汇率与油价波动对企业价值的影响研究
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摘要
企业价值评估是现代财务管理的重要工具之一。通过对企业未来价值创造结果的度量,可以判断企业的整体价值,从而为分析和衡量企业的公平市场价值提供有关信息,帮助投资人和企业管理层以及政府监管机构改善决策。随着近年来企业并购重组、联营合资、股权转让、资产置换、破产清算等交易活动的蓬勃开展,对企业价值进行合理的科学评估,在投融资活动中逐步显现出其重要性。
企业市场价值的变化除了决定于企业的核心价值,还受到外界经济环境、股权分配改革、宏观经济政策等因素的影响。随着全球经济一体化的发展和新的世界贸易格局的形成,中国企业,尤其是上市公司将越来越明显地受到汇率变动以及国际能源价格变动的影响。因此,要合理评估企业的价值,就不能对汇率与国际原油价格的波动视而不见。
在详细分析汇率和国际油价波动影响企业价值的机理后,为了进一步地明确企业价值与宏观经济要素之间的关系,本文在首先利用剩余收益比例模型估算得到企业价值的估计值,接着将估计值与实际有效汇率和国际油价的波动进行协整分析,并构建误差修正模型,分析三者变化的联动关系。
实证部分选取沪深证券市场810家2000年底前上市的上市公司为研究对象,对其企业价值进行估算,并通过编制企业价值指数与价格指数,验证了在全样本和分行业条件下,企业实际价值与市场价格波动之间的确存在内在联系。协整分析结果表明,企业价值与国际原油价格及实际有效汇率之间的确存在长期相互关系。最后的Granger检验结果表明,在5%的显著性水平下,人民币实际汇率与国际油价均为企业价值指数的Granger原因,但是反向假设不成立。企业价值与人民币实际有效汇率以及国际油价之间存在长期均衡关系的结果说明,企业尤其是上市公司的经营绩效,长期必然受到实际有效汇率价格波动和国际原油价格波动的影响。此外,人民币兑美元的实际汇率以及国际原油价格是制造业、信息技术业、金融保险业、社会服务业等相关行业的Granger原因。
在判定企业价值、国际原油价格和汇率波动三者之间存在本质的长期相互关系之后,本文进一步将3种经济变量视为影响企业市场价值即股价的影响因素,深入挖掘企业价值、汇率、国际油价波动与上市公司股价走势之间的内在联系。实证研究运用Vapnik提出的支持向量机方法(Support Vector Machines, SVM),将企业价值视为股价变动的直接因素,汇率及国际能源价格视为间接因素,共同作为支持向量机模型的输入变量,构建上市公司股价的非线性预测模型,并取得显著优于随机游走模型和传统时序ARMA模型的预测效果,具有较好的预测性能。进一步的,剔除汇率和国际油价变量,仅将企业价值作为SVM的输入变量,构建单因素模型,实证表明其预测误差远远高于前述的多因素模型,由此判定,汇率和国际油价是影响企业市场价值即股价的重要因素。
基于汇率与国际原油价格波动的企业价值研究,运用统计方法和计量分析工具,有效挖掘企业价值与国际油价及汇率波动之间的本质关系,并进一步构建SVM非线性预测模型,对上市公司股价进行合理估计,这不仅在理论上填充了国内在该研究领域的空白,在现实意义上为提高政府对宏观经济系统的有效监管和政策制定的正确性、企业的经营运行和管理目标的确定以及投资者制定正确的投资策略,也有着较重要的指导意义。
Enterprise valve evaluating is one of the most important tools for modern financial management. The whole enterprise value, which can be evaluated by measuring all of the future profit of the enterprise, provide useful information for analysing and measuring the intrinsic value of the company and support better decision-making for investors and governors. In recent years, many business activities, such as strategic reorganization and incorporation, joint venture or pool capital, transfer of share right, replacement of assets, bankruptcy and liquidation and so on, have been launched so frequently that it's very important to evaluate enterprises value correctly in the activities of investment and financing.
The change of market value is not only decided by the enterprise core value, but also influenced by the economic environment outside, the equity division reforming, the macroeconomic policies, and so on. With the development of economic globalization and the formation of the new world trade pattern, the Chinese enterprises, especially the listed companies, have been influenced by the exchange rate fluctuation and the international oil price change more and more obviously. Hence, in order to get a true value of enterprises, the fluctuation of exchange rate and international oil price should never be neglected.
In order to clear the relationship between enterprise value and the macroeconomic factors further, after expounding the exchange rate and international oil price fluctuation risk faced by the enterprises and the polices have been promoted to reduce the losses in detail, this paper uses Residual income proportion model to estimate the enterprise value firstly, then puts up Johansen co-integration method on the analysis of estimate value and the fluctuation of the real effective exchange rate and international oil prices, moreover, builds the Error Correction Model, analyzes the co-movement of the three ones.
The empirical research of this paper selects810listed companies, all of which have been listed before the end of2000, as the study object. Then estimate their actual enterprise value and compiles value index and price index. The results of empirical research show that there is true interconnection between the actual enterprise value and the fluctuations of market price of listed companies based on both bulk sample and sub-industry sample. Co-integration analysis shows that there are long-term relationship between enterprise value and the international oil prices and the real effective exchange rate. Lastly, Granger Causality Tests shows that the international oil price and the exchange rate are both the Granger reason of enterprise value index under the5%confidence level, while the reverse is not true. The long-term equilibrium relationship between the enterprise value of listed companies and the real effective exchange rate and the international oil prices reveals that the value of enterprises, especially the listed companies, could be suffered from the exchange rate and international oil price fluctuation in the long run. Besides, the international oil price and the exchange rate is the Granger reason of some relevant industries, such as manufacturing industry, information technology industry, finance and insurance industry, social services industry and so on.
After judging whether there is a long-run equilibrium relationship between the three variables, this paper treats the three economic variables as the factors influence the listed companies' stock price, then digging the intrinsical relationship between the three variables and share price movements of the listed companies. Empirical research applies the Support Vector Machines (SVM), promoted by Vapnik, on predicting. In the predicting model, enterprise value is treated as a direct factor of stock price changes, while exchange rates and international energy prices are teated as indirect factors. They are both selected as the input variables in supporting the SVM model. Then we build listed company's share price nonlinear forecasting model, which has good prediction performance, achieves significantly better prediction consequent than the random walk model and traditional time series ARMA model. Furthermore, this paper leaving out variables of exchange rate and international oil fluctuation, only enterprise value is chosen as input variable to build a single-factor model. Empirical research suggests that predicting performance of the single-factor model is worse than multi-factor model. So, we conclude that the exchange rate and international oil fluctuation are important variables for enterprises'marketing value.
Applying the statistics methods and metrology analysis tools in the analysis of enterprise value and the study of the stock price prediction based on the fluctuation of exchange rate and international oil price, effectively mining the essential relationship between the enterprise value and the fluctuation of international oil prices and exchange rate. And moreover, the SVM nonlinear model has been promoted for listed companies' stock price forecasting. This paper not only enriches the vacancy of related researches theoretically, but also provides precious suggestions for government's supervision, the companies'running and the determination of management objectives, the investors' investing decision making and so on in reality.
