本論文探討台灣債券型基金之風險管理、並檢定其擇時能力與門檻效果。首先，我們使用五個COPULA函數檢驗債券型基金實施分流政策對於風險與收益之影響。接著使用ARMAX-GARCH 模型檢驗債券市場的完整性和債券型基金擇時能力。最後，本文應用門檻自我迴歸模型(Threshold Autoregressive Model) 檢驗台灣債券型基金分流政策前後的基金流量和投資風險之間的門檻效果關係。
    實證結果顯示，在台灣債券型基金之風險管理方面，持有OS＆OP的比例與風險值呈正相關，這意味著OS＆OP是影響債券型基金的絕對關鍵因素，實施債券型基金分流政策後，解決基金市場面臨的流動性危機並降低市場風險值。
    而在擇時能力的實證結果顯示，由於台灣債券市場結構完整性和缺乏流動性，影響到債券經理人認為難以靈活調整投資組合的分配和系統性風險，造成除HM模型外，無論是在TM模型，TM-ARMAX-GARCH模型或HM ARMAX-GARCH模型下，大部分債券型基金均不具備選股能力和顯著的系統性風險及擇時能力。因此，本文建議台灣的債券市場應該開發出更多的投資產品，提高市場的流動性，並擴大基金經理人的操作空間。
    在門檻效果檢定方面，實證顯示債券型基金的投資者只關心的投資回報，而忽略了投資風險。特別是當規模不斷擴大的債券型基金，基金投資者相信該基金穩賺不賠。為了滿足投資者，債券基金經理人追逐短期績效以吸引投資者，而忽略了風險。本文建議投資者應注意風險，而基金經理人除了追求利潤之外，應該去善盡管理風險的專業與義務。

This dissertation discusses an empirical study on the risk management, market timing ability, and threshold effect of bond funds in Taiwan. First, we apply five widely used copula functions to understand the correlation between the OS&OP ratios and the mean return rate of the net value, as well as the VaR of Taiwan’s bond segregation policy. Second, we investigate bond market integrity and market timing ability in Taiwan’s bond market via the ARMAX-GARCH model. Third and finally, this paper constructs the threshold autoregressive model to investigate the relationship between bond funds’ net flows and the investment risk before and after the bond segregation policy.
    From examining the VaR of bond funds in Taiwan, findings show that the OS&OP ratio has a positive correlation with their VaR. This implies that the OS&OP ratio serves as an absolute key factor for bond funds. In fact, after Taiwan’s bond segregation policy in year 2007, investors had to immediately deal with a bond market of scarce liquidity. We thus conclude that the bond fund segregation policy significantly reduced the risk for investing in bond funds. 
   Taking a look at the market timing ability of bond funds in Taiwan, the results show that due to market integrity and the lack of liquidity in Taiwan’s bond market, a bond manager finds it difficult to flexibly adjust for any portfolio allocation and systemic risk. No matter in the T-M model, T-M ARMAX-GARCH model, or H-M ARMAX-GARCH model, this study’s results present that most bond funds do not have selective ability, timing ability, nor significant systemic risk, except for the H-M model. Hence, we recommend that Taiwan’s bond market should develop more investment products, in order to improve liquidity in the market and to enlarge the operating space of bond fund managers.
   For the measurement of the relationship between bond funds’ net flow and the investment risk of bond funds in Taiwan, the findings herein show that bond fund investors are concerned about their investment return while neglecting investment risk. In particular, when a bond fund expands its size, investors believe that the fund cannot lose any money on investment products. In order to satisfy such a belief, bond fund managers only target short-term returns so as to attract more or new investors, while ignoring any risk. Thus, this paper recommends that investors pay attention to risk and that fund managers should fulfill their obligations in addition to the pursuit of profit. Moreover, bond funds should include risk management professionals to help run the funds.

