AN OVER‐THE‐COUNTER APPROACH TO THE FOREX MARKET

The foreign exchange (FOREX) market is an over‐the‐counter market characterized by intermediation and significant bid–ask spreads. However, most of the existing international macroeconomics literature models the FOREX as a standard Walrasian market. This article constructs a dynamic general equilibrium model of intermediation in the FOREX market. We use our framework to compute standard measures of FOREX liquidity, such as bid–ask spreads and trade volume, and study how they are affected by macroeconomic fundamentals and market microstructure. We also study how FOREX market microstructure affects the volume of international trade and, consequently, welfare. Our empirical exercise offers support to the models' main predictions.     

A search model of centralized and decentralized trade

This paper presents a search model of centralized and decentralized trade. In a centralized market, trades are intermediated by market makers at publicly posted bid–ask prices. In a decentralized market, traders search counterparties. Prices are negotiated and transactions are conducted in private meetings among traders. Traders can choose which market to enter. The determinants of bid–ask spreads and liquidity are analyzed. The welfare consequence of the market fragmentation is also analyzed. It is shown that compared to the competitive market-making, monopolistic market-making may improve social welfare.     

Model uncertainty and liquidity

Extreme market outcomes are often followed by a lack of liquidity and a lack of trade. This market collapse seems particularly acute for markets where traders rely heavily on a specific empirical model such as in derivative markets like the market for mortgage backed securities or credit derivatives. Moreover, the observed behavior of traders and institutions that places a large emphasis on “worst-case scenarios” through the use of “stress testing” and “Value-at-Risk” seems different than Savage expected utility would suggest. In this paper, we capture model-uncertainty using an Epstein and Wang [Epstein, L.G., Wang, T., 1994. Intertemporal asset pricing under Knightian uncertainty. Econometrica 62, 283–322] uncertainty-averse utility function with an ambiguous underlying asset-returns distribution. To explore the connection of uncertainty with liquidity, we specify a simple market where a monopolist financial intermediary makes a market for a propriety derivative security. The market-maker chooses bid and ask prices for the derivative, then, conditional on trade in this market, chooses an optimal portfolio and consumption. We explore how uncertainty can increase the bid–ask spread and, hence, reduces liquidity. Our infinite-horizon example produces short, dramatic decreases in liquidity even though the underlying environment is stationary. We show how these liquidity crises are closely linked to the uncertainty aversion effect on the optimal portfolio. Effectively, the uncertainty aversion can, at times, limit the ability of the market-maker to hedge a position and thus reduces the desirability of trade, and hence, liquidity.     

Understanding spread in the electronic futures markets: financial crisis perspective

This article analyses bid–ask spreads in U.S. electronic futures markets around the recent financial crisis. We decompose the bid–ask spread into three components – order processing, inventory holding and adverse selection costs – and show that adverse selection costs increased the most during the crisis while order processing costs are the largest cost component. Volume significantly affects inventory holding and order processing costs, whereas volatility only influences inventory holding costs. The crisis period had a significant effect on these relations. This study extends the existing literature on liquidity in equity to futures markets.     

The impact of the French financial transaction tax on HFT activities and market quality

Based on the first results, the French government estimates that the tax on cancelled orders, considered as tax on High Frequency Trading (HFT), generated no revenue in 2012. Our paper question the effectiveness of a modified cancelled order tax with no exemptions, all orders cancelled or modified within half-second time span are taxed. Our study has important implications for the regulation of HFT; we provide recommendations for regulators in relation to market rules which have yet to be introduced, using an artificial market framework. This paper addresses the question of whether this tax leads to a reduction in HFT activities and, as a result, to deterioration or amelioration of market quality. The evidence we provide should help market regulators to better understand the role played by HFT firms as liquidity suppliers. We show that HFT liquidity is short-lived. With the implementation of tax, decreased HFT activities do not have a statistically significant impact on market volatility and market liquidity measured by bid/ask spreads, but decrease dollar volumes as a liquidity measure. In addition, reduced HFT activities lead to less efficient markets as the deviation from fundamentals increases.     

我国主要证券市场VaR模型变动性研究

对证券市场风险度量模型的探索,一直是国内外金融风险管理者关注和研究的热点之一。VaR(Value-at-Risk)风险度量模型,目前已成为金融机构、非金融企业、金融监管部门测量和监控市场风险的主流工具。然而VaR模型能否有效正确地度量证券市场风险,不但取决于估计的精度,还取决于选用VaR模型本身的变动性。因此,探索我国主要证券市场VaR模型的变动性,有一定的现实意义。针对我国主要证券市场指数,本文首先通过图形展示了三类(参数、半参数和非参数)VaR估计方法在不同的窗口设定下控制风险的表现;其次在平均相对偏差(MRB)和平方根相对偏差(RMSRB)的双重标准下,对三类VaR估计模型的变动性进行了比较研究,结果表明:在我国主要证券市场上,参数类VaR估计模型本身的变动性和偏离程度较小,半参数类VaR估计模型次之,而非参数类VaR估计模型本身的变动性和偏离程度较大,这在一定程度上符合新兴国家证券市场存在较大投机收益的特点。     

