American Institute of Mathematical Sciences

October  2018, 14(4): 1617-1649. doi: 10.3934/jimo.2018024

Tunneling behaviors of two mutual funds

 1 China Financial Policy Research Center, School of Finance, Renmin University of China, Beijing 100872, China 2 Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China

*Corresponding author

Received  June 2017 Revised  October 2017 Published  January 2018

Fund Project: The first author is supported by National Natural Science Foundation of China grant No.71501178; The second author is supported by National Natural Science Foundation of China grant No.11471183.

In practice, the mutual fund manager charges asset based management fee as the incentives. Meanwhile, we suppose that the investor could sustainedly obtain the fixed proportions of the fund values as the rewards. In this perspective, the objectives of the investor and the manager seem to be consistent. Unfortunately, it is a common situation that the fund managers have private relations, and they transfer the assets illegally. In this paper, we study the optimal tunneling behaviors of the two fund managers to maximize the overall performance criterions. It is the first time to use two prototypes whether the management fee rates are consistent with the investment returns to study the impacts of the two factors on the tunneling behaviors. We firstly study the problem without transaction cost between funds, and it is formalized as a two-dimensional stochastic optimal control problem, whose semi-analytical solution is derived by the dynamic programming methods. Furthermore, the transaction cost is considered, and we explore the penalty method and the finite difference method to establish the numerical solutions. The results show that the well performed and high rewarded fund manager obtains most of the total assets by tunneling, and only keep the other fund at the brink of maximal withdraws for the liquidity considerations. Moreover, the well performed and low rewarded fund manager obtains most of the total assets. Being inconsistent with the instinct, the high management fee rate could neither make the fund managers work efficiently, nor induce the beneficial tunneling behaviors.