Table of Content                                      Page 
LIST OF TABLES	VII
LIST OF FIGURES	VIII
CHAPTER 1 INTRODUCTION	1
1.1 MOTIVATION	         1
1.2 OBJECTIVES	         6
1.3 THE FLOW CHART	         8
CHAPTER 2 LITERATURE REVIEW	9
2.1 RISK MANAGEMENT	9
2.2 MARKET TIMING ABILITY	11
2.3 THRESHOLD EFFECT	12
CHAPTER 3 METHODOLOGY	14
3.1 DATA RESOURCE	         14
3.2 COPULA MODEL	         15
3.3 ARMAX-GARCH BASED CAPM MODEL	         19
3.4 THE THRESHOLD AUTOREGRESSIVE MODEL	21
CHAPTER 4 EMPIRICAL RESULTS AND ANALYSIS	30
4.1 RISK MANAGEMENT	                  30
4.2 MARKET TIMING ABILITY	                  41
4.3 THE THRESHOLD EFFECT	                  47
CHAPTER 5 CONCLUSION AND REMARKS	         54
5.1 RISK MANAGEMENT	                  55
5.2 MARKET TIMING ABILITY	                  56
5.3 THE THRESHOLD EFFECT	                  57
REFERENCES	                           59
 
LIST OF TABLES
TABLE4.1-1 SUMMARY STATISTICS OF BOND FUNDS - OS&OP, RP, S-CD, AND THE SCALE OF BOND FUND SALES	31
TABLE4.1-2. STUDENT’S PAIR T-TEST RESULTS	         33
TABLE4.1-3. KENDALL’S TAU OF COPULA FUNCTIONS	34
TABL4.1-4. SUMMARY STATISTICS OF VOLATILITY	         37
TABLE 4.1-4.  SUMMARY STATISTICS OF VAR	         39
TABLE 4.1-5.  KENDALL’S TAU OF COPULA FUNCTIONS	40
TABLE4.2-1. SUMMARY STATISTICS OF BOND FUNDS’ PERFORMANCES	                                              42
TABLE4.2-2. THE T-M MODEL AND T-M ARMAX-GARCH MODEL RESULTS	                                              43
TABLE4.3-1. SUMMARY STATISTICS OF BOND FUNDS	         47
TABLE4.3-2. PANEL UNIT ROOT TEST RESULTS	         48
TABLE4.3-3. ESTIMATED COEFFICIENTS OF THE FIXED EFFECT RESULTS	                                             50
TABLE4.3-4. TESTS FOR THE RESULTS OF THE THRESHOLD EFFECTS	                                             50
TABLE4.3-4. THRESHOLD AUTOREGRESSIVE MODEL’S RESULTS 52







LIST OF FIGURES
FIGURE 1.3-1 THE FLOW CHAT	                            8
FIGURE (4.1-1A). VARIATION OF OP&OS RATIO - BEFORE AND AFTER BOND SEGREGATION POLICY	                  32
FIGURE (4.1-1B).  VARIATION OF RP RATIO - BEFORE AND AFTER BOND SEGREGATION POLICY	                           32
FIGURE (4.1-1C). VARIATION OF ST-D - BEFORE AND AFTER BOND SEGREGATION POLICY	                                    32
FIGURE (4.1-1D). VARIATION OF THE SCALE - BEFORE AND AFTER BOND SEGREGATION POLICY	                           32
FIGURE (4.1-1E). OS&OP RATIO VERSUS MEAN RETURN RATE OF BOND FUNDS	                                    35
FIGURE (4.1-1F). P RATIO VERSUS MEAN RETURN RATE OF BOND FUNDS	                                             36
FIGURE (4.1-1G). S -CD RATIO VERSUS MEAN RETURN RATE OF BOND FUNDS	                                    36
FIGURE (4.1-1H). THE SCALE OF BOND FUND SALES VERSUS MEAN RETURN RATE OF BOND FUNDS	                           36
FIGURE (4.1-1I).  HISTORICAL VOLATILITY OF NET VALUE RETURN - BEFORE AND AFTER THE POLICY                  38
FIGURE (4.1-1J).  GARCH VOLATILITY OF NET VALUE RETURN - BEFORE AND AFTER THE POLICY	                           38
FIGURE (4.1-1K).  OS&OP RATIO VERUS VAR_HIS_ALL OF BOND FUNDS	                                             40
FIGURE (4.1-1L).  OS&OP RATIO VERUS VAR_GARCH_ALL OF BOND FUNDS	                                             41

References
Akaike, H. (1974) “A New Look at the Statistical Model Identification” IEEE Transactions on Automatic Control, Vol. 19, No.6, pp.716-723.