Short sale constraints and the information content of trading

We examine changes in the information content of trading when short sale constraints between prohibition and restriction exist on a stock exchange. This is made possible by a unique institutional arrangement at the Stock Exchange of Hong Kong. It maintains a list of stocks which can be sold short under regulations. Stocks not on the list are prohibited from short selling. The list is revised on a quarterly basis based on predetermined criteria. We find that the probability of information-based trading (PIN) significantly increases when a stock is added to the list. Further analysis shows that this is mainly because uninformed traders are driven out of the market. Elimination of uninformed traders also causes the aggregate trading volume to decrease rather than increase. In comparison, the PIN does not change when a stock is dropped from the list. We also find that market liquidity, measured by volatility and bid–ask spreads, slightly decreases when a stock is added to the list and significantly increases when a stock is dropped from the list. Possible explanations are discussed.     

Energy portfolio risk management using time-varying extreme value copula methods

This work is concerned with the statistical modeling of the dependence structure between three energy commodity markets (WTI crude oil, natural gas and heating oil) using the concept of copulas and proposes a method for estimating the Value at risk (VaR) of energy portfolio based on the combination of time series models with models of the extreme value theory before fitting a copula. Each return series is modeled by AR-(FI) GARCH univariate model. Then, we fit the GPD distribution to the tails of the residuals to model marginal residuals distributions. The extreme value copula to the iid residuals is fitted and we simulate from it to construct N portfolios and estimate VaR. As a first step, the method is applied to a two-dimensional energy portfolio. In second step, we extend method in trivariate context to measure VaR of three-dimensional energy portfolio. Dependences between residuals are modeled using a trivariate nested Gumbel copulas. Methods proposed are compared with various univariate and multivariate conventional VaR methods. The reported results demonstrate that GARCH-t, conditional EVT and FIGARCH extreme value copula methods produce acceptable estimates of risk both for standard and more extreme VaR quantiles. Generally, copula methods are less accurate compared with their predictive performances in the case of portfolio composed of exchange market indices.     

Liquidity commonality in order-driven trading: evidence from the Athens Stock Exchange

We examine the presence of liquidity commonality in the order-driven Athens Stock Exchange (ASE). Unlike the majority of liquidity commonality studies that focus on the bid–ask spread, our analysis extends deeper in the Limit Order Book, providing insight on the price impact of both small and large trades. We utilize a 6-month FTSE/ATHEX-20 intraday data set to estimate the liquidity factor model of Chordia et al. (2000). To this end, we conduct single-equation analysis as well as panel data analysis with the use of two-way clustered errors, correcting for simultaneous firm and time correlations. Moreover, we apply standard principal component analysis on stock liquidities to extract the marketwide liquidity component. We find that liquidity commonality is low at the bid–ask spread, whereas it increases deeper in the book; consequently, large traders face liquidity risks associated with both individual stock and marketwide illiquidity. Moreover, our empirical evidence hints that liquidity commonality is asynchronous, suggesting that the ASE trading process includes various levels of information speed. Our analysis contributes to the understanding of liquidity commonality in order-driven trading, especially in emerging markets like the ASE where trading activity is limited and information speed is low.     

Risk assessment of oil price from static and dynamic modelling approaches

The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.     

Environmental disclosure and stock market liquidity: evidence from Arab MENA emerging markets

The objective of this study is to examine the impact of environmental disclosure levels on the stock market liquidity of Arab Middle Eastern and North African (MENA) companies. For that, a self-constructed disclosure index was applied to the annual reports for the years 2010, 2011 and 2012 and the bid-ask spread was used as a proxy for stock market liquidity. Results indicate that levels of environmental disclosure in MENA companies are quite low. In addition, using a sample of 276 firm-year observations, multivariate analysis shows that the higher the level of environmental disclosure provided in the annual reports, the lower the spread between the market bid and ask prices, thereby indicating an increase in stock market liquidity.     

研究员收益预测差异与公司债券信用利差

机构研究员对上市公司的未来收益进行预测,预测差异常常造成债券价格出现偏差。以国内上市公司发行的债券为例,以研究员对收益预测的差异和债券信用利差进行了检验。结果发现,在卖空限制下,预测差异越大,债券信用利差越低。这种差异更多地代表了投资者的意见分歧,而非未来的风险水平。并且公司债券比企业债券的信用利差对投资者意见分歧更敏感。此外,还证实了银行间债券市场的流动性确实优于交易所债券市场;平均而言,公司债券的信用利差较企业债券的信用利差更低。     

Equity market information and credit risk signaling: A quantile cointegrating regression approach

Investigating linkages between credit and equity markets, we consider daily aggregate U.S. CDS spreads as well as well-chosen equity market and implied volatility indexes over ten years. We describe such robust (to spurious correlation) relationship with the quantile cointegrating regression approach. Such approach handles extreme quantiles/CDS values and their behavior with respect to the equity market's influence. Heteroskedastic patterns such as time-varying variance, but also autocorrelation, skewness and leptokurtosis are captured. Thus, the sensitivity of aggregate CDS spreads to equity market price and volatility channels is accurately measured across quantiles and spreads. Such quantile-dependent sensitivity exhibits asymmetric responses to equity market shocks. A sub-period analysis investigates potential regime shifts in estimated quantile cointegrating regressions. Quantile cointegrating coefficients vary over time and quantiles, and exhibit different magnitudes across sub-periods and spreads. Therefore, the relationship is unstable over time. We also propose a scenario analysis and risk signaling application for credit risk management prospects. Under specific risk levels, credit risky situations are described conditional on the equity market's information over time, and related expected aggregate CDS spreads are computed. Estimated conditional quantiles/CDS spreads act as credit alert triggers.     

