Skip to main content

Measuring structural risk disposition in Brazilian equities

Published: Sep 15, 2026
Volume: 24
Keywords: Investor sentiment Composite indicators Formative measurement Credit conditions Discriminant validity Brazilian equity market

Authors

Luiz Fernando Nunes da Silva
Radar Perene Research

Abstract

We propose a measurement architecture for persistent structural risk disposition in the Brazilian equity market and evaluate one implementation, the Structural Risk Disposition Composite (SRDC). The composite aggregates four weakly correlated market-derived dimensions—options positioning, credit conditions, market breadth, and external capital allocation—each expressed as a rolling one-year percentile, over 2016–2026 (2,388 daily observations). The construct is formative, in the tradition of financial conditions indexes. Replacing a price-momentum dimension with credit conditions yields a pair of results: an informational gain over financial-stress criteria that placebo substitutions cannot reproduce (an incremental criterion gain ΔR²(credit–noise) of 0.112 on realized volatility, a criterion sharing no input with the composite), and a reduction of the composite's price-trend correlation from 0.60 to 0.34—generic, by our own placebos, to any slow price-orthogonal replacement, meaningful only within the pair. The composite describes market state; it does not predict returns.


How to cite

Luiz Fernando Nunes da Silva. Measuring structural risk disposition in Brazilian equities. Brazilian Review of Finance, v. 24, n. 1, 2026. p. e202615. DOI: 10.12660/rbfin.v24n1.2026.98843.


References

Ang, A. & Bekaert, G. (2002). International asset allocation with regime shifts, Review of Financial Studies, 15(4), 1137–1187. https://doi.org/10.1093/rfs/15.4.1137
Baker, M. & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns, Journal of Finance, 61(4), 1645–1680. https://doi.org/10.1111/j.1540-6261.2006.00885.x
Baker, M. & Wurgler, J. (2007). Investor sentiment in the stock market, Journal of Economic Perspectives, 21(2), 129–152. https://doi.org/10.1257/jep.21.2.129
Barberis, N., Shleifer, A. & Vishny, R. (1998). A model of investor sentiment, Journal of Financial Economics, 49(3), 307–343. https://doi.org/10.1016/S0304-405X(98)00027-0
Bollen, K. A. & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation perspective, Psychological Bulletin, 110(2), 305–314. https://doi.org/10.1037/0033-2909.110.2.305
Brown, G. W. & Cliff, M. T. (2004). Investor sentiment and the near-term stock market, Journal of Empirical Finance, 11(1), 1–27. https://doi.org/10.1016/j.jempfin.2002.12.001
Campbell, D. T. & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix, Psychological Bulletin, 56(2), 81–105. https://doi.org/10.1037/h0046016
CNN Business (n.d.). Fear & Greed Index, Market data page and methodology note. Continuously updated practitioner composite. Accessed August 15, 2026. https://www.cnn.com/markets/fear-and-greed
Da, Z., Engelberg, J. & Gao, P. (2011). In search of attention, Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x
Da, Z., Engelberg, J. & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices, Review of Financial Studies, 28(1), 1–32. https://doi.org/10.1093/rfs/hhu072
De Long, J. B., Shleifer, A., Summers, L. H. & Waldmann, R. J. (1990). Noise trader risk in financial markets, Journal of Political Economy, 98(4), 703–738. https://doi.org/10.1086/261703
Diamantopoulos, A. & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development, Journal of Marketing Research, 38(2), 269–277. https://doi.org/10.1509/jmkr.38.2.269.18845
Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57(2), 357–384. https://doi.org/10.2307/1912559
Hatzius, J., Hooper, P., Mishkin, F. S., Schoenholtz, K. L. & Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis, NBER Working Paper 16150, National Bureau of Economic Research, Cambridge, MA. https://doi.org/10.3386/w16150
Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk, Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
Künsch, H. R. (1989). The jackknife and the bootstrap for general stationary observations, Annals of Statistics, 17(3), 1217–1241. https://doi.org/10.1214/aos/1176347265
Lo, A. W. (2004). The adaptive markets hypothesis: Market efficiency from an evolutionary perspective, Journal of Portfolio Management, 30(5), 15–29. https://doi.org/10.3905/jpm.2004.442611
Minsky, H. P. (1992). The financial instability hypothesis, Working Paper 74, The Jerome Levy Economics Institute of Bard College, Annandale-on-Hudson, NY. https://www.levyinstitute.org/publications/the-financial-instability-hypothesis/
Nunes da Silva, L. F. (2026). Radar Perene Working Paper Series — Data package for RPWP-001 (The Perene Risk Index) and RPWP-002 (The Structural Ânima Index), Zenodo data set, version 2026-07.2. Version DOI cited; concept DOI 10.5281/zenodo.21399426 resolves to the latest version. https://doi.org/10.5281/zenodo.21402528
Piccoli, P., da Costa Junior, N. C. A., da Silva, W. V. & Cruz, J. A. W. (2018). Investor sentiment and the risk–return tradeoff in the Brazilian market, Accounting & Finance, 58(S1), 599–618. https://doi.org/10.1111/acfi.12342
Shiller, R. J. (1981). Do stock prices move too much to be justified by subsequent changes in dividends?, American Economic Review, 71(3), 421–436. https://www.aeaweb.org/aer/top20/71.3.421-436.pdf
Shiller, R. J. (2000). Irrational Exuberance, Princeton University Press, Princeton, NJ. https://press.princeton.edu/books/paperback/9780691173122/irrational-exuberance
Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix, Psychological Bulletin, 87(2), 245–251. https://doi.org/10.1037/0033-2909.87.2.245
Williams, E. J. (1959). The comparison of regression variables, Journal of the Royal Statistical Society, Series B, 21(2), 396–399. https://doi.org/10.1111/j.2517-6161.1959.tb00346.x
Xavier, G. C. & Machado, M. A. V. (2017). Anomalies and investor sentiment: Empirical evidences in the Brazilian market, Brazilian Administration Review, 14(3), e170028. https://doi.org/10.1590/1807-7692bar2017170028
Yoshinaga, C. E. & de Castro Junior, F. H. F. (2012). The relationship between market sentiment index and stock rates of return: A panel data analysis, Brazilian Administration Review, 9(2), 189–210. https://doi.org/10.1590/S1807-76922012000200005