A New Approach to Measuring Financial Contagion

This article proposes a new approach to evaluate contagion infinancial markets. Our measure of contagion captures the coincidenceof extreme return shocks across countries within a region andacross regions. We characterize the extent of contagion, itseconomic significance, and its determinants using a multinomiallogistic regression model. Applying our approach to daily returnsof emerging markets during the 1990s, we find that contagionis predictable and depends on regional interest rates, exchangerate changes, and conditional stock return volatility. Evidencethat contagion is stronger for extreme negative returns thanfor extreme positive returns is mixed.     

BETA,SIZE, RISK,AND RETURN

We relate the cross‐section of stock returns to firm size, beta, and total risk. We find that as extreme monthly security returns are censored from the data, the significance level decreases rapidly for the size variable and increases for beta and total risk. An analysis of up and down markets reaffirms our findings. Consequently, average returns relate positively with beta, negatively with total risk, and not at all with firm size. We infer that investors willingly accept a lower average return on high‐total‐risk investments as the trade‐off for buying a chance at an extreme positive return. JEL classification: G1.     

A Generalized Extreme Value Approach to Financial Risk Measurement

This paper develops an unconditional and conditional extreme value approach to calculating value at risk (VaR), and shows that the maximum likely loss of financial institutions can be more accurately estimated using the statistical theory of extremes. The new approach is based on the distribution of extreme returns instead of the distribution of all returns and provides good predictions of catastrophic market risks. Both the in-sample and out-of-sample performance results indicate that the Box–Cox generalized extreme value distribution introduced in the paper performs surprisingly well in capturing both the rate of occurrence and the extent of extreme events in financial markets. The new approach yields more precise VaR estimates than the normal and skewed t distributions.     

Risk management under extreme events

This article presents two applications of extreme value theory (EVT) to financial markets: computation of value at risk (VaR) and cross-section dependence of extreme returns (i.e., tail dependence). We use a sample comprised of the United States, Europe, Asia, and Latin America. Our main findings are the following. First, on average, EVT gives the most accurate estimate of VaR. Second, tail dependence of paired returns decreases substantially when both heteroscedasticity and serial correlation are filtered out by a multivariate GARCH model. Both findings are in agreement with previous research in this area for other financial markets.     

Extreme observations and risk assessment in the equity markets of MENA region: Tail measures and Value-at-Risk

The standard “delta-normal” Value-at-Risk methodology requires that the underlying returns generating distribution for the security in question is normally distributed, with moments which can be estimated using historical data and are time-invariant. However, the stylized fact that returns are fat-tailed is likely to lead to under-prediction of both the size of extreme market movements and the frequency with which they occur. In this paper, we use the extreme value theory to analyze four emerging markets belonging to the MENA region (Egypt, Jordan, Morocco, and Turkey). We focus on the tails of the unconditional distribution of returns in each market and provide estimates of their tail index behavior. In the process, we find that the returns have significantly fatter tails than the normal distribution and therefore introduce the extreme value theory. We then estimate the maximum daily loss by computing the Value-at-Risk (VaR) in each market. Consistent with the results from other developing countries [see Gencay, R. and Selcuk, F., (2004). Extreme value theory and Value-at-Risk: relative performance in emerging markets. International Journal of Forecasting, 20, 287–303; Mendes, B., (2000). Computing robust risk measures in emerging equity markets using extreme value theory. Emerging Markets Quarterly, 4, 25–41; Silva, A. and Mendes, B., (2003). Value-at-Risk and extreme returns in Asian stock markets. International Journal of Business, 8, 17–40], generally, we find that the VaR estimates based on the tail index are higher than those based on a normal distribution for all markets, and therefore a proper risk assessment should not neglect the tail behavior in these markets, since that may lead to an improper evaluation of market risk. Our results should be useful to investors, bankers, and fund managers, whose success depends on the ability to forecast stock price movements in these markets and therefore build their portfolios based on these forecasts.     

投资者关注对金银期货市场收益影响的时频分位研究

根据Google投资者关注度指数和金银期货市场交易数据,构建基于小波分解序列的时频门限自回归分布滞后模型,通过分位数模型参数估计,基于时域与频域联合分析视角,考量投资者关注度对金银期货市场收益的影响。结果表明：投资者关注度对金银期货市场的影响具有异质性;在低频域内,投资者关注度对金银期货市场影响相对较小;极端分位数水平下,投资者关注度对金银期货市场收益影响的时效性较短,投资者关注度对白银期货市场收益的影响较弱。     