企业市场价值的变化除了决定于企业的核心价值,还受到外界经济环境、股权分配改革、宏观经济政策等因素的影响。随着全球经济一体化的发展和新的世界贸易格局的形成,中国企业,尤其是上市公司将越来越明显地受到汇率变动以及国际能源价格变动的影响。因此,要合理评估企业的价值,就不能对汇率与国际原油价格的波动视而不见。
在详细分析汇率和国际油价波动影响企业价值的机理后,为了进一步地明确企业价值与宏观经济要素之间的关系,本文在首先利用剩余收益比例模型估算得到企业价值的估计值,接着将估计值与实际有效汇率和国际油价的波动进行协整分析,并构建误差修正模型,分析三者变化的联动关系。
实证部分选取沪深证券市场810家2000年底前上市的上市公司为研究对象,对其企业价值进行估算,并通过编制企业价值指数与价格指数,验证了在全样本和分行业条件下,企业实际价值与市场价格波动之间的确存在内在联系。协整分析结果表明,企业价值与国际原油价格及实际有效汇率之间的确存在长期相互关系。最后的Granger检验结果表明,在5%的显著性水平下,人民币实际汇率与国际油价均为企业价值指数的Granger原因,但是反向假设不成立。企业价值与人民币实际有效汇率以及国际油价之间存在长期均衡关系的结果说明,企业尤其是上市公司的经营绩效,长期必然受到实际有效汇率价格波动和国际原油价格波动的影响。此外,人民币兑美元的实际汇率以及国际原油价格是制造业、信息技术业、金融保险业、社会服务业等相关行业的Granger原因。
在判定企业价值、国际原油价格和汇率波动三者之间存在本质的长期相互关系之后,本文进一步将3种经济变量视为影响企业市场价值即股价的影响因素,深入挖掘企业价值、汇率、国际油价波动与上市公司股价走势之间的内在联系。实证研究运用Vapnik提出的支持向量机方法(Support Vector Machines, SVM),将企业价值视为股价变动的直接因素,汇率及国际能源价格视为间接因素,共同作为支持向量机模型的输入变量,构建上市公司股价的非线性预测模型,并取得显著优于随机游走模型和传统时序ARMA模型的预测效果,具有较好的预测性能。进一步的,剔除汇率和国际油价变量,仅将企业价值作为SVM的输入变量,构建单因素模型,实证表明其预测误差远远高于前述的多因素模型,由此判定,汇率和国际油价是影响企业市场价值即股价的重要因素。
基于汇率与国际原油价格波动的企业价值研究,运用统计方法和计量分析工具,有效挖掘企业价值与国际油价及汇率波动之间的本质关系,并进一步构建SVM非线性预测模型,对上市公司股价进行合理估计,这不仅在理论上填充了国内在该研究领域的空白,在现实意义上为提高政府对宏观经济系统的有效监管和政策制定的正确性、企业的经营运行和管理目标的确定以及投资者制定正确的投资策略,也有着较重要的指导意义。
Enterprise valve evaluating is one of the most important tools for modern financial management. The whole enterprise value, which can be evaluated by measuring all of the future profit of the enterprise, provide useful information for analysing and measuring the intrinsic value of the company and support better decision-making for investors and governors. In recent years, many business activities, such as strategic reorganization and incorporation, joint venture or pool capital, transfer of share right, replacement of assets, bankruptcy and liquidation and so on, have been launched so frequently that it's very important to evaluate enterprises value correctly in the activities of investment and financing.
The change of market value is not only decided by the enterprise core value, but also influenced by the economic environment outside, the equity division reforming, the macroeconomic policies, and so on. With the development of economic globalization and the formation of the new world trade pattern, the Chinese enterprises, especially the listed companies, have been influenced by the exchange rate fluctuation and the international oil price change more and more obviously. Hence, in order to get a true value of enterprises, the fluctuation of exchange rate and international oil price should never be neglected.
In order to clear the relationship between enterprise value and the macroeconomic factors further, after expounding the exchange rate and international oil price fluctuation risk faced by the enterprises and the polices have been promoted to reduce the losses in detail, this paper uses Residual income proportion model to estimate the enterprise value firstly, then puts up Johansen co-integration method on the analysis of estimate value and the fluctuation of the real effective exchange rate and international oil prices, moreover, builds the Error Correction Model, analyzes the co-movement of the three ones.
The empirical research of this paper selects810listed companies, all of which have been listed before the end of2000, as the study object. Then estimate their actual enterprise value and compiles value index and price index. The results of empirical research show that there is true interconnection between the actual enterprise value and the fluctuations of market price of listed companies based on both bulk sample and sub-industry sample. Co-integration analysis shows that there are long-term relationship between enterprise value and the international oil prices and the real effective exchange rate. Lastly, Granger Causality Tests shows that the international oil price and the exchange rate are both the Granger reason of enterprise value index under the5%confidence level, while the reverse is not true. The long-term equilibrium relationship between the enterprise value of listed companies and the real effective exchange rate and the international oil prices reveals that the value of enterprises, especially the listed companies, could be suffered from the exchange rate and international oil price fluctuation in the long run. Besides, the international oil price and the exchange rate is the Granger reason of some relevant industries, such as manufacturing industry, information technology industry, finance and insurance industry, social services industry and so on.
After judging whether there is a long-run equilibrium relationship between the three variables, this paper treats the three economic variables as the factors influence the listed companies' stock price, then digging the intrinsical relationship between the three variables and share price movements of the listed companies. Empirical research applies the Support Vector Machines (SVM), promoted by Vapnik, on predicting. In the predicting model, enterprise value is treated as a direct factor of stock price changes, while exchange rates and international energy prices are teated as indirect factors. They are both selected as the input variables in supporting the SVM model. Then we build listed company's share price nonlinear forecasting model, which has good prediction performance, achieves significantly better prediction consequent than the random walk model and traditional time series ARMA model. Furthermore, this paper leaving out variables of exchange rate and international oil fluctuation, only enterprise value is chosen as input variable to build a single-factor model. Empirical research suggests that predicting performance of the single-factor model is worse than multi-factor model. So, we conclude that the exchange rate and international oil fluctuation are important variables for enterprises'marketing value.
Applying the statistics methods and metrology analysis tools in the analysis of enterprise value and the study of the stock price prediction based on the fluctuation of exchange rate and international oil price, effectively mining the essential relationship between the enterprise value and the fluctuation of international oil prices and exchange rate. And moreover, the SVM nonlinear model has been promoted for listed companies' stock price forecasting. This paper not only enriches the vacancy of related researches theoretically, but also provides precious suggestions for government's supervision, the companies'running and the determination of management objectives, the investors' investing decision making and so on in reality.
