Revisiting the ICAPM under the distortion of risk–return tradeoff in short-horizon stock returns

We suggest that the distortion of the positive risk–return relation in the ICAPM is a consequence of trading by informed investors to exploit mispricing. We hypothesize and demonstrate that a non-positive (strongly positive) risk–return relation following positive (negative) market returns is attributed to short-selling (purchasing) of overpriced (underpriced) stocks along with optimistic (pessimistic) expectations conditional on good (bad) market news. We verify this asymmetry in the risk–return relation through the indirect risk–return relation conditional on good (bad) market news. We also find that the attenuation (reinforcement) of the positive risk–return relation is more profound in high- (low-) sentiment periods.     

南方丘陵区新增耕地质量空间特征研究*——以江西省宜春市为例

［目的］粮食安全的根本是在耕地，关键在于耕地质量。目前新增耕地主要源于土地开发项目、城乡建设用地增减挂钩土地复垦项目等，这些新增耕地需要对其开展耕地质量等别评定工作，了解新增耕地的质量状况，分析其空间特征，这对落实国家耕地保护制度、开展农村土地整治工作等具有重要作用。［方法］文章以南方典型丘陵区域——江西省宜春市作为研究区域，在新增耕地质量评价的基础上，运用地统计学、景观生态学、Arcgis空间分析技术和典型相关分析方法，研究宜春市新增耕地质量的空间特征，掌握耕地质量等别的分布规律，了解耕地质量的影响因素，为制定合理的耕地资源利用与保护政策提供依据。［结果］（1）Moran′s I值结果表明宜春市2014年新增耕地利用质量在空间分布上的空间自相关性最强，而耕地自然质量空间自相关性最弱。（2）景观破碎度指数结果表明优、高等别的新增耕地质量破碎度大于中、低等别的； 多样性指数结果表明新增耕地质量多样性指数比较大； 优势度指数结果表明新增耕地质量等别优势度指数比较小，与多样性指数结果相呼应； 均匀度指数结果表明，新增耕地质量等别均匀度指数相差不大，新增耕地质量等别比较均匀。（3）质心结果表明2013—2014年间宜春市新增耕地质量的格局整体上是向西南方向变化。［结论］宜春市新增耕地质量不高； 新增耕地的利用水平差异性较小，自然本底状况差异较大； 新增耕地质量等别类型多，各质量等别类型耕地均有增加，耕地质量参差不齐，较高等地的新增耕地相对低等地而言更破碎化； 新增耕地的开发格局向着西南方向移动； 该研究为南方丘陵区的新增耕地保护提供了一定的参考依据。     

Investor protection and value creation in cross‐border M&As by emerging economies

Previous research investigating cross‐border M&As (CBM&As) by emerging economies (EEs) provided contrasting evidence on the value enhancement role of investor protection rules. We conduct a new empirical study to address the issue with an accurate sample selection of bidders from more homogeneous developing countries and transactions on developed countries only. Our analysis over the 1997–2012 period on a sample of M&A deals by companies from Brazil, Russia, India, China, and South Africa (BRICS) does not provide evidence that better institutional standards in the destination country are rewarded by the local stock market. We find that foreign governance quality is not associated with positive excess stock returns around the announcement date. Rather, these returns are affected by firm‐specific and deal‐specific factors, such as the relative deal size, the listed status of the target company, and the acquirer size. Comparison with other studies on excess returns for emerging markets (including BRICs) suggests that the results could be driven at least partially by country choice.     

Investment decision-making under economic policy uncertainty

It is widely established that economic policy uncertainty (EPU) affects investment decisions and performance, yet research in this area has overlooked the direct property investment market. This article seeks to rectify this and proposes a multistage multilevel analytical framework to offer new insights and a richness of findings. Using a news-based measure of EPU in the United Kingdom, and controlling for economic conditions, a national-level analysis reveals some evidence of Granger-Causality between EPU and total returns, indicating that pricing is responsive to uncertainty. These findings suggest that EPU is an important risk factor for direct property investments, with pricing implications. Differences in data and performance measure are important, however, with income returns unresponsive. A micro-level investigation begins to reveal some of the asset-pricing decisions underpinning the national results, indicating investors’ concerns for income streams are consistently high, regardless of varying EPU. Pricing can also cause changes in EPU, such as in the retail and industrial markets (increasingly linked through logistics) reflecting sector-specific stakeholder groups and newsworthy issues. This evidence highlights how important it is for policy-makers to understand the complex and bi-directional relationship, that indecision can undermine investment confidence and cause investment market volatility, in turn raising EPU.     

