Evidence exists that emerging market stock returns are influenced by a different set of factors than those that influence the returns for stocks traded in developed countries. This study uses ...artificial neural networks to predict stock price movement (i.e., price returns) for firms traded on the Shanghai stock exchange. We compare the predictive power using linear models from financial forecasting literature to the predictive power of the univariate and multivariate neural network models. Our results show that neural networks outperform the linear models compared. These results are statistically significant across our sample firms, and indicate neural networks are a useful tool for stock price prediction in emerging markets, like China.
The applicability conditions of a recently reported Central Limit Theorem-based approximation method in statistical physics are investigated and rigorously determined. The failure of this method at ...low and intermediate temperature is proved as well as its inadequacy to disclose quantum criticalities at fixed temperatures. Its high temperature predictions are in addition shown to coincide with those stemming from straightforward appropriate expansions up to (
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. Our results are clearly illustrated by comparing the exact and approximate temperature dependence of the free energy of some exemplary physical system.
Purpose - The purpose of this study is to demonstrate the use of weather derivatives to hedge firm exposure to previously unmanageable risk events caused by natural phenomenon such as excessive ...rainfall.Design methodology approach - The paper adopts a case study approach to meet the objectives above, focusing on golf courses in the Midwest USA, which provide perfect examples of businesses with seasonal cash flows.Findings - It is shown that a firm can reduce its revenue volatility by up to 80 per cent. Weather derivatives are important additions to firm portfolios of risk management tools. Purchasing weather derivatives will improve the owner's ability to forecast revenues and assure expenditure coverage, both important goals for a small business owner.Practical implications - Many firms find the uneven revenue streams associated with their industry to be difficult to manage. One of the primary risks faced by firms is exposure to weather phenomena. With the introduction of weather derivatives, firms can now hedge their exposure to climatologic events. The application for weather derivatives is quite limitless. Weather derivatives are a relatively new product, and most firms are either unaware of their existence or believe them to be complicated. It is an industry that may experience explosive growth in the coming years.Originality value - This paper demonstrates the use of derivatives to hedge exposure to climatic events.
Since the establishment of the Shanghai Stock Exchange (SHSE) in 1990 and the Shenzhen Stock Exchange (SZSE) in 1991, China’s stock markets have expanded rapidly. Although this rapid growth has ...attracted considerable academic interest, few studies have examined the ability of conventional financial models to predict the share price movements of Chinese stock. This gap in the literature is significant, given the volatility of the Chinese stock markets and the added risk that arises from the Chinese legal and regulatory environment. In this paper we address this research gap by examining the predictive ability of several well-established forecasting models, including dynamic versions of a single-factor CAPM-based model and Fama and French’s three-factor model. In addition, we compare the forecasting ability of each of these models with that of an artificial neural network (ANN) model that contains the same predictor variables but relaxes the assumption of model linearity. Surprisingly, we find no statistical differences in the forecasting accuracy of the CAPM and three-factor model, a result that may reflect the emerging nature of the Chinese stock markets. We also find that each ANN model outperforms the corresponding linear model, indicating that neural networks may be a useful tool for stock price prediction in emerging markets.
Rats exposed to repeated unavoidable stress show decreased dopamine output in the nucleus accumbens shell (NAcS) and do not acquire vanilla sugar (VS)-sustained appetitive behavior (VAB). Rats ...treated with lithium for 3 weeks also show decreased NAcS dopamine output, yet they acquire VAB. Feeding a novel palatable food increases extraneuronal dopamine levels in the NAcS and medial prefrontal cortex (mPFC) in rats. In order to investigate the role of food-induced dopamine release in VAB acquisition, we studied by microdialysis the dopaminergic response in the NAcS and mPFC to the presentation and consumption of VS in satiated control rats, and in satiated rats exposed to repeated stress or lithium treatment. The dopaminergic response to VS was also studied in rats familiar with VS, or that had acquired VAB.
In control rats, VS feeding was accompanied by increased dopamine output in the NAcS and mPFC, and one-trial habituation to this effect developed in the NAcS. Rats exposed to a 7-day stress showed reduced interest in VS pellets, and when fed VS they did not show a dopaminergic response in the NAcS and mPFC. Lithium-treated rats rapidly ate VS pellets and showed increased dopamine output in the NAcS and mPFC, with no habituation in the NAcS response. Rats familiar with VS and rats that had already learned VAB ate VS pellets. The first group showed a lower dopaminergic response to VS consumption than the control group, but the latter showed no dopaminergic response in the NAcS and mPFC.
We propose that the limbic dopaminergic response to a novel palatable food plays a role in associative learning and that it is predictive of the competence to learn an appetitive behavior. Moreover, in our experimental conditions a phasic increase in mesolimbic dopamine no longer signals the VS stimulus once it has become a reinforcer in an appetitive task.
We show that a two-atom Bose–Hubbard model exhibits three different phases in the behavior of thermal entanglement in its parameter space. These phases are demonstrated to be traceable back to the ...existence of level crossings in the ground state of the same system. Significant similarities between the behaviors of thermal entanglement and heat capacity in the parameter space are brought to light thus allowing to interpret the occurrence and the meaning of all these three phases.
► Entanglement sudden transitions are found in non-trivial exactly solvable Hubbard models. ► Entanglement and heat capacity exhibit three anti-correlated phases. ► Qualitative changes of thermal entanglement or heat capacity occur at critical points. ► We propose thermodynamical measurements to single out entanglement critical points.
Using intraday data on individual stocks included in the S&P 500 index, we present evidence of herd formation over the duration and aftermath of the Flash Crash on May 6, 2010, while no evidence of ...herding is observed preceding the event. The findings establish a clear link between herding among market participants and flash events that can drive sudden price fluctuations and underscore the importance of monitoring herd activity, particularly in the case of automated markets.