Combining conditional volatility forecasts using neural networks: an application to the EMS exchange rates

The present paper examines the out-of-sample forecasting performance of four conditional volatility models applied to the European Monetary System (EMS) exchange rates. In order to provide improved volatility forecasts, the four models’ forecasts are combined through simple averaging, an ordinary least squares model, and an artificial neural network. The results support the EGARCH specification especially after the foreign exchange crisis of August 1993. The superiority of the EGARCH model is consistent with the nature of the EMS as a managed float regime. The ANN model performed better during the August 1993 crisis especially in terms of root mean absolute prediction error.     

Short-term Dynamics in the Cyprus Stock Exchange

Abstract

This paper investigates the short-term dynamics of stock returns in an emerging stock market namely, the Cyprus Stock Exchange (CYSE). Stock returns are modelled as conditionally heteroscedastic processes with time-dependent serial correlation. The conditional variance follows an EGARCH process, while for the conditional mean three nonlinear specifications are tested, namely: (a) the LeBaron exponential autoregressive model; (b) the Sentana and Wadhwani positive feedback trading model; and finally (c) a model that nests both (a) and (b). There is an inverse relationship between volatility and autocorrelation consistent with the findings from several other stock markets, including the US. This pattern could be the manifestation of a certain form of noise trading namely positive feedback trading or, momentum trading strategies. There is little evidence that market declines are followed with higher volatility than market advances, the so-called ‘leverage effect’, that has been observed in almost all developed stock markets. In out of sample forecasts, the nonlinear specifications provide better results in terms of forecasting both first and second moments of the distribution of returns.     

中国股票市场波动性研究：模型选择及实证

以日收盘数据计算出的市场日收益率作为研究的基础数据,利用准极大似然估计方法QML估计三种ARCH类模型(GARCH、T-GARCH和E-GARCH)对中国股市波动性与稳定性的运行效果进行了实证研究的结果,得出EGARCH(1,1)模型是最优的拟合模型。运用最优模型实证发现中国股市不仅波动性很大,而且波动是不对称的。     

Taiwan's Foreign Exchange Market—Volatile but Still Efficient?

This paper investigates the importance of return heterogeneity and volatility for the foreign exchange rate on the New Taiwan (NT) dollar in terms of the U. S. dollar. We describe the price behavior of the foreign exchange market through the Power GARCH (1,1) and EGARCH (1,1) models. The time knots of market events are found to have deep impacts on the behavior of both market agents and the intraday characteristics of the price process. Evidence also reveals that Taiwan's foreign exchange market is semi-strong efficient.     

Competition between Exchanges: Euronext versus Xetra

Exchanges in Europe are in a process of consolidation. After the failure of the proposed merger between Deutsche Börse and Euronext, these two groups are likely to become the nuclei for further mergers and co‐operation with currently independent exchanges. A decision for one of the groups entails a decision for the respective trading platform. Against that background we evaluate the attractiveness of the two dominant continental European trading systems. Though both are anonymous electronic limit order books, there are important differences in the trading protocols. We use a matched‐sample approach to compare execution costs in Euronext Paris and Xetra. We find that both quoted and effective spreads are lower in Xetra. The differences are more pronounced for less liquid stocks. When decomposing the spread we find no systematic differences in the adverse selection component. Realised spreads, on the other hand, are significantly higher in Euronext. Neither differences in the number of liquidity provision agreements nor differences in the minimum tick size or in the degree of domestic competition for order flow explain the different spread levels. We thus conclude that Xetra is the more efficient trading system.     

Hedge fund return,volatility asymmetry,and systemic effects: A higher-moment factor-EGARCH model

We investigate whether: (i) co-skewness and co-kurtosis are significant factors in modeling hedge fund (HF) returns, (ii) HF return volatility displays clusters, asymmetry and shock persistence, (iii) volatility clusters of HF styles drive volatility clusters of one another, major asset classes, and major banking organizations, (iv) HF return and volatility patterns changed after the financial crises of 1998 and 2007–2009. A higher-moment EGARCH model and monthly data over January 1993–April 2014 period on 13 HF styles are employed. Out-of-sample forecasts are generated over the period of May 2014–April 2016. Results show: (i) most of the co-skewness and co-kurtosis coefficients are statistically significant, strongly supporting the higher-moment return generating models; (ii) there is strong evidence in favor of EGARCH specification, volatility clustering, asymmetry, and shock persistence; (iii) there were distinct effects on the returns and volatilities of HFs during the 1998 Russian bond crisis, Long-Term Capital Management crisis, and the 2007–2009 financial crisis; and (iv) shocks to volatility clusters of a HF style do spillover to other HF styles, major banking firms, and key asset classes. Our findings have major implications for regulators, investors, HF managers and hedging strategists.     