引文
[1]单炳亮.公司价值评估理论的发展.当代经济科学,2004,26(1)：70-76
[2]钱莉,雷欣欣,刘珉璐.企业价值评估方法的对比研究.商业研究,2008,24(1)：56-57
[3]张人骥,刘浩,胡晓斌.充分利用会计信息的企业价值评估模型——RIR模型的建立与应用.财经研究,2002,28(7)：68-74
[4]Vapnik V N. The Nature of Statistical Learning Theory. New York:Springer Verlag, 1995
[5]Fisher I. The nature of capital and income. New York:The Macmillan Company, 1906
[6]Miller M, Modigliani F. Dividend policy, growth and the valuation of shares. Journal of Business,1961,10(1):411-433
[7]Ohlson J A. Book values and dividends in equity valuation. Contemporary Accounting Research,1995,11(2):661-687
[8]Bernard V L. The Feltham-Ohlson framework:implications for empiricists. Contemporary Accounting Research,1995,11(2):733-747
[9]Frankel R, Charles M C. Accounting valuation, market expectation and cross-sectional stock returns. The Journal of Accounting and Economics,1998,25(1): 283-319
[10]田志龙,李玉清.一种基于账面价值和未来收益的公司财富评估方法.会计研究,1997,5(1)：47-49
[11]陆宇峰.净资产倍率和市盈率的投资决策有用性——基于“费森—奥尔森估值模型”的实证研究：[上海财经大学博士论文].上海：上海财经大学,1999,34-41
[12]陈信元,陈冬华,朱红军等.净资产、剩余收益与市场定价：会计信息的价值相关性.金融研究,2002,4(1)：59-70
[13]欧阳励励.剩余收益模型在我国价值评估中的应用研究.财会通讯,2008,5(1)：62-66
[14]谢赤,王雅瑜,孙柏.外汇风险度量：方法与评述.金融经济(理论版),2007,11(2)：134-136
[15]陆茹.我国企业外汇风险管理研究：[南京理工大学硕士论文].南京：南京理工大学,2002,27-35
[16]韩晓亚.浮动汇率条件下国内企业外汇风险防范机制研究：[吉林大学硕士论文].长春：吉林大学,2007,39-42
[17]黄赜琳.国际石油价格波动对我国经济的影响及对策.经济纵横,2006,18(3)：5-8
[18]Engle R F, Granger C J. Co-integration and error correction:representation estimation and testing. Econometrics,1987,55(2):251-277
[19]Engle R F, Granger C J, Hallman J J. Merging short-and long-run forecasts:An application of seasonal cointegration to monthly electricity sales forecasting. Journal of Econometrics,1989,40(1):45-62
[20]Johansen S. Statistical analysis of co-integrating vectors. Journal of Economic Dynamics and Control,1988,12(1):231-254
[21]Wei H, Yoshiteru N, Shou-Yang W. Forecasting stock market movement direction with support fine machine. Computers & Operations Research,2005,32(10): 2513-2522
[22]Viviana F. Wavelet and SVM-based forecasts:An analysis of the U. S. metal and materials manufacturing industry. Resources Policy,2007,32(1):80-89
[23]Modigliani F, Miller M H. Corporation income taxes and the cost of capital:a correction. The American Economic Review,1963,53(3):433-443
[24]Fama E F. Agency problems and the theory of the firm. Journal of Political Economy,1980,88(2):288-307
[25]Black F, Scholes M S. The Pricing of Options and Corporate Liabilities, Journal of Political Economy,1973,81(3):637-654
[26]Miller M H, Modigliani F. Dividend policy, growth, and the valuation of shares. Journal of Business,1961,34(4):411-433
[27]鲜文铎,贺琴.企业价值影响因素浅析.财会月刊,2005,(11)：77-78
[28]李敬,陈收.企业战略管理.湖南：湖南大学出版社,50-64
[29]陈远志,梁彤缨.行业特征、股权结构与公司绩效的实证分析,系统工程,2006,24(2)：72-80
[30]Porter M E. The structure within industries and companies'performance. Review of Economics & Statistics,1979,61(2):214-227
[31]Schwartz E. Theory of the capital structure of the firm. The Journal of Finance, 1959,14(1):18-39
[32]Francesco L, Rosa A S. A comparison between neural networks and chaotic models for exchange rate prediction. Computational Statistics & Data Analysis, 1999,30(1):87-102
[33]谢赤,杨妮.汇率行为的混沌性及其分形维描述.湖南大学学报(社会科学版),2005,19(5)：50-56
[34]Xie Chi, Yang Ni. Analysis and empirical research on the long-memory property of exchange rate time series. In:Wireless Communications, Networking and Mobile Computing 2007(WiCom 2007),2007,8:5906-5909
[35]杨妮,谢赤,孙柏.汇率时间序列多重分形特征分析及实证研究.湖南大学学报(自然科学版),2008,35(8)：89-92
[36]谢赤,杨妮,孙柏.汇率时间序列非线性特征分析及实证研究.系统工程,2008,26(11)：98-102
[37]Johnson N F, Jefferies P, Ming H P. Financial market complexity. Oxford:Oxford University Press,2003:78-84
[38]陈伟,王伟.我国跨国公司汇率风险的计量与实证分析.河南金融管理干部学院学报,2006,14(3)：70-74
[39]Chow L, Solt E. The exchange rate risk exposure of asset returns. Journal of Business,1997, (1):105-123
[40]Taylor J B. Low inflation, pass-through, and the pricing power of firms. European Economic Review,2000,44(7):1389-1408
[41]Krugman P. The narrow moving band, the Dutch disease, and the competitive consequences of Mrs. Thatcher:Notes on trade in the presence of dynamic scale economies. Journal of Development Economics,1987,27(1-2):41-55
[42]Menon J. Exchange rate pass-through. Journal of Economic Surveys,1995,9(2): 197-231
[43]Campa J M, Goldberg L S. Exchange rate pass-through into import prices. The Review of Economics and Statistics, MIT Press,2005,87(4):679-690
[44]Feenstra R C, Gagnon J E, Knetter M M. Market share and exchange rate pass-through in world automobile trade. Journal of international Economics,1996, 40(1-2):187-207
[45]Dornbusch R. Exchange rates and prices. American Economic Review,1987,77(1): 93-106
[46]Hooper P, Mann C L. Exchange rate pass-through in the 1980s:the case of US imports of manufactures. Brookings Papers on Economic Activity,1989,1989(1): 297-337
[47]Goldberg L S, Campa J M. Distribution margins, import input and the sensitivity exchange rates. Federal Reserve Bank of New York Staff Reports,2006
[48]朱路,于李娜.有效汇率波动对国内价格的传递效应研究.世界经济研究,2008,(6)：3842
[49]陈六傅,刘厚俊.人民币汇率的价格传递效应.金融研究,2007,(4)：1-13
[50]Sohnke M B. Corporate cash flow and stock price exposures to foreign exchange rate risk. Journal of Corporate Finance,2007,13(5):981-994
[51]Hoa N, Robert F, Andrew M. Exchange rate exposure, foreign currency derivatives and the introduction of the euro:French evidence. International Review of Economics & Finance,2007,16(4):563-577
[52]Elaine H, Anthony O. Firm-level exchange rate exposure in the Euro zone. International Business Review, In Press, Corrected Proof, Available online 9 April 2009
