Home bias: a persistent phenomenon in global investing

Contents
  1. Summary: the seven findings that matter
  2. The scale of the phenomenon
  3. The bias also happens at home
  4. Who has the most home bias
  5. How much the label alone weighs
  6. The assessment that justifies it
  7. What to do with this in practice
  8. Frequently asked questions
  9. What we do not know
  10. References

Back in 2016, the United States represented 56 % of global stock market capitalization, meaning a domestic investor owning the market portfolio should have allocated 44 % to international equities. Yet, the real figure sat at just 23 %. Home bias remains the most stubborn anomaly within cross-border finance, having outlasted thirty years of academic efforts to decode it. Nonetheless, an overlooked interpretation suggests this tendency might not be a total miscalculation. This piece examines the empirical findings, even touching upon the evidence indicating that keeping investments local can occasionally be advantageous.

Summary: the seven findings that matter

Every single row lists the research along with its publication date. It is beneficial to distinguish international bias from prejudices present in one’s native country.

FindingResultStudy and year
Foreign equity in the US portfolio23 % against a 44 % benchmarkHnatkovska, Oxford Res. Encycl. (2019)
Where the bias is largestIn developing economies; Europe the lowestHnatkovska (2019)
Bias within one’s own countryPreference for firms headquartered nearbyCoval and Moskowitz, Journal of Finance (1999)
Which firms are preferredSmall, leveraged producers of non-tradable goodsCoval and Moskowitz (1999)
Who has the most home biasOlder man, not very wealthy, public employeeKarlsson and Nordén, J. Banking and Finance (2007)
Effect of labelling an asset as one’s own+25 % portfolio weight, with nothing else changedDlugosch et al., J. Economics and Business (2023)
The reading that qualifies the errorMay reflect the local investor’s superior informationGaar et al., Management Review Quarterly (2020)

What you will find here

  • The scale of the bias, accompanied by benchmark statistics that are virtually never provided.
  • The discovery that this bias operates within a single country as well.
  • The exact profile of the investor with the most home bias.

• The experiment that measured how much the label “ours” weighs on its own.

• Why part of the literature argues it is not exactly a mistake.

The scale of the phenomenon

Viktoria Hnatkovska’s review for the Oxford Research Encyclopedia of Economics and Finance gives the benchmark that makes the magnitude intelligible. Under the international asset pricing model with homogeneous investors, every investor should hold the world market portfolio: the share of domestic assets equal to the share of those assets in world capitalisation.

Applied to the best documented case: since the share of US equity in world capitalisation was 56 % in 2016, US investors should have allocated 56 % of their equity portfolio to domestic assets and the remaining 44 % to foreign equity. Foreign equity accounted for only 23 % of the US portfolio in 2016.

And the global trend indicates: domestic equity preference is generally more pronounced across emerging markets than throughout advanced nations, with European territories exhibiting the smallest domestic bias and Central and South American territories recording the largest. The writer points out that, notwithstanding the long-term erosion of this tendency across every nation, it persists as a resilient characteristic within the empirical record.

An explanation regarding what constitutes a puzzle

One point the review itself stresses is worth keeping: whether home bias is a puzzle depends on the benchmark allocation used. It is a puzzle against a model of homogeneous investors. It is not necessarily one against models that incorporate the costs of trading in international markets, or against theories stressing that local equity can hedge real exchange rate risk and non-tradable income risk, such as labour income.

StudyWhat it analysedWhat it foundWhat it does not support
Hnatkovska (2019)Review of the macroeconomic evidence23 % foreign against a 44 % benchmarkIt is a review; the benchmark depends on the model
Coval and Moskowitz (1999)US managers’ portfolios and firm headquartersStrong preference for the geographically closeProfessional managers, not individual investors
Karlsson and Nordén (2007)Swedish pension plan, multinomial logit modelClear demographic profile of the biased investorOne particular pension system
Dlugosch et al. (2023)Experiment with ambiguous urns and labelsThe label raises weight by 25 %, only under high ambiguityExperimental decision, not a real portfolio
Gaar et al. (2020)Review of home bias and local biasMay reflect superior information and be rationalIt is a review; it does not quantify that share

The bias also happens at home

Joshua Coval and Tobias Moskowitz published in Journal of Finance the discovery that deepened the issue: the inclination to invest near home extends to domestic equity portfolios as well.

