Performance of Moving Average Trading Rules in a Volatile Stock Market: The Russian Evidence

This article examines the profitability of dual moving average crossover (DMAC) trading strategies in the Russian stock market over the 2003–12 period. It contributes to the existing technical analysis (TA) literature by testing, for the first time, the applicability of ordered weighted moving averages (OWMA) as an alternative calculation basis for determining DMACs. In addition, this article provides the first comprehensive performance comparison of DMAC trading rules in the stock market that is known as one of the most volatile markets in the world. The results show that the best trading strategies of the in-sample period can also outperform their benchmark portfolio during the subsequent out-of-sample period. Moreover, the outperformance of the best DMAC strategies is mostly attributable to their superior performance during bearish periods and, particularly, during stock market crashes.     

How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns

We explore whether the market variance risk premium (VRP) can be predicted. We measure VRP by distinguishing the investment horizon from the variance swap’s maturity. We extract VRP from actual S&P 500 variance swap quotes and we test four classes of predictive models. We find that the best performing model is the one that conditions on trading activity. This relation is also economically significant. Volatility trading strategies which condition on trading activity outperform popular benchmark strategies, even once we consider transaction costs. Our finding implies that broker dealers command a greater VRP to continue holding short positions in index options in the case where trading conditions deteriorate.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Does high frequency algorithmic trading matter for non-AT investors?

The extant literature has typically measured the impact of high frequency algorithmic trading (HFT) on short term outcomes, in seconds or minutes. We focus on outcomes of concern for longer term non-algorithm investors. We find in some cases HFT increases volatility arising from news relating to fundamentals. Furthermore HFT is associated with the transmission of that volatility across industries, and that transmission is based on short term correlations. Finally, we find that the period since the introduction of algorithmic trading (AT) has seen increases in both the variances and covariances of return volatility in most industries. However increases in the variances has not been uniform in that it has fallen sharply in a few industries. The magnitudes are such that, overall, AT has coincided with reduced return volatility variance.     

#br# 融资融券加大了沪深股市波动吗*

融资融券设计初衷是通过融资加强市场流动性和通过融券提供投资者规避价格下跌风险的金融工具，改善由供求关系严重失衡导致市场巨幅震荡的局面，实现资本市场长期稳定的目标。实际操作中，融资融券疏通货币市场和资本市场间的资金流动，撬动巨额资金涌入股市；融资规模扩张过快而融券做空力量薄弱，业务结构发展严重失衡，导致两融业务具有“小冲击、大波动”的金融加速效应，放大了外部冲击引起股价上涨和下跌的幅度。协整回归分析表明，两融业务规模的扩张和收缩对上证指数涨跌具有显著的同向影响。TGARCH事件模型结果进一步证实融资融券从稳定股价到加剧波动的功能变化。随着标的股票扩容和业务常规化，两融业务导致股市投机过度，加剧了沪深两市的资产价格异动，没有达到平抑波动的设计预期。     

Assessment of land use compatibility and noise pollution at Imam Khomeini International Airport

This study aimed to investigate land use planning around airports, by employing Remote Sensing (RS) and Geographic Information Systems (GIS), in conjunction with an optimization algorithm using an Integrated Noise Model (INM) software, to establish the potential effects of aircraft noise at Imam Khomeini International Airport (IKIA) in Tehran. We also checked for land use compatibility with the noise levels around IKIA and the residents' reaction to the noise. The research was carried out in three stages: a) the establishment of Strategic Noise Map (SNM) scenarios of the airport operation in the years 2011, 2020 and 2030 using the INM software; b) the assessment of the results with emphasis on the study area land uses and application of RS and GIS and the exposure of residents at different levels of environmental noise; and c) the assessment of the intensity of aircraft noise annoyance at various times of day and night. The results indicated that developing IKIA together with the residential development will increase airport noise. Hence proper management and control of noise at IKIA is essential.     

Trade-size clustering and price efficiency

Using a sample of 26 markets, this paper investigates if trade-size clustering affects price efficiency. Our results suggest that more clustering trades are associated with greater resemblance of a random walk, less pricing errors, and shorter price delays. Moreover, we examine three underlying mechanisms to explain how clustering improves efficiency. First, we show that clustering trades are informative, consistent with the idea that stealth traders leverage such tactics to convey private information to prices. Second, we discover that clustering trades are positively related to investor attention (stock liquidity), implying that informed clustering trades happen at the presence of enormous uninformed investors. High attention and liquid markets help reduce the trading friction, thereby prompting quick price adjustments to private information released by the stealth trading.     

LACK OF RIGOUR IN DEFENDING FAIRTRADE: A REJOINDER TO ALISTAIR SMITH

Smith (2010 ) does not deny that he made errors in economic theory, logic and fact, and that he had misused evidence. He says that I misrepresented a large body of theory, that I distorted what he said in four places and that I was wrong in one sentence. These statements are false.     

绿色经济问题研究新进展

顺应新发展理念的提出，2016 年学者们对绿色经济相关问题进行了广泛而深入的研究，主要在环境效率、环境规制绩效和绿色发展三方面取得了卓有成效的进展。一是从环境效率评估方法、环境效率状况和区域差异等方面对环境效率进行了评估，并拓展研究了环境效率的影响因素；二是从评估环境政策、税收、排污权分配、碳交易等环境规制绩效入手，理论和实证分析了环境规制的影响因素和绩效改进方向；三是探讨了绿色发展的可能性，提出了优化产业结构、加强地区联防联控、推出碳交易政策、优化城市结构和规划、促进共享经济发展和优化环境管理手段等绿色发展的路径选择。