[53]Hekman A. Financial model of foreign exchange exposure. Journal of International Business Studies,1985,16(1):83-99
[54]Flood E J, Donald R. L. On the measurement of operating exposure to exchange rates:a conceptual. Financial Management,1986,15(1):25-36
[55]Shapiro A C. Exchange rate changes, inflation, and the value of the multinational Corporation. Journal of Finance,1975, (5):485-502
[56]幸惊,揭水利.运用外汇风险管理工具防范外汇风险.企业经济,2005,294(2)：153-154
[57]张毅娜.基于TOPSIS优选法和灰色关联度法的房地产项目投资决策研究：[西安建筑科技大学].西安：西安建筑科技大学,2008,25-32
[58]Joao R F, Andre V M, Pedro H A. The effect of oil price on China's exports. China Economic Review, Available online 18 April 2009
[59]田春荣.1999年我国石油进出口状况分析.国际石油经济,2000,(3)：5-9
[60]Papapetrou E. Oil price shocks, stock market, economic activity and employment in Greece. Energy Economics,2001,23(3):511-532
[61]中国银行业监督管理委员会.商业银行市场风险管理指引.http://www.China court.org/flwk/showl.php?file_id=98798,2004-12-29
[62]Hamilton J D. Oil and the macroeconomy since World War Ⅱ. Journal of Political Economy,1983,91(2):228-248
[63]Huang R D, Masulis R W, Stoll H R. Energy shocks and financial markets. Journal of Futures Markets,1996,16(1):1-27
[64]Jones C M, Kaul G. Oil and the stock markets. The Journal of Finance,1996,51(2): 463-491
[65]黄赜琳,国际石油价格波动对我国经济的影响及对策,经济纵横,2006,(3)：5-8
[66]Perry S, Assessing the impact of oil prices on firms of different sizes:Its tough being in the middle, Energy Policy,2008,36(10):3854-3861
[67]EI-Sharif I, Brown D, Burton B. Evidence on the nature and extent of the relationship between oil prices and equity values in the UK. Energy Economics, 2005,27(6),819-830
[68]张鼎祖.企业价值评估的市场法研究：[中南大学硕士论文].长沙：中南大学商学院,2005,24-29
[69]高绯.EVA在企业价值评估中的应用研究：[上海师范大学硕士论文].上海：上海师范大学,2008,17-25
[70]Thomas E C, Fred W. Financial Theory and Corporate Policy. London:Prentice Hall,1998
[71]肖明.企业价值估计的理论研究与实证分析：[北京科技大学博士论文].北京：北京科技大学,2006,5-14
[72]王荣.高新技术企业的价值评估方法在烽火通信公司价值评估的应用研究：[吉林大学硕士论文].长春：吉林大学,2005,19-26
[73]谷峰.企业并购中目标企业的价值评估.北方经贸,2006,206(6)：19-20
[74]肖翔.高新技术企业价值评估方法研究.数量经济技术经济研究,2003,22(2)：61-64
[75]李永红.基于EVAN念的企业价值管理体系再造.科学管理研究,2005,23(1)：114-116
[76]Schueler A, Krotter S. The link between residual income and value created for levered firms:A note. Management Accounting Research,2008,19(4):270-277
[77]刘蓬川.对完善我国风险投资机制的思考.投资分析,2007,498(9)：176-177
[78]范丽斌.基于实物期权的高科技企业价值评估研究：[江苏大学硕士论文].镇江：江苏大学,2008,17-20
[79]Dechow P M, Hutton A, Sloan R. An empirical assessment of the residual income valuation model. Journal of Accounting and Economics,1999,26(1):1-34
[80]Feltham G A, Ohlson J A. Valuation and clean surplus accounting for operating and financial activities. Contemporary Accounting Research,1995,11(2):689-731
[81]Magni C A. Splitting up value:A critical review of residual income theories. European Journal of Operational Research,2009,192(3):1-22
[82]Ohlson J A. On accounting-based valuation formulas. Review of Accounting Studies,2005,10(1):67-81
[83]陈懿华.利用财务信息评估企业价值——RIR模型的实证研究：[贵州大学硕士论文].贵阳：贵州大学,2007,23-27
[84]Patricia M D, Amy P H, Richard G S. An empirical assessment of the residual income valuation model. Journal of Accounting and Economics,1999,26(1):1-34
[85]Schueler A, Krotter S. The link between residual income and value created for levered firms:A note. Management Accounting Research,2008,19(4):270-277
[86]Carlo A M. Splitting up value:A critical review of residual income theories. European Journal of Operational Research,2009,198(1):1-22
[87]Shawkat H, Sel D, Eisa A. Relationships among U.S. oil prices and oil industry equity indices. International Review of Economics & Finance,2004,13(4):427-453
[88]Ewing B T, Thompson M A. Dynamic cyclical co-movements of oil prices with industrial production, consumer prices, unemployment, and stock prices. Energy Policy,2007,35(4):5535-5540
[89]Park J, Ratti R A. Oil price shocks and stock markets in the US and 13 European countries. Energy Economics,2008,30(5):2587-2608
[90]Rong G C, Yi M W, Jian L J et al. Relationships between oil price shocks and stock market:An empirical analysis from China. Energy Policy,2008,36(9):3544-3553
[91]Yue J Z, Ying F, Hsien T T et al. Spillover effect of US dollar exchange rate on oil prices. Journal of Policy Modeling,2008,30(6):973-991
[92]余乐安,汪寿阳,黎建强.外汇汇率与国际原油价格波动预测——TEI@I方法论.长沙：湖南大学出版社,2006：67-81
[93]黄运成,李畅,马卫锋.中国石油价格风险管理的困境与选择.世界经济研究,2005,10(1)：22-26
[94]中华人民共和国国家统计局.中国统计年鉴——2008.北京：中国统计出版社,2008
[95]程伟力.影响国际石油价格因素的定量分析.国际石油经济,2005,8(1)：40-43
[96]黄海峰,高农农.调整产业结构,开创环保新路.环境保护,2009,422(12)：23-24
[97]刘仲元.借力燃料油期货规避石油风险.财经界,2004,25(10)：38-40
[98]上海社科院中国国际地位报告课题组.论中国的石油安全问题.石油化工技术经济,2004,20(3)：7-11
[99]刘晓梅.探索新能源的利用——秸秆发电.安徽电气工程职业技术学院学报,2006,11(4)：61-63
[100]何晓群,魏涛远.世界石油价格上涨对我国经济的影响.经济理论与经济管理,2002,11(4)：11-15
[101]任东明,曹静.论中国可再生能源发展机制.中国人口·资源与环境,2003,13(5)：16-19
[102]闵劲华.关于政府推行强制性节能采购的现实思考.中国政府采购,2008,58(12)：76-78
[103]王宁.应对金融危机,优化产业结构.财会研究,2009,47(11)：73-74
[104]杜占元.科技创新是新型工业化的动力源泉.中国科技产业,2004,12(1)：27-31
[105]黄范章.国际金融危机与宏观经济政策的国际合作.对外经贸实务,2009,24(7)：4-8
[106]李惠茹.欧、美、日的环保探索之路.环境保护,2009,56(12)：34-35
[107]马茁卉,黄凤文,马立新.应对能源安全挑战,构建能源安全体系.中国国土资源经济,2007,20(6)：14-17
[108]徐青.西方企业价值评估方法研究综述.现代管理科学,2005,(7)：61-62
[109]马学亮.金融学前沿译丛总序.北京：中国人民大学出版社,2002
[110]Lux T, Marchesi M. Volatility clustering in financial markets:a micro-simulation of interacting agents. International Journal of Theoretical and Applied Finance, 2000,3(1):675-702
[111]Shefrin H, Meir S. Behavioral portfolio theory. Journal of Finance and Quantitative Analysis,2000,35(2):127-151