A MULTIFACTOR ANALYSIS OF COUNTRY FUND RETURNS

Previous closed‐end country fund research concludes that returns behave more like the U.S. market than like their target markets. We argue this finding may be biased by model misspecification and inappropriate estimation techniques. We propose a single‐equation model containing five hypothesized factors of fund returns. We estimate this model for nineteen pooled seasoned funds using a time‐series cross‐section regression that corrects for two types of autocorrelation. We show that returns are strongly related to target markets. Returns are also related to changes in discounts, exchange rates, and other countries' markets, but are only weakly related to the U.S. market. JEL classification: G10, G12     

El efecto de la volatilidad del peso mexicano en los rendimientos y riesgo de la Bolsa Mexicana de Valores

The effect of heavy tails due to rare events and different levels of asymmetry associated with high volatility clustering in the emerging financial markets requires sophisticated models for statistical modelling of such stylized facts. This article applies extreme value theory (EVT) to quantify tail risk on the daily returns of Mexican stock market under aggregation of foreign exchange rate risk from January 1971 to December 2010. This study focuses on the maximum-block method and generalized extreme value distribution (GEVD) to model the asymptotic behavior of extreme returns in US dollars. The empirical results show that EVT-Based VaR measured at high confidence levels performs better than simulation historical and delta-normal VaR models on capturing fat-tails in the returns of highly volatile stock markets. Additionally, international investors holding long positions in Mexican stock market are more prone to experience larger potential losses than investors with short positions during local currency depreciation and financial crisis periods.     

Do large-cap exchange-traded funds perform better than their small-cap counterparts in extreme market conditions?

This study proposes a new threshold model that differentiates between the size and sign-dependent responses of large- and small-cap exchange-traded funds (ETFs) to changes in extreme market conditions. The asymmetric returns in extreme upsides, extreme downsides, and “in-between” markets are estimated using three sets of betas. Findings support the notion that small-cap ETFs in all seven countries fall more in extreme downturns than they rise in extreme upturns. By contrast, six out of nine large-cap ETFs climb up in upside more than they fall in downswing. Therefore, investors should be cautious when assigning excessive weights to small-cap ETFs in their portfolio.     

Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis

The response of renewable energy stock returns to the dynamics of fossil energy markets is a vital concern of low-carbon transitions. There is still sparse literature documenting the directional dependence of renewable energy stock returns on the connectedness among fossil energy returns, even though previous studies have examined the relationship among renewable energy stocks and fossil energy markets. Additionally, the conclusions of prior studies are quite far from reaching a consensus regarding the relationship between the renewable energy stock and the fossil energy markets. To this end, by using the TVP-VAR based connectedness approach and Cross-Quantilogram techniques, this study does the first attempt to unpack the complicated and controversial directional dependence of renewable energy stock returns on the returns and connectedness of fossil energy markets, considering various market conditions and time horizons. The empirical analysis demonstrates that, first, the directional dependence of renewable energy stock returns on fossil energy returns is pronounced during extreme market conditions, whereas they appear to be decoupled from fossil energy returns during normal market conditions. Second, the total connectedness between fossil energy returns transmits a substantial shock to renewable energy stock returns during most market conditions, which is in stark contrast to the information transmission directly originating from fossil energy markets. The performance of renewable energy stock markets improves with stronger fossil energy return connectedness, whereas weaker fossil energy return connectedness hinders it. Additionally, further study reveals that the directional dependence of renewable energy stock returns on the net connectedness of the crude oil market is dominated by negative dependence when the net connectedness of the crude oil market is low, whereas it displays positive dependence when the net connectedness of the crude oil market is high. This directional dependence pattern on the net connectedness of the crude oil market is opposite to that exhibited in the net connectedness of the coal and natural gas markets. Third, in general, the directional dependence of renewable energy stock returns on fossil energy returns is more pronounced in the short term but diminishes over the medium and long terms. Conversely, the directional dependence of renewable energy stock returns on fossil energy return connectedness persists over the medium and long terms. Final, with the outbreak of the Global Financial Crisis during 2007–2008, we notice an abrupt jump in the directional dependence of renewable energy stock returns on fossil energy returns and their connectedness, particularly during extreme market conditions. Our findings provide noteworthy implications for energy transformation, energy security, and climate mitigation.     

New evidence on price impact of analyst forecast revisions

Previous research shows a positive relationship between consensus forecast revisions and stock returns in developed markets. We obtain new evidence from four major Asia-Pacific markets that suggest that abnormal returns are related to latest forecast revisions. The price impact of negative revisions is consistently stronger than that of the positive revisions. We also found considerable differences in price impact between developed and emerging markets for positive revisions, while no such difference is detected for negative revisions. The latest forecast revisions and category of analysts (those working in international broking firms) appear to be two key determinants of abnormal stock returns.     

