模控學於風險評估與管理之跨領域研究準則與詮釋

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研究生：	許劭偉 XU,SHAO-WEI
論文名稱：	模控學於風險評估與管理之跨領域研究準則與詮釋 The principle and interpretation of transdisciplinary researches in risk prediction and management by cybernetics
指導教授：	薛義誠 XUE,YI-CHENG
口試委員:
學位類別：	碩士 Master
系所名稱：	管理學院 - 資訊管理學系 Department of Information Management
論文出版年：	2018
畢業學年度：	106
語文別：	中文
論文頁數：	96
中文關鍵詞：	跨領域、模控學、風險管理、波動度變化
外文關鍵詞：	Transdisciplinarity, Cybernetic, Risk management, Volatility change
相關次數：	點閱：22 下載：0
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跨領域研究被認為是有創造性解決不同領域間見解的重要方向。模控學之因果網路及環路變化具有暫時性、動態性的複雜系統和現實現象的分析和模擬能力，對於微觀和巨觀問題可提出一致且完整的質性和量化的方法，因此本研究將以跨領域研究框架將企業風險於會計理論之微觀分析方法，轉換為財務學中波動度變化和風險關連性巨觀之現象，並歸納實證研究中的不同實證結果，觀察模型中之結構狀態轉換變化來預測企業風險變化。
利用Hsiao et al.（2016）於會計學中的風險觀念建立之因果網路，由會計元素間的系統相關動態變化因果關係可得知風險之變化，並且以美國前500 大公司為實驗對象，分析各迴圈的變化時間、週期以及資金缺口變化率，並將各迴圈分析結果整合，歸納出可能存在的迴圈組合，並說明各模型中的結構狀態與風險變化，再以樹狀圖的方式呈現，其中風險變化共有6 種，分別為風險減少、風險增加、風險先減後增、風險先增後減、風險先減後增再減，及風險增加或減少。藉此企業可以知道，選擇的作為代表了迴圈組合的風險與波動度變化。因此，本研究的貢獻為，一，企業可透過各迴圈的分析結果，選擇適合發展的作為，二，歸納出所有可能發生模型的結構狀態與風險變化，三，以跨領域方法詮釋會計和財務領域中不同結論之爭議。

This study uses the interdisciplinary analysis framework to transform corporate risks into the micro-analysis of accounting theory, and uses interdisciplinary analysis methods to convert into volatility and risk-related dimensions of financial science. The phenomenon, and induction of different empirical results in empirical research, observed changes in the structural state of the model to predict changes in corporate risk.
Hsiao et al. (2016) who establishes a causal network of risk concepts in accounting is used. The system-related dynamic changes between accounting elements can be used to understand the changes in risk, and the top 500 companies in the United States are the experimental subjects to analyze the change time, cycle, and funding gap change rate of each loop, integrate the loop analysis results, summarize the possible loop combinations, and explain the structural status and risk changes in each model, and the way of graphs is
presented so that companies can predict risk changes through changes in the various elements of the company. Therefore, the contributions of this study are: First, companies can select activities suitable for development through the analysis results of the various loops. Second, induction all possible models, and their structural status and risk changes. And third, interpret disputes over different conclusions in the accounting and financial domains in a cross-cutting manner.

摘要 ................................................................................................................................ i
Abstract ........................................................................................................................ ii
誌謝 .............................................................................................................................. iii
目錄 .............................................................................................................................. iv
圖目錄 ......................................................................................................................... vii
表目錄 .......................................................................................................................... ix
數學公式符號對照表 ................................................................................................... x
會計暨相關專有名詞中英對照表 .............................................................................. xi
第一章 緒論 ................................................................................................................. 1
1 研究背景 ......................................................................................................... 1
2 研究動機 ......................................................................................................... 2
3 研究目的 ......................................................................................................... 3
4 研究流程 ......................................................................................................... 4
第二章 文獻回顧 ......................................................................................................... 6
1 歷史波動度與隱含波動度 ............................................................................. 6
2 波動度微笑曲線 ............................................................................................. 6
3 波動度不對稱現象 ......................................................................................... 8
4 會計學對風險的概念 ................................................................................... 10
4.1 槓桿效應 ............................................................................................. 11
4.2 營運槓桿 ............................................................................................. 11
4.3 財務槓桿 ............................................................................................. 12
4.4 複合槓桿 ............................................................................................. 13
5 模控學於跨領域研究 ................................................................................... 14
v
5.1 企業風險的因果網絡 ........................................................................ 15
5.2 具有極性和延遲的因果關係 ............................................................ 16
第三章 研究方法 ....................................................................................................... 18
1 實驗架構 ....................................................................................................... 18
2 實驗模型及參數設定 ................................................................................... 19
2.1 模型假設及系統邊界 ........................................................................ 19
2.2 因果網路模型和迴路框架 ................................................................ 20
2.3 五個因果迴圈 .................................................................................... 24
3 實驗一 ........................................................................................................... 25
4 實驗二 ........................................................................................................... 26
第四章 實驗結果 ....................................................................................................... 27
1 實驗設定 ....................................................................................................... 27
1.1 資料來源 ............................................................................................. 27
1.2 資料集 ................................................................................................. 28
2 實驗一結果 ................................................................................................... 28
2.1 資金缺口變化率 ................................................................................. 28
2.2 迴圈一 ................................................................................................. 30
2.3 迴圈二 ................................................................................................. 31
2.4 迴圈三 ................................................................................................. 32
2.5 迴圈四 ................................................................................................. 33
2.6 迴圈五 ................................................................................................. 34
3 實驗二結果 ................................................................................................... 35
3.1 五取一 ................................................................................................. 35
3.2 五取二 ................................................................................................. 36
vi
3.3 五取三 ................................................................................................. 42
3.4 五取四 ................................................................................................. 47
3.5 五取五 ................................................................................................. 49
4 樹狀圖 ............................................................................................................ 51
第五章 結論與建議 ................................................................................................... 54
1 研究結論與貢獻 ........................................................................................... 54
2 研究限制及建議 ........................................................................................... 55
3 未來研究 ....................................................................................................... 56
參考文獻 ..................................................................................................................... 57
附錄一 迴圈時間分析結果 ....................................................................................... 62
                                