[112]Fama E F. The behavior of stock markets prices. Journal of Business,1965,38(1): 34-105
[113]Scheinkman J A, LeBaron B. Nonlinear dynamics and stock returns. Business, 1989,62(3):11-37
[114]谢赤,熊一鹏.深圳股票市场多标度分形特征分析.财经理论与实践,2005,26(133)：53-55
[115]Paul D G, Marianna G. Exchange rate puzzles:a tale of switching attractors. European Economic Review,2006,50(1):1-33
[116]Ramesh G. Accounting based valuation models and security prices in India:An Empirical Assessment. The Business Review,2007,10(1):58-67
[117]Granger C W, Newman H. Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns. Journal of Empirical Finance, 2004,11(1):399-421
[118]Panas E. Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange. Applied Financial Economics,2001,11(2):395-402
[119]Iori G. A microsimulation of traders activity in the stock market:the role of heterogeneity, agents'interactions and trade frictions. Journal of Economic Behavior and Organization,2002,49(2):269-285
[120]Mike K P. Long-term memory in stock market volatility. Applied Financial Economics,2000,10(1):519-524
[121]Bacry E, Delour J, Muzy J F. Modeling financial time series using multifractal random walks. Physica A,2001,299(1):84-92
[122]Mulligan R F. Fractal analysis of highly volatile markets:an application to technology equities. The Quarterly Review of Economics and Finance,2004, 44(3):155-179
[123]Strozzi F, Zaldivar J M. Non-linear forecasting in high-frequency financial time series. Physica A,2005,353(2):463-479
[124]Kenya A, Alvaro V, Elton C. Using artificial neural networks to forecast chaotic time series. Physica A,2000,284(9):393-404
[125]Timo T, Dick D, Marcelo C. Linear models, smooth transition auto regressions, and neural networks for forecasting macroeconomic time series:A re-examination. International Journal of Forecasting,2005,21(1):755-774
[126]Ping F P, Chih S. L. A hybrid ARIMA and support fine machines model in stock price forecasting. Omega,2005,33(6):497-505
[127]杨一文,杨朝军.基于支持向量机的金融时间序列预测.系统工程理论方法应用,2005,14(2)：176-181
[128]George S A, Kimon P V. Surveying stock market forecasting techniques Part Ⅱ: Soft computing methods. Expert Systems with Applications,2009,36(3):5932-5941
[129]Hulisi O, Mete D, Ramazan A. Detecting stock-price manipulation in an emerging market:The case of Turkey. Expert Systems with Applications,2009,36(9): 11944-11949
[130]陈佐,谢赤,陈晖.基于小波聚类方法的股票收益率序列时间模式挖掘.系统工程,2005,23(11)：102-107
[131]谭华,谢赤,罗长青,江洲.基于模糊粗糙集挖掘方法的证券价格预测研究.运筹与管理,2008,17(4)：118-123
[132]祝金荣.基于支持向量机的石油期货价格预测.工业技术经济,2007,26(2)：59-61
[133]杜贤利,姚洪兴.基于LS-MWSVM的股票价格预测.统计与决策,2008,19(1)：62-64
[134]罗福来.人民币汇率的混沌特征分析及其基于支持向量机的预测：[湖南大学硕士论文].长沙：湖南大学,2008,57-62
[135]Shuheng C. Testing for non-linear structure in an artificial financial market. Journal of Economic Behavior & Organization,2001,46(3):327-342
[136]Wei H, Yoshiteru N, Shou-Yang W. Forecasting stock market movement direction with support vector machine. Computers & Operations Research,2005,32(10): 2513-2522
[137]Jiao R L, Wei X, Wenxian X, Zheng Z R. Research on nonlinear stochastic dynamical price model. Chaos, Solitons and Fractals,2006,42(7):1381-1393
[138]肖智,陈婷婷.基于支持向量机的外贸出口预测.科技管理研究,2006,7(1)：231-231
[139]Hyun J K, Kyung S S. A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets. Applied Soft Computing,2007,7(2):569-576
[140]Kyoung J K. Financial time series forecasting using support vector machines. Neurocomputing,2003,55(1):307-319
[141]姜明辉,袁绪川.基于Logistic回归和后验概率SVM的住房贷款组合评估模型.黑龙江大学自然科学学报,2008,25(3)：281-286
[142]李海生,钟震宇,张严林.基于最小二乘支持向量机的预测控制.计算技术与自动化,2009,28(1)：32-36
[143]Valeriy V G, Supriya B G. Volatility forecasting from multiscale and high-dimensional market data. Neurocomputing,2003,55(1):285-305
[144]Kyoung J K. Financial time series forecasting using support vector machines. Neurocomputing,2003,55(1):307-319
[145]Kim H, Shin K. A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets. Applied Soft Computing,2007,7(2):569-576
[146]Qing H W, Ze H Y, Yi X S et al. Automatic stock decision support system based on box theory and SVM algorithm. Expert Systems with Applications, In Press, Corrected Proof, Available online 8 June 2009
[147]Viviana F. Wavelet and SVM-based forecasts:An analysis of the U.S. metal and materials manufacturing industry. Resources Policy,2007,32(1):80-89
[148]Cao S G, Liu Y B, Wang Y P. A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM. Journal of China University of Mining & Technology,2008,18(1):172-176
[149]Jian C S, Chong X Z, Ya T Z et al. Nonlinear noise reduction of chaotic time series based on multidimensional recurrent LS-SVM. Neuro-computing,2008, 71(16):3675-3679
[150]张勇,郑建国.基于遗传支持矢量机的股市预测.中国管理信息化,2008,11(10)：45-46
[151]Keerthi S, Lin C. Asymptotic behaviors of support fine machines with Gaussian kernel. Neural Computation,2003,15(7):1667-1689
[152]高铁梅,王金明,吴桂珍.计量经济分析方法与建模：Eviews应用及实例.北京：清华大学出版社,2006
[153]谢非,陈利军,秦建成.人民币汇率变动视角下我国商业银行的汇率风险管理.重庆理工大学学报,2010,24(3)：50-58
[154]朱贺.构筑汇率风险预警机制必要性及框架分析.开发研究,2009,(4)：96-99
[155]Logue D E.When theory fails:Globalization as a response to the market for foreign exchange. Journal of Applied Corporate Finance.1995,8(3):39-48
[156]Chowdhry B, Howe J. Corporate risk management for multinational corporations: financial and operating hedging policies. European Financial Review,1999,2(2): 229-246
[157]Allayannis G, Ihrig J, Weston J P. Exchange-Rate hedging:financial versus operational strategies. The Ametican Eeonomic Review.2001,91(2):391-395.