Extreme return–volume dependence in East-Asian stock markets: A copula approach

A copula approach is used to examine the extreme return–volume relationship in six emerging East-Asian equity markets. The empirical results indicate that there is significant and asymmetric return–volume dependence at extremes for these markets. In particular, extremely high returns (large gains) tend to be associated with extremely large trading volumes, but extremely low returns (big losses) tend not to be related to either large or small volumes.     

Extreme spillovers of VIX fear index to international equity markets

This study analyzes the impact of VIX spillovers on market activities during extreme market conditions in 42 international equity markets from 1998 to 2014. Specifically, tail cross-dependence suggests that a small change in VIX significantly influences global market activities during extreme market conditions. The impact of VIX is asymmetric, which is more pronounced in bearish, highly volatile, and low trading volume markets. Moreover, VIX spillovers exhibit a stronger impact on returns in developed markets and on volatility in emerging markets. In terms of geographical location, the impact of VIX spillovers is more pronounced on returns in Europe and on volatility in Latin America. These findings indicate that international investors can potentially benefit from international portfolio diversification and can serve as useful guidance to policymakers in designing appropriate policies.

     

The Incremental Information Content of Earnings and Cash Flows from Operations Affected by Their Extremity

Previous returns studies have shown that extreme earnings and extreme cash flows from operations are less informative than moderate (i.e., less extreme) earnings and moderate cash flows. Studies also report that cash flows supplement to earnings in firm valuation by showing a higher association of cash flows with returns when earnings are extreme than when earnings are moderate. We propose that this supplementary role of cash flows is affected by cash flows extremity. Using data from the US capital markets, we find that the supplementary role of cash flows exists only when cash flows are not extreme. We also investigate the supplementary role of earnings to cash flows and search for a higher association of earnings with returns when cash flows are extreme than when cash flows are moderate. Similar to results on cash flows, our findings show that the supplementary role of earnings exists only when earnings are not extreme. Our results imply that investors and researchers should consider both earnings and cash flows extremity when assessing the information content of these variables.     

Are the gains from international portfolio diversification exaggerated? The influence of downside risk in bear markets

The fundamental rationale for international portfolio diversification is that it expands the opportunities for gains from portfolio diversification beyond those that are available through domestic securities. However, if international stock market correlations are higher than normal in bear markets, then international diversification will fail to yield the promised gains just when they are needed most. We evaluate the extent to which observed correlations to monthly returns in bear, calm and bull markets are captured by three popular bivariate distributions: (1) the normal, (2) the restricted GARCH(1,1) of J. P. Morgan’s RiskMetrics, and (3) the Student-t with four degrees of freedom. Observed correlations during calm and bull markets are unexceptional compared to these models. In contrast, observed correlations during bear markets are significantly higher than predicted. Higher-than-normal correlations during extreme market downturns result in monthly returns to equal-weighted portfolios of domestic and international stocks that are, on average, more than two percent lower than those predicted by the normal distribution. If the extent of non-normality during bear markets persists over time, then a US investor allocating assets into foreign markets might want to allocate more assets into foreign markets with near-normal correlation profiles and avoid markets with higher-than-normal bear market co-movements.     

Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union

Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.     

Extreme downside risk spillover from the United States and Japan to Asia-Pacific stock markets

This paper proposes a binary response model approach to measure and forecast extreme downside risks in Asia-Pacific markets given information on extreme downside risks in the U.S. and Japanese markets. The extreme downside risk of a market is measured as the occurrence of extreme downside movement—market returns falling below left-tail Value at Risk in a Markov switching framework. The empirical findings are consistent with the following notions. First, extreme downside movements of the S&P 500 and Nikkei 225 are significantly predictive for the likelihood of extreme downside movements in all the investigated Asia-Pacific markets. Second, the majority of Asia-Pacific markets become more sensitive to Japan's extreme downside risk when the Japanese market switches into high volatility periods, whereas the U.S. spillover effect is intensified only on Taiwan during high volatility periods in the U.S. Third, mainland China is the least sensitive to extreme downside risk in the U.S. and Japan, Australia is the most sensitive to the U.S., and Singapore is the most sensitive to Japan.     

Conditional Properties of Hedge Funds: Evidence from Daily Returns*

Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investments and between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations.     

Dependence structure and extreme comovements in international equity and bond markets

Common negative extreme variations in returns are prevalent in international equity markets. This has been widely documented with statistical tools such as exceedance correlation, extreme value theory, and Gaussian bivariate GARCH or regime-switching models. We point to limits of these tools to characterize extreme dependence and propose an alternative regime-switching copula model that includes one normal regime in which dependence is symmetric and a second regime characterized by asymmetric dependence. We apply this model to international equity and bond markets, to allow for inter-market movements. Empirically, we find that dependence between international assets of the same type is strong in both regimes, especially in the asymmetric one, but weak between equities and bonds, even in the same country.