Put-call parity revisited: intradaily tests in the foreign currency options market

We test exchange-traded (PHLX) German mark options for conformance to put-call parity (PCP). Puts and calls are matched to the nearest minute, and the relative impact of competing spot exchange rate sources (Reuters vs. Telerate) is assessed. We find that PCP usually holds (roughly 96% of put-call pairs), with the exception of a notable incident in the European options pits. In those instances in which PCP is violated, we find sharp intradaily and intraweekly seasonalities for American options, with disproportionate PCP violations occurring during the relatively light trading periods in early evening and on Fridays. We also conclude that the Telerate prices as recorded by the PHLX are not as accurate as the Reuters exchange rates provided by Olsen and Associates, probably because of time lags in the Telerate data.     

Speculative attacks: A laboratory study in continuous time

We examine speculative attacks in a controlled laboratory environment featuring continuous time, size asymmetries, and varying amounts of public information. Attacks succeeded in 233 of 344 possible cases. When speculators have symmetric size and access to information: (a) weaker fundamentals increase the likelihood of successful speculative attacks and hasten their onset, and (b) contrary to some theory, success is enhanced by public access to information about either the net speculative position or the fundamentals. The presence of a larger speculator further enhances success, and experience with large speculators increases small speculators' response to the public information. However, giving the large speculator increased size or better information does not significantly strengthen his impact.     

A change in market microstructure: the switch to electronic screen trading on the New Zealand stock exchange

The New Zealand Stock Exchange (NZSE) switched from open outcry trading to an electronic screen trading system on June 24, 1991. The change was made by the members of the exchange to improve the trading system and to reduce costs. This paper investigates empirically whether improvement was achieved through a reduction in transaction costs. The tests and results focus on order-flow migration to the exchange from alternative execution locations and changes in bid-ask spreads. On balance, we conclude that transaction costs have declined.     

The market microstructure approach to foreign exchange: Looking back and looking forward

Research on foreign exchange market microstructure stresses the importance of order flow, heterogeneity among agents, and private information as crucial determinants of short-run exchange rate dynamics. Microstructure researchers have produced empirically-driven models that fit the data surprisingly well. But FX markets are evolving rapidly in response to new electronic trading technologies. Transparency has risen, trading costs have tumbled, and transaction speed has accelerated as new players have entered the market and existing players have modified their behavior. These changes will have profound effects on exchange rate dynamics. Looking forward, we highlight fundamental yet unanswered questions on the nature of private information, the impact on market liquidity, and the changing process of price discovery. We also outline potential microstructure explanations for long-standing exchange rate puzzles.     

Speculative trading and stock returns: A stochastic dominance analysis of the Chinese A-share market

The pricing of A-shares in China has long puzzled financial economists. This paper applies recent tests of stochastic dominance (SD) to examine whether differences in the return distributions of A- and B-shares in China are consistent with market efficiency. As SD is nonparametric, market efficiency can be examined without the joint test problem arising from misspecifications in the asset pricing benchmark. Our results show A-shares have second-order dominated B-shares from 1996 to 2005. This dominance was most significant during the market segmentation period, but has continued, albeit to a lesser extent even after the B-share market was opened to local investors in 2001. Our results are robust to using residual returns from an international asset pricing model instead of raw returns. We conclude that the superior performance of A-shares cannot be attributed to risk. The results are more likely due to a return bias caused by intense speculation among retail individuals under limited arbitrage.     

Real-time market microstructure analysis: online transaction cost analysis

Motivated by the practical challenge in monitoring the performance of a large number of algorithmic trading orders, this paper provides a methodology that leads to automatic discovery of causes that lie behind poor trading performance. It also gives theoretical foundations to a generic framework for real-time trading analysis. The common acronym for investigating the causes of bad and good performance of trading is transaction cost analysis Rosenthal [Performance Metrics for Algorithmic Traders, 2009]). Automated algorithms take care of most of the traded flows on electronic markets (more than 70% in the US, 45% in Europe and 35% in Japan in 2012). Academic literature provides different ways to formalize these algorithms and show how optimal they can be from a mean-variance (like in Almgren and Chriss [J. Risk, 2000, 3(2), 5–39]), a stochastic control (e.g. Guéant et al. [Math. Financ. Econ., 2013, 7(4), 477–507]), an impulse control (see Bouchard et al. [SIAM J. Financ. Math., 2011, 2(1), 404–438]) or a statistical learning (as used in Laruelle et al. [Math. Financ. Econ., 2013, 7(3), 359–403]) viewpoint. This paper is agnostic about the way the algorithm has been built and provides a theoretical formalism to identify in real-time the market conditions that influenced its efficiency or inefficiency. For a given set of characteristics describing the market context, selected by a practitioner, we first show how a set of additional derived explanatory factors, called anomaly detectors, can be created for each market order (following for instance Cristianini and Shawe-Taylor [An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, 2000]). We then will present an online methodology to quantify how this extended set of factors, at any given time, predicts (i.e. have influence, in the sense of predictive power or information defined in Basseville and Nikiforov [Detection of Abrupt Changes: Theory and Application, 1993], Shannon [Bell Syst. Tech. J., 1948, 27, 379–423] and Alkoot and Kittler [Pattern Recogn. Lett., 1999, 20(11), 1361–1369]) which of the orders are underperforming while calculating the predictive power of this explanatory factor set. Armed with this information, which we call influence analysis, we intend to empower the order monitoring user to take appropriate action on any affected orders by re-calibrating the trading algorithms working the order through new parameters, pausing their execution or taking over more direct trading control. Also we intend that use of this method can be taken advantage of to automatically adjust their trading action in the post trade analysis of algorithms.     