Feedback trading and the ramadan effect in frontier markets

We examine the presence of the Ramadan effect in feedback trading drawing on a sample of eleven majority Muslim markets for the period of 29/6/2001 to 1/8/2016. Feedback trading is significant in several of these markets, appearing stronger outside, rather than within, Ramadan. These results hold for the full sample period, including before and after the global financial crisis raising the possibility that Ramadan’s widely documented lower volatility is related to the reduced presence of feedback trading during that month. We attribute our findings to Ramadan’s traditionally documented low volumes rendering feedback trading less feasible during that month.     

On the Role of Futures Trading in Spot Market Fluctuations: Perpetrator of Volatility or Victim of Regret?

We examine the role of index futures trading in spot market volatility. We use the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) approach to measure volatility, analyze causality and feedback relations between volatilities in the spot and futures markets, and test various hypotheses in the context of a multivariate model that incorporates other macrostate variables. Our empirical results suggest index futures trading may not be blamed for the observed volatility in the spot market. Rather, we find stronger and more consistent support for the alternative posture that volatility in the futures market is an outgrowth of a turbulent cash market. We use the regret (cognitive dissonance) theory to explain our results.     

Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests

This paper investigates the nonlinear dynamic co-movements between gold returns, stock market returns and stock market volatility during the recent global financial crisis for the UK (FTSE 100), the US (S&P 500) and Japan (Nikkei 225). Initially, the bivariate dynamic relationships between i) gold returns and stock market returns and ii) gold returns and stock market volatility are tested; both of these relationships are further investigated in the multivariate nonlinear settings by including changes in the three-month LIBOR rates. In this paper correlation integrals based on the bivariate model show significant evidence of nonlinear feedback effect among the variables during the financial crisis period for all the countries understudy. Very limited evidence of significant feedback is found during the pre-crisis period. Results from the multivariate tests including changes in the LIBOR rates provide results similar to the bivariate results. These results imply that gold may not perform well as a safe haven during the financial crisis period due to the bidirectional interdependence between gold returns and, stock returns as well as stock market volatility. However, gold may be used as a hedge against stock market returns and volatility in stable financial conditions.     

Box-Cox stochastic volatility models with heavy-tails and correlated errors

This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the marginal density of asset returns has heavy-tails. We employed the Bayes factor and the Bayesian information criterion (BIC) to examine whether the Box-Cox transformation of squared volatility is favored against the log-transformation. When applying the heavy-tailed asymmetric Box-Cox transformed SV model, three competing SV models and the t-GARCH(1,1) model to continuously compounded daily returns of the Australian stock index, we find that the Box-Cox transformation of squared volatility is strongly favored by Bayes factors and BIC against the log-transformation. While both criteria strongly favor the t-GARCH(1,1) model against the heavy-tailed asymmetric Box-Cox transformed SV model and the other three competing SV models, we find that SV models fit the data better than the t-GARCH(1,1) model based on a measure of closeness between the distribution of the fitted residuals and the distribution of the model disturbance. When our model and its competing models are applied to daily returns of another five stock indices, we find that in terms of SV models, the Box-Cox transformation of squared volatility is strongly favored against the log-transformation for the five data sets.     

Can SRI funds better resist global financial crisis? Evidence from Japan

This paper compared Socially Responsible Investment (SRI) funds and conventional funds in the Japanese market with respect to the impact of the global financial crisis in 2008. Taking the bankruptcy of Lehman Brothers as a particular event, we estimated the average cumulative abnormal returns of both funds by event study methodology using a Fama–French three-factor model and EGARCH model. Our results suggest that SRI funds better resisted the bankruptcy of the Lehman Brothers than conventional funds. We also found that this result can be attributed to the existence of international funds, possibly because investors might evaluate the CSR activities of international firms more than those of domestic firms. Alternatively, it can be interpreted that the universe of domestic SRI funds is too limited to enjoy risk diversification.     

Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?

This study mainly investigates which predictors (VIX or EPU index) are useful to forecast future volatility for 19 equity indices based on HAR framework during coronavirus pandemic. Out-of-sample analysis shows that the HAR-RV-VIX model exhibits superior forecasting performance for 12 stock markets, while EPU index just can improve forecast accuracy for 5 equity indices, implying that VIX index is more useful for most stock markets' future volatility during coronavirus crisis. The results are robust in recursive window method, alternative realized measures and sub-sample analysis; moreover, VIX index still contains the strongest predictive ability by considering kitchen sink model and mean combination forecast. Furthermore, we further discuss the predictive effect of VIX and EPU index before the coronavirus crisis. Our article provides policy makers, researchers and investors with new insights into exploiting the predictive ability of VIX and EPU index for international stock markets during coronavirus pandemic.     

