Skip to main content
Log in

The effect of customer concentration on stock sentiment risk

  • Original Research
  • Published:
Review of Quantitative Finance and Accounting Aims and scope Submit manuscript

Abstract

The impact of stock sentiment risk on their returns has been well documented in literature, but exploration into the determinants of stock sentiment risk is lacking. We theorize that concentrated customer bases help mitigate stock sentiment risk. Empirical results based on a large sample from the U.S. market strongly support this hypothesis. Specifically, the mitigating effect takes place through three channels. Companies with high customer concentration tend to have better performance and information quality and attract more long-horizon institutional investors. All these factors contribute to diminishing stock sentiment risk. The results are robust when the endogeneity concern is addressed by investigating the effect of an exogenous shock, or when they are examined with alternative measures of sentiment risk. The negative relationship between customer concentration and stock sentiment risk is ubiquitous but even stronger during the 2008 financial crisis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. The idea that stocks’ systematic risk can be explained by firm fundamentals is prevalent. For example, Campbell et al. (2010) argue that the betas of growth and value stocks are determined by the cash-flow fundamentals of these companies. Ng (2011) links liquidity risk to companies’ information quality, and Cao and Petrasek (2014) demonstrate that certain types of institutional ownership lower liquidity risk of stocks.

  2. We appreciate a reviewer making these suggestions.

  3. We appreciate the valuable comments by the reviewers that suggest explorations into the impact of data frequency, foreign sales, and firm age.

  4. To formally test the potential impact of thin trading, we follow Miller et al. (1994) to adjust stock returns for thin trading. Then we rerun the main regressions with the adjusted sentiment beta, whose results are consistent with those in the paper and are thus unreported.

  5. For a robustness test on this issue, we assign delisting-month returns following Shumway (1997) and Shumway and Warther (1999). We also employ the Heckman (1979) model to test the possible impact of delisting bias on our main results. The untabulated results are consistent with those reported in the paper and thus refute concerns for delisting and survivorship bias.

References

Download references

Acknowledgements

We thank Ramesh Rao for helpful comments.

Funding

Wang and Huang acknowledge financial support from the National Natural Science Foundation of China (Grant Numbers 71571038 and 71971048), the Fundamental Research Funds for Central Universities in China (Grant Number N2006010) and LiaoNing Revitalization Talents Program in China (Grant Number XLYC1907015).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hongrui Feng.

Ethics declarations

Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A: description of main variables

Appendix A: description of main variables

Variable name

Description

\(\beta^{ST4}\)

Sentiment beta of stocks obtained from Carhart four-factor model, following Baker and Wurgler (2006)

\(\beta^{ST1}\)

Sentiment beta of stocks obtained from market single-factor model (CAPM)

\(\beta^{ST3}\)

Sentiment beta of stocks obtained from Fama–French there-factor model

\(\beta^{CCI}\)

Sentiment beta of stocks based on Consumer Confidence Index (CCI), following Keiber and Samyschew (2019)

Concus

HHI ratio of Customer Concentration as defined in Patatoukas (2012)

InstTO

Institutional investor turnover as proposed by Gaspar et al. (2005)

Audit_fee

Audit fees in $US thousands from Audit Analytics

Total_fee

The sum of audit and audit-related fees in $US thousands from Audit Analyticsa

Restatement

An indicator variable for restatements of previously audited financial statementsb

Leverage

The ratio of total debt divided by total asset

mtb

The ratio of the market value of equity to the book value of equity measured at the beginning of the fiscal year

ppe

The ratio of net PP&E to the total asset

Cash

The ratio of cash and all securities readily transferable to cash as listed in the Current Asset section to the total assets

cf_na

The ratio of the Operating Income Before Depreciation (OIBDP) to non-current assets

nwc_na

The working capital minus cash and short-term investments, divided by the non-current assets

Capex

The ratio of capital expenditures to non-current assets

rd

Research and development expenditure divided by total assets

Log_at

The natural log of total assets

inst_ratio

Institutional ownership, defined as the equity held by institutional investors at the end of the last quarter in fiscal year t

lnage

The natural log of the number of years since IPO

roa

The return-on-assets calculated as the ratio of operating income after depreciation divided by total assets

sg

The annual percentage of growth rate in sales

Loss

An indicator variable for negative operating income after depreciationc

Debtmaturity

The ratio of short-term debt to total debt

Foreign

An indicator variable for foreign income or foreign income taxesd

△csale

The year-over-year growth in cash sales, where cash sales is calculated as sales minus the change in accounts receivables

△roa

The year-over-year change in return-on-assets

Soft

The ratio of total assets minus net PP&E minus cash and cash equivalents divided by total assets

gp

The firm’s gross profitability as revenues minus cost of goods sold, scaled by total assets following Novy-Marx (2013)

Ebitda

Earnings before interest, tax, depreciation and amortization scaled by the market value of equity

∆sale

Sales growth from year t to year t + 1

cfvol

The annualized standard deviation of cash flow in 5 years

  1. aAudit-related fees are assurance and related services that traditionally are performed by the independent accountant and include employee benefit plan audits, due diligence related to mergers and acquisitions, accounting consultations and audits in connection with acquisitions, internal control reviews, attest services that are not required by statute or regulation, and consultation concerning financial accounting and reporting standards
  2. bIndicator variable = 1 for financial statement restatements not attributed to clericala errors identified by Audit Analytics, 0 otherwise
  3. cIndicator variable = 1 if operating income after depreciation is negative, 0 otherwise.
  4. dIndicator variable = 1 if the firm reports foreign income or foreign income taxes, 0 otherwise.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Huang, Y., Feng, H. et al. The effect of customer concentration on stock sentiment risk. Rev Quant Finan Acc 60, 565–606 (2023). https://doi.org/10.1007/s11156-022-01104-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11156-022-01104-5

Keywords

JEL Classification

Navigation