EXCHANGE RATE FUNDAMENTALS,FORECASTING, AND SPECULATION: BAYESIAN MODELS IN BLACK MARKETS

Although speculative activity is central to black markets for currency, the out‐of‐sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out‐of‐sample performance of linear models and non‐parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals‐based models outperform the benchmark in out‐of‐sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real‐time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright © 2013 John Wiley & Sons, Ltd.     

Institutional investors' attention to environmental information,trading strategies,and market impacts: Evidence from China

Using a large proprietary database of intraday high‐frequency trading, we investigate the trading strategies of institutional investors in dealing with the negative environmental event disclosure of listed companies and their impact on markets, aiming to reveal the mechanism of the lack of “green efficiency” in China's capital market from the perspective of institutional investors. The results show that institutional investors react to negative environmental events prior to the announcements, indicating premature information leakage in the market; in addition, their trading behaviors mitigate the immediate effect of negative environmental event announcements on stock price. After the event is disclosed, institutional investors engage in short‐term selling and long‐term buy and hold. This trading strategy undermines the irrational selling of individual investors in the event of disclosure, short‐term decline in stock price, and long‐term reversal of market overreaction. In a China context, institutional investors generally take environmental information into consideration. However, they fail to recognize the long‐term value effect of negative environmental events and instead cater to trading strategies towards market volatility.     

Structural estimation of behavioral heterogeneity

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit‐maximizing agents switch between trading strategies in response to dynamic market conditions. Owing to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set—a small sub‐population—to point identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.     

重大事件披露、股价异常波动与内幕交易——基于重大信息披露违规公司的经验证据

规范化的信息披露是证券市场正常运转的基石。本文利用重大事件披露违规公司研究信息披露违规背后是否存在股价异常波动与内幕交易现象，并将样本公司按照处分类型和公司类型分类检验。研究表明，总体样本公司的股票存在显著的内幕交易行为，并呈现出牛市背景下的新特征：受到公开谴责的公司股票内幕交易程度显著高于受到公开处罚的公司股票，ST公司股票的内幕交易程度显著高于非ST公司股票。     

The impact of individual investor trading on information asymmetry in the Korean stock market

This paper examines the impact of individual investor trading on information asymmetry in the market. In particular, we examine the relationship between the trading volume by individual investors and the corresponding bid-ask spread in the Korean stock market, where the majority of the trading activity is driven by individual investors and therefore information asymmetry can be evident. We find that high trading activity by individual investors increases the bid-ask spread in a short investment horizon, suggesting that individual investors, as uninformed and unsophisticated traders, amplify the degree of information asymmetry in the market through trading.     

信息披露与内部人股票交易获利策略——以六起内部人股票交易为基础的案例研究

本文以近期A股市场内部人股票交易活跃的六家公司为例,通过考查信息披露与内部人股票交易间的关系,解释内部人股票交易的获利策略。研究发现,在允许内部人交易本公司股票的情况下,信息披露与内部人股票交易关系密切,内部人存在利用私有信息和策略性信息披露两类获利策略。信息权力是内部人股票交易的获利基础,公司业绩是影响内部人股票交易获利策略选择的重要因素,而法律诉讼风险并没有对我国内部人股票交易和信息披露产生明显约束作用。这些发现对完善我国资本市场内部人股票交易行为规范具有一定借鉴意义。     

Testing the stabilization hypothesis in the UK short-term interest rates: Evidence from a GARCH-X model

The objective of this paper is to examine the validity of one of the recurring arguments made against futures markets that they give rise to price instability. The paper concentrates on the impact of futures trading on the spot market volatility of short-term interest rates. The analytical framework employed is based on a new statistical approach aiming to reconcile the traditional models of short-term interest rates and the conditional volatility processes. More specifically, this class of models aims to capture the dynamics of short-term interest rate volatility by allowing volatility to depend on both scale effects and information shocks. Using a GARCH-X and asymmetric GARCH-X model four main conclusions emerge from the present study. First, the empirical results suggest that there is an indisputable change in the nature of volatility with evidence of mean reversion after the onset of futures trading. Second, the information flow into the market has improved as a result of futures trading. Third, a stabilization effect has been detected running from the futures market to the cash market by lowering volatility levels and decreasing the risk in the spot market. Finally, trying to capture the leverage effect the findings suggest that positive shocks have a greater impact on volatility than negative shocks.     

News will tell: Forecasting foreign exchange rates based on news story events in the economy calendar

The paper proposes a novel approach to predict intraday directional-movements of currency-pairs in the foreign exchange market based on news story events in the economy calendar. Prior work on using textual data for forecasting foreign exchange market developments does not consider economy calendar events. We consider a rich set of text analytics methods to extract information from news story events and propose a novel sentiment dictionary for the foreign exchange market. The paper shows how news events and corresponding news stories provide valuable information to increase forecast accuracy and inform trading decisions. More specifically, using textual data together with technical indicators as inputs to different machine learning models reveals that the accuracy of market predictions shortly after the release of news is substantially higher than in other periods, which suggests the feasibility of news-based trading. Furthermore, empirical results identify a combination of a gradient boosting algorithm, our new sentiment dictionary, and text-features based-on term frequency weighting to offer the most accurate forecasts. These findings are valuable for traders, risk managers and other consumers of foreign exchange market forecasts and offer guidance how to design accurate prediction systems.     

