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1.
Transport infrastructure is an important subsector within infrastructure, but knowledge of its equities in terms of risk-return characteristics and contribution to portfolio performance is still limited. This study assesses the subsector individually and in a multi-asset, index-based portfolio. In doing so, we apply a t-Copula-based Conditional Value-at-Risk model to simulate risk and returns. Our findings reveal that the subsector has a relatively low dependency on other equities, performs like other alternative asset classes such as general real estate, and does not grant significant risk diversification benefits for mainstream institutional investors such as pension funds. Investors aiming for higher target returns may however assign substantial weights to transport infrastructure, supporting our conjecture that it does not share the same asset class characteristics as general infrastructure. By contrasting Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) scores for both the mean-variance framework and the t-Copula simulation, we further document the limitations of traditional VaR approaches. Hence, this study’s results support the use of risk assessment tools that incorporate non-normal distributions to represent multivariate dependence structures.  相似文献   
2.
In order to challenge the existing literature that points to the detachment of Bitcoin from the global financial system, we use daily data from August 17, 2011–February 14, 2020 and apply a risk spillover approach based on expectiles. Results show reasonable evidence to imply the existence of downside risk spillover between Bitcoin and four assets (equities, bonds, currencies, and commodities), which seems to be time dependent. Our main findings have implications for participants in both the Bitcoin and traditional financial markets for the sake of asset allocation, and risk management. For policy makers, the findings suggest that Bitcoin should be monitored carefully for the sake of financial stability.  相似文献   
3.
This paper develops a novel time-varying multivariate Copula-MIDAS-GARCH (TVM-Copula-MIDAS-GARCH) model with exogenous explanatory variables to model the joint distribution of returns. The model accounts for mixed frequency factors that affect the time-varying dependence structure of financial assets. Furthermore, we examine the effectiveness of the proposed model in VaR-based portfolio selection. We conduct an empirical analysis on estimating the 90%, 95%, 99% VaRs of the portfolio constituted of the Shanghai Composite Index, Shanghai SE Fund Index, and Shanghai SE Treasury Bond Index. The empirical results show that the proposed TVM-Copula-MIDAS-GARCH model is effective to investigate the nonlinear time-varying dependence among those three indices and performs better in portfolio selection.  相似文献   
4.
选取上海证券交易所金融、工业指数的收盘价为观察对象,分别对静态及动态模型、上证金融及工业指数的风险程度以及不同置信水平下的度量准确性进行了比较研究,结果表明:动态风险度量模型对VaR、ES的度量比静态模拟更加准确;上证金融指数的风险程度要略高于上证工业指数的风险程度;置信度为99%时度量风险模型要比置信度为95%时更加精确。  相似文献   
5.
本文以中国2016年之前上市商业银行作为中国银行业的代表,测算银行业系统性 风险VaR。整体来讲,我国银行业系统性风险较低,但VaR在2015年较高。虽如此,我国银行业资本持有量能够抵御银行体系的系统性风险。在系统性风险VaR贡献度方面,本文实证分析表明,在样本期间内,浦发银行、中国银行、农业银行、交通银行贡献度较高。银行体系系统 性风险VaR受GDP增长率和沪深300指数收益率的显著影响。  相似文献   
6.
The projection of mortality rates is an essential part of valuing liabilities in life insurance portfolios and pension schemes. An important tool for risk management and solvency purposes is a stochastic projection model. We show that ARIMA models can be better representations of mortality time-series than simple random-walk models. We also consider the issue of parameter risk in time-series models from the point of view of an insurer using them for regulatory risk reporting – formulae are given for decomposing overall risk into undiversifiable trend risk (parameter uncertainty) and diversifiable volatility. Particular attention is given to the contrasts in how academic researchers might view these models and how insurance regulators and practitioners in life offices might use them. Using a bootstrap method we find that, while certain kinds of parameter risk are negligible, others are too material to ignore. We also find that an objective model selection criterion, such as goodness of fit to past data, can result in the selection of a model with unstable parameter values. While this aspect of the model is superficially undesirable, it also leads to slightly higher capital requirements and thus makes the model of keen interest to regulators. Our conclusions have relevance to insurers using value-at-risk capital assessments in the European Union under Solvency II, but also territories using conditional tail expectations such as Australia, Canada and Switzerland.  相似文献   
7.
Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.  相似文献   
8.
As market intermediaries, electricity suppliers purchase electricity from the wholesale market or self-generate to deliver their customers. However, electricity suppliers are uncertain about how much electricity their residential customers will use at any hour of the day until they actually turn switches on. While demand uncertainty is a common feature of all commodity markets, suppliers generally rely on storage to manage it. Singularly, electricity suppliers are exposed to joint volumetric and price risk on an hourly basis given the physical attributes of electricity. In the literature on electricity markets, few articles compare the efficiency of forward contracts, options and physical assets (i.e. power plants) within intraday hourly hedging portfolios, whereas electricity markets are precisely hourly markets. We analyse portfolios made of forwards, options and/or power plants for specific hourly clusters (9 am, 12 pm, 18 pm, 9 pm) based on electricity market data from 2013 to 2015 from the integrated German–Austrian spot market. Through a VaR model, we prove that intraday hedging with forwards is structurally inefficient compared to financial options and physical assets, no matter the cluster hour. Moreover, our results demonstrate the contribution of ‘out of the money’ options for all hours within volatile spot markets.  相似文献   
9.
中国证券市场起步于90年代初期,由于缺乏风险对冲工具和做空机制,市场长期以来一直处于单边市状态,即投资者只能通过买入股票并等待其上涨来获得收益,如果市场处于下跌通道之中,投资者或者被动忍受损失,或者离场观望。而中国证券市场波动又比较剧烈,这就更加大了投资者的投资风险。沪深300股指期货的推出将使得国内证券市场格局发生重大变革:一方面,投资者可以通过投机来获利;另一方面,投资者可以通过股指期货进行避险,即所谓的套期保值。  相似文献   
10.
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