Universitätspublikationen
Refine
Year of publication
Document Type
- Working Paper (19)
- Part of Periodical (15)
- Report (2)
Has Fulltext
- yes (36)
Is part of the Bibliography
- no (36) (remove)
Keywords
- Household Finance (12)
- Consumers (4)
- Coronavirus (4)
- Household Crisis Barometer (4)
- Household income (4)
- Investor Protection (4)
- Private Investment (4)
- Financial Literacy (3)
- Household finance (3)
- Monetary Policy (3)
Institute
- Sustainable Architecture for Finance in Europe (SAFE) (36) (remove)
Self-control failure is among the major pathologies (Baumeister et al. (1994)) affecting individual investment decisions which has hardly been measurable in empirical research. We use cigarette addiction identified from checking account transactions to proxy for low self-control and compare over 5,000 smokers to 14,000 nonsmokers. Smokers self-directing their investment trade more frequently, exhibit more biases and achieve lower portfolio returns. We also find that smokers, some of which might be aware of their limited levels of self-control, exhibit a higher propensity than nonsmokers to delegate decision making to professional advisors and fund managers. We document that such precommitments work successfully.
We study the redistributive effects of inflation combining administrative bank data with an information provision experiment during an episode of historic inflation. On average, households are well-informed about prevailing inflation and are concerned about its impact on their wealth; yet, while many households know about inflation eroding nominal assets, most are unaware of nominal-debt erosion. Once they receive information on the debt-erosion channel, households update upwards their beliefs about nominal debt and their own real net wealth. These changes in beliefs causally affect actual consumption and hypothetical debt decisions. Our findings suggest that real wealth mediates the sensitivity of consumption to inflation once households are aware of the wealth effects of inflation.
Cryptocurrencies have received growing attention from individuals, the media, and regulators. However, little is known about the investors whom these financial instruments attract. Using administrative data, we describe the investment behavior of individuals who invest in cryptocurrencies with structured retail products. We find that cryptocurrency investors are active traders, prone to investment biases, and hold risky portfolios. In line with attention effects and anticipatory utility, we find that the average cryptocurrency investor substantially increases log-in and trading activity after his or her first cryptocurrency purchase. Our results document which investors are more likely to adopt new financial products and help inform regulators about investors' vulnerability to cryptocurrency investments.
Previous studies document a relationship between gambling activity at the aggregate level and investments in securities with lottery-like features. We combine data on individual gambling consumption with portfolio holdings and trading records to examine whether gambling and trading act as substitutes or complements. We find that gamblers are more likely than the average investor to hold lottery stocks, but significantly less likely than active traders who do not gamble. Our results suggest that gambling behavior across domains is less relevant compared to other portfolio characteristics that predict investing in high-risk and high-skew securities, and that gambling on and off the stock market act as substitutes to satisfy the same need, e.g., sensation seeking.
Smart(phone) investing? A within investor-time analysis of new technologies and trading behavior
(2021)
Using transaction-level data from two German banks, we study the effects of smartphones on investor behavior. Comparing trades by the same investor in the same month across different platforms, we find that smartphones increase purchasing of riskier and lottery-type assets and chasing past returns. After the adoption of smartphones, investors do not substitute trades across platforms and buy also riskier, lottery-type, and hot investments on other platforms. Using smartphones to trade specific assets or during specific hours contributes to explain our results. Digital nudges and the device screen size do not mechanically drive our results. Smartphone effects are not transitory.