Aragon, G. (2005) “Timing Multiple Markets: Theory and Evidence from Balanced Mutual Funds” Unpublished Working Paper, Arizona State University.
Barber, B. M., T. Odean and L. Zheng (2000) “Out of Sight, Out of Mind : The Effects of Expenses on Mutual Fund Flows” Journal of Business Vol. 78, No.6, pp. 2095-2120.
Berk, J. and R. Green (2004) “Mutual Fund Flows and Performance in Rational Markets” Journal of Political Economy, Vol. 112, No. 6, pp.1269-1295.
Blake, C., E. Elton and M. Gruber (1993) “The Performance of Bond Mutual Funds” Journal of Business, Vol. 66, No. 3, pp. 371– 403.
Brown, S., and W. N. Goetzmann (1997) “Mutual Fund Styles” Journal of Financial Economics, Vol.43, No. 3,pp.373-399.
Brown, K., V. Harlow and S. Laura (1996) “Of Tournaments and Temptations: an Analysis of Managerial Incentives in the Mutual Fund Industry” Journal of Finance, Vol.51, No. 1, pp.85-110.
Chan, K. S. (1993) “Consistency and Limiting Distribution of the Least Squares Estimator of a Continuous Threshold Autoregressive Model” The Annals of Statistics, Vol.21, No. 6, pp.520-533.
Chevalier, J. and G. Ellison (1997) “ Risk Taking by Mutual Funds as a Response to Incentives” Journal of Political Economy , Vol.105, No. 6, pp.1167-1200.
Chen, Y, Ferson and H.W. E, Peters (2010) “Measuring the Timing Ability and Performance of Bond Mutual Funds” Journal of Financial Economics , Vol. 98, No. 1, pp. 72-89.
Chiou, S C and R S. Tsay (2008) “ A Copula-Based Approach to Option Pricing and Risk Assessment” Journal of Data Science , Vol. 6, No. 3, pp.273-301.
Davies, R. B. (1977) “ Hypothesis Testing When a Nuisance Parameter is Present Only Under the Alternative” Biometrika ,Vol. 64, No. 2, pp.247-254.
Davies, R. B. (1987) “Hypothesis Testing When a Nuisance Parameter is Present Only Under the Alternative” Biometrika , Vol. 74, No. 2, pp.33-43.
Detzler M. (1999) “The Performance of Global Bond Mutual Funds” Journal of Banking and Finance, Vol. 23, No. 8, pp.1195-217.
Edelen, R. M. (1999) “Investor Flows and The Assessed Performance of Open-End Mutual Funds” Journal of Financial Economics, Vol. 52, No. 1, pp.439-466.
Elton, E J, M J. Gruber and C R. Blake (1995) “Fundamental Economic Variables, Expected Returns, and Bond Fund Performance” Journal of Finance , Vol. 50, No. 4, pp.1229-1256.
Fama, E. F. and J. MacBeth (1973) “Risk, Return and Equilibrium: Empirical Tests” Journal of Political Economy, Vol.81, No. 3, pp.607-636.
Frazzini, A. and O. Lamont (2006) “Dumb Money: Mutual Fund Flows and the Cross-Section of Stock Returns” Journal of Financial Economics, Vol.88, No. 2, pp.299-322.
Friesen, G. C..and T. R. A. Sapp (2007) “Mutual Fund Flows and Investor Returns: An Empirical Examination of Fund Investor Timing Ability” Journal of Banking & Finance, Vol. 31, No. 9, pp.2796-2816.
Gallagher, D. R. and E. Jarnecic (2002) The Performance of Active Australian Bond Funds, Australian Journal of Management , Vol. 27, No. 2, pp.163-185.
Goetzmann, W. N. and N. Peles (1997)“Cognitive Dissonance and Mutual Fund Investors” Journal of Financial Research, Vol. 20, No. 2, pp.145-158.
