Forecasting the Daily Time‐Varying Beta of European Banks During the Crisis Period: Comparison Between GARCH Models and the Kalman Filter

This intention of this paper is to empirically forecast the daily betas of a few European banks by means of four generalized autoregressive conditional heteroscedasticity (GARCH) models and the Kalman filter method during the pre‐global financial crisis period and the crisis period. The four GARCH models employed are BEKK GARCH, DCC GARCH, DCC‐MIDAS GARCH and Gaussian‐copula GARCH. The data consist of daily stock prices from 2001 to 2013 from two large banks each from Austria, Belgium, Greece, Holland, Ireland, Italy, Portugal and Spain. We apply the rolling forecasting method and the model confidence sets (MCS) to compare the daily forecasting ability of the five models during one month of the pre‐crisis (January 2007) and the crisis (January 2013) periods. Based on the MCS results, the BEKK proves the best model in the January 2007 period, and the Kalman filter overly outperforms the other models during the January 2013 period. Results have implications regarding the choice of model during different periods by practitioners and academics. Copyright © 2016 John Wiley & Sons, Ltd.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

On the Difficulty of Measuring Forecasting Skill in Financial Markets

The use of correlation between forecasts and actual returns is commonplace in the literature, often used as a measurement of investors' skill. A prominent application of this is the concept of the information coefficient (IC). Not only can the IC be used as a tool to rate analysts and fund managers but it also represents an important parameter in the asset allocation and portfolio construction process. Nevertheless, a theoretical understanding of it has typically been limited to the partial equilibrium context where the investing activities of each agent have no effect on other market participants. In this paper we show that this can be an undesirable oversimplification and we demonstrate plausible circumstances in which conventional empirical measurements of IC can be highly misleading. We suggest that improved understanding of IC in a general equilibrium setting can lead to refined portfolio decision making ex ante and more informative analysis of performance ex post. Copyright © 2015 John Wiley & Sons, Ltd.     

A Neuro‐wavelet Model for the Short‐Term Forecasting of High‐Frequency Time Series of Stock Returns

We propose a wavelet neural network (neuro‐wavelet) model for the short‐term forecast of stock returns from high‐frequency financial data. The proposed hybrid model combines the capability of wavelets and neural networks to capture non‐stationary nonlinear attributes embedded in financial time series. A comparison study was performed on the predictive power of two econometric models and four recurrent neural network topologies. Several statistical measures were applied to the predictions and standard errors to evaluate the performance of all models. A Jordan net that used as input the coefficients resulting from a non‐decimated wavelet‐based multi‐resolution decomposition of an exogenous signal showed a consistent superior forecasting performance. Reasonable forecasting accuracy for the one‐, three‐ and five step‐ahead horizons was achieved by the proposed model. The procedure used to build the neuro‐wavelet model is reusable and can be applied to any high‐frequency financial series to specify the model characteristics associated with that particular series. Copyright © 2013 John Wiley & Sons, Ltd.     

关于我国现行财政转移支付制度的思考

从制度经济学的角度出发,论述了我国现行财政转移支付制度的作用和我国财政转移制度的主要形式、构成、特点,分析了其存在的缺陷,并提出了完善我国财政转移支付制度的一些建议。     

水平评估对高职院校图书馆的影响

阐述了水平评估的概况及图书馆在评估中的重要地位,分析了评估给高职院校图书馆带来的发展机遇和负面影响,并提出促进图书馆良性发展的机制。     

国家财政支农的效益性与路径选择

通过对国家财政支农宏观、中观、微观效益低下的实证分析,从国家预算、财政意识、政府博弈、配套政策诸方面探讨了影响财政支农效益的深层原因,进而指出国家财政支农的路径选择。     

非国有企业收购国有控股权绩效实证分析

选取了1997年到2004年中国证券市场上的非国有企业收购国有控股权的72个案例为样本,通过财务数据法以及事件分析法,对目标公司并购前后的财务绩效以及股票价格的变化进行了实证分析.研究发现,目标公司在被收购前业绩普遍比较差,与同行业平均水平相比,被收购前的财务指标均显著地小于0.并购后目标公司的财务指标有明显的好转,可见通过转让国有股权完成非国有企业并购国有企业是比较有效的.然而在证券市场上并没有得到充分的反映,股价仅表现为短期的投机性上涨.     

金融危机背景下影响购房者消费心理之因素探析

分析了金融危机大背景下影响我国消费者购房心理的主要因素,阐述了目前国家推动房地产行业健康发展所出台的优惠政策,提出从消费者层面恢复购房者信心的一些想法。     

论我国房地产市场再次调整的可能性

结合2008年金融危机以来我国房地产市场调整的一些主要特征及现状,尝试从经济发展与房地产市场发展的历史规律中寻求未来我国房地产市场的发展趋势,从而有助于更好地理解房地产行业的短期波动和长期发展。