Combining wavelet decomposition with machine learning to forecast gold returns

This paper combines the discrete wavelet transform with support vector regression for forecasting gold-price dynamics. The advantages of this approach are investigated using a relatively small set of economic and financial predictors. I measure model performance by differentiating between a statistically-motivated out-of-sample forecasting exercise and an economically-motivated trading strategy. Disentangling the predictors with respect to their time and frequency domains leads to improved forecasting performance. The results are robust compared to alternative forecasting approaches. My findings on the relative importances of such wavelet decompositions suggest that the influences of short-term and long-term trends are not stable over the full evaluation period.     

How justified is abandoning money in the conduct of monetary policy in Australia on the grounds of instability in the money‐demand function?

The role of money in the design and conduct of monetary policy has reemerged as an important issue in both advanced and developing economies, especially since the 2007 global financial crisis. A growing body of recent literature suggests that the causal relationship between money supply growth and inflation remains intact across countries and over time and that this relation is not conditional on the stability of the money‐demand function or whether money is endogenous or exogenous. Moreover, critical for a rule‐based monetary policy is the presence of a long‐run stable money‐demand function, rather than a short‐run money‐demand model that may exhibit instability for many reasons, including problems with estimating a money‐demand model with high‐frequency data. Provided that a stable money‐demand function exists, it could be useful to establish long‐run equilibrium relations among money, output, prices, and exchange rates, as the classical monetary theory suggests. Within this analytical framework, this paper addresses the question of whether money has any role in the conduct of monetary policy in Australia. The conventional wisdom is that the money‐demand function in Australia has been unstable since the mid‐1980s due to financial deregulation and reforms; this led to a change in the strategy of monetary policy for price stability in the form of inflation targeting that ignores money insofar as inflation and its control are concerned. This paper reports empirical findings for Australia, obtained from a longer quarterly data series over the period 1960Q1–2015Q1, which suggest that instability in the narrow‐money‐demand function in Australia was primarily due to the exclusion of variables which have become important in the deregulated environment since the 1980s. These findings are confirmed by an expanded form of the narrow‐money‐demand function that was found stable over the past two decades, although it experienced multiple structural breaks over the study period. The paper draws the conclusion that abandoning the monetary aggregate as an instrument of monetary policy in Australia, under a rule‐based monetary policy such as inflation targeting, cannot be justified by instability in the money‐demand function or even by lack of a causal link between money supply growth and inflation.     

Dynamic relationship between stock market trading volumes and investor fear gauges movements

This article applies multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) to investigate cross-correlation behaviours between two kinds of stock markets trading volumes and investor fear gauges covering the data of U.S. stock markets from 2 January 2004 to 31 July 2018. The empirical results show that the dynamic relationship between stock markets trading volume fluctuations and different kinds of investor fear gauges are multifractal and find that the dynamic relationship is strongly anti-persistent. Moreover, financial crisis in 2008 has a significant impact on the cross-correlated behaviour, suggesting that stock market trading volume fluctuations and investor fear gauges are more susceptible to each other during the financial crisis period. Through the rolling windows analysis, we also find that the stock markets trading volume fluctuations and different kinds of investor fear gauges are anti-persistent dynamic cross-correlated.     

Positive Feedback Trading and Investor Sentiment

This article examines how investor sentiment affects positive feedback trading behavior. By analyzing the daily closing total return of CSI 300 index and its individual returns of stocks, we find that relatively high or low sentiment induces active positive feedback trading. With a specific indicator of sentiment, we explain the microstructure setting of the relationship between positive feedback trading and sentiment. We adopt the classical feedback model from Sentana and Wadhwani (1992) to measure positive feedback trading behavior. By adding sentiment factor to the model, we successfully explain how sentiment influences the behavior of both feedback traders and rational investors. The empirical findings suggest that positive feedback traders are more likely to trade when the prices of most securities move forward together. When the sentiment of feedback traders is at an intermediate level, the feedback trading behavior is insignificant.     

加强师德师风建设提高以德治校能力

教育大计，教师为本；教师培养，师德师风为先。师德师风建设是高校思想政治教育的重要内容，是进一步推动廉政文化进校园工作的重中之重，是增强以德治校水平和提高以德治校能力的关键，是贯彻落实学校党风廉政建设和深入推进反腐败工作的重要举措。     

Aggregate insider trading and market returns: The role of transparency

Using a sample of countries that require timely disclosures of insider trades, I investigate the effect of country‐level institutions that promote transparency on the extent to which aggregate insider trades predict market returns. I find that financial information transparency mitigates the predictive content of aggregate insider trades when markets are more likely to deviate from fundamentals (i.e., during market fads), and when there is greater co‐movement in stock prices. In contrast, there is some evidence that governance and investor protection mitigate the association between aggregate insider trades and future earnings surprises. Hence, holding constant the timely disclosures of insider trades, other capital market institutions play complementary roles in mitigating the informational frictions that give rise to the predictive content of aggregate insider trades.