Grinblatt, M. and S. Titman (1992)“The Persistence of Mutual Fund Performance” Journal of Finance, Vol.45, No. 5, pp.1977-1984.
Gruber, M. J. (1996)“ Another Puzzle: The Growth in Actively Managed Mutual Funds” Journal of Finance, Vol.51, No. 3, pp.783- 810.
Hansen, B. E. (1996) “Inference When a Nuisance Parameter is not Identified Under the Null Hypothesis” Econometrica, Vol.64, No. 2, pp.413-430.
Hansen, B. E. (1999) “Threshold Effects in Non-Dynamic Panels: Estimation, Testing and Inference” Journal of Econometrics, Vol.93, No. 2, pp.345-368.
Henriksson, R. D. and R. C. Merton (1981) “On Market Timing and Investment Performance II: Statistical Procedures for Evaluating Forecasting Skills” Journal of Business, Vol.54, No. 4, pp.513–534.
Hendricks, D., Patel, J. and R. J. Zeckhauser (1993) “Hot Hands in Mutual Funds: Short-Run Persistence of Performance” Journal of Finance,Vol.48,No.1, pp.93-130.
Hsu, C. C., C. P. Tseng and Y H. Wang (2008)“Dynamic Hedging With Futures: a Copula-Based GARCH Model” Journal of Futures Markets, Vol.28, No. 11, pp. 1095-1116.
Hu, L. (2006)“Dependence Patterns Across Financial Markets: a Mixed Copula Approach” Applied Financial Economics , Vol.16, No. 10, pp.717-729.
Hull, J.(2010) “Risk Management and Financial Institutions” 2nd Edition, Pearson Prentice Hall.
Im, K.S.,M. H. Pesaran and Shin, Y.(2003)“Testing for Unit Roots in Heterogeneous  Panels” Journal of Econometrics, Vol. 115, No. 1, pp.53-74.
Jensen, C. Michael (1968) “The Performance of Mutual Funds in the Period 1945–1964 ” Journal of Finance, Vol. 23, No. 2, pp. 389-416.
Jain, P. C. and J. S. Wu (2000)“Truth in Mutual Fund Advertising: Evidence on Future Performance and Fund Flows” Journal of Finance, Vol. 55, No. 2, pp.937-958.
Jiang, G. T., T. Yao and T. Yu (2007) “Do Mutual Funds Time the Market? Evidence from Portfolio Holdings”Journal of Financial Economics, Vol. 86, No. 3, pp.724-758.
Joe H.(1997) “Multivariate Models and Dependence Concepts”  London: Chapman & Hall.
Junker M, A. Szimayer and N. Wagner (2006) “Nonlinear Term Structure Dependence: Copula Functions, Empirics, and Risk Implications” Journal of Banking and Finance , Vol. 30, No. 4, pp.1171-1199.
Kaplan, S. and B. J. Garrick (1981) “On the Quantitative Definition of Risk” Risk Analysis, Vol.1, No.1, pp. 11- 27.
Lee, C. F. and S. Rahman (1990) “Market Timing, Selectivity, and Mutual Fund Performance: An Empirical Investigation” The Journal of Business, Vol. 63, No. 2, pp. 261-278.
Litterman, R. and J. Sheinkman (1991) “Common Factors Affecting Bond Returns” Journal of Fixed Income, Vol. 1, No. 1, pp.54–61. 
Lintner, J. (1965) “Security Prices, Risk, and Maximal Gains from Diversification” Journal of  Finance, Vol. 20, No. 4, pp.587-615.
Levin, A., Lin, C. F., and C. S. Chu (2002) “Unit Root in Panel Data: Asymptotic and Finite-Sample Properties” Journal of Econometric, Vol. 108, No. 2, pp.1-24.
Lee, W. C. and J. M. Lee (2012a) “An Empirical Investigation into the Effects of a Bond Fund Segregation Policy–Evidence from Taiwan” The Empirical Economics Letters , Vol. 11, No. 12, pp.1227-1236.
