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Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
Consuming dividends
(2020)
This paper studies why investors buy dividend-paying assets and how they time their consumption accordingly. We combine administrative bank data linking customers’ consumption transactions and income to detailed portfolio data and survey responses on financial behavior. We find that private consumption is excessively sensitive to dividend income. Investors across wealth, income, and age distributions increase spending precisely around days of dividend receipt. Importantly, the consumption response is driven by financially prudent investors who select dividend portfolios, anticipate dividend income, and plan consumption accordingly. Our results contribute to the literature on a dividend clientele and provide evidence of ‘planned’ excess sensitivity.
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.
Manipulative communications touting stocks are common in capital markets around the world. Although the price distortions created by so-called “pump-and-dump” schemes are well known, little is known about the investors in these frauds. By examining 421 “pump-and-dump” schemes between 2002 and 2015 and a proprietary set of trading records for over 110,000 individual investors from a major German bank, we provide evidence on the participation rate, magnitude of the investments, losses, and the characteristics of the individuals who invest in such schemes. Our evidence suggests that participation is quite common and involves sizable losses, with nearly 6% of active investors participating in at least one “pump-and-dump” and an average loss of nearly 30%. Moreover, we identify several distinct types of investors, some of which should not be viewed as falling prey to these frauds. We also show that portfolio composition and past trading behavior can better explain participation in touted stocks than demographics. Our analysis offers insights into the challenges associated with designing effective investor protection against market manipulation.
This paper investigates the determinants of value and growth investing in a large administrative panel of Swedish residents over the 1999-2007 period. We document strong relationships between a household’s portfolio tilt and the household’s financial and demographic characteristics. Value investors have higher financial and real estate wealth, lower leverage, lower income risk, lower human capital, and are more likely to be female than the average growth investor. Households actively migrate to value stocks over the life-cycle and, at higher frequencies, dynamically offset the passive variations in the value tilt induced by market movements. We verify that these results are not driven by cohort effects, financial sophistication, biases toward popular or professionally close stocks, or unobserved heterogeneity in preferences. We relate these household-level results to some of the leading explanations of the value premium.
This paper solves a dynamic model of households' mortgage decisions incorporating labor income, house price, inflation, and interest rate risk. It uses a zero-profit condition for mortgage lenders to solve for equilibrium mortgage rates given borrower characteristics and optimal decisions. The model quantifies the effects of adjustable vs. fixed mortgage rates, loan-to-value ratios, and mortgage affordability measures on mortgage premia and default. Heterogeneity in borrowers' labor income risk is important for explaining the higher default rates on adjustable-rate mortgages during the recent US housing downturn, and the variation in mortgage premia with the level of interest rates.