How useful are signals? A micro-structure analysis

We analyze how the market processes a signaling event by studying a sample of self-tender offers, events often viewed as signals of firm value. By examining changes in the degree of informed trading, we find asymmetric information costs fall at announcement, remain low throughout the event, and increase at offer expiration. By one month following expiration, informed trading returns to a level not significantly different from that prior to the offer. Higher risk firms have significantly larger declines in information asymmetry during the offer. Increases in information asymmetry persist one month following expiration for firms with lower pre-offer informed trading. (JEL G14, G32)     

Carbon management accounting and financial performance: Evidence from the European Union emission trading system

Companies are responding to the effects of climate change by reducing CO₂ emissions as a way of managing stakeholder interests and complying with legal and regulatory requirements. In Europe, the emissions trading system is consolidated as a limiting market and control scheme to support business climate change management through a collaborative relationship between government and industry. This work focuses on the economic accounting field, analysing carbon management accounting and its impact on financial performance in scenarios attached to that trading system. The methodological approach used is quantitative, empirically testing the hypotheses through a multiple regression analysis with a sample of 350 European companies. The results attest to the importance of carbon management accounting (CMA) control and its effects on financial performance. Compared with European emission trading, the results failed to display significant differences in the relationship studied between those that make up this type of market and those that do not.     

Dissemination of Accruals Information,Role of Semi‐Annual Reporting,and Analysts' Earnings Forecasts: Evidence from Japan

Our study investigates the effects of dissemination of accounting accruals information on stock prices using Japanese annual reports as our sample. We conduct month‐by‐month detailed analyses of price adjustment behavior with a particular focus on revisions of analysts' earnings forecasts and changes in trading volume around the period of upcoming semi‐annual reports. We find that analysts' forecasts are often revised around this time, and analysts use this as auxiliary information. In addition, an accompanying re‐adjustment of abnormal returns and an increase in trading volume are observed. Our findings demonstrate that informational uncertainty initially triggered by the announcement of annual reports decreases as semi‐annual reports are disclosed and analysts change their earnings forecasts, and confirms the importance of semi‐annual reporting.     

Competitive market equilibrium under asymmetric information

This paper studies the existence of a competitive market equilibrium under asymmetric information. There are two agents involved in the trading of the risky assets: an “informed” trader and an “ordinary” trader. The market is competitive and the ordinary agent can infer the insider information from the price dynamics of the risky assets. The insider information is considered to be the total supply of the risky assets. The definition of market equilibrium is based on the law of supply-demand as described by a rational expectations equilibrium of the Grossman and Stiglitz (Am Econ Rev 70:393–408, 1980) model. We show that equilibrium can be attained by linear dynamics of an admissible price process of the risky assets for a given linear supply dynamics.      

Market efficiency, discount-rate changes, and stock returns: A long-term perspective

This paper examines the market efficiency issue by analyzing stock returns surrounding Fed announcements of discount-rate changes. Based on an analysis ofex post returns over a 58-year period, the results provide evidence of long-term market efficiency. Consistent with recent literature, the findings also reveal some predictability in return patterns where an active trading strategy based on directional reversals in the pattern of discount rate changes outperforms a passive buy-and-hold approach. The results indicate that the proposed active trading produces substantially higher risk-adjusted returns than the buy-and-hold strategy.     

Forecasting volatility via stock return,range, trading volume and spillover effects: The case of Brazil

For the purpose of developing alternative approach for forecasting volatility, we consider heterogeneous VAR (HVAR) model which accommodates the market effects of different horizons, namely, daily, weekly and monthly effects, and examine the interdependence of stock markets in Brazil and the US, based on information of daily return, range and trading volume. To compare with the new approach, we also work with the univariate and multivariate GARCH models with asymmetric effects, trading volumes and fat-tails. The heteroskedasticity-corrected Granger causality tests based on the HVAR show the strong evidence of such spillover effects. We assess the value-at-risk thresholds for Brazil, based on the out-of-sample forecasts of the HVAR model, finding the new approach works satisfactory for the periods including the global financial crisis, without assuming heavy-tailed conditional distributions.     

How to Identify and Forecast Bull and Bear Markets?

Because the state of the equity market is latent, several methods have been proposed to identify past and current states of the market and forecast future ones. These methods encompass semi‐parametric rule‐based methods and parametric Markov switching models. We compare the mean‐variance utilities that result when a risk‐averse agent uses the predictions of the different methods in an investment decision. Our application of this framework to the S&P 500 shows that rule‐based methods are preferable for (in‐sample) identification of the state of the market, but Markov switching models for (out‐of‐sample) forecasting. In‐sample, only the mean return of the market index matters, which rule‐based methods exactly capture. Because Markov switching models use both the mean and the variance to infer the state, they produce superior forecasts and lead to significantly better out‐of‐sample performance than rule‐based methods. We conclude that the variance is a crucial ingredient for forecasting the market state. Copyright © 2016 John Wiley & Sons, Ltd.     

