Contents
In 2016 the United States accounted for 56 % of world stock market capitalisation, so a US investor holding the market portfolio would have 44 % in foreign equity. The actual share was 23 %. Home bias is the most persistent phenomenon in international investing, and it has survived three decades of attempts to explain it. But there is a less quoted reading: it may not be entirely a mistake. This article goes through what has been measured, including the part suggesting that investing close to home sometimes pays.
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.
| Finding | Result | Study and year |
|---|---|---|
| Foreign equity in the US portfolio | 23 % against a 44 % benchmark | Hnatkovska, Oxford Res. Encycl. (2019) |
| Where the bias is largest | In developing economies; Europe the lowest | Hnatkovska (2019) |
| Bias within one’s own country | Preference for firms headquartered nearby | Coval and Moskowitz, Journal of Finance (1999) |
| Which firms are preferred | Small, leveraged producers of non-tradable goods | Coval and Moskowitz (1999) |
| Who has the most home bias | Older man, not very wealthy, public employee | Karlsson and Nordén, J. Banking and Finance (2007) |
| Effect of labelling an asset as one’s own | +25 % portfolio weight, with nothing else changed | Dlugosch et al., J. Economics and Business (2023) |
| The reading that qualifies the error | May reflect the local investor’s superior information | Gaar 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 precise 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.
| Study | What it analysed | What it found | What it does not support |
|---|---|---|---|
| Hnatkovska (2019) | An overview of macroeconomic data | 23 percent foreign versus a 44 percent benchmark | Being purely a literature review, the benchmark relies on the chosen model |
| Coval and Moskowitz (1999) | The portfolios of United States managers alongside corporate headquarters | A pronounced tendency toward geographical proximity | Institutional professionals rather than retail investors |
| Karlsson and Nordén (2007) | A Swedish pension scheme using a multinomial logit framework | A distinct demographic profile characterizing the biased investor | Generalizability beyond a single pension arrangement |
| Dlugosch et al. (2023) | An experimental setup featuring ambiguous urns and distinct labels | The presence of a label increases weighting by 25 percent solely under conditions of high ambiguity | Simulated choices rather than actual investment portfolios |
| Gaar et al. (2020) | An evaluation of home and local biases | Such patterns might indicate superior insights and thus prove rational | As an analytical review, it lacks a precise quantification of that proportion |
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 introduce an implication for asset pricing models: the connection linking investment proximity with corporate scale and financial leverage could potentially clarify multiple established financial market 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 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 the label alone weighs
Dennis Dlugosch, Kristian Horn and Mei Wang designed in Journal of Economics and Business the experiment that isolates the purely symbolic component. Participants allocated their portfolio among assets whose returns depended on a draw from an ambiguous urn, with all other information held constant and the level of ambiguity controlled.
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 condition | What happens to portfolio weight | Reading |
|---|---|---|
| Asset labelled as familiar | +25 % approximately | Only the name changes, not the return |
| Asset labelled as from the home country | +25 % approximately | Effect equivalent to that of familiarity |
| Under low ambiguity | No effect | The label only operates under uncertainty |
| Under high ambiguity | Effect present | Where decisions are made with least information |
| Consequence for the portfolio | More high-ambiguity assets | Greater 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 reading that qualifies 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 its existence is hardly questioned, the scale differs among nations and investor segments, and it should be viewed as a multifactorial occurrence driven by a blend of multiple causes that act in synergy.
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. The reviews agree that no single explanation accounts for the whole magnitude of the bias, and that it probably reflects a combination of rational and behavioural factors. What the evidence does not allow is treating it as pure error or as an informed strategy: it is both at once, in proportions that have not been measured.
How to apply this practically
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
How much home bias is there?
The standard benchmark makes quantification possible. Because American stocks represented 56 percent of global market capitalization back in 2016, the market portfolio should theoretically allocate 44 percent to international equities, whereas the actual proportion found in American portfolios sat at only 23 percent. This skew proves more pronounced across emerging markets, drops to its minimum in Europe, reaches its maximum peaks throughout Central and South America, and has gradually shrank over the years while still persisting.
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 lot, and it has been isolated experimentally. In the experiment with ambiguous urns, labelling assets as familiar or as from the subjects’ home country increases their portfolio weight by around 25 % even though the return-generating process does not change, and the effect appears only when returns are highly ambiguous, so familiarity ends up loading the portfolio with assets carrying greater downside risk.
Is investing close to home always a mistake?
Not necessarily, and that is the least quoted part. The review published in Management Review Quarterly concludes that, unlike other biases, home bias can be explained at least partly by reasons unrelated to irrationality, that information asymmetries and the superior information of domestic investors are important factors, and that performance may benefit from a home bias. The reviews do agree, however, that no single explanation accounts for the whole magnitude.
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.