[158]赵子丰.企业全面风险管理体系的建立与实施策略.中国管理信息化,2010,13(21)：49-52
[159]高志强,张梦琳.全面风险管理体系中的风险整合问题.系统工程理论与实践,2009,29(12)：73-79
[160]徐辉,商业银行信贷风险识别及其模糊测度.工业技术经济,2007,26(4)：132-135
[161]曾忠禄,张冬梅.不确定环境下解读未来的方法：情景分析法.情报方法,2005,(5)：14-16
[162]花俊洲.金融市场风险度量方法研究.生产力研究,2007,(17)：30-35
[163]吴秋南.管理石油价格风险.国际石油经济,2001,8(1)：28-31
[2]钱莉,雷欣欣,刘珉璐.企业价值评估方法的对比研究.商业研究,2008,24(1)：56-57
[3]张人骥,刘浩,胡晓斌.充分利用会计信息的企业价值评估模型——RIR模型的建立与应用.财经研究,2002,28(7)：68-74
[4]Vapnik V N. The Nature of Statistical Learning Theory. New York:Springer Verlag, 1995
[5]Fisher I. The nature of capital and income. New York:The Macmillan Company, 1906
[6]Miller M, Modigliani F. Dividend policy, growth and the valuation of shares. Journal of Business,1961,10(1):411-433
[7]Ohlson J A. Book values and dividends in equity valuation. Contemporary Accounting Research,1995,11(2):661-687
[8]Bernard V L. The Feltham-Ohlson framework:implications for empiricists. Contemporary Accounting Research,1995,11(2):733-747
[9]Frankel R, Charles M C. Accounting valuation, market expectation and cross-sectional stock returns. The Journal of Accounting and Economics,1998,25(1): 283-319
[10]田志龙,李玉清.一种基于账面价值和未来收益的公司财富评估方法.会计研究,1997,5(1)：47-49
[11]陆宇峰.净资产倍率和市盈率的投资决策有用性——基于“费森—奥尔森估值模型”的实证研究：[上海财经大学博士论文].上海：上海财经大学,1999,34-41
[12]陈信元,陈冬华,朱红军等.净资产、剩余收益与市场定价：会计信息的价值相关性.金融研究,2002,4(1)：59-70
[13]欧阳励励.剩余收益模型在我国价值评估中的应用研究.财会通讯,2008,5(1)：62-66
[14]谢赤,王雅瑜,孙柏.外汇风险度量：方法与评述.金融经济(理论版),2007,11(2)：134-136
[15]陆茹.我国企业外汇风险管理研究：[南京理工大学硕士论文].南京：南京理工大学,2002,27-35
[16]韩晓亚.浮动汇率条件下国内企业外汇风险防范机制研究：[吉林大学硕士论文].长春：吉林大学,2007,39-42
[17]黄赜琳.国际石油价格波动对我国经济的影响及对策.经济纵横,2006,18(3)：5-8
[18]Engle R F, Granger C J. Co-integration and error correction:representation estimation and testing. Econometrics,1987,55(2):251-277
[19]Engle R F, Granger C J, Hallman J J. Merging short-and long-run forecasts:An application of seasonal cointegration to monthly electricity sales forecasting. Journal of Econometrics,1989,40(1):45-62
[20]Johansen S. Statistical analysis of co-integrating vectors. Journal of Economic Dynamics and Control,1988,12(1):231-254
[21]Wei H, Yoshiteru N, Shou-Yang W. Forecasting stock market movement direction with support fine machine. Computers & Operations Research,2005,32(10): 2513-2522
[22]Viviana F. Wavelet and SVM-based forecasts:An analysis of the U. S. metal and materials manufacturing industry. Resources Policy,2007,32(1):80-89
[23]Modigliani F, Miller M H. Corporation income taxes and the cost of capital:a correction. The American Economic Review,1963,53(3):433-443
[24]Fama E F. Agency problems and the theory of the firm. Journal of Political Economy,1980,88(2):288-307
[25]Black F, Scholes M S. The Pricing of Options and Corporate Liabilities, Journal of Political Economy,1973,81(3):637-654
[26]Miller M H, Modigliani F. Dividend policy, growth, and the valuation of shares. Journal of Business,1961,34(4):411-433
[27]鲜文铎,贺琴.企业价值影响因素浅析.财会月刊,2005,(11)：77-78
[28]李敬,陈收.企业战略管理.湖南：湖南大学出版社,50-64
[29]陈远志,梁彤缨.行业特征、股权结构与公司绩效的实证分析,系统工程,2006,24(2)：72-80
[30]Porter M E. The structure within industries and companies'performance. Review of Economics & Statistics,1979,61(2):214-227
[31]Schwartz E. Theory of the capital structure of the firm. The Journal of Finance, 1959,14(1):18-39
[32]Francesco L, Rosa A S. A comparison between neural networks and chaotic models for exchange rate prediction. Computational Statistics & Data Analysis, 1999,30(1):87-102
[33]谢赤,杨妮.汇率行为的混沌性及其分形维描述.湖南大学学报(社会科学版),2005,19(5)：50-56
[34]Xie Chi, Yang Ni. Analysis and empirical research on the long-memory property of exchange rate time series. In:Wireless Communications, Networking and Mobile Computing 2007(WiCom 2007),2007,8:5906-5909
[35]杨妮,谢赤,孙柏.汇率时间序列多重分形特征分析及实证研究.湖南大学学报(自然科学版),2008,35(8)：89-92
[36]谢赤,杨妮,孙柏.汇率时间序列非线性特征分析及实证研究.系统工程,2008,26(11)：98-102
[37]Johnson N F, Jefferies P, Ming H P. Financial market complexity. Oxford:Oxford University Press,2003:78-84
[38]陈伟,王伟.我国跨国公司汇率风险的计量与实证分析.河南金融管理干部学院学报,2006,14(3)：70-74
[39]Chow L, Solt E. The exchange rate risk exposure of asset returns. Journal of Business,1997, (1):105-123
[40]Taylor J B. Low inflation, pass-through, and the pricing power of firms. European Economic Review,2000,44(7):1389-1408
[41]Krugman P. The narrow moving band, the Dutch disease, and the competitive consequences of Mrs. Thatcher:Notes on trade in the presence of dynamic scale economies. Journal of Development Economics,1987,27(1-2):41-55
[42]Menon J. Exchange rate pass-through. Journal of Economic Surveys,1995,9(2): 197-231
[43]Campa J M, Goldberg L S. Exchange rate pass-through into import prices. The Review of Economics and Statistics, MIT Press,2005,87(4):679-690
[44]Feenstra R C, Gagnon J E, Knetter M M. Market share and exchange rate pass-through in world automobile trade. Journal of international Economics,1996, 40(1-2):187-207
[45]Dornbusch R. Exchange rates and prices. American Economic Review,1987,77(1): 93-106
[46]Hooper P, Mann C L. Exchange rate pass-through in the 1980s:the case of US imports of manufactures. Brookings Papers on Economic Activity,1989,1989(1): 297-337
[47]Goldberg L S, Campa J M. Distribution margins, import input and the sensitivity exchange rates. Federal Reserve Bank of New York Staff Reports,2006
[48]朱路,于李娜.有效汇率波动对国内价格的传递效应研究.世界经济研究,2008,(6)：3842
[49]陈六傅,刘厚俊.人民币汇率的价格传递效应.金融研究,2007,(4)：1-13
[50]Sohnke M B. Corporate cash flow and stock price exposures to foreign exchange rate risk. Journal of Corporate Finance,2007,13(5):981-994
[51]Hoa N, Robert F, Andrew M. Exchange rate exposure, foreign currency derivatives and the introduction of the euro:French evidence. International Review of Economics & Finance,2007,16(4):563-577
