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1.
中国的通货膨胀预测:基于ARIMA模型的实证分析   总被引:8,自引:0,他引:8  
通货膨胀预测已经成为中央银行制定货币政策的一个关键性变量。我们在研究国外学者对通货膨胀预测研究的基础上,根据我国1990年1月到2007年11月的CPI月度数据,运用ARIMA模型,对我国通货膨胀进行分析和短期预测。实证结果表明,运用ARIMA(1,1,10)模型为我国的通货膨胀提供了较好的预测,如果央行能依据通货膨胀预测的结果制定相应的货币政策,将有助于避免货币政策的时滞,有利于正确地引导和稳定市场预测,最终提高货币政策的有效性。  相似文献
2.
Recent studies in the empirical finance literature have reportedevidence of two types of asymmetries in the joint distributionof stock returns. The first is skewness in the distributionof individual stock returns. The second is an asymmetry in thedependence between stocks: stock returns appear to be more highlycorrelated during market downturns than during market upturns.In this article we examine the economic and statistical significanceof these asymmetries for asset allocation decisions in an out-of-samplesetting. We consider the problem of a constant relative riskaversion (CRRA) investor allocating wealth between the risk-freeasset, a small-cap portfolio, and a large-cap portfolio. Weuse models that can capture time-varying moments up to the fourthorder, and we use copula theory to construct models of the time-varyingdependence structure that allow for different dependence duringbear markets than bull markets. The importance of these twoasymmetries for asset allocation is assessed by comparing theperformance of a portfolio based on a normal distribution modelwith a portfolio based on a more flexible distribution model.For investors with no short-sales constraints, we find thatknowledge of higher moments and asymmetric dependence leadsto gains that are economically significant and statisticallysignificant in some cases. For short sales-constrained investorsthe gains are limited.  相似文献
3.
Differential Market Reactions to Revenue and Expense Surprises   总被引:4,自引:1,他引:3  
This study investigates investors' reactions to revenue and expense surprises around preliminary earnings announcements. Results show that investors value more highly a dollar of revenue surprise than a dollar of expense surprise. Results further show that these differential market reactions to revenue and expense surprises vary systematically for growth versus value firms and depend on (a) the proportion of variable to total costs, (b) the relative persistence of sales and expenses, and (c) the proportion of operating to total expenses. Results highlight the importance of interpreting the earnings surprise in the context of its sources—e.g. surprise in revenues or in total expenses.  相似文献
4.
基于KMV模型对我国上市保险公司的信用风险度量   总被引:4,自引:0,他引:4  
目前,我国对保险公司的监管主要是静态监管,不能完全满足未来经济发展对保险业监管提出的挑战。为此,本文在介绍了KMV模型后,利用KMV模型对我国已上市的保险公司的风险进行了度量,旨在探讨在未来时机成熟时保险监管中引入KMV模型,利用KMV模型良好的风险预测能力,加强和改善保险监管的可能性。  相似文献
5.
基于RBF网络的商业银行信用风险控制研究   总被引:3,自引:0,他引:3  
方先明  熊鹏 《金融论坛》2005,10(4):33-38
对信用风险的有效控制与管理,在现代商业银行日常运行过程中具有举足轻重的地位。基于信用风险系统是一个高度复杂的非线性动态系统,利用神经网络的自适应学习、并行分布处理和较强的鲁棒性及容错性等特性,建立基于RBF神经网络的信用风险预测控制模型,从理论上探寻信用风险非线性智能控制。仿真试验表明,信用风险度能被控制在以最佳风险度为中心的一定范围内。因此,该预测控制系统适合于商业银行信用风险的控制。  相似文献
6.