Empirics of currency crises: A duration analysis approach

This paper empirically analyzes the origins of currency crises for a group of OECD economies from 1970 through 1998. We apply duration analysis to examine how the probability of a currency crisis depends on the length of non‐crisis periods, contagion channels, and macroeconomic fundamentals. Our findings confirm the negative duration dependence of a currency crisis—the likelihood of speculative attack sharply increases at the beginning of non‐crisis periods and then declines over time until it abruptly rises again. The results also indicate the hazard of a crisis increase with high values of the volatility of unemployment rates, inflation rates, contagion factors—which mostly work through trade channels, unemployment rates, real effective exchange rate, trade openness, and size of economy. To address concerns regarding validity of the identified crisis episodes, we exploit crisis episodes that are identified by a more objective approach based on the extreme value theory. Our results are robust under various specifications including two different crisis event sets that are identified on monthly and quarterly basis.     

Comparing COVID-19 with the GFC: A shockwave analysis of currency markets

I analyze the shockwave effect of the COVID-19 pandemic on currency markets, with a comparison to the global financial crisis (GFC), employing Kapetanios m-break unit root test, investigations of standalone risk measures—downside variance, upside risk, volatility skewness, Gaussian Value at Risk (VaR), historical VaR, modified VaR—and Diebold–Yilmaz volatility spillover analysis. Standalone risk analysis shows that the turmoil in the initial months of COVID-19 was not as severe as that in the GFC. However, examination of co-movements and volatility spillovers illustrates a different scenario. According to the results of the static connectedness measure of Diebold–Yilmaz, the shockwave of the COVID-19 pandemic in the total volatility spillover is about eight times greater than that of the GFC. Among standalone risk measures, the results closest to this finding are obtained from volatility skewness analysis. Additionally, of six foreign exchange rates, the Brazilian real and Turkish lira are the currencies experiencing the greatest increase in received volatility during the GFC and the COVID-19 pandemic, respectively. These findings suggest the severe effect of crises on emerging financial markets.     

Market microstructure: A review from down under

The early automation of the Australian and New Zealand financial markets provided researchers with access to high‐frequency data to undertake extensive empirical market microstructure research. We use this anniversary edition of Accounting and Finance to review some of this research and to discuss the development of the Australian and New Zealand markets since their automation. We identify issues currently facing the markets and highlight potential areas for future research. The paper also provides a review of market microstructure theory on inventory control models and asymmetric information models.     

A stopping time approach to assessing the effectiveness of foreign exchange intervention: An application to Japanese data

I propose a new methodology to assess the effect of foreign exchange (FX) intervention, based on the probability of an FX rate reaching. The variable is the probability of an FX rate reaching a particular threshold before reaching another. Importantly, the probability depends on not only the level, but also the trend and volatility of a current FX rate. When an intervention changes the probability in a desired direction, the intervention is effective. The notable feature of the probability is that it considers both the level and volatility of an FX rate comprehensively, while previous studies have examined these effects of FX intervention separately. Empirical results based on regression and nearest-neighbor analyses applied to Japanese data indicate that publicity and size are significant in the effectiveness of intervention.     

The first arrow hitting the currency target: A long-run risk perspective

This paper reconsiders the successful currency outcome of the first arrow of Abenomics. The Japanese yen depreciation against the U.S. dollar after the introduction of the first arrow co-moves tightly with long-term yield differentials between Japan and the United States. The estimated term structure of the sensitivity of the currency return of the Japanese yen to the two-country interest rate differential indeed shifts up and becomes steeper after the onset of Abenomics. To explain this structural change in the term structure of the Fama regression coefficient, we employ a long-run risk model endowed with real and nominal conditional volatilities as in Bansal and Shaliastovich (2013). Under a plausible calibration, the model replicates the structural change when nominal uncertainty dominates real uncertainty in the U.S. bond market. We conjecture that the arrow was shot off from the U.S. side, not the Japan side.     