[52]Elaine H, Anthony O. Firm-level exchange rate exposure in the Euro zone. International Business Review, In Press, Corrected Proof, Available online 9 April 2009
[53]Hekman A. Financial model of foreign exchange exposure. Journal of International Business Studies,1985,16(1):83-99
[54]Flood E J, Donald R. L. On the measurement of operating exposure to exchange rates:a conceptual. Financial Management,1986,15(1):25-36
[55]Shapiro A C. Exchange rate changes, inflation, and the value of the multinational Corporation. Journal of Finance,1975, (5):485-502
[56]幸惊,揭水利.运用外汇风险管理工具防范外汇风险.企业经济,2005,294(2)：153-154
[57]张毅娜.基于TOPSIS优选法和灰色关联度法的房地产项目投资决策研究：[西安建筑科技大学].西安：西安建筑科技大学,2008,25-32
[58]Joao R F, Andre V M, Pedro H A. The effect of oil price on China's exports. China Economic Review, Available online 18 April 2009
[59]田春荣.1999年我国石油进出口状况分析.国际石油经济,2000,(3)：5-9
[60]Papapetrou E. Oil price shocks, stock market, economic activity and employment in Greece. Energy Economics,2001,23(3):511-532
[61]中国银行业监督管理委员会.商业银行市场风险管理指引.http://www.China court.org/flwk/showl.php?file_id=98798,2004-12-29
[62]Hamilton J D. Oil and the macroeconomy since World War Ⅱ. Journal of Political Economy,1983,91(2):228-248
[63]Huang R D, Masulis R W, Stoll H R. Energy shocks and financial markets. Journal of Futures Markets,1996,16(1):1-27
[64]Jones C M, Kaul G. Oil and the stock markets. The Journal of Finance,1996,51(2): 463-491
[65]黄赜琳,国际石油价格波动对我国经济的影响及对策,经济纵横,2006,(3)：5-8
[66]Perry S, Assessing the impact of oil prices on firms of different sizes:Its tough being in the middle, Energy Policy,2008,36(10):3854-3861
[67]EI-Sharif I, Brown D, Burton B. Evidence on the nature and extent of the relationship between oil prices and equity values in the UK. Energy Economics, 2005,27(6),819-830
[68]张鼎祖.企业价值评估的市场法研究：[中南大学硕士论文].长沙：中南大学商学院,2005,24-29
[69]高绯.EVA在企业价值评估中的应用研究：[上海师范大学硕士论文].上海：上海师范大学,2008,17-25
[70]Thomas E C, Fred W. Financial Theory and Corporate Policy. London:Prentice Hall,1998
[71]肖明.企业价值估计的理论研究与实证分析：[北京科技大学博士论文].北京：北京科技大学,2006,5-14
[72]王荣.高新技术企业的价值评估方法在烽火通信公司价值评估的应用研究：[吉林大学硕士论文].长春：吉林大学,2005,19-26
[73]谷峰.企业并购中目标企业的价值评估.北方经贸,2006,206(6)：19-20
[74]肖翔.高新技术企业价值评估方法研究.数量经济技术经济研究,2003,22(2)：61-64
[75]李永红.基于EVAN念的企业价值管理体系再造.科学管理研究,2005,23(1)：114-116
[76]Schueler A, Krotter S. The link between residual income and value created for levered firms:A note. Management Accounting Research,2008,19(4):270-277
[77]刘蓬川.对完善我国风险投资机制的思考.投资分析,2007,498(9)：176-177
[78]范丽斌.基于实物期权的高科技企业价值评估研究：[江苏大学硕士论文].镇江：江苏大学,2008,17-20
[79]Dechow P M, Hutton A, Sloan R. An empirical assessment of the residual income valuation model. Journal of Accounting and Economics,1999,26(1):1-34
[80]Feltham G A, Ohlson J A. Valuation and clean surplus accounting for operating and financial activities. Contemporary Accounting Research,1995,11(2):689-731
[81]Magni C A. Splitting up value:A critical review of residual income theories. European Journal of Operational Research,2009,192(3):1-22
[82]Ohlson J A. On accounting-based valuation formulas. Review of Accounting Studies,2005,10(1):67-81
[83]陈懿华.利用财务信息评估企业价值——RIR模型的实证研究：[贵州大学硕士论文].贵阳：贵州大学,2007,23-27
[84]Patricia M D, Amy P H, Richard G S. An empirical assessment of the residual income valuation model. Journal of Accounting and Economics,1999,26(1):1-34
[85]Schueler A, Krotter S. The link between residual income and value created for levered firms:A note. Management Accounting Research,2008,19(4):270-277
[86]Carlo A M. Splitting up value:A critical review of residual income theories. European Journal of Operational Research,2009,198(1):1-22
[87]Shawkat H, Sel D, Eisa A. Relationships among U.S. oil prices and oil industry equity indices. International Review of Economics & Finance,2004,13(4):427-453
[88]Ewing B T, Thompson M A. Dynamic cyclical co-movements of oil prices with industrial production, consumer prices, unemployment, and stock prices. Energy Policy,2007,35(4):5535-5540
[89]Park J, Ratti R A. Oil price shocks and stock markets in the US and 13 European countries. Energy Economics,2008,30(5):2587-2608
[90]Rong G C, Yi M W, Jian L J et al. Relationships between oil price shocks and stock market:An empirical analysis from China. Energy Policy,2008,36(9):3544-3553
[91]Yue J Z, Ying F, Hsien T T et al. Spillover effect of US dollar exchange rate on oil prices. Journal of Policy Modeling,2008,30(6):973-991
[92]余乐安,汪寿阳,黎建强.外汇汇率与国际原油价格波动预测——TEI@I方法论.长沙：湖南大学出版社,2006：67-81
[93]黄运成,李畅,马卫锋.中国石油价格风险管理的困境与选择.世界经济研究,2005,10(1)：22-26
[94]中华人民共和国国家统计局.中国统计年鉴——2008.北京：中国统计出版社,2008
[95]程伟力.影响国际石油价格因素的定量分析.国际石油经济,2005,8(1)：40-43
[96]黄海峰,高农农.调整产业结构,开创环保新路.环境保护,2009,422(12)：23-24
[97]刘仲元.借力燃料油期货规避石油风险.财经界,2004,25(10)：38-40
[98]上海社科院中国国际地位报告课题组.论中国的石油安全问题.石油化工技术经济,2004,20(3)：7-11
[99]刘晓梅.探索新能源的利用——秸秆发电.安徽电气工程职业技术学院学报,2006,11(4)：61-63
[100]何晓群,魏涛远.世界石油价格上涨对我国经济的影响.经济理论与经济管理,2002,11(4)：11-15
[101]任东明,曹静.论中国可再生能源发展机制.中国人口·资源与环境,2003,13(5)：16-19
[102]闵劲华.关于政府推行强制性节能采购的现实思考.中国政府采购,2008,58(12)：76-78
[103]王宁.应对金融危机,优化产业结构.财会研究,2009,47(11)：73-74
[104]杜占元.科技创新是新型工业化的动力源泉.中国科技产业,2004,12(1)：27-31
[105]黄范章.国际金融危机与宏观经济政策的国际合作.对外经贸实务,2009,24(7)：4-8
[106]李惠茹.欧、美、日的环保探索之路.环境保护,2009,56(12)：34-35
[107]马茁卉,黄凤文,马立新.应对能源安全挑战,构建能源安全体系.中国国土资源经济,2007,20(6)：14-17
[108]徐青.西方企业价值评估方法研究综述.现代管理科学,2005,(7)：61-62
[109]马学亮.金融学前沿译丛总序.北京：中国人民大学出版社,2002
[110]Lux T, Marchesi M. Volatility clustering in financial markets:a micro-simulation of interacting agents. International Journal of Theoretical and Applied Finance, 2000,3(1):675-702
[111]Shefrin H, Meir S. Behavioral portfolio theory. Journal of Finance and Quantitative Analysis,2000,35(2):127-151
[112]Fama E F. The behavior of stock markets prices. Journal of Business,1965,38(1): 34-105
[113]Scheinkman J A, LeBaron B. Nonlinear dynamics and stock returns. Business, 1989,62(3):11-37