Knightian Uncertainty in Financial Markets: An Assessment

If information is too vague and imprecise to be summarized by a unique additive probability measure, an agent faces Knightian uncertainty or ambiguity rather than risk. Under Knightian uncertainty, an agent's beliefs may be represented by a capacity or a set of additive probabilities. It is proved that an agent's attitude towards ambiguity has a crucial role in asset price determination and portfolio choice. Knightian uncertainty attitude provides an alternative explanation of financial market failures and enables puzzles to be solved, such as market breakdowns, price indeterminacy and volatility, bid and ask spreads, portfolio inertia, violation of call and put parity.
(J.E.L.: D81, G11, G12).     

Pricing and Informational Efficiency of the MIB30 Index Options Market. An Analysis with High‐frequency Data

We analyse the pricing and informational efficiency of the Italian market for options written on the most important stock index, the MIB30. We report that a striking percentage of the data consists of option prices violating basic no‐arbitrage conditions. This percentage declines when we relax the no‐arbitrage restrictions to accommodate the presence of bid/ask spreads and other frictions but never becomes negligible. We also investigate the informational efficiency of the MIBO and conclude that option prices are poor predictors of the volatility of MIB30 returns. This conclusion is robust to a number of statistical and sampling methods.
(J.E.L.: G13, G14).     

Default and liquidity regimes in the bond market during the 2002–2012 period

Using a real‐time random regime shift technique, we identify and discuss two different regimes in the dynamics of credit spreads during 2002–2012: a liquidity regime and a default regime. Both regimes contribute to the patterns observed in credit spreads. The liquidity regime seems to explain the predictive power of credit risk on the 2007–2009 NBER recession, whereas the default regime drives the persistence of credit spreads over the same recession. Our results complement the recent dynamic structural models as well as monetary and credit supply effects models by empirically supporting two important patterns in credit spreads: the persistence and the predictive ability toward economic downturns.     

Budgetary decomposition and yield spreads

With a panel VAR of 10 Euro area countries, we studied the budgetary determinants of government bond yield spreads vis-à-vis Germany between 1999Q1 and 2012Q4. We find that rising bid ask, VIX and debt differentials increase yield spreads; and improvements in the budget balance, higher growth prospects and depreciation lower the spreads. Moreover, rises in public wages or in social expenditure increase spreads, while increases in direct and indirect taxes lower the yield spreads. In the post-2007Q3 crisis period, rising expenditure components (except subsidies) increased spreads.     

Value at risk estimation by threshold stochastic volatility model

This article proposes a threshold stochastic volatility model that generates volatility forecasts specifically designed for value at risk (VaR) estimation. The method incorporates extreme downside shocks by modelling left-tail returns separately from other returns. Left-tail returns are generated with a t-distributional process based on the historically observed conditional excess kurtosis. This specification allows VaR estimates to be generated with extreme downside impacts, yet remains empirically widely applicable. This article applies the model to daily returns of seven major stock indices over a 22-year period and compares its forecasts to those of several other forecasting methods. Based on back-testing outcomes and likelihood ratio tests, the new model provides reliable estimates and outperforms others.     

Uncertainty and liquidity in corporate bond market

We examine the uncertainty–liquidity connection in the corporate bond market. Using monthly corporate bond data from 2005 to 2010, we construct proxies for parameter uncertainty by using firm-level parameters generated from a structural model of corporate debt. We find that uncertainty about firm parameters decreases trading volume but increases bid-ask spreads and price bouncing in the cross-section and across time. In addition, the panel VAR results show that parameter uncertainty has negative forecasting power for future bond liquidity, with greater uncertainty in the current month leading to lower trading volume, higher bid-ask spreads and higher price fluctuations on subsequent months. We conclude that parameter uncertainty is one of the underlying factors giving rise to the high level of illiquidity in the corporate bond market.     

What drives spreads in the euro area government bond market?

Spreads between euro area government bond yields are related to short-term interest rates, which are in turn related to market liquidity, to cyclical conditions, and to investors' incentives to take risk. In theory, lower interest rates are associated with lower degrees of risk aversion and smaller government bond spreads. Empirically, the Eurosystem's short-term interest rates are positively related to those spreads, which our econometric model finds to include significant and policy-relevant default risk and liquidity risk components.
— Simone Manganelli and Guido Wolswijk