Extreme asymmetric volatility: Stress and aggregate asset prices

Aboura, Sofiane; Wagner, Niklas

doi:10.1016/j.intfin.2015.12.004

Cited by 37 publications

(30 citation statements)

References 47 publications

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“…If we call the volatility resulting from the market's expectation of a bright and a dismal future as good volatility and bad volatility, respectively, our results indicate that the dependence of the good volatility on market return is evidently lower than that of the bad volatility. This is consistent with the "asymmetric volatility" phenomenon documented in the literature (e.g., Aboura and Wagner 2016). We also observe strong leverage effect over the probability intervals, [0.4, 0.45), [0.45, 0.5), [0.5, 0.55), and [0.55, 0.6), and the noteworthy leverage effect when the market return falls into its [0.5, 0.55] probability interval dominates the relation of the log-increments of the VIX on the market return in the same probability interval.…”

Section: Conditional Dependence Indexsupporting

confidence: 92%

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Sun

2018

JRFM

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This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. We find that: (a) the two series exhibit strong, negative, extreme tail dependence; (b) the negative dependence is stronger in extreme bearish markets than in extreme bullish markets; (c) the dependence gradually weakens as the market return moves toward the center of its distribution, or in quiet markets. The unique dependence structure supports the VIX as a barometer of markets' mood in general. Moreover, applying the proposed method to the S&P 500 returns and the implied variance (VIX 2), we find that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in general, both effects are weaker than the dependence relation between the market returns and the log-increments of the VIX.

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Section: Conditional Dependence Indexsupporting

confidence: 92%

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Sun

2018

JRFM

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“…If we call the volatility resulting from market's expectation of a bright and a dismal future as good volatility and bad volatility, respectively, our results indicate that the dependence of the good volatility on market return is evidently lower than that of the bad volatility. This is consistent with the "asymmetric volatility" phenomenon documented in the literature (e.g., Aboura and Wagner, 2016). We also The volatility feedback e¤ect.…”

Section: Contemporaneous and Lagged Conditional Distributionssupporting

confidence: 92%

“…As bearish markets frequently observed counter-movements between S&P 500 index prices and the VIX, the VIX earned itself a reputation of market barometer of investors'fear (see Figure 1). 1 Motivated by this observation, we join the traditional …nance literature to study the leverage and volatility feedback e¤ects via nonparametric method, where asymmetric GARCH-in-mean type of models are popularly used in such study (see Bekaert and Wu (2000), and references therein).…”

Section: Introductionmentioning

confidence: 99%

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Sun¹,

Wu²

2018

Preprint

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This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies across different segments of the market return distribution. We find that: (a) the two series exhibit strong, negative, extreme tail dependence; (b) the negative dependence is stronger in extreme bearish markets than in extreme bullish markets; (c) the dependence gradually weakens as the market return moves toward the center of its distribution, or in quiet markets. The unique dependence structure supports the VIX as a barometer of markets' mood in general. Moreover, applying the proposed method to the S&P 500 returns and the implied variance (VIX²), we find that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in general, both effects are weaker than the dependence relation between the market returns and the log-increments of the VIX.

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“…Since most investors face risks of undiversified portfolios, they rely greatly on firms' reported performance (Breitenfellner & Wagner, 2010). Aboura and Wagner (2016) found that the volatility caused by GFC decreases the price of assets, and Liu and Di Iorio (2016) added that such volatility creates macroeconomic threats to the economy. Economic crises lead to GDP plunge, decreased demand or more severe, unemployment, and moral hazard, thus results in lower firm performance (Pearce II & Michael, 2006;Richardson et al, 1998).…”

Section: Literature Reviewmentioning

confidence: 99%

Macroeconomic factors or firm-specific factors? An examination of the impact on corporate profitability before, during and after the global financial crisis

Cheong

Hoang

2021

Cogent Economics & Finance

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The purpose of this paper is to examine the impact of macroeconomic variables and firm-specific factors on corporate profitability in Singapore and Hong Kong before, during and after the global financial crisis. This paper uses the two-step system Generalized Method of Moments to examine the impact of macroeconomic and firm-specific factors on corporate profitability. The model includes firm-specific factors (firm size, leverage, liquidity, sales growth and previous year's profitability) and macroeconomic factors (real GDP growth and inflation rate). Corporate profitability is represented by ROA, ROE and Tobin's Q. Results from the pooled sample showed that past profitability, firm size and leverage have a strong relationship with firm performance. Our pooled sample results also showed that Hong Kong firms are more affected by macroeconomic factors during the global financial crisis than Singapore firms. Our study provides insights into the relationship between firm-specific factors, macroeconomic factors and firm performance under three different economic periods in two developed economies in the Asia-Pacific.

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Extreme asymmetric volatility: Stress and aggregate asset prices

Cited by 37 publications

References 47 publications

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Leverage and Volatility Feedback Effects and Conditional Dependence Index: A Nonparametric Study

Macroeconomic factors or firm-specific factors? An examination of the impact on corporate profitability before, during and after the global financial crisis

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