Extreme returns and intensity of trading

Asymmetric information models of market microstructure claim that variables such as trading intensity are proxies for latent information on the value of financial assets. We consider the interval‐valued time series (ITS) of low/high returns and explore the relationship between these extreme returns and the intensity of trading. We assume that the returns (or prices) are generated by a latent process with some unknown conditional density. At each period of time, from this density, we have some random draws (trades) and the lowest and highest returns are the realized extreme observations of the latent process over the sample of draws. In this context, we propose a semiparametric model of extreme returns that exploits the results provided by extreme value theory. If properly centered and standardized extremes have well‐defined limiting distributions, the conditional mean of extreme returns is a nonlinear function of the conditional moments of the latent process and of the conditional intensity of the process that governs the number of draws. We implement a two‐step estimation procedure. First, we estimate parametrically the regressors that will enter into the nonlinear function, and in a second step we estimate nonparametrically the conditional mean of extreme returns as a function of the generated regressors. Unlike current models for ITS, the proposed semiparametric model is robust to misspecification of the conditional density of the latent process. We fit several nonlinear and linear models to the 5‐minute and 1‐minute low/high returns to seven major banks and technology stocks, and find that the nonlinear specification is superior to the current linear models and that the conditional volatility of the latent process and the conditional intensity of the trading process are major drivers of the dynamics of extreme returns.     

上证180指数流动性效应的实证研究

本文从实证的角度探讨了上证180指数创立事件对其成份股流动性的影响以及进一步改善的方法。上证180指数的成立事件一方面促进了成份股价差水平和交易信息对称程度的改善,另一方面又促使交易深度水平和交易活跃性的降低。这些流动性效应是由于机构投资者对180成份股偏好所造成的:机构投资者增加了180成份股的需求同时减少了供给,就导致了交易深度和活跃性的降低;机构投资者作为相对知情交易者,它们的偏好增加了市场的需求竞争程度,从而降低了交易者之间的信息不对称程度以及改善了市场价差水平。根据国外的经验,ETF可以有效地增强市场交易深度,因此本文建议创立上证180指数ETF弥补180指数对深度方面的负面影响。     

沪深300股指期货在现货交易和非交易时段交易特征的比较研究

我国沪深300股指期货交易2010年4月16日正式推出,但沪深300股指期货市场与沪深300现货市场的交易时间存在显著的差异,即相对于股票现货市场,沪深300股指期货市场提前15分钟开盘,延迟15分钟收盘。运用日内分笔数据和分钟数据,对沪深300股指期货不同交易时段的交易特征进行比较。研究表明,不同交易时段知情交易者市场参与度存在明显差异,提前交易时段知情交易的概率最高,现货交易时段次之,延迟交易时段最低;沪深300股指期货在开盘时段的交易提供了较大的价格发现,特别是开盘的第一笔交易包含有大量的私有信息,价格贡献最大;提前交易时段私有信息的价格发现贡献度最高;尽管提前交易时段的交易提供了较大的价格发现,但定价效率较低。     

Measuring Financial Contagion Using Time‐Aligned Data: The Importance of the Speed of Transmission of Shocks*

This paper presents a new empirical approach to address the problem of trading time differences between markets in studies of financial contagion. In contrast to end‐of‐business‐day data common to most contagion studies, we employ price observations, which are exactly aligned in time to correct for time‐zone and end‐of‐business‐day differences between markets. Additionally, we allow for time lags between price observations in order to test the assumption that the shock is not immediately transmitted from one market to the other. Our analysis of the financial turmoil surrounding the Asian crisis reveals that such corrections have an important bearing on the evidence for contagion, independent of the methodology employed. Using a correlation‐based test, we find more contagion the faster we assume the shock to be transmitted.     

Simple agent-based dynamical system models for efficient financial markets: Theory and examples

We propose an agent-based framework, based on simple piecewise linear time-invariant continuous-time dynamical systems models, as a means for describing efficient financial markets. We show by examples that many of the common agent-specific trading strategies occurring in the academic literature, including chartists and fundamentalists of various kinds, can be described in the proposed framework. We present definitions for weak and strong market efficiency and provide necessary and sufficient conditions for them to hold. We present minimal examples of strongly and weakly efficient markets to show that these concepts are natural and easy to satisfy in agent-based models, and that the models can reproduce both statistical and behavioral stylized facts of real markets. We provide examples to demonstrate that the framework can be extended for agents with delays in information processing, as well as for agents with time-varying strategies and for nonlinear market impact functions. We also provide a counterexample to show that the proposed market efficiency concepts may require modification in generalizations for nonlinear trading strategies.