International tail risk and World Fear

Hollstein, Fabian; Nguyen, Duc Binh Benno; Prokopczuk, Marcel; Simen, Chardin Wese

doi:10.1016/j.jimonfin.2019.01.004

Cited by 29 publications

(11 citation statements)

References 68 publications

(94 reference statements)

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“…In a wider context, Atilgan et al (2019) examine the relationship between systematic tail risk and stock returns globally but do not find that systematic tail risk has a positive impact on expected returns. However, this finding would appear to contradict the study of Hollstein et al (2019) who find that global tail risk strongly predict stock returns.…”

Section: Introductioncontrasting

confidence: 67%

Does systematic tail risk matter?

Stoja

Polanski

Nguyen

et al. 2023

Journal of International Financial Markets, Institutions and Mo

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Section: Introductioncontrasting

confidence: 67%

Does systematic tail risk matter?

Stoja

Polanski

Nguyen

et al. 2023

Journal of International Financial Markets, Institutions and Mo

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“…In the wake of multiple recent episodes of financial distress, like the Lehman default, the "Great Recession" followed by the European debt crisis, and the Chinese stock market crash, and currently the ongoing COVID-19 pandemic, the issue of tail risks has emerged as an important research question (Baker et al, 2015;2020;Adrian et al, 2019). This is mainly because tail risks have been shown to predict not only equity returns, but also real economic variables, such as employment, investment and output (Kelly and Jiang, 2014;Chevapatrakul et al, 2019;Hollstein et al, 2019;Salisu et al, 2021a). Naturally, determining which factors drive the future evolution of tail risks is an important question for both investors and policymakers.…”

Section: Introductionmentioning

confidence: 99%

Predictability of tail risks of Canada and the U.S. Over a Century: The role of spillovers and oil tail Risks☆

Salisu

Gupta

Pierdzioch

2022

The North American Journal of Economics and Finance

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Motivated by the long standing strong economic ties between Canada and the United States (U.S.), we examine whether such relations can be extended to their stock-market tail risks using over a century of monthly data, while also accounting for the role of tail risks of other advanced economies such as France, Germany, Japan, Italy, Switzerland, and the United Kingdom (U.K.) as well as the role of oil-market tail risk. We employ the Conditional Autoregressive Value at Risk (CAViaR) model developed by Engle and Manganelli (2004) to measure tail risks, where we estimate four variants (Adaptive, Symmetric absolute value, Asymmetric slope and Indirect GARCH) of the CAViaR model to compute the 5% Value-at-Risk (VaR). We then use model diagnostics such as the Dynamic Quantile test (DQ) test, %Hits and Regression Quantile (RQ) statistic to determine the model that best fits the data. Relying on the "best" tail-risk model and a predictive model that additionally accounts for the salient features of the tail-risk data, we find a strong positive relation between the stock-market tail risks of Canada and the U.S., consistent with risk spillovers between the two economies. Our findings hold for various out-of-sample forecast horizons. We also find contrasting evidence for the oil-market tail risk, whose effect is positive for Canada (being a net oil exporter) and negative for the U.S. (being a net oil importer). Further results obtained after accounting for the role of tail risks of other advanced economies combined using a principal-component analysis reveal a positive relation with the U.S. and negative one for Canada, supporting the diversification potential of the latter in the presence of tail risks of advanced economies other than the U.S. Our findings have implications for investors and policymakers, and are robust to alternative VaR measures.

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“…Some of them documented significant relationships, while others were less successful. Hollstein et al (2019) investigate the pricing of tail risk in international stock markets. They find that both local and our newly computed global tail risk strongly predict global equity index excess returns.…”

Section: Price Riskmentioning

confidence: 99%

The Cross Section of Country Equity Returns: A Review of Empirical Literature

Zaremba

2019

JRFM

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The last three decades brought mounting evidence regarding the cross-sectional predictability of country equity returns. The studies not only documented country-level counterparts of well-established stock-level anomalies, such as size, value, or momentum, but also demonstrated some unique return-predicting signals such as fund flows or political regimes. Nonetheless, the different studies vary remarkably in terms of their dataset and methods employed. This study aims to provide a comprehensive review of the current literature on the cross-section of country equity returns. We focus on three particular aspects of the asset pricing literature. First, we study the choice of dataset and sample preparation methods. Second, we survey different aspects of the methodological approaches. Last but not least, we review the country-level equity anomalies discovered so far. The discussed cross-sectional return patterns not only provide new insights into international asset pricing but can also be potentially translated into effective country allocation strategies.

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International tail risk and World Fear

Cited by 29 publications

References 68 publications

Does systematic tail risk matter?

Does systematic tail risk matter?

Predictability of tail risks of Canada and the U.S. Over a Century: The role of spillovers and oil tail Risks☆

The Cross Section of Country Equity Returns: A Review of Empirical Literature

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