The role of banks in the governance of nonfinancial firms: Evidence from Europe

The aim of our research is to investigate the important role of banks in the governance of companies listed in the Euronext 100 index. Primarily, this research seeks to examine the impact of a bank’s presence within a firm, as a creditor or shareholder, on firm performance, as well as the motivations of banks to acquire holdings, and whether the presence of a bank as a shareholder of a firm facilitates its access to bank loans. Empirical analyses are conducted with a sample of 86 nonfinancial institutions listed in the Euronext 100 index over the period 2008–2013 using the three-stage least squares method. The study shows, first, that the presence of a bank within a firm, as a creditor or shareholder, is positively related to firm performance. Moreover, the firm’s performance is an important determinant of the presence of bank shareholding. Finally, the presence of a bank as a shareholder of a firm does not facilitate its access to bank loans.     

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.     

Option pricing under time-varying risk-aversion with applications to risk forecasting

We present a two-factor option-pricing model, which parsimoniously captures the difference in volatility persistences under the historical and risk-neutral probabilities. The model generates an S-shaped pricing kernel that exhibits time-varying risk aversion. We apply our model for two purposes. First, we analyze the risk preference implied by S&P500 index options during 2001–2009 and find that risk-aversion level strongly increases during stressed market conditions. Second, we apply our model for Value-at-Risk (VaR) forecasts during the subprime crisis period and find that it outperforms several leading VaR models.     

A Modified GARCH Model with Spells of Shocks

The GARCH model is modified to capture the effect on volatilities of the consecutive number of positive or negative shocks. The new model is tested against the Shanghai Shcomp and Nikkei225 indices and found particularly useful in analyzing the Shcomp index. Similarly, the EGARCH model is extended along the same line as the GARCH model and is applied to the same sets of data. Stationarity of the new GARCH (1, 1) model is proved, and also derived is the asymptotic distribution of the quasi-maximum likelihood estimator.     

Premiums,discounts and feedback trading: Evidence from emerging markets' ETFs

This study investigates the extent to which ETFs' premiums and discounts motivate feedback trading in emerging markets' ETFs. Using a sample of the first-ever launched broad-index ETFs from four emerging markets (Brazil, India, South Africa and South Korea), we produce evidence denoting that feedback trading grows in significance in the presence of lagged premiums. The significance of feedback trading becomes more widespread across our sample's ETFs as the lagged premiums grow in magnitude, with evidence also suggesting that the effect of lagged premiums over feedback trading varies prior to and after the outbreak of the recent global financial crisis.     

Identification and critical time forecasting of real estate bubbles in the USA

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: (1) the Log Periodic Power Law Singular model to describe endogenous price dynamics originated from positive feedback loops among economic agents; and (2) a diffusion index that creates a parsimonious representation of multiple macroeconomic variables. We explicitly compare the in-sample and out-sample behaviour of our model on the housing price indices of 380 US metropolitan areas. Empirical results suggest that the model is able to forecast the end of the bubbles and to identify the variables that are highly relevant during the bubble regime.     

The Informational Role of Option Trading Volume in Equity Index Options Markets

This paper examines the dynamic relations between future price volatility of the S&P 500 index and trading volume of S&P 500 options to explore the informational role of option volume in predicting the price volatility. The future volatility of the index is approximated alternatively by implied volatility and by EGARCH volatility. Using a simultaneous equation model to capture the volume-volatility relations, the paper finds that strong contemporaneous feedbacks exist between the future price volatility and the trading volume of call and put options. Previous option volumes have a strong predictive ability with respect to the future price volatility. Similarly, lagged changes in volatility have a significant predictive power for option volume. Although the volume-volatility relations for individual volatility and volume terms are somewhat different under the two volatility measures, the results on the predictive ability of volume (volatility) for volatility (volume) are broadly similar between the implied and EGARCH volatilities. These findings support the hypothesis that both the information- and hedge-related trading explain most of the trading volume of equity index options.     

What is the correct meaning of implied volatility?

This paper presents a closed-form solution for the valuation of European options under the assumption that the excess returns of an underlying asset follow a diffusion process. In light of our model, the implied volatility computed from the Black–Scholes formula should be viewed as the volatility of excess returns rather than as the volatility of gross returns. Using the SPX and the OMX options data, we test whether implied volatility obtained from Black-Scholes option price explains the volatilities of excess returns better than gross returns, even though the result is not statistically significant.