Citation: Lin He, Zongxia Liang, Xiaoyang Zhao. Tunneling behaviors of two mutual funds. Journal of Industrial & Management Optimization, 2018, 14 (4) : 1617-1649. doi: 10.3934/jimo.2018024
References:
 [1] H. Albrecher, P. Azcue and N. Muler, Optimal dividend strategies for two collaborating insurance companies, Applied Probability, 49 (2017), 515-548.  doi: 10.1017/apr.2017.11.  Google Scholar [2] B. Avanz, Strategies for dividend distribution: A review, North American Actuarial Journal, 13 (2009), 217-251.  doi: 10.1080/10920277.2009.10597549.  Google Scholar [3] F. Avram, Z. Palmowski and M. R. Pistorius, On the optimal dividend problem for a spectrally negative l$\acute{e}$vy process, The Annals of Applied Probability, 17 (2007), 156-180.  doi: 10.1214/105051606000000709.  Google Scholar [4] P. Azcue and N. Muler, Minimizing the ruin probability allowing investments in two assets: A two-dimensional problem, Mathematical Methods of Operations Research, 77 (2013), 177-206.  doi: 10.1007/s00186-012-0424-3.  Google Scholar [5] K. C. Brown, W. V. Harlow and L. T. Starks, Of tournaments and temptations: an analysis of managerial incentives in the mutual fund industry, Journal of Finance, 51 (1996), 85-110.   Google Scholar [6] J. Chevalier and G. Ellison, Risk taking by mutual funds as a response to incentives, Journal of Political Economy, 105 (1997), 1167-1199.   Google Scholar [7] J. L. Davis, G. Tyge Payne and G. C. McMahan, A few bad apples? scandalous behavior of mutual fund managers, Journal of Business Ethics, 76 (2007), 319-334.   Google Scholar [8] J. S. Demski and G. A. Feltham, Econiomic incentives in budgetary control systems, Accounting Review, 53 (1978), 336-360.   Google Scholar [9] K. M. Eisenhardt, Agency theory: An assessment and review, Academy of Management Review, 14 (1989), 57-74.   Google Scholar [10] L. F. Fant and E. S. O'Neal, Temporal changes in the determinants of mutual fund flows, Journal of Financial Research, 23 (2000), 353-371.   Google Scholar [11] D. P. Foster and H. Peyton Young, Gaming performance fees by portfolio managers, The Quarterly Journal of Economics, 125 (2010), 1435-1458.   Google Scholar [12] J. Gil-Bazo and P. Ruiz-Verd$\acute{u}$, The relation between price and performance in the mutual fund industry, The Journal of Finance, 64 (2009), 2153-2183.   Google Scholar [13] W. N. Goetzmann and R. G. Ibbotson, Do winners repeat, Journal of Portfolio Management, 20 (1994), 9-18.   Google Scholar [14] L. Gomez-Mejia and R. M. Wiseman, Refraining executive compensation: An assessment and out look, Journal of Management, 23 (1997), 291-374.   Google Scholar [15] D. Guercio and P. A. Tkac, The determinants of the flow of funds of managed portfolios: Mutual funds versus pension funds, Journal of Financial and Quantitative Analysis, 37 (2002), 523-557.   Google Scholar [16] T. Houge and J. Wellman, Fallout from the mutual fund trading scandal, Journal of Business Ethics, 62 (2005), 129-139.   Google Scholar [17] Z. Jin, H. L. Yang and G. Yin, A numerical approach to optimal dividend policies with capital injections and transaction costs, Acta Mathematicae Applicatae Sinica, 33 (2017), 221-238.  doi: 10.1007/s10255-017-0653-6.  Google Scholar [18] W. Li and S. Wang, A penalty approach to the hjb equation arising in european stock option pricing with proportional transation costs, Journal of Optimization Theory and Applications, 143 (2009), 279-293.  doi: 10.1007/s10957-009-9559-7.  Google Scholar [19] W. Li and S. Wang, Pricing American options under proportional transaction costs using a penalty approach and a finite difference scheme, Journal of Industrial and Management Optimization, 9 (2013), 365-389.  doi: 10.3934/jimo.2013.9.365.  Google Scholar [20] P. L. Lions and A. S. Sznitman, Stochastic differential equations with reflecting boundary conditions, Communications on Pure and Applied Mathematics, 37 (1984), 511-537.  doi: 10.1002/cpa.3160370408.  Google Scholar [21] B. Maiden, SEC faces critics over mutual funds scandal, International Financial Law Review, 22 (2003), 21-23.   Google Scholar [22] B. Øksendal and A. Sulem, Applied Stochastic Control of Jump Diffusions, 2nd edition, Springer, 2007.  Google Scholar [23] S. Reynolds, F. Schultz and D. Hekman, Stakeholder theory and managerial decision-making: Constraints and implications of balancing stakeholder interests, Journal of Business Ethics, 64 (2006), 285-301.   Google Scholar [24] E. R. Sirri and P. Tufano, Costly search and mutual fund flows, Journal of Finance, 53 (1998), 1589-1622.   Google Scholar [25] N. Stoughton, Moral hazard and the portfolio management problem, Journal of Finance, 48 (1993), 2009-2028.   Google Scholar [26] J. H. Witte and C. Reisinger, A penalty method for the numerical solution of Hamilton-Jacobi-Bellman (HJB) equations in finance, SIAM Journal on Numerical Analysis, 49 (2011), 213-231.  doi: 10.1137/100797606.  Google Scholar [27] J. Yong and X. Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations, Springer Science and Business Media, 1999.  Google Scholar