Their specific result: US investment managers show a strong preference for locally headquartered firms, particularly small firms that are highly leveraged and produce non-tradable goods.

The choice of those three traits is intentional, and the researchers explain it by proposing that information gaps between domestic and external backers could fuel the bias toward nearby business ventures. These happen to be the exact enterprises regarding which publicly available data is most limited and where local familiarity carries the highest value.

They also add a consequence for pricing theory: the relationship between investment proximity and firm size and leverage may shed light on several documented asset pricing anomalies.

Who has the most home bias

Anders Karlsson and Lars Nordén used the Swedish pension system, where each member chooses among funds, to do in Journal of Banking and Finance something that did not exist: analyse home bias at the individual investor level, controlling for transaction costs and risk level.

By employing a multinomial logit model that incorporates demographic traits, statistically and economically significant relationships between individual characteristics and the probability of home bias are uncovered by them. Specifically, age, gender, net wealth, occupation, and familiarity with risky investments play a crucial role.

And the resulting profile is unusually specific: the demographic most prone to exhibiting home bias tends to be an older man of modest wealth, employed within the public sector, and possessing zero alternative risky investments.

How much the label alone weighs

Dennis Dlugosch, Kristian Horn alongside Mei Wang outlined an experiment within the Journal of Economics and Business to isolate the strictly symbolic element. Subjects distributed their portfolio across assets featuring returns tied to an ambiguous urn draw, while every other variable remained constant and the ambiguity degree was regulated.

The manipulation was only the name: labelling assets as familiar or as coming from the subjects’ home country increases portfolio weight by around 25 %, even though the return-generating process is unaffected.

Experimental conditionWhat happens to portfolio weightReading
Asset labelled as familiar+25 % approximatelyOnly the name changes, not the return
Asset labelled as from the home country+25 % approximatelyEffect equivalent to that of familiarity
Under low ambiguityNo effectThe label only operates under uncertainty
Under high ambiguityEffect presentWhere decisions are made with least information
Consequence for the portfolioMore high-ambiguity assetsGreater downside loss risk

The authors’ practical conclusion is the one worth keeping: familiarity and affinity for one’s own can lead to portfolios containing more high-ambiguity assets, that is, with greater downside risk. The bias does not only reduce diversification: it tilts the portfolio towards the worst-measured assets.

The assessment that justifies it

Eduard Gaar, David Scherer, and Dirk Schiereck analyzed the complete body of research regarding home bias and local bias within Management Review Quarterly, ultimately arriving at a conclusion that diverges from the conventional narrative.

First they place the phenomenon: although there is little doubt about its existence, its magnitude varies across countries and investor groups, and it must be regarded as a multifactorial phenomenon, a combination of numerous causes contributing synergistically.

And then they introduce the qualification: unlike other biases, home bias can be explained at least partly by reasons unrelated to irrational investor behaviour. While institutional restrictions play a minor role, information asymmetries and the superior information of domestic investors are important factors.

Hence the uncomfortable conclusion for anyone who treats it as a plain mistake: investment performance may well benefit from a home bias, and the bias would then cease to be a puzzle and become rational behaviour, given that a lower level of diversification can lead to higher returns.

This reading should not be taken alone either. Critics concur that no isolated explanation accounts for the full scale of the bias, suggesting it likely stems from a blend of rational and behavioural drivers. What the available data forbids is dismissing it as a mere mistake or viewing it as a calculated tactic: it functions as both simultaneously, in proportions that remain unquantified.

What to do with this in practice

Ordered by the strength of the evidence behind each point:

  • Work out your benchmark before judging your portfolio. Your own country’s market share is the starting point; for most countries it is a small fraction of world capitalisation.

