What Free Lunch? The Costs of Overdiversification

McKayShawn,; ShapiroRobert,; ThomasRic,

doi:10.2469/faj.v74.n1.2

Cited by 13 publications

(2 citation statements)

References 15 publications

(19 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite longstanding conventional financial advice to minimize idiosyncratic risk by holding well-diversified portfolios (c.f., McKay et al, 2018), several studies document that both individuals and investment funds concentrate their trades and holdings in certain firms or industries (Brands et al, 2005;Baks et al, 2006;Goldman et al, 2016). Researchers have offered several reasons, including reducing investment information overload (Simon 1972;Agnew andSzykman, 2004: Garvey et al, 2017), possessing an information advantage (Lee and Rahman, 1991;Kacperczyk et al, 2005;Hiraki et al, 2015), and behavioral biases like familiarity (Pool et al, 2012) or overconfidence (Goetzmann and Kumar, 2008), for why individuals and funds would concentrate investment activity and holdings.…”

Section: Introductionmentioning

confidence: 99%

“…Prior research has documented the return benefits of portfolio concentration (c.f., Goldman et al, 2016;Jennings and Payne, 2016;McKay et al, 2018) and have often ascribed it to an information advantage (Ke and Petroni, 2004;Kacperczyk et al, 2005;Cohen et al, 2008Cohen et al, , 2010. This is largely because most of the proposed reasons for investment concentration predict no association or an ambiguous relation between concentration and performance; yet only the more sophisticated institutional investor's use of the NHTSA complaint data because less sophisticated investors are likely to overlook data that is harder to interpret and that requires more time and attention to assimilate due to the time needed and the cognitive difficulty in extracting usable information from complex data sources (Bloomfield, 2002).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Trading Concentration and Industry-Specific Information: An Analysis of Auto Complaints

Geiger,

Keskek,

Kumas

2018

SSRN Journal

View full text Add to dashboard Cite

We investigate whether sophisticated investors' trading concentration in the auto industry is associated with their use of auto complaint data. We find that the extent to which mutual funds incorporate the complaint information into their trading decisions is positively associated with their concentration of trading in the auto industry. We provide direct evidence that information advantage can arise from superior information processing. We find that pension funds, regardless of their level of trading concentration, do not use the customer complaint information to inform their trading decisions. Our findings suggest that pension funds concentrate trading for reasons other than information advantage. JEL Classification: G14 1.information advantage reason predicts a purely positive relation (Kacperczyk et al., 2005;Ekholm and Maury, 2014;Hiraki et al., 2015). However, prior research has generally not identified nor investigated the kind of information advantage utilized by concentrated investors.Information advantage can occur in two ways: 1) obtaining private information (i.e., information asymmetry), and 2) superior processing or analysis of public information based on the investor's superior ability, prior experience, knowledge or expertise (i.e., specialization) (Bodnaruk and Simonov, 2015). In fact, most studies on investment concentration generally conclude that it is due to information advantage without any attempt to determine the cause. (e.g., Brands et al., 2005;Baks et al., 2006). Moreover, most earlier studies either do not distinguish between the underlying source of information advantage (e.g., Kacpercyzk et al., 2005) or assume that it arises from private information without testing this assumption (e.g., Ekholm and Maury, 2014;Jiang and Sun, 2014). Examination of specific sources of possible information advantage, or its use by investors, is sparse, perhaps because testing the information advantage reason for investor behavior is difficult as the nature, timing, and information content of an investor's actual information set is usually unobservable by researchers. Specifically, the possibility of investment concentration occurring out of an investor's superior ability to utilize public information rather than having access to private information has yet to be examined. In this study, we address this issue by utilizing a value relevant, industry-specific information source that is available to all investors that could be exploited as an informational advantage, if a sophisticated investor so desired. Specifically, we examine whether institutional investors that have greater trading concentration in the auto industry are more likely to exploit the product complaint data freely available from the National Highway Traffic Safety Administration (NHTSA). We examine the

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Trading Concentration and Industry-Specific Information: An Analysis of Auto Complaints

Geiger,

Keskek,

Kumas

2018

SSRN Journal

View full text Add to dashboard Cite

show abstract

Trading concentration and industry-specific information: an analysis of auto complaints

Geiger

Keskek

Kumas

2022

Rev Quant Finan Acc

View full text Add to dashboard Cite

Modeling of Stock Returns in Continuous Vis-À-Vis Discrete Time Is Equivalent, Respectively, to the Conditioning of Stock Returns on a Random Walk Process for Trade Imbalances Vis-À-Vis a Random Walk Process for Evolution of Information

Obrimah

Wong

2022

Ann. Finan. Econ.

View full text Add to dashboard Cite

Let [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] denote, respectively, the current stock price, the future stock price that is conditioned on information, the minimum stock market tick size and the realized future stock price. Formal theoretical proofs in this study show modeling of stock returns in continuous time induces stock returns that have parameterization as gambles over lotteries. Stock returns have parameterization as gambles because in the presence of fairness of formation of [Formula: see text], regardless arrival of liquidity and speculative trades feasibly induces [Formula: see text]. Evolution of ‘(conditional) trade imbalances’ as random walks is shown to be a necessary and sufficient condition for parameterization of stock returns as gambles over lotteries. Suppose, on the contrary, a resort to modeling of stock returns in discrete time. The formal theory arrives at two dichotomous sufficiency conditions, which predict directionality and sizes of price changes, and facilitate evolution of stock returns as random walks. In presence of the two dichotomous conditions, fairness of formation of [Formula: see text] necessarily induces, regardless of arrival of liquidity and speculative trades, [Formula: see text]. Risk is parameterized by [Formula: see text], because all else constant, an inversion of the perturbing conditionally positive trade imbalance induces [Formula: see text]. Whereas then, [Formula: see text] has parameterization as ‘materialization of risk’, always, it is [Formula: see text] that is statistic for risk; risk, as such is well parameterized, that is, does not coincide with its materialization (note that whereas volatility is statistic for risk, it is not a statistic for materialization of risk; a statistic for risk necessarily is robust to non-materialization of risk). Given modeling in continuous time does not facilitate either of the two sufficiency conditions, always, risk has parameterization as the probability that [Formula: see text]. Since risk, as such coincides qualitatively with its materialization, it is not well parameterized. Given study findings parameterize general equilibrium, formal theoretical predictions have characterization as axiomatic statements, as opposed to propositional (parameter-dependent) statements.

show abstract

What Free Lunch? The Costs of Overdiversification

Cited by 13 publications

References 15 publications

Trading Concentration and Industry-Specific Information: An Analysis of Auto Complaints

Trading Concentration and Industry-Specific Information: An Analysis of Auto Complaints

Trading concentration and industry-specific information: an analysis of auto complaints

Modeling of Stock Returns in Continuous Vis-À-Vis Discrete Time Is Equivalent, Respectively, to the Conditioning of Stock Returns on a Random Walk Process for Trade Imbalances Vis-À-Vis a Random Walk Process for Evolution of Information

Contact Info

Product

Resources

About