Exchange rate regime choice and currency crises

Exchange rate regime choice is not exogenous, but it depends on the structural, political and financial features of countries. However, it is often the case that the regime actually pursued and the one that is imposed by country features do not match one to one. The existing empirical crisis models do not take fully into account the regime in which the crisis unfolded. The aim of this paper is to incorporate the appropriateness of the regime choice into the standard currency crisis model. The results show that the odds of crisis increase significantly in countries which have chosen regimes inconsistently.     

Measuring price discovery: The variance ratio, the R, and the weighted price contribution

We analyze the statistical properties of three price discovery measures: The variance ratio, the weighted price contribution (WPC), and the R² of unbiasedness regressions. We find that, if the price process is a driftless martingale, only the WPC is an unbiased estimator for the return variance explained during a time interval. For autocorrelated processes with a drift, only the R² of the unbiasedness regression is consistent, but it is biased for small samples.     

Assessing the historical role of credit: Business cycles,financial crises and the legacy of Charles S. Peirce

This paper provides a historical overview of financial crises and their origins. The objective is to discuss a few of the modern statistical methods that can be used to evaluate predictors of these rare events. The problem involves the prediction of binary events, and therefore fits modern statistical learning, signal processing theory, and classification methods. The discussion also emphasizes the need for statistics and computational techniques to be supplemented with economics. The success of a forecast in this environment hinges on the economic consequences of the actions taken as a result of the forecast, rather than on typical statistical metrics of prediction accuracy.     

The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naïve Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.     

计算机相关学科的PDSIPE教学模式应用

随着国家应用型教学变革的推进,应用型教学途径与具体策略成为学校关注的焦点。借鉴已有的应用型研究成就并在课堂中直接运用,无疑会成为应用型教学改革成败的关键。PDSIPE应用型教学理论与技术的出现较好地解决了这一问题。燕京理工学院以计算机学科为试验对象,开展应用型课堂教学试验,验证PDSIPE教学理念与操作技术在计算机相关学科中的教学价值。     

Research on a diagnostic system of rural vitalization based on development elements in China

In 2017, the Chinese government implemented a national strategy of "Rural Vitalization" that sought to realize full-scale rural vitalization. However, is it possible to achieve vitalization for all the villages in China? How should their development potential be determined? This paper identified and analyzed the "element-composite" messages of rural development based on 99 exemplary sites of “Beautiful Villages” in China. Combined with the projection pursuit classification method, a diagnostic system of rural vitalization was established; then, Dehua County was taken as a case study for an in-depth analysis. Based on national data analysis, the final results indicated that livelihood resources (LR), agglomeration effects (AE), location and transportation (LT), cultural/natural landscapes (CN), and economic circumstance (EC) are essential elements for successful rural development. Additionally, EC was the only exogenous element, while the remaining elements were endogenous. Furthermore, the villages with better EC presented urbanization rates of 38∼82 % and Engel coefficients of 29∼41 % in their counties; exemplary sites lacking LR, CN, LT, and AE account for 13.13 %, 19.19 %, 26.26 %, and 60.61 % respectively, so the indispensability of these elements decreases progressively in sequence. Only 2 % of villages rely on single element for success, therefore, the composite pattern of development element was also critical; 10 out of 16 types were found to successfully facilitate village development, among which, the type of R-a-L-C (32.32 %) and R-A-L-C (15.15 %) were considered as the greatest potential patterns for vitalization. Finally, by means of the diagnostic system, the ratio of representative villages for high-low potential in Dehua County is evenly split; then, development paths, and land use policies that match with paths were proposed, on the basis of development potential and “element-composite” condition of themselves.     

Waste of money or growth opportunity: The causal effect of EU subsidies on Hungarian SMEs

Although EU subsidies aiming at economic development play a pivotal role not only for Hungary but for the entire European Union as well, there is a debate regarding their effectiveness in the literature. This paper investigates the impact of direct economic development subsidies extended in the context of Structural Funds and the Cohesion Fund as part of the 2007–2013 programming period of the European Union on Hungarian micro, small and medium-sized enterprises. Based on a micro database, we evaluate the impact of corporates’ first subsidies on various performance indicators, using a combination of propensity score matching and fixed effects panel regression. According to our results, economic development funds had a significant positive effect on the number of employees, sales revenue, gross value added and, in some cases, operating profit. However, the labour productivity of enterprises was not significantly affected by any of the support schemes. Furthermore, by explicitly comparing non-refundable subsidies (grants) and refundable assistance (financial instruments), we find that there is no significant difference in the effectiveness of the two types of subsidy.     

Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

全面从严治党视野下的暂缓就业学生党员管理研究

暂缓就业党员管理工作是高校学生党建工作中的重要内容,全面从严治党对暂缓就业党员管理提出了新的要求.在新时期,暂缓就业党员呈现出量少质优等新特点,高校党组织可以通过建立专兼结合的暂缓就业党员管理干部队伍、做好暂缓就业党员的分类管理和教育引导、建立有关管理工作制度、促进暂缓就业党员发挥先锋模范作用等具体措施以实现从细从严的管理目标.