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排序方式: 共有744条查询结果,搜索用时 515 毫秒
81.
This paper compares the empirical performances of statistical projection models with those of the Black–Scholes (adapted to account for skew) and the GARCH option pricing models. Empirical analysis on S&P500 index options shows that the out-of-sample pricing and projected trading performances of the semi-parametric and nonparametric projection models are substantially better than more traditional models. Results further indicate that econometric models based on nonlinear projections of observable inputs perform better than models based on OLS projections, consistent with the notion that the true unobservable option pricing model is inherently a nonlinear function of its inputs. The econometric option models presented in this paper should prove useful and complement mainstream mathematical modeling methods in both research and practice. 相似文献
82.
Jian Yang R. Brian Balyeat David J. Leatham 《Journal of Business Finance & Accounting》2005,32(1-2):297-323
Abstract: This paper examines the lead‐lag relationship between futures trading activity (volume and open interest) and cash price volatility for major agricultural commodities. Granger causality tests and generalized forecast error variance decompositions show that an unexpected increase in futures trading volume unidirectionally causes an increase in cash price volatility for most commodities. Likewise, there is a weak causal feedback between open interest and cash price volatility. These findings are generally consistent with the destabilizing effect of futures trading on agricultural commodity markets. 相似文献
83.
This paper examines the effect of exchange rate risk on interest rates within the uncovered interest rate parity condition for Turkey. When the interest rate is measured with the Treasury auction interest rate and the exchange rate risk is measured with the conditional variance of the exchange rate, then we found that there is a positive relation between the exchange rate risk and interest rate with the data from December 1986 to January 2001. 相似文献
84.
This paper shows that greater uncertainty about monetary policy can lead to a decline in nominal interest rates. In the context of a limited participation model, monetary policy uncertainty is modeled as a mean preserving spread in the distribution for the money growth process. This increase in uncertainty lowers the yield on short-term maturity bonds because the household sector responds by increasing liquidity in the banking sector. Long-term maturity bonds also have lower yields but this decrease is a result of the effect that greater uncertainty has on the nominal intertemporal rate of substitution—which is a convex function of money growth. We examine the nature of these relations empirically by introducing the GARCH-SVAR model—a multivariate generalization of the GARCH-M model. The predictions of the model are broadly supported by the data: higher uncertainty in the federal funds rate can lower the yields of the three- and six-month treasury bill rates. 相似文献
85.
Empirical estimates of conditional return autocorrelation are generated over the period 1973 to 2000 for S&P500 index data, as well as for a small selection of individual U.S. stocks. We find that conditional autocorrelation is highly variable, and these dynamics are consistent with changes in point autocorrelation estimates generated in various subperiods. The conditional autocorrelation estimates for some stocks exhibited a pattern of mean reversion, while for others, evidence of long-term trends and structural breaks was found. While we were unable to uncover what characteristics drive the nature of these autocorrelation patterns, our analysis ruled out industry, investor type or degree of internationalisation as explanations. 相似文献
86.
Value-at-Risk Prediction: A Comparison of Alternative Strategies 总被引:4,自引:0,他引:4
Kuester Keith; Mittnik Stefan; Paolella Marc S. 《The Journal of Financial Econometrics》2006,4(1):53-89
Given the growing need for managing financial risk, risk predictionplays an increasing role in banking and finance. In this studywe compare the out-of-sample performance of existing methodsand some new models for predicting value-at-risk (VaR) in aunivariate context. Using more than 30 years of the daily returndata on the NASDAQ Composite Index, we find that most approachesperform inadequately, although several models are acceptableunder current regulatory assessment rules for model adequacy.A hybrid method, combining a heavy-tailed generalized autoregressiveconditionally heteroskedastic (GARCH) filter with an extremevalue theory-based approach, performs best overall, closelyfollowed by a variant on a filtered historical simulation, anda new model based on heteroskedastic mixture distributions.Conditional autoregressive VaR (CAViaR) models perform inadequately,though an extension to a particular CAViaR model is shown tooutperform the others. 相似文献
87.
This paper investigates the hedging effectiveness of Australian, Hong Kong, and Japanese stock futures markets. The traditional hedge and the minimum variance hedge ratios are all constant whereas the bivariate GARCH hedge ratio is time varying. The effectiveness of the hedge ratio is compared by investigating the out-of-sample performance of the three ratios. The whole sample consists of weekly returns from January 1990 to December 2000. Two 1-year, out-of-sample periods are used: January 1999 to December 1999 and January 2000 to December 2000. Results show that the time-varying GARCH hedge ratio outperforms the constant ratios in most of the cases. This is true using both out-of-sample periods. 相似文献
88.
This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days. It is also found that the static market model overstates non-market or, unsystematic risk by more than 10%. On the basis of an array of diagnostics it is confirmed that the vector GARCH model provides a richer framework for the analysis of the dynamics of systematic risk. 相似文献
89.
This paper investigates the volatility persistence, volatility variability from day to day and transmission of volatility in seven Southeast Asian stock markets from 1980 to 1991 using the ARV approach. We found strong evidence that shocks to volatility are persistent in Taiwan. Moreover, the Stock Exchange of Thailand Daily Index has the strongest interday volatility fluctuation. Instantaneous causality of volatility among six of the seven markets (except Seoul) was discovered. Besides, there is significant volatility spillover effect from Hong Kong to Taiwan, Malaysia to Singapore and Singapore to Malaysia in the period 1980 to 1991. 相似文献
90.
Recent research examining high-frequency financial data has suggested that volatility dynamics may be confounded by the existence
of an intra-day periodic pattern and multiple sources of volatility. This paper examines whether these dynamics are present
in the US Dollar exchange rates of five Pacific Basin economies. Using 30-min sampled returns, evidence of a ‘U’-shape intra-day
pattern in volatility for regional markets is reported and controlled for using a Flexible Fourier transform. Supportive evidence
for the existence of multiple volatility components is offered by semi-parametric fractional difference estimates of the long-memory
properties of absolute exchange rate returns at various intra-day data sampling frequencies. Further parametric evidence of
an explicit component structure in such high frequency exchange rate volatility is offered by the estimates of a component-GARCH
model which comprises both a long-run volatility component exhibiting slow shock decay and a short-run volatility component
exhibiting far more rapid decay, and provides a generally superior fit to the data. Further application of these C-GARCH models
in the analysis of high frequency volatility spillovers between the currencies considered also reveals that such spillovers
are predominantly transitory rather than highly persistent in nature, but that where volatility spillovers do impact on the
long-run component of exchange rate volatility the Australian Dollar plays a pivotal role in the localised causality transmission
mechanism.
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