• Watch the bias inside the country too. The preference for the close operates between regions and sectors as well, not only between countries.

• Distrust familiarity as a criterion. Labelling an asset as one’s own raises its weight by 25 % with nothing about its return changing.

• Be careful when information is scarce. The label effect appears only under high ambiguity, which is when being wrong costs most.

  • Do not assume all home bias is error. Part of it may reflect the local investor’s superior information, although nobody has quantified how much.

Frequently asked questions

To what extent does home bias exist?

The usual benchmark allows it to be quantified. Since US equity accounted for 56 % of world capitalisation in 2016, the market portfolio would imply 44 % in foreign equity; the actual share in the US portfolio was 23 %. The bias is larger in developing countries, lowest in Europe and highest in Central and South America, and it has declined over time without disappearing.

Is it exclusively a cross-border occurrence?

No, it happens within each country too. The study published in Journal of Finance documents that US investment managers show a strong preference for locally headquartered firms, particularly small, highly leveraged producers of non-tradable goods, which the authors interpret as evidence of informational asymmetry between local and non-local investors.

Who holds the most?

There is a profile identified with individual data. In the analysis of the Swedish pension plan with a multinomial logit model, age, gender, net wealth, occupation and familiarity with risky investments are significant, and the type of individual most likely to display home bias is an older man, not very wealthy, who works for the public administration and holds no other risky assets.

How much does it matter that something merely sounds like one’s own?

Quite a large amount, and it has been isolated through experimentation. During the study utilizing ambiguous urns, characterizing holdings as familiar or originating from the participants’ native nation boosts their portfolio allocation by roughly 25 % despite the underlying return-generating mechanism remaining identical, while this outcome emerges exclusively when returns exhibit high ambiguity, meaning familiarity ultimately burdens the portfolio with instruments bearing elevated downside exposure.

Is investing close to home always a mistake?

Not necessarily, and that is precisely the least cited aspect. The paper featured in Management Review Quarterly concludes that, unlike alternative cognitive errors, home bias can be justified at least partially through rational motives, that informational gaps together with the advantage held by local investors represent key elements, and that financial returns might actually gain from a domestic preference. Nonetheless, the evaluations concur that no isolated factor fully explains the entire scale of the phenomenon.

What we do not know

• What share is information and what share is bias. It is the central question of the field and no review resolves it.

• How much it costs in returns. There are estimates of the cost of under-diversification, but they depend entirely on the chosen benchmark model.

• Whether the secular decline continues. The bias has fallen with financial globalisation; whether it stabilises or reverses with geopolitical fragmentation remains to be seen.

• How it operates through funds. Much of an individual’s international exposure is indirect, and the classic measurements do not always capture it.

References

1. Hnatkovska, V. V. Home Bias in International Macroeconomics. Oxford Research Encyclopedia of Economics and Finance, 2019. DOI: 10.1093/acrefore/9780190625979.013.311

2. Coval, J. D. and Moskowitz, T. J. Home Bias at Home: Local Equity Preference in Domestic Portfolios. Journal of Finance, 1999. DOI: 10.1111/0022-1082.00181

3. Karlsson, A. and Nordén, L. Home Sweet Home: Home Bias and International Diversification Among Individual Investors. Journal of Banking and Finance, 2007. DOI: 10.1016/j.jbankfin.2006.04.005

4. Dlugosch, D., Horn, K. and Wang, M. New experimental evidence on the relationship between home bias, ambiguity aversion and familiarity heuristics. Journal of Economics and Business, 2023. DOI: 10.1016/j.jeconbus.2023.106131

5. Gaar, E., Scherer, D. and Schiereck, D. The home bias and the local bias: A survey. Management Review Quarterly, 2020. DOI: 10.1007/s11301-020-00203-8

This content is for information only and does not constitute financial advice or an investment recommendation. The studies cited analyse countries, periods and investor types that are not comparable with one another, and none of them allows the appropriate allocation for any particular portfolio to be determined.