Evaluating Interest Rate Covariance Models Within a Value-at-Risk Framework   总被引:2,自引:0,他引:2  
A key component of managing international interest rate portfoliosis forecasts of the covariances between national interest ratesand accompanying exchange rates. How should portfolio managerschoose among the large number of covariance forecasting modelsavailable? We find that covariance matrix forecasts generatedby models incorporating interest-rate level volatility effectsperform best with respect to statistical loss functions. However,within a value-at-risk (VaR) framework, the relative performanceof the covariance matrix forecasts depends greatly on the VaRdistributional assumption, and forecasts based just on weightedaverages of past observations perform best. In addition, portfoliovariance forecasts that ignore the covariance matrix generatethe lowest regulatory capital charge, a key economic decisionvariable for commercial banks. Our results provide empiricalsupport for the commonly used VaR models based on simple covariancematrix forecasts and distributional assumptions.  相似文献
7.
A New Approach to Markov-Switching GARCH Models   总被引:2,自引:0,他引:2  
The use of Markov-switching models to capture the volatilitydynamics of financial time series has grown considerably duringpast years, in part because they give rise to a plausible interpretationof nonlinearities. Nevertheless, GARCH-type models remain ubiquitousin order to allow for nonlinearities associated with time-varyingvolatility. Existing methods of combining the two approachesare unsatisfactory, as they either suffer from severe estimationdifficulties or else their dynamic properties are not well understood.In this article we present a new Markov-switching GARCH modelthat overcomes both of these problems. Dynamic properties arederived and their implications for the volatility process discussed.We argue that the disaggregation of the variance process offeredby the new model is more plausible than in the existing variants.The approach is illustrated with several exchange rate returnseries. The results suggest that a promising volatility modelis an independent switching GARCH process with a possibly skewedconditional mixture density.  相似文献
8.
Stochastic chaos or ARCH effects in stock series?: A comparative study   总被引:2,自引:0,他引:2  
Recent empirical studies have shown that the chaotic behaviour and excess volatility of financial series are the result of interactions between heterogeneous investors. In our article, we propose verifying this hypothesis. Thus, we use the Chen et al. [Testing for non-linear structure in an artificial financial market. Working Paper, University of Bonn (2000).] model to show that the modification of the agents' homogeneity hypothesis can drive to stochastic chaotic evolution of price series. Then, through an econometric procedure, we try to identify the underlying process of the Paris Stock Exchange returns series (CAC40). To this end, we apply several different tests: (1) dealing with long-memory components derives from the fractional integration test of Geweke and Porter-Hudak (GPH) [J. Time Ser. Anal. 4 (1983) 221.] and (2) dealing with chaotic structures comes from the work on correlation dimension of Grassberger and Procaccia [Physica 9D (1983) 189.] and the Lyapunov exponents method of Gençay and Dechert [Physica D (1992) 142.]. Finally, we forecast the CAC40 returns series using the recent methods of Principal Components Regression (PCR) and Radial Basis Functions (RBF). We conclude with the implications of the presence of chaotic structures in stock markets and future research on ARCH and chaotic models' relationships.  相似文献
9.
The effect of cash flow forecasts on accrual quality and benchmark beating   总被引:2,自引:0,他引:2  
When analysts provide forecasts of both earnings and operating cash flow, they also implicitly provide a forecast of total operating accruals. We posit that this increases the transparency and the expected costs of accrual manipulations used to manage earnings. As a consequence, we predict and find that accrual quality improves and firms’ propensity to meet or beat earnings benchmarks declines following the provision of cash flow forecasts. We also predict and find that firms turn to other benchmark-beating mechanisms, such as real activities manipulation and earnings guidance in response to the provision of cash flow forecasts.  相似文献
10.
Recent research provides evidence of a market premium accruing to firms that meet or beat analysts’ forecasts. We find similar results for our sample of firms. However, we also find a market premium for firms that meet or beat time-series forecasts, and that the highest market premium accrued to firms that meet or beat both analysts’ and time-series forecasts. These findings are supported by assessments of future financial performance over the next two subsequent years. Our findings are consistent with the notion that when time-series benchmark is used in conjunction with analysts’ forecasts, investors obtain a more reliable (i.e., less noisy) signal regarding whether firms have actually met or beaten market expectations.
Weihong Xu (Corresponding author)Email:
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