经济增长影响因素实证研究

本文将人力资本作为生产要素之—,运用误差校正模型,估计出中国1952-1998年期间扩展的索洛模型。研究结果表明,物质资本存量的增长仍然是经济增长的主要因素,教育对经济增长有显著作用但贡献率不高(12.00%),劳动对经济增长的作用十分有限,三种投入要素对经济增长的总贡献仅占69.11%,其余应归功于包括技术进步在内的综合要素。     

基于误差理论的区间主成分分析及其应用

针对区间数样本,传统的主成分分析需进行拓展。首先讨论了区间样本数据的两种主要来源,即观测误差和符号数据分析。然后将区间数看作一个由中点和半径构成的具有一定误差的数,从误差理论出发,研究基于误差传递公式的区间主成分分析方法,并获得以区间数为表达形式的主成分。最后,结合我国2005年第四季度股票市场的数据进行了实证分析。结果表明,面对海量数据,区间PCA较传统PCA更容易从总体上把握样本的属性。     

Neural Networks for Financial Time Series Forecasting

Financial and economic time series forecasting has never been an easy task due to its sensibility to political, economic and social factors. For this reason, people who invest in financial markets and currency exchange are usually looking for robust models that can ensure them to maximize their profile and minimize their losses as much as possible. Fortunately, recently, various studies have speculated that a special type of Artificial Neural Networks (ANNs) called Recurrent Neural Networks (RNNs) could improve the predictive accuracy of the behavior of the financial data over time. This paper aims to forecast: (i) the closing price of eight stock market indexes; and (ii) the closing price of six currency exchange rates related to the USD, using the RNNs model and its variants: the Long Short-Term Memory (LSTM) and the Gated Recurrent Unit (GRU). The results show that the GRU gives the overall best results, especially for the univariate out-of-sample forecasting for the currency exchange rates and multivariate out-of-sample forecasting for the stock market indexes.     

The Cross-Sectional Intrinsic Entropy—A Comprehensive Stock Market Volatility Estimator

To take into account the temporal dimension of uncertainty in stock markets, this paper introduces a cross-sectional estimation of stock market volatility based on the intrinsic entropy model. The proposed cross-sectional intrinsic entropy (CSIE) is defined and computed as a daily volatility estimate for the entire market, grounded on the daily traded prices—open, high, low, and close prices (OHLC)—along with the daily traded volume for all symbols listed on The New York Stock Exchange (NYSE) and The National Association of Securities Dealers Automated Quotations (NASDAQ). We perform a comparative analysis between the time series obtained from the CSIE and the historical volatility as provided by the estimators: close-to-close, Parkinson, Garman–Klass, Rogers–Satchell, Yang–Zhang, and intrinsic entropy (IE), defined and computed from historical OHLC daily prices of the Standard & Poor’s 500 index (S&P500), Dow Jones Industrial Average (DJIA), and the NASDAQ Composite index, respectively, for various time intervals. Our study uses an approximate 6000-day reference point, starting 1 January 2001, until 23 January 2022, for both the NYSE and the NASDAQ. We found that the CSIE market volatility estimator is consistently at least 10 times more sensitive to market changes, compared to the volatility estimate captured through the market indices. Furthermore, beta values confirm a consistently lower volatility risk for market indices overall, between 50% and 90% lower, compared to the volatility risk of the entire market in various time intervals and rolling windows.     

主动发起的融资融券交易对中国股票市场的影响

本文以融资买入和融券卖出为研究对象,分析了投资者主动发起的融资融券交易对股票回报、流动性和波动性的影响,给出了中国股票市场融资融券发展现状。研究发现,融资买入(融券卖出)对当日股票回报有显著为正(负)的影响,交易表现与政策制定动机——融资反映投资者看涨情绪、融券反映投资者看跌情绪一致。此外,融资买入(融券卖出)增加了(降低)股票流动性;融资买入(融券卖出)降低(增加)了股票波动性;融资融券对股票交易特征的影响有随时间逐渐改善的趋势。最后,本文发现融资融券对股票回报、流动性和波动性产生的影响与股票所在板块有关,随着中小板和创业板股票所占比重的增加,调整和优化融资融券对股票市场的影响仍然是监管者未来主要任务之一。     

带缓冲串行生产系统预防性维护建模及运行参数优化研究

为了保证串行生产系统的产能和提高系统可靠性,提出了带缓冲区的串行生产系统预防性维护决策模型。首先,分析了生产线各执行单元可靠性和运行参数之间的关系,建立了考虑执行单元运行参数和缓冲库存的维护模型。在此基础上,结合串行生产线的特点,建立综合考虑维护成本、有效运行速度和缓冲库存的多目标优化函数。最后,构建启发式算法求解目标函数,并以串行包装生产线为例进行仿真实验分析,结果表明本文所建模型是有效且实用的。     

我国中药出口贸易发展现状分析及对策研究

对中药出口贸易的发展现状进行了分析,从机遇与挑战方面阐述了其发展趋势,对中药实现现代化,推动国际化,知识产权保护以及如何消除贸易壁垒等方面提出了对策及建议。由于国家政府各项政策的倾斜,将进一步加快我国中药产业的发展,从现代化走向国际化。     

Dynamics of Information Flow between the Chinese A-Share Market and the U.S. Stock Market: From the 2008 Crisis to the COVID-19 Pandemic Period

The relationship between the Chinese market and the US market is widely concerned by researchers and investors. This paper uses transfer entropy and local random permutation (LRP) surrogates to detect the information flow dynamics between two markets. We provide a detailed analysis of the relationship between the two markets using long-term daily and weekly data. Calculations show that there is an asymmetric information flow between the two markets, in which the US market significantly affects the Chinese market. Dynamic analysis based on weekly data shows that the information flow evolves, and includes three significant periods between 2004 and 2021. We also used daily data to analyze the dynamics of information flow in detail over the three periods and found that changes in the intensity of information flow were accompanied by major events affecting the market, such as the 2008 financial crisis and the COVID-19 pandemic period. In particular, we analyzed the impact of the S&P500 index on different industry indices in the Chinese market and found that the dynamics of information flow exhibit multiple patterns. This study reveals the complex information flow between two markets from the perspective of nonlinear dynamics, thereby helping to analyze the impact of major events and providing quantitative analysis tools for investment practice.     

岱衢族大黄鱼不同组织的同工酶谱

于2006年11月,在象山港采集30尾网养岱衢族大黄鱼,采用聚丙烯酰胺凝胶垂直电泳方法,研究分析了岱衢族大黄鱼眼睛、肌肉、肝脏、肾脏、脾脏、心脏、胸鳍、鳃和脑9种组织中16种同工酶（LDH、ADH、MDH、ME、SOD、POD、EST、GAD、ALP、ATP、FDH、SCD、IDH、GDH、ACP、GcDH）的表达情况,发现除IDH、GDH、ACP、GcDH 4种酶只显示微弱且不稳定的区带外,其他酶类在各组织中都显示出清晰稳定的酶谱,且这些酶在表型、分布和活性上均表现出高度的组织特异性,与各组织的生理功能相一致.     

Bilateral representation of trade for inter- regional models

A representation of trade is given for an inter-regional model in which the origin and destination of exports and imports of each commodity traded can be tracked. This representation retains the structure of the original model (i.e. one with trade ‘pools’ undifferentiated by origin or destination) in that the same algebraic and computational tools can be used, with minor modifications. Scenarios that can be studied with this formulation but not with the original one are presented.