show all references

References:
 [1] H. Albrecher, P. Azcue and N. Muler, Optimal dividend strategies for two collaborating insurance companies, Applied Probability, 49 (2017), 515-548.  doi: 10.1017/apr.2017.11.  Google Scholar [2] B. Avanz, Strategies for dividend distribution: A review, North American Actuarial Journal, 13 (2009), 217-251.  doi: 10.1080/10920277.2009.10597549.  Google Scholar [3] F. Avram, Z. Palmowski and M. R. Pistorius, On the optimal dividend problem for a spectrally negative l$\acute{e}$vy process, The Annals of Applied Probability, 17 (2007), 156-180.  doi: 10.1214/105051606000000709.  Google Scholar [4] P. Azcue and N. Muler, Minimizing the ruin probability allowing investments in two assets: A two-dimensional problem, Mathematical Methods of Operations Research, 77 (2013), 177-206.  doi: 10.1007/s00186-012-0424-3.  Google Scholar [5] K. C. Brown, W. V. Harlow and L. T. Starks, Of tournaments and temptations: an analysis of managerial incentives in the mutual fund industry, Journal of Finance, 51 (1996), 85-110.   Google Scholar [6] J. Chevalier and G. Ellison, Risk taking by mutual funds as a response to incentives, Journal of Political Economy, 105 (1997), 1167-1199.   Google Scholar [7] J. L. Davis, G. Tyge Payne and G. C. McMahan, A few bad apples? scandalous behavior of mutual fund managers, Journal of Business Ethics, 76 (2007), 319-334.   Google Scholar [8] J. S. Demski and G. A. Feltham, Econiomic incentives in budgetary control systems, Accounting Review, 53 (1978), 336-360.   Google Scholar [9] K. M. Eisenhardt, Agency theory: An assessment and review, Academy of Management Review, 14 (1989), 57-74.   Google Scholar [10] L. F. Fant and E. S. O'Neal, Temporal changes in the determinants of mutual fund flows, Journal of Financial Research, 23 (2000), 353-371.   Google Scholar [11] D. P. Foster and H. Peyton Young, Gaming performance fees by portfolio managers, The Quarterly Journal of Economics, 125 (2010), 1435-1458.   Google Scholar [12] J. Gil-Bazo and P. Ruiz-Verd$\acute{u}$, The relation between price and performance in the mutual fund industry, The Journal of Finance, 64 (2009), 2153-2183.   Google Scholar [13] W. N. Goetzmann and R. G. Ibbotson, Do winners repeat, Journal of Portfolio Management, 20 (1994), 9-18.   Google Scholar [14] L. Gomez-Mejia and R. M. Wiseman, Refraining executive compensation: An assessment and out look, Journal of Management, 23 (1997), 291-374.   Google Scholar [15] D. Guercio and P. A. Tkac, The determinants of the flow of funds of managed portfolios: Mutual funds versus pension funds, Journal of Financial and Quantitative Analysis, 37 (2002), 523-557.   Google Scholar [16] T. Houge and J. Wellman, Fallout from the mutual fund trading scandal, Journal of Business Ethics, 62 (2005), 129-139.   Google Scholar [17] Z. Jin, H. L. Yang and G. Yin, A numerical approach to optimal dividend policies with capital injections and transaction costs, Acta Mathematicae Applicatae Sinica, 33 (2017), 221-238.  doi: 10.1007/s10255-017-0653-6.  Google Scholar [18] W. Li and S. Wang, A penalty approach to the hjb equation arising in european stock option pricing with proportional transation costs, Journal of Optimization Theory and Applications, 143 (2009), 279-293.  doi: 10.1007/s10957-009-9559-7.  Google Scholar [19] W. Li and S. Wang, Pricing American options under proportional transaction costs using a penalty approach and a finite difference scheme, Journal of Industrial and Management Optimization, 9 (2013), 365-389.  doi: 10.3934/jimo.2013.9.365.  Google Scholar [20] P. L. Lions and A. S. Sznitman, Stochastic differential equations with reflecting boundary conditions, Communications on Pure and Applied Mathematics, 37 (1984), 511-537.  doi: 10.1002/cpa.3160370408.  Google Scholar [21] B. Maiden, SEC faces critics over mutual funds scandal, International Financial Law Review, 22 (2003), 21-23.   