A market model with medium/long-term effects due to an insider

In this article, we consider a modification of the Karatzas–Pikovsky model of insider trading. Specifically, we suppose that the insider agent influences the long/medium-term evolution of Black–Scholes type model through the drift of the stochastic differential equation. We say that the insider agent is using a portfolio leading to a partial equilibrium if the following three properties are satisfied: (a) the portfolio used by the insider leads to a stock price which is a semimartingale under his/her own filtration and his/her own filtration enlarged with the final price; (b) the portfolio used by the insider is optimal in the sense that it maximises the logarithmic utility for the insider when his/her filtration is fixed; and (c) the optimal logarithmic utility in (b) is finite. We give sufficient conditions for the existence of a partial equilibrium and show in some explicit models how to apply these general results.     

Why do Japanese giant trading companies prefer foreign currency to Japanese yen?: A supplementary note

This note extends the Chen and Chiang (1992) analysis to examine the possibility that trades may be denominated in the currency of the third country. Two main conclusions are found in this note. First, the quantities of trade and employment are still invariant to invoicing strategies chosen. Second, the currency of the trading partner may not be chosen by the monopolistic trader.     

A framework to measure integrated risk

A framework underlying various models that measure the credit risk of a portfolio is extended in this paper to allow the integration of credit risk with a range of market risks using Monte Carlo simulation. A structural model is proposed that allows interest rates to be stochastic and provides closed-form expressions for the market value of a firm's equity and its probability of default. This model is embedded within the integrated framework and the general approach illustrated by measuring the risk of a foreign exchange forward when there is a significant probability of default by the counterparty. For this example moving from a market risk calculation to an integrated risk calculation reduces the expected future value of the instrument by an amount that could not be calculated using the common pre-settlement exposure technique for estimating the credit risk of a derivative.     

A new approach to measuring riskiness in the equity market: Implications for the risk premium

We introduce a new approach to measuring riskiness in the equity market. We propose option implied and physical measures of riskiness and investigate their performance in predicting future market returns. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P 500 index option implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic variables. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.     

Strategic Early Warning System for the French milk market: A graph theoretical approach to foresee volatility

This paper presents a new approach for developing a Strategic Early Warning System aiming to better detect and interpret weak signals. We chose the milk market as a case study, in line with the recent call from the EU Commission for governance tools which help to better address such highly volatile markets. Furthermore, on the first of April 2015, the new Common Agricultural Policy ended quotas for milk, which led to a milk crisis in the EU. Thus, we collaborated with milk experts to get their inputs for a new model to analyse the competitive environment. Consequently, we constructed graphs to represent the major factors that affect the milk industry and the relationships between them. We obtained several network measures for this social network, such as centrality and density. Some factors appear to have the largest major influence on all the other graph elements, while others strongly interact in cliques. Any detected changes in any of these factors will automatically impact the others. Therefore, scanning ones competitive environment can allow an organisation to get an early warning to help it avoid an issue (as much as possible) and/or seize an opportunity before its competitors. We conclude that Strategic Early Warning Systems as a corporate foresight approach utilising graph theory can strengthen the governance of markets.     

Barriers to the investment in the Concentrated Solar Power sector in Morocco: A foresight approach using the Cross Impact Analysis for a large number of events

The Scenario Analysis methods have often been used by policy makers as an instrument to manage uncertainty and to support the shaping of long-term economy policies. In this research, we apply Scenario Analysis in order to identify the barriers affecting the decision to invest in the Concentrated Solar Power (CSP) sector in Morocco. Our results aim at facilitating the process of defining different paths in strategic political and policy actions. Using data from a survey on a panel of experts, the Cross Impact Analysis (CIA) and the Cross Impact Matrix System (SMIC) techniques are applied. The advantage of these techniques is that they allow including in the analysis the interlinkages between the events that will define the future scenarios. However, their limitation is that the number of events analyzed cannot be too high since the information collected from the experts increases exponentially according to the number of events introduced. We thus expand our analysis with a new methodological approach, combining the use of prospective and statistics techniques. This approach allows addressing the mentioned limitation and applying these techniques, initially restricted to 6 events in its common application, to a large number of events. The results show that uncertainty and informality would be key factors in promoting the arrival of companies in this sector. Additionally, regarding companies that already have a presence in Morocco’s renewable energy sector, an increase in activity would be achieved through improvements in the easing of financial and legal barriers.     

From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets

This paper presents stylized facts concerning the spot intra-daily foreign exchange markets. It first describes intra-daily data and proposes a set of definitions for the variables of interest. Empirical regularities of the foreign exchange intra-daily data are then grouped under three major topics: the distribution of price changes, the process of price formation and the heterogeneous structure of the market. The stylized facts surveyed in this paper shed new light on the market structure that appears composed of heterogeneous agents. It also poses several challenges such as the definition of price and of the time-scale, the concepts of risk and efficiency, the modeling of the markets and the learning process.