Lee, W. C. and J. M. Lee (2012b) “ A Study on Taiwan`s Bond Market Integrity and Market Timing Ability - Based on the ARMAX-GARCH Model”Asian Economic and Financial Review, Vol. 2, No. 8,pp.991-1000.
Morey, M. R. and E S. O’Neal (2006) “Window Dressing in Bond Mutual Funds”Journal of Financial Research, Vol. 29, No. 3,pp.325-347.
Manner, H. and O. Reznikova (2009) “Time-Varying Copulas: a Survey”Econometric Reviews, forthcoming.
Mark, W. R. , D. P. James, A. P. Paul and X.. Fran (2001) “ Selecting a Bond Mutual Fund: Just Keep it Simple”Journal of Financial Planning , Vol. 14, No. 4,pp.44-49.
Nelsen, R. B.( 2006) Introduction to Copulas, Springer Verlag , New York. 2nd Edition.
Odean, T. (1998) “ Are Investors Reluctant to Realize Their Losses? ” Journal of Finance, Vol. 53, No. 5, pp.1775-1798.
Okoli, M. N.(2012) “Return-Volatility Interactions in the Nigerian Stock Market” Asian Economic and Financial Review, Vol. 2, No. 2, pp. 389-399.
Parks, R. W.(1967) “ Efficient Estimation of a System of a Regression Equations When Distributions are Both Serially and Contemporaneously Correlated” Journal of the American Statistical Association, Vol. 62, No. 318, pp.500-509.
Patel, J., R. J. Zeckhauser, and D. Hendricks (1994) “ Investment Flows and Performance: Evidence from Mutual Funds, Cross-Border Investments, and New Issues” Japan, Europe, and International Financial Markets, Vol. 4,No. 5,  pp.51-72.
Palmon, O. and P. Jeffrey (1991) “ Inflation Uncertainty, Real Interest Rate Uncertainty and the Liquidity Premium on Government Bonds” The Financial Review, Vol. 26,No. 4, pp.459-477.
Palaro, H. P. and L. K.. Hotta (2006)“Using Conditional Copula to Estimate Value at Risk” Journal of Data Science ,Vol. 4,No. 1, pp.93-115.
Rodriguez, J. C..(2007) “ Measuring Financial Contagion: A copula Approach” Journal of Empirical Finance ,Vol. 14,No. 3, pp. 401-423.
Sawicki, J.(2001) “ Investors’ Differential Response to Managed Fund Performance” Journal of Financial Research, Vol. 24,No. 3, pp367-384.
Schwarz, G.(1978) “Estimating the Dimension of A Model” Annals of Statistics , Vol. 6,No. 2, pp. 461-464.
Sharpe, W.(1964) “Capital asset Prices: a Theory of Market Equilibrium Under Conditions of Risk” Journal of Finance, Vol. 19,No. 3, pp.425–442.
Shefrin, H. and M. Statman.(1985) “ The Disposition to Sell Winners too Early and Ride Losers too Long: Theory and Evidence” Journal of Finance, Vol. 40,No. 3, pp.777-7990.
Shu, P. G., Y. H. Yeh and T. Yamada (2002) “ The Behavior of Taiwan Mutual Fund Investors – Performance and Fund Flows” Pacific-Basin Finance Journal, Vol. 10,No. 1,pp.583-600.
Sirri, E. R. and P. Tufano (1998)“Costly Search and Mutual Fund Flows” Journal of Finance, Vol. 53,No. 5, pp.1589-1622.
Sklar, A.(1959)“Fonctions De Repartition an Dimensions Et Leurs Marges” Institute for Statistics , Vol. 8, pp. 229-231.
Treynor, J. and K.. Mazuy (1966) “Can Mutual Funds Outguess the Market?” Harvard Business Review, Vol.44, No. 4, pp.131–136.
Zheng, L.(1999)“Is Money Smart? A Study of Mutual Fund Investors’ Fund Selection Ability” Journal of Finance, Vol. 54, No. 3, pp.901-933.
Zoran, Ivkovića, and Scott. Weisbennerb (2009)“Individual Investor Mutual Fund Flows” Journal of Financial Economics, Vol.92, No. 2, pp.223-227.