Risk Early-Warning Method for Natural Disasters Based on Integration of Entropy and DEA Model

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and DEA model, whose steps were put forward. On the basis of standard risk early-warning DEA model of natural disasters, weight coefficient of risk early-warning factors was determined with Information Entropy method, which improved standard risk early-warning DEA model with non-Archimedean infinitesimal, and established risk early-warning preference DEA model based on integrated entropy weight and DEA Model. Finally, model was applied into landslide risk early-warning case in earthquake-damaged emergency process on slope engineering, which exemplified the outcome could reflect more risk information than the method of standard DEA model, and reflected the rationality, feasibility, and impersonality, revealing its better ability on comprehensive safety and structure risk.

The risk early-warning of gas hazard in coal mine based on Rough Set-neural network

This article proposed the risk early-warning model of gas hazard based on Rough Set and neural network. The attribute quantity was reduced by Rough Set, the main characteristic attributes were withdrawn, the complexity of neural network system and the computing time was reduced, as well. Because of fault-tolerant ability, parallel processing ability, anti-jamming ability and processing non-linear problem ability of neural network system, the methods of Rough Set and neural network were combined. The examples research indicate： applying Rough Set and BP neural network to the gas hazard risk early-warning coal mines in coal mine, the BPNN structure is greatly simplified, the network computation quantity is reduced and the convergence rate is speed up.

Time-varying impact of political risk on copper prices

Using the International Country Risk Guide(ICRG)index to represent countries’political risk,the time-varying effect of political risk on copper prices was examined based on the time-varying parameter structural vector autoregression with stochastic volatility(TVP-SVAR-SV)model.The empirical results show that the impact of political risk on copper prices is time-varying and has tended to increase gradually in recent years.There are significant country-level differences in the impact of political risk on copper prices.Political risk has a stronger and longer-lasting impact on copper prices in exporting countries.In terms of risk sources,external and internal conflicts contribute most to international copper price fluctuations in the sample period.The impact of political risk on copper prices reaches an extreme level during the international financial crisis,the European debt crisis,and the election of Donald Trump.

An Approach to Quantify the Heat Wave Strength and Price a Heat Derivative for Risk Hedging

Mitigating the heat stress via a derivative policy is a vital financial option for agricultural producers and other business sectors to strategically adapt to the climate change scenario. This study has provided an approach to identifying heat stress events and pricing the heat stress weather derivative due to persistent days of high surface air temperature （SAT）. Cooling degree days （CDD） are used as the weather index for trade. In this study, a call-option model was used as an example for calculating the price of the index. Two heat stress indices were developed to describe the severity and physical impact of heat waves. The daily Global Historical Climatology Network （GHCN-D） SAT data from 1901 to 2007 from the southern California, USA, were used. A major California heat wave that occurred 20-25 October 1965 was studied. The derivative price was calculated based on the call-option model for both long-term station data and the interpolated grid point data at a regular 0.1~ x0.1~ latitude-longitude grid. The resulting comparison indicates that （a） the interpolated data can be used as reliable proxy to price the CDD and （b） a normal distribution model cannot always be used to reliably calculate the CDD price. In conclusion, the data, models, and procedures described in this study have potential application in hedging agricultural and other risks.

Investor Attention,Analyst Optimism,and Stock Price Crash Risk

This paper used the A-shares listed companies in China as samples,constructed a comprehensive indicator of investor attention,and conducted an empirical analysis on the correlations among investor attention,analyst optimism,and stock price crash risk.The results indicated that investor attention aggravates the stock price crash risk and has a positive effect on analyst optimism.Meanwhile,the analyst optimism plays a mediating role in the positive correlation between investor attention and stock price crash risk.In addition to that,institutional investor attention also has direct and indirect effects on the crash risk.

Research on Agricultural Product Price Risk and Risk Management

There are a variety of reasons for agricultural product price risk,and drastic volatility in agricultural product price can give a tremendous negative impact on agriculture and even whole society. The paper argues that the agricultural product price risks include( i) price risk caused by decrease in yield and quality of agricultural products due to natural disasters;( ii) price risk caused by actual change of the market supply and demand;( iii) price fluctuation risk caused by the change of the price of the related products;( iv) sharp price volatility risk caused by market speculation;( v) risk caused by periodic property of agricultural products and lack of elasticity of agricultural demand;( vi)risk caused by lack of government management. Agricultural product price risk poses great harm to farmers,small and medium-sized agricultural operators and general consumers. This paper brings forward the specific recommendations for solving agricultural product price risk.