Google Scholar [22] B. Øksendal and A. Sulem, Applied Stochastic Control of Jump Diffusions, 2nd edition, Springer, 2007.  Google Scholar [23] S. Reynolds, F. Schultz and D. Hekman, Stakeholder theory and managerial decision-making: Constraints and implications of balancing stakeholder interests, Journal of Business Ethics, 64 (2006), 285-301.   Google Scholar [24] E. R. Sirri and P. Tufano, Costly search and mutual fund flows, Journal of Finance, 53 (1998), 1589-1622.   Google Scholar [25] N. Stoughton, Moral hazard and the portfolio management problem, Journal of Finance, 48 (1993), 2009-2028.   Google Scholar [26] J. H. Witte and C. Reisinger, A penalty method for the numerical solution of Hamilton-Jacobi-Bellman (HJB) equations in finance, SIAM Journal on Numerical Analysis, 49 (2011), 213-231.  doi: 10.1137/100797606.  Google Scholar [27] J. Yong and X. Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations, Springer Science and Business Media, 1999.  Google Scholar
The amount of assets transferred from Fund Two to Fund One in Case 1(without transaction cost).
The amount of assets transferred from Fund Two to Fund One in Case 2 (without transaction cost).
The amount of assets transferred from Fund Two to Fund One in Case 1 (with transaction cost).
The amount of assets transferred from Fund Two to Fund One in Case 2(with transaction cost).
The amount of assets transferred from Fund Two to Fund One in Case 1(with correlation).
The amount of assets transferred from Fund Two to Fund One in Case 2 (with correlation).
Values of the parameters in the model
 Parameter Value $a_1$ 0.8 $a_2$ 0.8 $\beta$ 0.03 $l_1$ 0.04 $l_2$ 0.04 $\sigma_1$ 0.3 $\sigma_2$ 0.3 $x_{10}$ 10.7 $x_{20}$ 10.7 Case 1. $\mu_1$ 0.1 $c_1$ 0.05 $\mu_2$ 0.08 $c_2$ 0.03 Case 2. $\mu_1$ 0.06 $c_1$ 0.05 $\mu_2$ 0.08 $c_2$ 0.03
 Parameter Value $a_1$ 0.8 $a_2$ 0.8 $\beta$ 0.03 $l_1$ 0.04 $l_2$ 0.04 $\sigma_1$ 0.3 $\sigma_2$ 0.3 $x_{10}$ 10.7 $x_{20}$ 10.7 Case 1. $\mu_1$ 0.1 $c_1$ 0.05 $\mu_2$ 0.08 $c_2$ 0.03 Case 2. $\mu_1$ 0.06 $c_1$ 0.05 $\mu_2$ 0.08 $c_2$ 0.03
The impacts of the tunneling behaviors in Case 1.
 Keynote Value The management fee of Fund One without tunneling: $V^{x_{10}}_1$ 15.55 The management fee of Fund Two without tunneling: $V^{x_{20}}_2$ 9.65 The total management fee without tunneling: $V^{x_{10}}_1+V^{x_{20}}_2$ 25.2 The management fee of Fund One with tunneling: $\tilde{V}^{x_{10}}_1$ 31.02 The management fee of Fund Two with tunneling: $\tilde{V}^{x_{20}}_2$ 0.46 The total management fee with tunneling: $V^{x_{10},x_{20}}=\tilde{V}^{x_{10}}_1+\tilde{V}^{x_{20}}_2$ 31.48 The duration of the Fund One without tunneling(year): $\mathbf{E}_{x_{10}}\{T_1\}$ 47.14 The duration of the Fund Two without tunneling(year): $\mathbf{E}_{x_{20}}\{T_2\}$ 49.28 The duration of the Fund One with tunneling(year): $\mathbf{E}_{x_{10}}\{\tau_1\}$ 49.22 The duration of the Fund Two with tunneling(year): $\mathbf{E}_{x_{20}}\{\tau_2\}$ 49.19 The average exchange amount(Fund Two to Fund One): $\mathbf{E}_{x_{10},x_{20}}\frac{\int^{\tau^1}_0 \delta(s)\mathrm{d}s}{\tau^1}$ 0.012
 Keynote Value The management fee of Fund One without tunneling: $V^{x_{10}}_1$ 15.55 The management fee of Fund Two without tunneling: $V^{x_{20}}_2$ 9.65 The total management fee without tunneling: $V^{x_{10}}_1+V^{x_{20}}_2$ 25.2 The management fee of Fund One with tunneling: $\tilde{V}^{x_{10}}_1$ 31.02 The management fee of Fund Two with tunneling: $\tilde{V}^{x_{20}}_2$ 0.46 The total management fee with tunneling: $V^{x_{10},x_{20}}=\tilde{V}^{x_{10}}_1+\tilde{V}^{x_{20}}_2$ 31.48 The duration of the Fund One without tunneling(year): $\mathbf{E}_{x_{10}}\{T_1\}$ 47.14 The duration of the Fund Two without tunneling(year): $\mathbf{E}_{x_{20}}\{T_2\}$ 49.28 The duration of the Fund One with tunneling(year): $\mathbf{E}_{x_{10}}\{\tau_1\}$ 49.22 The duration of the Fund Two with tunneling(year): $\mathbf{E}_{x_{20}}\{\tau_2\}$ 49.19 The average exchange amount(Fund Two to Fund One): $\mathbf{E}_{x_{10},x_{20}}\frac{\int^{\tau^1}_0 \delta(s)\mathrm{d}s}{\tau^1}$ 0.012