Aboura, S., Valeyre, S., Wagner, N.（2014）2014 Option pricing with a dynamic fat-tailed
model. J Derivatives Hedge Funds, 20, 131–155.
Aït-Sahalia, Y., & Lo, A. W（. 1998）. Nonparametric estimation of state-price densities implicit
in financial asset prices. Journal of Finance, 53（2）, 499-547.
Bayer, S.（2004）. Business dynamics: Systems thinking and modeling for a complex world.
Interface, 34, 324–326.
Borland, L., Bouchaud, J.P.（2004）. A non-Gaussian option pricing model with skew. Quant
Finance, 4, 499–514.
Bae, K. H., & Karolyi, G. A. (1994). Good news, bad news and international spillovers of
stock return volatility between Japan and the US. Pacific-Basin Finance Journal, 2(4),
405-438.
Black, F.（1976）. Studies of stock price volatility changes. Proceedings of the 1976 Meetings
of the Business and Economics Statistics Section, 177-181.
Chang, I.J., Lin, B.H.（2010）. Determinants of the implied volatility skew in LIFFE equity
options. Int Res J Finance Econ, 46, 16–31.
Cheung, Y. W., & Ng, L. K.（1992a）. Stock price dynamics and firm size: An empirical
investigation. Journal of Finance, 47（5）, 1985-1997.
Christie, A. A. (1982). The stochastic behavior of common stock variances: Value, leverage
and interest rate effects. Journal of financial Economics, 10(4), 407-432.
Cox, J. C., & Ross, S. A. (1976). The valuation of options for alternative stochastic
processes. Journal of financial economics, 3(1-2), 145-166.
Dennis, P., & Mayhew, S.（2002）. Risk-neutral skewness: Evidence from stock options.
Journal of Financial and Quantitative Analysis, 37（3）, 471-493.
58
Derman, E., & Kani, I.（1994）. Riding on a smile. Risk, 7（2）, 32-39.
Duffee, G. R. (1995). Stock returns and volatility a firm-level analysis. Journal of Financial
Economics, 37(3), 399-420.
Dumas, B., Fleming, J., & Whaley, R. E.（1998）. Implied volatility functions: Empirical tests.
Journal of Finance, 53（6）, 2059-2106.
Dupire, B.（1994）. Pricing with a smile. Risk, 7（1）, 18-20.
Engle, R. F., & Kroner, K. F.（1995）. Multivariate simultaneous generalized ARCH.
Econometric Theory, 11, 122-150.
Figlewski, S., & Wang, X. (2000). Is the'Leverage Effect'a Leverage Effect?.
Forde, M., Jacquier, A., & Lee, R. (2012). The small-time smile and term structure of implied
volatility under the Heston model. SIAM Journal on Financial Mathematics, 3(1),
690-708.
French, K. R., Schwert, G. W., & Stambaugh, R. F.（1987）. Expected stock returns and
volatility. Journal of Financial Economics, 19（1）, 3-29. doi: 10.1016/0304-405X（87）
90026-2
Forrester, J.W.（1980）. Information sources for modeling the national economy. J Am Stat
Assoc 1980, 75, 555–566.
Garc´ıa, S., Luengo, J., S´aez, J. A., L´opez, V., & Herrera, F. (2013). A survey of
discretization techniques : taxonomy and empirical analysis in supervised learning.
IEEE Transactions on Knowledge and Data Engineering, 25, 734-750.
Gupta, A., Mehrotra, K. G., & Mohan, C. (2010). A clustering-based discretization for
supervised learning. Statistics & Probability Letters, 80(9-10), 816-824.
Garcia, R., Renault, É., & Luger, R. (2001). Asymmetric smiles, leverage effects and
structural parameters. CIRANO.
59
Glosten, L. R., Jagannathan, R., & Runkle, D. E.（1993）. On the relation between the
expected value and the volatility of the nominal excess return on stocks. Journal of
Finance, 48（5）, 1779-1801.
Geske, R. (1979). The valuation of compound options. Journal of financial economics, 7(1),
63-81.
Havel, I. M. (2008). Sixty years of cybernetics: cybernetics still alive. Kybernetika, 44(3),
314-327.
Hsiao, C. T., Chang, D. S., & Liu, S. M.（2016）. Complex relationships among firm risk,
asymmetric volatility, volatility skew, and the leverage effect. Complexity, 21（S2）,
329-341.
