Extreme returns: The case of currencies

Financial market crashes can occur even in the absence of news. This paper highlights four properties of price-contingent trading that increase the frequency of such events. Price-contingent trading is common across financial market, since it includes algorithmic trading, technical trading, and dynamic option hedging. The four properties we consider are: (1) high kurtosis in the distribution of order sizes; (2) clustering of trades within the day; (3) clustering of trades at certain prices; and (4) feedback between trading and returns. The paper estimates the relative importance of these factors using data from the foreign exchange market. Calibrated simulations indicate that interactions among these factors are at least as important as any single one. Among individual factors, the orders’ size distribution and feedback effects have the strongest influence. Overall, price-contingent trading could account for half of realized excess kurtosis. The paper suggests that extreme returns unaccompanied by news are statistically inevitable in the presence of price-contingent trading.     

Extreme risk spillovers from commodity indexes to sovereign CDS spreads of commodity dependent countries: A VAR quantile analysis

Given the financialization of commodities and the increase in the CDS markets' size and structure, we examine the co-movement and dependence structure between four commodity indexes and sovereign credit risk via an extreme volatility risk spillover methodology. We use the daily change in sovereign CDS data between October 1, 2010 to March 31, 2020 for ten commodity-dependent countries and four commodity indexes (agricultural, precious and industrial metals, and energy). The results of White et al.'s (2015) VAR for Value at Risk (VaR) and the pseudo quantile impulse response function (QIRF) show that the volatility of the primary commodity export category (e.g., agriculture, mineral, and energy) substantially influences the volatility of sovereign spreads (except for two agriculture-dependent exporters). Still, it does not always have the strongest risk spillover effect when other commodity indixes are included in the analysis. When drilling down on the data and examining the single commodity index (i.e., gold, corn, etc.), our results indicate that the primary commodity exports significantly influence the volatility of its sovereign CDS spreads. Based on the results of the QIRF, most shocks are absorbed within 30 days. Most risk spillover from the volatility of sovereign CDS spreads to the volatility of commodity indexes is found to be insignificant.     

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.

     

Intraday return spillovers and its variations across trading sessions

The main purpose of this paper is to study the intraday return spillovers and their real time variations amongst selected technology stocks. Based upon randomly selected technology stocks in terms of multilateral analysis, we find the following evidence. Firstly, we find that positive spillover effects are discernible amongst medium- and large-sized stocks, with the effects being directionally asymmetric between different size groups. Secondly, we find that for most stocks, the full effects of the firm-specific shocks over other stocks are realized within approximately 30 min to 2 h. Finally, we show that the spillover effects tend to follow an M-shaped intraday pattern. Our results suggest that during the opening and closing sessions, trades motivated by information spilled over from other firms are relatively subordinated, with the trading at these times being largely dominated by those based upon common market factor or firm-specific fundamental information.     

Volatility spillovers across NFTs news attention and financial markets

The aim of this study is to investigate the volatility spillover connectedness between NFTs attention and financial markets. This paper firstly proposes a new direct proxy for the public’s attention in the NFT market: the non-fungible tokens attention index (NFTsAI), based on 590m news stories from the LexisNexis News & Business database and applies the historical decomposition to assess the historical variations of the NFTsAI. Then the empirical analysis is performed via a TVP-VAR volatility spillover connectedness model. The empirical results show that NFTsAI indicates NFT markets are dominated by cryptocurrency, DeFi, equity, bond, commodity, F.X. and gold markets. And NFT markets are volatility spillover receivers. In addition, NFT assets could impede financial contagion and have significant diversification benefits. Employing a panel pooled OLS regression model as a supplementary analysis and a GARCH-MIDAS model as a robustness test. This study reveals that NFTsAI has sufficient power to explain the return of NFT assets from a fixed effect perspective, and NFTsAI contains useful forecasting information for both short and long-term volatility of NFT markets, separately. The new NFTsAI and the empirical findings contain useful insights for risk-averse investors, portfolio managers, institutional investors, academics and financial policy regulators.     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

Are financial spillovers stable across regimes?: Evidence from the 1997 Asian crisis

We investigate breaks in financial spillovers between the US and eight South-East Asian capital markets before and during the 1997 Asian crisis. We construct threshold vector autoregressive models and apply novel techniques to test whether causality patterns between markets are characterized by one or two regimes. Linkages between the US and Asian markets are shown to follow the threshold model with two regimes, turmoil and tranquility, pointing to differences in cross-border return spillovers in stable and crisis periods. The causality analysis shows that spillovers between US and Asian markets become stronger in the turmoil regime.     

