Wealth transfer through private placements: Evidence from China

We examine private issuance of public equity (PIPE) in China, and our results suggest that PIPE investors benefit from the price manipulation before and after issuance. These investors tend to cash out after lockup expiration and make large profits. We also find evidence that the trading of PIPE investors after lockup expiration is informed. Tests about the abnormal returns in the 3 years after lockup expiration suggest that at least part of the benefits PIPE investors receive come from wealth transfer from outside investors. Overall, PIPE issuers in China seem to use an opaque mechanism to compensate PIPE investors.     

Strategic insider trading around earnings announcements in Australia

This paper tests, within the Australian setting, whether directors strategically time trades in their own firms, around earnings announcements, in the context of impediments to trading in the immediately preceding period. I show that both signed and unsigned trade activity are insignificantly different from zero in the preceding period, and significantly negative and positive after the event. Further, directors in Australia significantly sell following positive earnings news, and buy after negative news, providing evidence of ‘indirect’ trading. Directors’ trades in the longer-term pre-announcement period are also negatively related to the news content sentiment, contrary to expectation. Finally, I find evidence of positive autocorrelation between directors’ trades over the longer-term past, and those executed after earnings announcements, which, in the absence of the ‘short-swing’ rule in Australia, casts doubt over short-term strategic insider trading, more generally.     

广东湖北碳排放权市场动态相依性分析与风险测度

选择具有代表性的湖北和广东碳排放权交易市场为研究对象,利用GARCH-POT-Copula模型对这两个市场的动态相依性与组合风险度量进行分析。研究结果表明:广东和湖北碳排放权市场之间的相依度较小,两个碳排放权市场价格波动不能给对方市场带来较大的影响,两市场近似于独立存在。提出了要从配额指标、基础设施建设、报送系统、市场交易主体等方面建立健全和完善全国统一的碳排放权交易市场的建议。     

我国碳排放交易会计问题研究

从碳排放交易所涉及重点排放企业的角度出发,通过分析我国碳排放交易市场的现状,借鉴相关的研究与规范,就碳排放配额的会计确认问题、碳排放权交易的会计处理问题、企业碳排放相关的会计信息披露问题进行研究分析,提出了碳排放交易的会计处理的意见和建议。     

Share trading activity and the rise of the rentier in the UK before 1920*

Abstract

Using a hand-collected dataset, we examine share trading activity over the period 1882–1920 for the North British and Mercantile Insurance Company, one of the largest UK companies of the time. Our main finding is that the steady flow of rentiers into the shareholding constituency of this company stymied share trading activity. Another important finding is that share trading still occurred during the closure of the stock exchange in 1914, but on a much-reduced scale. We also find that there was a substantial boom in share trading and in insurance stock prices after World War I.     

Does trade size restriction affect trading behavior? Evidence from Indian single stock futures market

Algorithmic traders use their advantage of speed to execute a large number of small-sized trades in a very short time. In the presence of a minimum trading unit (MTU) restriction, they are forced to trade at the smallest possible sizes, often restricted by the MTU. Using a novel data set of single stock futures market obtained from the National Stock Exchange of India, we show that the MTU restriction acts as a binding constraint for traders while optimizing trade sizes. Contrary to expectation, we find weak evidence that liquidity is positively impacted by the contract size revision.     

Hedging costs and joint determinants of premiums and spreads in structured financial products

Evaluating more than 317,000 discount certificates in the German secondary market, we find that premiums and spreads are endogenous and negatively related but depend on different key determinants. The fundamental determinants of the premiums are mainly profit-related, that is, dividends of the underlying, issuers’ credit risk, lifecycle effect, and competition, whereas hedging costs are less important. However, initial hedging costs (IHC) are priced into the premium in the case of large inventory changes. The spread is mostly determined by hedging costs and risk components, such as IHCs, rebalancing costs, volatility, scalper risk, and overnight gap risk—but also by dividends.     

林权流转价格及其影响因素分析

以林农拥有的活立木为研究对象,利用2007—2017年浙江省1546宗活立木流转样本,采用多元线性回归实证分析了是否在林权交易中心交易对活立木流转价格存在影响。结果表明:关键解释变量是否在林权交易中心进行交易对活立木流转价格具有显著的正向影响;流转面积、单位面积蓄积、区域虚拟变量、坡度等对流转价格都产生一定程度的影响;流转期限对流转价格的影响不大。因此,需要加强对林权交易中心的宣传,降低相关的交易成本,从而吸引更多的小规模林农参与交易。     

Is faster or slower trading better? An examination of order type execution speed and costs

We examine order type execution speed and costs for US equity traders. Marketable orders that execute slower exhibit lower execution costs. Those who remove liquidity faster and pay higher trading costs transact in smaller size, spread trading across more venues, take more liquidity, and are better informed. Nonmarketable limit orders that execute slower exhibit greater adverse selection; and larger, uninformed traders who concentrate their trading in fewer venues submit them. Our findings suggest that slowing down the trading process, when faster options exist, can benefit certain market participants who seek to cross the bid–ask spread.     

A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.