Reason Analysis and Risk Prevention of Soaring Price of Traditional Chinese Medicinal Materials

In recent years,the price of traditional Chinese medicinal materials soars continuously,and the resulting price risk increasingly looms large,which has critically affected midstream and downstream industries and peoples' demand for drug,and imperiled healthy and orderly development of traditional Chinese medicinal industries.Based on the status quo of continuous skyrocketing price of traditional Chinese medicinal materials at present,we winkle out the root cause of soaring price as follows:the supply and demand lose balance;the production costs hike up;there are other factors responsible for soaring price.This paper further analyses the impact of sharp increase in price of traditional Chinese medicinal materials on all links of industry chain as follows:the medicinal herb growers never benefit from soaring price;the counterfeiters and forgers in midstream industry increase;the gross profit rate of Chinese medicine enterprises declines.In accordance with the risk arising from abnormal fluctuation in price of traditional Chinese medicinal materials,corresponding precautionary measures are put forward as follows:promote the quality of traditional Chinese medicinal materials through management of value chain;curtail the production and management cost of traditional Chinese medicinal materials through management of organization chain;stabilize price of traditional Chinese medicinal materials through management of information chain;reduce transaction cost of traditional Chinese medicinal materials through management of logistics chain.

Carbon emission trading system and stock price crash risk of heavily polluting listed companies in China:based on analyst coverage mechanism

This study reveals the inconsistencies between the negative externalities of carbon emissions and the recognition condition of accounting statements.Hence,the study identifies that heavily polluting enterprises in China have severe off-balance sheet carbon reduction risks before implementing the carbon emission trading system(CETS).Through the staggered difference-in-difference(DID)model and the propen-sity score matching-DID model,the impact of CETS on reducing the risk of stock price crashes is examined using data from China’s A-share heavily polluting listed companies from 2007 to 2019.The results of this study are as follows:(1)CETS can significantly reduce the risk of stock price crashes for heavily polluting companies in the pilot areas.Specifically,CETS reduces the skewness(negative conditional skewness)and down-to-up volatility of the firm-specific weekly returns by 8.7%and 7.6%,respectively.(2)Heterogeneity analysis further shows that the impacts of CETS on the risk of stock price crashes are more significant for heavily polluting enterprises with the bear market condition,short-sighted management,and intensive air pollution.(3)Mechanism tests show that CETS can reduce analysts’coverage of heavy polluters,reducing the risk of stock price crashes.This study reveals the role of CETS from the stock price crash risk perspective and helps to clarify the relationship between climatic risk and corporate financial risk.

Corporate pledgeable asset ownership and stock price crash risk

We investigate how a firm’s corporate pledgeable asset ownership(CPAO)affects the risk of future stock price crashes.Using pledgeable asset ownership and crash risk data for a large sample of U.S.firms,we provide novel empirical evidence that a firm’s risk of a future stock price crash decreases with an increase in its pledgeable assets.Our main findings are valid after conducting various robustness tests.Further channel tests reveal that firms with pledgeable assets increase their collateral value,thereby enhancing corporate transparency and limiting bad news hoarding,resulting in lower stock price crash risk.Overall,the results show that having more pledgeable assets enables easier access to external financing,making it less likely that managers will hoard bad news.

Production response to price risk and market liberalization of Nigerian major agricultural crops

This study models supply response for major agricultural crops in Nigeria which include the standard arguments and price risk. The data comes from Central Bank of Nigeria annual reports and statement of account, National Bureau of Statistics＇ abstract of statistics and annual Agricultural survey manual. The data are analyzed using autoregressive distributed lag and cointegration and error correction models. The results indicate that producers are responsive not only to price but also to price risk and exchange rate.

Risk Management via Measuring Impacts of Micro and Macro Economic Factors on Financial Firm Stock Price—A Case of Mitsubishi UFJ in Japan

Mitsubishi UFJ(MUFJ)has made very positive contributions to the overall achievements of the banking industry,deserving its position as one of the leading financial groups in Japan,contributing to helping government stabilizes the market and successfully implement monetary policy.MUFJ is aiming for growth of approximately¥250 billion in net operating profits,with MUFG Group companies,business groups,and the corporate center.Movement of stock price in financial groups such as MUFJ will reflect the business health of bank and financial system and the whole economy.Good business management requires us to consider the impacts of multi micro and macro factors on stock price,and it contributes to promoting business plan and economic policies for economic growth and stabilizing macroeconomic factors.By data collection method through statistics,analysis,synthesis,comparison,quantitative analysis to generate qualitative comments and discussion;using econometric method to perform regression equation and evaluate quantitative results,the article analyzed and evaluated the impacts of six(6)micro and macro economic factors such as:cost,net sale,lending rate,inflation,GPD growth,S&P 500,etc.on stock price of a big financial group,MUFJ in Japan in the period of 2010-2019,both positive and negative sides.The results of quantitative research,in a seven-factor model,show that the decrease in inflation,GDP,and high lending rate has a significant effect on reducing MUFJ stock price with the highest impact coefficient,the second is increase in cost.This research finding and recommended policy also can be used as reference in policy for commercial bank and financial system in many developing countries.

Coal price fluctuations and the impact on financial risk Evidence from China＇s coal listed companies

With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal industry in A-share market from 1995 to 2007. Empirical results show that Year-Based price index of coal price has a negative correlation with the financial risk but has no significance, and coal chain price has a significant negative correlation with the financial risk. Further research indicates that enterprises increase bad investment, and a lot of debts caused by short-term rise in coal prices. The results also show that the financial risk in the coal industry declines with the rise of GDP growth rate and increases with the rise of inflation rate.