The forward market in emerging currencies: Less biased than in major currencies

Many studies have replicated the finding that the forward rate is a biased predictor of the future change in the spot exchange rate. Usually the forward discount actually points in the wrong direction. But, at least until recently, those studies applied only to advanced economies and major currencies. We apply the same tests to a sample of 14 emerging market currencies. We find a smaller bias than for advanced country currencies. The coefficient is on average positive, i.e., the forward discount at least points in the right direction. It is never significantly less than zero. To us this suggests that a time-varying exchange risk premium may not be the explanation for traditional findings of bias. The reasoning is that emerging markets are probably riskier; yet we find that the bias in their forward rates is smaller. Emerging market currencies probably have more easily-identified trends of depreciation than currencies of advanced countries.     

Sovereign risk spillovers: A network approach

Understanding the global financial network for sovereign debt, particularly with a focus on interaction and spillover effects of sovereign risk, has become important for policy makers as they look to protect the stability of their economies. Using high dimensional Vector Autoregression techniques and network simulation on Sovereign Credit Default Swaps (CDS)’ data of 57 countries, we identify that the global sovereign CDS network is fully integrated as there is virtually no country without any connection to at least one specific node in the system. However, each country has a unique attribute in the network, as a risk exporter or importer and/or risk transmitter. Among developed countries, the US (unsurprisingly) holds the dominant position as a risk exporter while Germany is identified as a connecting country that transmits shocks. The most connected countries in the sovereign CDS network belong to the new European Union members. We examine possible drivers of the network relationships observed, in order to better understand the risk transmission process, and find that connections in the sovereign risk network are stronger within regional groups and countries with the same level of economic development. Central and Eastern Europe and Middle East and Africa have more interactive networks than Northern Western Europe, Asia Pacific and Latin America. We also identify that financial volatility and economic policy uncertainty increase the interactions in market-based default risk assessment.     

Extreme quantile spillovers and drivers among clean energy,electricity and energy metals markets

This paper examines return and volatility spillover effects among the clean energy (electric vehicles, solar and wind), electricity and 8 energy metals (silver, tin, nickel, cobalt, lead, zinc, aluminum and copper) markets and their drivers under the conditions of the mean and extreme quantiles. The results show moderate spillovers among the clean energy, electricity and energy metals markets, and greater connectivity among the three markets under extreme quantile conditions. Among them, the clean energy markets always play the role of the transmitter, and the electricity market always plays the role of the receiver of spillover effects. In addition, the return and volatility spillovers among the three markets have remarkable time-varying features, and they increase dramatically when extreme events occur, especially under extreme quantile conditions. Finally, we reveal the drivers of return and volatility spillovers among these markets by the OLS and quantile regression methods. The COVID-19 and the Arca Tech 100 (PSE) index are found to be important drivers.     

Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

This paper examines how the most prevalent stochastic properties of key metal futures returns have been affected by the recent financial crisis using both mapped and unmapped data. Our results suggest that copper and gold futures returns exhibit time-varying persistence in their corresponding conditional volatilities over the crisis period; in particular, such persistence increases during periods of high volatility compared with low volatility. The estimation of a bivariate GARCH model further shows the existence of time-varying volatility spillovers between these returns during the different stages of such a crisis. Our results, which are broadly the same in relation to the use of mapped or unmapped data, suggest that the volatilities of copper and gold are inherently linked, although these metals have very different applications.     

Price discovery and volatility spillovers in the European Union emissions trading scheme: A high-frequency analysis

This paper models the relationship of European Union Allowance spot- and futures-prices within the second commitment period of the European Union emissions trading scheme. Based on high-frequency data, we analyze the transmission of information in first and second conditional moments. To reveal long-run price discovery, we compute common factor weights of Schwarz and Szakmary (1994) and information shares of Hasbrouck (1995) based on estimated coefficients of a VECM. To analyze the short-run dynamics, we perform Granger-causality tests. We identify the futures market to be the leader of the long-run price discovery process, whereas the informational role of the futures market increases over time. In addition, we employ a version of the UECCC-GARCH model as introduced by Conrad and Karanasos (2010) to analyze the volatility transmission structure. The volatility analysis indicates a close relationship between the volatility dynamics of both markets, whereas in particular we observe spillovers from the futures to the spot market. As a whole the investigation reveals that the futures market incorporates information first and then transfers the information to the spot market.     

