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