The effects of robo-advisers on stock market participation and household investment behavior

A TFI research project by Vincent Skiera
Posted on July 02, 2021

Participating in the financial market isn't for everyone, and rightfully so. Investing is risky and can lead to consequences if you don't have the proper background knowledge. That is the one of the reasons why many people tend to choose investments with the least amount of risk. But what if there was a tool that would help introduce people to investing based on their investing preference and risk appetite? In this TFI research report, Vincent Skiera explores how Robo-advisers influence one's participation in the financial market as well as investment behavior.


Download the report or read about the summary below to find out about the results

In developed countries, stock market participation is surprisingly low. In Germany, for example, less than one-sixth of the population invests in stocks (Deutsches Aktieninstitut, 2019). In the US, the average "middle-aged" US family (a family led by an individual aged 41–60) holds more wealth in cars than in stocks (Ravikumar & Karson, 2018). Moreover, even high-income families invest far less in the stock market than might be expected. For example, only 40% of US households making an income between $100,000 and $200,000 even invest in stocks (Chien & Morris, 2017).

A lack of financial literacy is a key reason why households feel uncomfortable investing in the financial market (Deutsches Aktieninstitut, 2019). Until recently, reliance on the assistance of a professional financial adviser was the primary means of overcoming this obstacle. However, this solution was out of reach for most households, as financial advisers commonly require high minimum investments (often 500,000 Euro) to compensate for the cost of human labor. However, this situation is beginning to change due to recent developments in FinTech, which have replaced human labor with machines in many financial services, thereby reducing costs. Such technologies have the potential to bring many personalized services, previously only available to high-net-worth households, to the average retail investor. One such service, at the focus of this study, is the Robo-Adviser—an automated system that invests clients' money according to academically vetted principles like Value-at-Risk or Strategic Asset Allocations, while personalizing investment portfolios to each retail investor.

The process of investing with a Robo-Adviser generally works as follows. First, the retail investor fills out a survey indicating his or her investment preferences (e.g., with regard to risk tolerance) and allocates the Robo-Adviser a sum of money for investment. Then, on the basis of the client's elicited preferences, the Robo-Adviser determines how to invest the money into ETFs covering most asset classes (stocks, corporate bonds, sovereign bonds, and real estate, among others) and most regions of the world. As the prices of ETFs change, the Robo-Adviser determines how to adapt the portfolio so as to retain an investment allocation that is aligned with the retail investor's preferences. Because the investment process is fully automated—from determining the retail investor's risk preferences to the Robo-Adviser's actual investment decisions—Robo-Advisers require much lower minimum investments compared with (human) financial advisers. Moreover, their management fees are lower than those charged by human advisers—which can exceed 1.5% annually for the underlying products[1].



The lower minimum amounts suggest that Robo-Advisers can lower the barriers preventing retail investors from accessing financial advice—and thus increase stock market participation of households that might otherwise opt out because of low financial literacy. But do Robo-Advisers indeed fulfill this potential? To examine this question, we carried out a study to in collaboration with a large German retail bank that introduced a Robo-Adviser service in 2017. We investigated whether, over time, the Robo-Adviser attracted new households to participate in financial markets.

Specifically, we compared a sample of users who began to use the Robo-Adviser in the year of its introduction (treatment group) with a random sample of bank customers who did not adopt the Robo-Adviser but who traded at least once in the year in which the Robo-Adviser was introduced (control group). Figure 1 shows the percentage of users in each group who joined the market for the first time in 2016—the year before the introduction of the Robo-Adviser—and in 2017, the year of the Robo-Adviser's introduction. The percentage of investors who joined the market in 2016 was similar in the two groups—roughly 5%. In 2017, in contrast, the percentage of new market participants differed starkly between the groups: 7% in the control group, as compared with 36.25% in the group of retail investors who invested with the Robo-Adviser. While we cannot rule out that investors held portfolios at other banks, we have reasons to believe that these retail investors are really new to financial markets, especially if they invest through the Robo-Adviser (see the accompanying technical report). On the basis of these findings, we determine that, in 2017, the Robo-Adviser attracted 3,462 new investors that otherwise would not have participated in financial markets[2]. It is worth noting, however, that the initial investment requirement of the Robo-Adviser seems to be a barrier to adoption. Many retail investors invest at or near the minimum investment requirement, suggesting that they would ideally invest a lower amount.


Figure 1: Share of Retail Investors New to Financial Market

Note: This bar graph shows the share of new participants in financial markets for 2016 and 2017, in both the control group of retail investors and Robo-Adviser users. We classify a retail investor as a new participant in financial markets if the retail investor starts investing with either the Robo-Adviser or in an active portfolio for the first time that year.

We recognize that investing with a Robo-Adviser is not a binary choice. Indeed, most retail investors have an active portfolio besides their investment with the Robo-Adviser. Our evidence suggests that these investors approached the Robo-Adviser as more of a "curiosity" rather than as a replacement for investing done by the retail investor. They invest close to the minimum amount with the Robo-Adviser. Therefore, the main effect of the Robo-Adviser mainly affects their investment outcome through spillovers on their active investing.

