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In this paper, we present the results of a Learning-to-Forecast Experiment (LtFE) where we eliciting short- as well as long-run expectations regarding the future price dynamics in markets with positive and negative expectations feedback. Comparing our results on short-run expectations with the LtFE literature, we prove that eliciting long-run expectations has no impact on the price dynamics nor on short-run expectations formation. In particular, we confirm that the Rational Expectation Equilibrium (REE) is a good benchmark only for the markets with negative feedback. Interestingly, our data show that while the term structure of the cross-sectional dispersion of expectations is convex in positive feedback markets, it is concave in negative feedback markets. Differences in the slope of the term structure stem from diverse degrees of uncertainty regarding the evolution of prices in the two feedback systems: (1) in the negative feedback system, the convergence of the price to the REE reflects a tendency for coordination of long-run expectations around the fundamental value; (2) conversely, oscillatory price dynamics observed in the positive feedback system is responsible for the diverging pattern of long-run expectations. Finally, we propose a new measure of heterogeneity of expectations based on the scaling of the dispersion of expectations over the forecasting horizon.

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Inspired by the Bank of America Merrill Lynch global breath rule, we propose an investor sentiment index based on the collective movement of stock prices in a given market. We show that the time evolution of the sentiment index can be reasonably described by the herding model proposed by Kirman in his seminal paper “Ants, rationality and recruitment” (Kirman in Q J Econ 108:137–156, 1993). The correspondence between the index and the model allowed us to easily estimate its parameters. Based on the model and the empirical evolution of the sentiment index, we propose an early warning indicator able to identify optimistic and pessimistic phases of the market. As a result, investors and policy-makers can set different strategies anticipating financial market instability. Investors can reduce the risk of their portfolio while policy-makers can set more efficient policies to avoid the effects of financial instability on the real economy. The validity of our results is supported by means of a robustness analysis showing the application of the early warning indicator in eight different worldwide stock markets.

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From a statistical point of view, the prevalence of non-Gaussian distributions in financial returns and their volatilities shows that the Central Limit Theorem (CLT) often does not apply in financial markets. In this article, we take the position that the independence assumption of the CLT is violated by herding tendencies among market participants, and investigate whether a generic probabilistic herding model can reproduce non-Gaussian statistics in systems with a large number of agents. It is well known that the presence of a herding mechanism in the model is not sufficient for non-Gaussian properties, which crucially depend on the details of the communication network among agents. The main contribution of this article is to show that certain hierarchical networks, which portray the institutional structure of fund investment, warrant non-Gaussian properties for any system size and even lead to an increase in system-wide volatility. Viewed from this perspective, the mere existence of financial institutions with socially interacting managers contributes considerably to financial volatility.  相似文献   
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In a previous study the authors have identified a small core of directors who are both highly central to the entire network of German corporate boards as well as closely connected among themselves. In this note the authors provide an update of their previous results using the composition of management and supervisory boards as of December 2010. Almost all qualitative properties of previous samples are confirmed despite considerable turnover within the group of people constituting the network core.  相似文献   
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In this paper, we analyze the distributional properties of the balance sheets of Icelandic firms by performing an empirical analysis of total assets, profit rates and growth rates using a data set of 2,818 Icelandic firms during the period 2000–2009. We find that the firms size measure, i.e. total assets, have the same heavy tail characteristics as various studies have shown, e.g. for US and Italian firms. The heavy tail nature of the total assets distribution seems to be robust w.r.t. a boom-bust cycle of the economy as well as special characteristics of Icelandic firms, e.g. their relatively small size and private ownership. Another important finding is that the profit rates, or return on assets, of Icelandic firms follow a Laplace like distribution similar to US firms. Additionally, we identified deviations from the distributional regularities, namely the power law behavior of firms’ size and Laplacian distributions of growth and profit rates, during the booming period of the economy 2005–2007.  相似文献   
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The worldwide financial crisis of 2007–2008 raised serious concerns about the soundness of banks’ activities and about the extent to which banking regulation should supervise banks’ investment decisions. We contribute to this topic by examining the Spanish case, which has been emblematic of the bubble and burst dynamics in the credit market. In particular, we study the allocation of bank credit among Spanish companies from 1999 to 2014, showing that larger companies accumulated greater amounts of bank loans per unit of total assets, thus leading to a notable concentration. We also find that, during the Spanish boom period, bank loans shifted from the manufacturing to the construction industry, and in particular to the largest companies of the latter sector. This happened in spite of the high leverage of large construction firms, which was increasing also due to their growing debt. We argue that the higher operating benefits, reflecting the increase of the housing price during the boom period, overvalued construction firms as potential borrowers. The bankruptcy of several large construction companies during the Spanish crisis supports the need for monitoring and regulation, to avoid an excessive concentration of bank credit to a few large companies, especially if they belong to a specific sector.

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