[114]谢赤,熊一鹏.深圳股票市场多标度分形特征分析.财经理论与实践,2005,26(133)：53-55
[115]Paul D G, Marianna G. Exchange rate puzzles:a tale of switching attractors. European Economic Review,2006,50(1):1-33
[116]Ramesh G. Accounting based valuation models and security prices in India:An Empirical Assessment. The Business Review,2007,10(1):58-67
[117]Granger C W, Newman H. Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns. Journal of Empirical Finance, 2004,11(1):399-421
[118]Panas E. Estimating fractal dimension using stable distributions and exploring long memory through ARFIMA models in Athens Stock Exchange. Applied Financial Economics,2001,11(2):395-402
[119]Iori G. A microsimulation of traders activity in the stock market:the role of heterogeneity, agents'interactions and trade frictions. Journal of Economic Behavior and Organization,2002,49(2):269-285
[120]Mike K P. Long-term memory in stock market volatility. Applied Financial Economics,2000,10(1):519-524
[121]Bacry E, Delour J, Muzy J F. Modeling financial time series using multifractal random walks. Physica A,2001,299(1):84-92
[122]Mulligan R F. Fractal analysis of highly volatile markets:an application to technology equities. The Quarterly Review of Economics and Finance,2004, 44(3):155-179
[123]Strozzi F, Zaldivar J M. Non-linear forecasting in high-frequency financial time series. Physica A,2005,353(2):463-479
[124]Kenya A, Alvaro V, Elton C. Using artificial neural networks to forecast chaotic time series. Physica A,2000,284(9):393-404
[125]Timo T, Dick D, Marcelo C. Linear models, smooth transition auto regressions, and neural networks for forecasting macroeconomic time series:A re-examination. International Journal of Forecasting,2005,21(1):755-774
[126]Ping F P, Chih S. L. A hybrid ARIMA and support fine machines model in stock price forecasting. Omega,2005,33(6):497-505
[127]杨一文,杨朝军.基于支持向量机的金融时间序列预测.系统工程理论方法应用,2005,14(2)：176-181
[128]George S A, Kimon P V. Surveying stock market forecasting techniques Part Ⅱ: Soft computing methods. Expert Systems with Applications,2009,36(3):5932-5941
[129]Hulisi O, Mete D, Ramazan A. Detecting stock-price manipulation in an emerging market:The case of Turkey. Expert Systems with Applications,2009,36(9): 11944-11949
[130]陈佐,谢赤,陈晖.基于小波聚类方法的股票收益率序列时间模式挖掘.系统工程,2005,23(11)：102-107
[131]谭华,谢赤,罗长青,江洲.基于模糊粗糙集挖掘方法的证券价格预测研究.运筹与管理,2008,17(4)：118-123
[132]祝金荣.基于支持向量机的石油期货价格预测.工业技术经济,2007,26(2)：59-61
[133]杜贤利,姚洪兴.基于LS-MWSVM的股票价格预测.统计与决策,2008,19(1)：62-64
[134]罗福来.人民币汇率的混沌特征分析及其基于支持向量机的预测：[湖南大学硕士论文].长沙：湖南大学,2008,57-62
[135]Shuheng C. Testing for non-linear structure in an artificial financial market. Journal of Economic Behavior & Organization,2001,46(3):327-342
[136]Wei H, Yoshiteru N, Shou-Yang W. Forecasting stock market movement direction with support vector machine. Computers & Operations Research,2005,32(10): 2513-2522
[137]Jiao R L, Wei X, Wenxian X, Zheng Z R. Research on nonlinear stochastic dynamical price model. Chaos, Solitons and Fractals,2006,42(7):1381-1393
[138]肖智,陈婷婷.基于支持向量机的外贸出口预测.科技管理研究,2006,7(1)：231-231
[139]Hyun J K, Kyung S S. A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets. Applied Soft Computing,2007,7(2):569-576
[140]Kyoung J K. Financial time series forecasting using support vector machines. Neurocomputing,2003,55(1):307-319
[141]姜明辉,袁绪川.基于Logistic回归和后验概率SVM的住房贷款组合评估模型.黑龙江大学自然科学学报,2008,25(3)：281-286
[142]李海生,钟震宇,张严林.基于最小二乘支持向量机的预测控制.计算技术与自动化,2009,28(1)：32-36
[143]Valeriy V G, Supriya B G. Volatility forecasting from multiscale and high-dimensional market data. Neurocomputing,2003,55(1):285-305
[144]Kyoung J K. Financial time series forecasting using support vector machines. Neurocomputing,2003,55(1):307-319
[145]Kim H, Shin K. A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets. Applied Soft Computing,2007,7(2):569-576
[146]Qing H W, Ze H Y, Yi X S et al. Automatic stock decision support system based on box theory and SVM algorithm. Expert Systems with Applications, In Press, Corrected Proof, Available online 8 June 2009
[147]Viviana F. Wavelet and SVM-based forecasts:An analysis of the U.S. metal and materials manufacturing industry. Resources Policy,2007,32(1):80-89
[148]Cao S G, Liu Y B, Wang Y P. A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM. Journal of China University of Mining & Technology,2008,18(1):172-176
[149]Jian C S, Chong X Z, Ya T Z et al. Nonlinear noise reduction of chaotic time series based on multidimensional recurrent LS-SVM. Neuro-computing,2008, 71(16):3675-3679
[150]张勇,郑建国.基于遗传支持矢量机的股市预测.中国管理信息化,2008,11(10)：45-46
[151]Keerthi S, Lin C. Asymptotic behaviors of support fine machines with Gaussian kernel. Neural Computation,2003,15(7):1667-1689
[152]高铁梅,王金明,吴桂珍.计量经济分析方法与建模：Eviews应用及实例.北京：清华大学出版社,2006
[153]谢非,陈利军,秦建成.人民币汇率变动视角下我国商业银行的汇率风险管理.重庆理工大学学报,2010,24(3)：50-58
[154]朱贺.构筑汇率风险预警机制必要性及框架分析.开发研究,2009,(4)：96-99
[155]Logue D E.When theory fails:Globalization as a response to the market for foreign exchange. Journal of Applied Corporate Finance.1995,8(3):39-48
[156]Chowdhry B, Howe J. Corporate risk management for multinational corporations: financial and operating hedging policies. European Financial Review,1999,2(2): 229-246
[157]Allayannis G, Ihrig J, Weston J P. Exchange-Rate hedging:financial versus operational strategies. The Ametican Eeonomic Review.2001,91(2):391-395.
[158]赵子丰.企业全面风险管理体系的建立与实施策略.中国管理信息化,2010,13(21)：49-52
[159]高志强,张梦琳.全面风险管理体系中的风险整合问题.系统工程理论与实践,2009,29(12)：73-79
[160]徐辉,商业银行信贷风险识别及其模糊测度.工业技术经济,2007,26(4)：132-135
[161]曾忠禄,张冬梅.不确定环境下解读未来的方法：情景分析法.情报方法,2005,(5)：14-16
[162]花俊洲.金融市场风险度量方法研究.生产力研究,2007,(17)：30-35
[163]吴秋南.管理石油价格风险.国际石油经济,2001,8(1)：28-31
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