Compared with the portfolio of the typical retail investor, the Robo-Adviser's investments are more diversified, comprising ETFs. Another difference is that the Robo-Adviser trades much more frequently than the retail investor—82.99 times on average per year, compared with 21.85 times, respectively. Retail investors would benefit from adopting greater diversification but would lose from trading more frequently, since compared to the Robo-Adviser they pay much higher costs to trade.

We find, however, that usage of the Robo-Adviser did not affect the behavior of retail investors who managed active portfolios, in terms of either diversification or trading frequency. This result is in line with prior findings (Koestner, Loos, Meyer, & Hackethal, 2017) that retail investors have a hard time avoiding past mistakes. The accompanying technical report provides more details.

Summing up, we conclude that the Robo-Adviser increases participation in financial markets by attracting retail investors who would otherwise not have participated, possibly because of their perceived lack of financial literacy. Nevertheless, the minimal investment amount required for such services may still be a barrier to adoption. For retail investors who also manage active portfolios on their own, the Robo-Adviser does not seem beneficial. Still, this lack of benefit is likely to be outweighed by the potential increase in societal welfare associated with expanded market participation—particularly in countries such as Germany, where only 16.2% of the population owns stocks.

Footnotes

  1. [1] There is a separate discussion of whether advisers deliver on the fees that they are paid. Traditionally, studies in this vein have focused on human advisers (Hackethal, Haliassos, & Jappelli, 2012). However, similar criticism applies to non-human advisers, but is beyond the scope of this paper.
  2. [2] We also determine whether the Robo-Adviser deterred investors from investing on their own, i.e., would have invested in financial markets without the introduction of the Robo-Adviser. However, we find no evidence that the number of active investors in the control group is in any way changed—suggesting that Robo-Adviser services are indeed expanding stock market participation. See the accompanying technical report for an in-depth discussion of these results.

References

  • Abraham, F., Schmukler, S. L., & Tessada, J. (2019). Robo-Advising: Investing through Machines. Research and Policy Briefs(21), 1-4.
  • Barber, B., & Odean, T. (2000). Trading Is Hazardous to Your Wealth:The Common Stock Investment Performance of Individual Investors. Journal of Finance, 55(2), 773-806.
  • Barras, L., Scaillet, O., & Wermers, R. (2010). False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas. Journal of Finance, 65(1), 179-216.
  • Chien, Y., & Morris, P. (2017). Household Participation in Stock Market Varies Widely by State. The Regional Economist, 4-5.
  • D’Acunto, F., Prabhala, N., & Rossi, A. G. (2019). The Promises and Pitfalls of Robo-Advising. Review of Financial Studies, 32(5), 1983-2020.
  • D’Hondt, C., Winne, R. D., Ghysels, E., & Raymond, S. (2019). Artificial Intelligence Alter Egos: Who benefits from Robo-Investing. Working Paper.
  • Deutsches Aktieninstitut. (2019). Aktionärszahlen des deutschen Aktieninstituts 2018. Frankfurt a.M.: Deutsches Aktieninstitut e.V.
  • Deutsches Aktieninstitut. (2019). Mehr Aktionäre in Deutschland. Frankfurt a.M.: Deutsches Aktieninstitut e.V.
  • Fama, E. F., & French, K. R. (2010). Luck versus Skill in the Cross-Section of Mutual Fund Returns. Journal of Finance, 65(5), 1915-1947.
  • Gallup. (2019). What Percentage of Americans Owns Stocks?
  • Goldstein, I., Jiang, W., & Karolyi, G. A. (2019). To FinTech and Beyond. Review of Financial Studies`, 332(5), 1647-1661.
  • Hackethal, A., Haliassos, M., & Jappelli, T. (2012). Financial Advisors: A Case of Babysitters. Journal of Banking and Finance, 36(2), 509-524.
  • Jappelli, T. (2010). Economic Literacy: An International Comparison. Economic Journal, 120(548), 429-451.
  • Koestner, M., Loos, B., Meyer, S., & Hackethal, A. (2017). Do Individual Investors Learn from their Mistakes? Journal of Business Economics, 87(5), 669-704.
  • Lusardi, A., & Mitchell, O. S. (2011). Financial Literacy around the World: An Overview. Journal of Pension Economics and Finance, 10(4), 497-508.
  • Markowitz, H. (1952). Portfolio Selection. Journal of Finance, 7(1), 77-97.
  • Ravikumar, B., & Karson, E. (2018). How Has Stock Ownership Trended in the Past Few Decades? St. Louis Fed On the Economy.
  • van Rooij, M. C., Lusardi, A., & Alessie, R. J. (2012). Financial Literacy, Retirement Planning and Household Wealth. Economics Journal, 122(560), 449-478.