Hübler, A. W. (2007). Understanding complex systems: Defining an abstract
concept. Complexity, 12(5), 9-11.
Hull, J., & White, A.（1987）. The pricing of options on assets with stochastic volatilities.
Journal of Finance, 42（2）, 281-300.
Jones, C.S.（2003）. The dynamics of stochastic volatility: Evidence from underlying and
options markets. J Econom, 116, 181–224.
Jackwerth, J. C., & Rubinstein, M.（1996）. Recovering probability distributions from option
prices. Journal of Finance, 51（5）, 1611-1631.
Kim, M.J., Lee, S.Y., Hwang, D.I., Kim, S.Y., Ko, I.K. （2010）. Dynamics of implied volatility
surfaces from random matrix theory. Phys. A, 389, 2762–2769.
Kou, S. G. (2002). A jump-diffusion model for option pricing. Management science, 48(8),
1086-1101.
Koutmos, G., & Saidi, R. (1995). The leverage effect in individual stocks and the debt to
equity ratio. Journal of Business Finance & Accounting, 22(7), 1063-1075.
60
Li, M., Deng, S., Feng, S., & Fan, J. (2011 ). An effective discretization based on
Class-Attribute Coherence Maximization. Pattern Recognition Letters, 32, 1962–1973.
Nelson, D. B.（1991）. Conditional heteroskedasticity in asset returns: A new approach.
Econometrica, 59（2）, 347-370.
Nissani, M.（1997）. Ten cheers for interdisciplinarity: The case for interdisciplinary
knowledge and research. Social Science Journal, 34（2）, 201-216.
Mandelker, G. N. and S. G. Rhee (1984), “The Impact of the Degrees of Operating and
Financial Leverage On Systematic Risk of Common Stock,” Journal of Financial and
Quantitative Analysis, 45-57.
Rubinstein, M.（1985）. Nonparametric tests of alternative option pricing models using all
reported trades and quotes on the 30 most active CBOE option classes from August 23,
1976 through August 31, 1978. Journal of Finance, 40（2）, 455-480.
Rubinstein, M.（1994）. Implied binomial trees. Journal of Finance, 49（3）, 771-818.
Rubinstein, Mark E. (1973), “A Mean-Variance Synthesis of Corporate Financial Theory,”
Journal of Finance, 167-181.
Ryan, S. G.（1997）. A survey of research relating accounting numbers to systematic equity
risk, with implications for risk disclosure policy and future research. Accounting
Horizons, 11（2）, 85-95.
Schwert, G. W.（1989）. Why does stock market volatility change over time? Journal of
Finance, 44（5）, 1115-1153.
Schwert, G. W.（1990）. Stock volatility and the crash of '87. Review of Financial Studies, 3
（1）, 77-102.
Senge, P. M.（1990）. The fifth discipline : the art and practice of the learning organization.
New York: Doubleday/Currency.
61
Sharpe, William F., J. Lintner, and J. Mossin (1965),“The valuation of risky assets and the
selection of risky investments in stock portfolios and capital budgets,” Review of
Economics and Statistics ,47, 425-442.
Simon, D. P. (1997). Implied volatility asymmetries in treasury bond futures options. Journal
of Futures Markets: Futures, Options, and Other Derivative Products, 17(8), 873-885.
Toft, K. B., & Prucyk, B. (1997). Options on leveraged equity: Theory and empirical
tests. The Journal of Finance, 52(3), 1151-1180.
Vargas, V., Dao, T. L., & Bouchaud, J. P. (2015). Skew and implied leverage effect: smile
dynamics revisited. International Journal of Theoretical and Applied Finance, 18(04),
1550022.
Wolstenholme, E. F. (2003). Towards the definition and use of a core set of archetypal
structures in system dynamics. System Dynamics Review, 19(1), 7-26.
Zhao, J., Han, C., Wei, B., & Han, D. (2012). A novel Univariate Marginal Distribution
Algorithm based discretization algorithm. Statistics & Probability Letters, 82(11),
2001-2007.
Zhuravlev, Y. I., & Gurevich, I. B. (2010). Sixty years of cybernetics. Pattern recognition and
image analysis, 20(1), 1-20.
劉書銘（2013）以系統動態學討論波動度微笑曲線之研究-以權益選擇權為例。

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