After the tide: Commodity currencies and global trade

The decade prior to the Great Recession saw a boom in global trade and rising transportation costs. High-yielding commodity exporters׳ currencies appreciated, boosting carry trade profits. The Global Recession sharply reversed these trends. We interpret these facts with a two-country general equilibrium model that features specialization in production and endogenous fluctuations in trade costs. Slow adjustment in the shipping sector generates boom–bust cycles in freight rates and, as a consequence, in currency risk premia. We validate these predictions using global shipping data. Our calibrated model explains about 57% of the narrowing of interest rate differentials post-crisis.     

Detecting signed spillovers in global financial markets: A Markov-switching approach

We examine the dynamics of the signed-spillover across financial markets using historical decomposition approach. By incorporating Markov-switching framework into the VAR model, this paper assesses the dynamics of signed-spillover during turbulent periods and period of tranquillity. Additionally, this approach enables us to detect the source and direction of the spillover and identify its signs. We show that this approach outperforms the classical single-regime spillover estimation by distinguishing shocks under different economic conditions. Specifically, we assess spillovers in global financial markets using realised variance between January 1999 and December 2017. Our empirical findings clearly indicate that spillovers are intense during period of turbulence and moderate during periods of tranquillity.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Cointegration analysis of the intensity of the ERM currencies under the European Monetary System

This paper examines the (long-run) intra-zonal elasticities between the spot exchange rates of the deutschemark and other major ERM currencies (French franc, Belgian franc, Dutch guilder, Danish krone, Italian lira and British pound) under the EMS. The findings show that under the fixed-but-adjustable rate system, the hypothesis of no cointegration can be rejected for all chosen ERM currency pairs and unit restriction on zonal elasticities can be accepted for almost all cointegrated currency pairs. On the other hand, under the fixed-rate system, Danish krone, Italian lira and British pound fail the cointegration test and the zonal elasticities for all cointegrated currency pairs are rejected to be unity. The study signifies less intense linkages of the ERM currencies without parity realignments. Finally, the deutschmark took the role of error-correcting process for one cointegrated currency pair under the fixed-but-adjustable-rate system, and it performed the same role for two pairs under the fixed-rate system. Hence, deutschmark should not be assumed a priori statistically exogenous under the EMS     

Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures

We provide empirical evidence on the patterns of intra- and inter-regional transmission of information across 10 developed and 11 emerging markets in Asia, the Americas, Europe and Africa using both stock indices and stock index futures. The main transmission channels are examined in the period from 2005 to 2014 through the analysis of return and volatility spillovers around the most recent crises based on the generalized vector autoregressive framework. Our findings demonstrate that markets are more susceptible to domestic and region-specific volatility shocks than to inter-regional contagion. A novel result reported in our study is a difference in patterns of international signals transmission between models employing indices and futures data. We conclude that futures data provide more efficient channels of information transmission because the magnitude of return and volatility spillovers across futures is larger than across indices. Our findings are relevant to practitioners, such as stock market investors, as well as policy makers and can help enhance their understanding of financial markets interconnectedness.     

Emerging floaters: Pass-throughs and (some) new commodity currencies

In spite of early skepticism on the merits of floating exchange rate regimes in emerging markets, 8 of the 25 largest countries in this group have now had a floating exchange rate regime for more than a decade. Using parsimonious VAR specifications covering the period of floating exchange rates, this study computes the dynamics of exchange rate pass-throughs to consumer price indices. We find that pass-throughs have typically been moderate even though emerging floaters have seen considerable nominal and real exchange rate volatilities. Previous studies that set out to estimate exchange rate pass-throughs ignored changes in policy regimes, making them vulnerable to the Lucas critique. We find that, within the group of emerging floaters, estimated pass-throughs are higher for countries with greater nominal exchange rate volatilities and that trade more homogeneous goods. These findings are consistent with the pass-through model of Floden and Wilander (2006) and earlier findings by Campa and Goldberg (2005), respectively. Furthermore, we find that the Indonesian Rupiah, the Thai Baht and possibly the Mexican Peso are commodity currencies, in the sense that their real exchange rates are cointegrated with international commodity prices.     

Stockholding: Participation, location, and spillovers

This paper provides the first joint analysis of household stockholding participation, location among stockholding modes, and participation spillovers. Our model matches observed participation, conditional and unconditional, and asset location patterns. We find that financial sophistication correlates strongly only with direct stockholding and mutual fund participation, while social interactions mainly influence stockholding through retirement accounts. Whether retirement account owners include stocks in their accounts strongly depends on owner characteristics, which is not the case with mutual fund owners and investment in stock funds. Stockholding is more common among retirement account owners, but mainly because of owner characteristics rather than of any participation spillovers from retirement account ownership.