Opportunities and Risks of Natural Gas Investment in China under the Circumstance of Low Oil Prices

After more than 30 years of rapid growth, the Chinese economy has entered the "new normal" of moderately high growth. Due to the effects of multiple factors, the international oil price has remained consistently low. The low oil price has exerted critical effects on international natural gas investment. At the same time, the market-oriented price mechanism of natural gas in China is gradually taking shape; the concept of low carbon development is widely advocated; and the use of natural gas gains popularity in the city. Such factors provide great opportunities for investment in the natural gas market of China, including boiler coal-to-gas transformation, natural gas distributed energy and natural gas vehicles. However, risks also exist, such as the lower competitiveness of natural gas, its excess production capacity and dwindling consumption in some gas consumption industries, an insufficient driving force for facilitating the coal-to-gas transformation of industrial fuel users, reverse substitution of "coal in place of gas" in some enterprises, nontransparent costs of the downstream link of the natural gas price chain, and mismatches and nonsynchronous adjustments in natural gas prices and electricity prices.

Pricing Catastrophe Options with Credit Risk in a Regime-Switching Model

In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.

Rapid Price Hike and Tumble of Cocoon Risks in Chinese Silk Industry

Back to 1994, a transient price hike of cocoon silk eventually led to a predicament for Chinese silk industry in the following years. A decade later, is that slump going to happen again?

Price-taker在两个电力市场中的交易决策 (二)发电商的策略

在对购电商两市场交易量优化分配问题研究的基础上,讨论了Price-taker发电商如何在考虑两市场电价风险的情况下进行交易电量的优化分配,以便在规避价格风险的同时追求尽可能大的收益。文中对Price-taker发电商的两市场交易量分配策略进行了建模和研究,给出了总交易量和各市场交易的优化解并为发电商如何选择风险因子提出了建议。文中给出了仿真算例。

Price-taker在两个电力市场中的交易决策 (一)购电商的策略

多市场交易量分配问题是电力市场参与者竞标决策中的重要问题之一。研究了考虑电价风险的情况下,Price—taker购电商在两个市场之间的交易量优化问题。讨论了购电商在两市场中优化分配问题的建模及解析解,引入风险因子概念,并用条件概率模型反映电价的不确定性,目标是总费用及风险均较低。用美国加州电力市场的实际数据进行了仿真。

Optimizing continuous cover management of boreal forest when timber prices and tree growth are stochastic

Background： Decisions on forest management are made under risk and uncertainty because the stand development cannot be predicted exactly and future timber prices are unknown. Deterministic calculations may lead to biased advice on optimal forest management. The study optimized continuous cover management of boreal forest in a situation where tree growth, regeneration, and timber prices include uncertainty. Methods： Both anticipatory and adaptive optimization approaches were used. The adaptive approach optimized the reservation price function instead of fixed cutting years. The future prices of different timber assortments were described by cross-correlated auto-regressive models. The high variation around ingrowth model was simulated using a model that describes the cross- and autocorrelations of the regeneration results of different species and years. Tree growth was predicted with individual tree models, the predictions of which were adjusted on the basis of a climate-induced growth trend, which was stochastic. Residuals of the deterministic diameter growth model were also simulated. They consisted of random tree factors and cross- and autocorrelated temporal terms. Results： Of the analyzed factors, timber price caused most uncertainty in the calculation of the net present value of a certain management schedule. Ingrowth and climate trend were less significant sources of risk and uncertainty than tree growth. Stochastic anticipatory optimization led to more diverse post-cutting stand structures than obtained in deterministic optimization. Cutting interval was shorter when risk and uncertainty were included in the analyses. Conclusions： Adaptive optimization and management led to 6%-14% higher net present values than obtained in management that was based on anticipatory optimization. Increasing risk aversion of the forest landowner led to earlier cuttings in a mature stand. The effect of risk attitude on optimization results was small.

PRICING CATASTROPHE OPTIONS WITH COUNTERPARTY CREDIT RISK IN A REDUCED FORM MODEL

In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.

基于改进的RiskMetrics模型的股票市场风险度量

对RiskMetrics模型两个假设做出改进,并运用改进的RiskMetrics模型对2007年1月至2018年9月的国内外股票指数日收盘价序列进行建模,实证结果表明:改进的RiskMetrics模型可以更加精准刻画三类股指序列的在险价值。美国股市对利空消息的反应非常剧烈,沪深股市与香港股市之间具有趋同性,但两者对新息冲击的反应有所不同,沪深股市对利空消息与利好消息的反应区别不明显,而香港股市对利空消息的反应明显强于利好消息。另外,三类指数的收益率序列均呈“尖峰厚尾”特性;股票价格波动对冲击的反应速度由高到低依次是美国股市、香港股市、内地股市,而对冲击的持久性由强至弱的排序则恰恰相反。