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1.
地基处理技术是近年来我国房屋建筑工程施工中一种较常见的施工处理技术,多见于房屋建筑工程中的软土地基施工环节。通过以往的房屋建筑经验,如果直接在软土地基上进行建筑施工,地基区域软土很容易会影响房屋建筑工程的稳定性,所以,在针对这一部分软土区域的施工环节,需要针对拟施工的地基软土区域进行处理,提升其软土的稳定性。到目前,地基处理技术已经在我国房屋建筑工程施工中广泛应用,这一技术应用过程中存在的不足也逐渐凸显,如何针对这一技术的不足予以完善,以此提升地基处理技术对房屋建筑质量的积极影响,成为了现阶段房屋建筑地基基础施工质量提升的重要环节之一。 相似文献
2.
基于玉米和大豆等粮食国际、国内价格历史数据,运用协整及误差修正模型、脉冲响应函数等方法,揭示国际粮价对国内粮价的传导作用及影响路径。理论分析表明,国际粮价通过进口直接路径、进口产品成本路径和进口替代路径等三个子路径传导至国内粮价。实证检验发现,国际大豆价格进口直接路径和进口产品成本路径传导均比较充分,即国际大豆价格会影响大豆进口价格,进而影响国内大豆价格,最终影响国内豆油价格;国际玉米价格进口直接路径和进口产品成本路径传导则不充分,国际玉米价格会影响玉米进口价格,但是对国内玉米价格和国内玉米淀粉价格影响程度较低;而在进口替代路径中,玉米和大豆的国际价格传导均不充分。我国应继续推进以提质增效为目标的农业供给侧结构性改革,加大粮食生产科技投入力度,调动农民种粮积极性,集中力量提高粮食供给质量和效率;坚持粮食进口仅为调剂国内供求余缺的方针,把握粮食安全的主动权;建立健全粮食市场的价格调控体系及风险防控体系,规避国际粮食市场剧烈波动对国内粮食市场的影响。 相似文献
3.
This paper proposes an empirical model for analysing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010–17 and 2010–19. Price discovery is achieved through the Gonzalo–Granger permanent‐transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period, a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalised by individuals' search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018–19 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices. 相似文献
4.
Using data on European Central Bank's (ECB's) reserve currency portfolios, we find that money managers react to relative rankings (i.e., own vs. peers’ performance) by adjusting portfolio active risk levels measured ex ante by actual deviations from their benchmark. This occurs in the absence of explicit incentives as no monetary reward is promised for winning this “tournament” among portfolio managers. We collect information on managers’ characteristics, including age, education, tenure, salary, and career path, and investigate the role played by implicit incentives. We provide evidence that both individual career concerns and institutional peer pressure contribute to the documented relationship between ranking and risk taking. 相似文献
5.
《The British Accounting Review》2021,53(5):101031
We examine the effect of corporate environmental innovation (hereafter eco-innovation) on stock price crash risk and document a significant negative association. Utilising a large sample of publicly listed U.S. firms for the period 2003 to 2017, we find that an increase in eco-innovation from the 25th to the 75th percentile is associated with 17.62% reduction in stock price crash risk. This outcome remains robust to a variety of sensitivity tests and after accounting for potential endogeneity concerns. Eco-innovative firms attract more institutional investors and equity analyst following and disclose more information leading to lower stock price crash risk. Additional tests reveal that the negative effect of eco-innovation is contingent on the political leadership's ideology and environmental sensitivity. Our paper contributes to the ongoing discourse on the costs and benefits of eco-innovation, documenting the value-enhancing perspective of eco-innovation. 相似文献
6.
股价同步性是衡量资本市场信息效率的重要指标。股价同步性的影响机制一直以来都是金融研究的热点问题。本文使用文本分析的方法,通过机器学习度量了东方财富股吧中股民发帖评论中的非理性噪音,检验了股票网络平台中的噪音与股价同步性之间的关系。研究发现:第一,股票网络平台中的噪音会促使投资者做出非理性的投资决策,进而降低股价变动的同步性。噪音评论占全部评论的比例越高,上市公司的股价同步性越低,而且两者之间呈现倒U型的非线性关系。第二,公司个股新闻与公告数量的增加、分析师关注度的提高与外部审计质量的提升,均可以减弱股票网络平台中的噪音对股价同步性的影响。本文关注网络新媒体中的噪音对股价同步性的影响,研究结论对于监管部门加强网络信息监测以及上市公司进一步完善信息披露渠道具有现实意义。 相似文献
7.
This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms.We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms.We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models.These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods. 相似文献
8.
《Review of Income and Wealth》2018,64(2):459-481
Using a novel data set for the U.S. states, this paper examines whether household debt and the protracted debt deleveraging help explain the dismal performance of U.S. consumption since 2007 in the aftermath of the housing bubble. By separating the concepts of deleveraging and debt overhang—a flow and a stock effect—we find that excessive indebtedness exerted a meaningful drag on consumption over and beyond wealth and income effects. The overall effect, however, is modest—‐around one sixth of the slowdown in consumption between 2000–06 and 2007–12—and mostly driven by states with particularly large imbalances in their household sector. This might be indicative of non‐linearities, whereby indebtedness begins to bite only when misalignments from sustainable debt dynamics become excessive. 相似文献
9.
Cheng Yan 《European Journal of Finance》2018,24(14):1190-1223
We explore the possible existence and behavior of hot money in six categories of disaggregated bilateral capital flows (equity inflows, equity outflows, bond inflows, bond outflows, banking credit inflows, and banking credit outflows) for 12 emerging markets vis-à-vis the US from 1995 to 2012 and provides several new findings. First, we identify the existence of hot money in all six categories above and conclude that both gross inflows and gross outflows can be the sources of hot money. Second, hot money in equity inflows (outflows) engages in positive (negative) feedback trading regarding local stock market returns. Third, some categories of hot money have a temporary influence on local stock market returns while the others have a permanent influence, supporting the explanations of both price pressures and information advantage. Finally, local stock market returns in half of our sample countries, which have tightened capital controls during the late 2000s global financial crisis (GFC), are more affected by hot money than in the other half. Our findings confirm several popular conjectures of hot money, and endorse the use of capital controls to limit financial vulnerability in the run-up to and during the GFC. 相似文献
10.
This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia’ economy, using novel Morlet’ wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969–2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy. 相似文献