The impacts of the tunneling behaviors in Case 2.
 Keynote Value The management fee of Fund One without tunneling: $V^{x_{10}}_1$ 3.05 The management fee of Fund Two without tunneling: $V^{x_{20}}_2$ 9.39 The total management fee without tunneling: $V^{x_{10}}_1+V^{x_{20}}_2$ 12.44 The management fee of Fund One with tunneling: $\tilde{V}^{x_{10}}_1$ 0.71 The management fee of Fund Two with tunneling: $\tilde{V}^{x_{20}}_2$ 17.41 The total management fee with tunneling: $V^{x_{10},x_{20}}=\tilde{V}^{x_{10}}_1+\tilde{V}^{x_{20}}_2$ 18.12 The duration of the Fund One without tunneling(year): $\mathbf{E}_{x_{10}}\{T_1\}$ 6.84 The duration of the Fund Two without tunneling(year): $\mathbf{E}_{x_{20}}\{T_2\}$ 45.87 The duration of the Fund One with tunneling(year): $\mathbf{E}_{x_{10}}\{\tau_1\}$ 45.13 The duration of the Fund Two with tunneling(year): $\mathbf{E}_{x_{20}}\{\tau_2\}$ 45.17 The average exchange amount(Fund Two to Fund One): $\mathbf{E}_{x_{10},x_{20}}\frac{\int^{\tau^1}_0 \delta(s)\mathrm{d}s}{\tau^1}$ -0.013
 Keynote Value The management fee of Fund One without tunneling: $V^{x_{10}}_1$ 3.05 The management fee of Fund Two without tunneling: $V^{x_{20}}_2$ 9.39 The total management fee without tunneling: $V^{x_{10}}_1+V^{x_{20}}_2$ 12.44 The management fee of Fund One with tunneling: $\tilde{V}^{x_{10}}_1$ 0.71 The management fee of Fund Two with tunneling: $\tilde{V}^{x_{20}}_2$ 17.41 The total management fee with tunneling: $V^{x_{10},x_{20}}=\tilde{V}^{x_{10}}_1+\tilde{V}^{x_{20}}_2$ 18.12 The duration of the Fund One without tunneling(year): $\mathbf{E}_{x_{10}}\{T_1\}$ 6.84 The duration of the Fund Two without tunneling(year): $\mathbf{E}_{x_{20}}\{T_2\}$ 45.87 The duration of the Fund One with tunneling(year): $\mathbf{E}_{x_{10}}\{\tau_1\}$ 45.13 The duration of the Fund Two with tunneling(year): $\mathbf{E}_{x_{20}}\{\tau_2\}$ 45.17 The average exchange amount(Fund Two to Fund One): $\mathbf{E}_{x_{10},x_{20}}\frac{\int^{\tau^1}_0 \delta(s)\mathrm{d}s}{\tau^1}$ -0.013
 [1] Hong Niu, Zhijiang Feng, Qijin Xiao, Yajun Zhang. A PID control method based on optimal control strategy. Numerical Algebra, Control & Optimization, 2020  doi: 10.3934/naco.2020019 [2] Qun Lin, Ryan Loxton, Kok Lay Teo. The control parameterization method for nonlinear optimal control: A survey. Journal of Industrial & Management Optimization, 2014, 10 (1) : 275-309. doi: 10.3934/jimo.2014.10.275 [3] Mou-Hsiung Chang, Tao Pang, Moustapha Pemy. Finite difference approximation for stochastic optimal stopping problems with delays. Journal of Industrial & Management Optimization, 2008, 4 (2) : 227-246. doi: 10.3934/jimo.2008.4.227 [4] Canghua Jiang, Zhiqiang Guo, Xin Li, Hai Wang, Ming Yu. An efficient adjoint computational method based on lifted IRK integrator and exact penalty function for optimal control problems involving continuous inequality constraints. Discrete & Continuous Dynamical Systems - S, 2020, 13 (6) : 1845-1865. doi: 10.3934/dcdss.2020109 [5] Karl Kunisch, Markus Müller. Uniform convergence of the POD method and applications to optimal control. Discrete & Continuous Dynamical Systems - A, 2015, 35 (9) : 4477-4501. doi: 10.3934/dcds.2015.35.4477 [6] Ugur G. Abdulla. On the optimal control of the free boundary problems for the second order parabolic equations. II. Convergence of the method of finite differences. Inverse Problems & Imaging, 2016, 10 (4) : 869-898. doi: 10.3934/ipi.2016025 [7] Ming Yan, Lili Chang, Ningning Yan. Finite element method for constrained optimal control problems governed by nonlinear elliptic PDEs. Mathematical Control & Related Fields, 2012, 2 (2) : 183-194. doi: 10.3934/mcrf.2012.2.183 [8] Andrew J. Whittle, Suzanne Lenhart, Louis J. Gross. Optimal control for management of an invasive plant species. Mathematical Biosciences & Engineering, 2007, 4 (1) : 101-112. doi: 10.3934/mbe.2007.4.101 [9] Alex Bombrun, Jean-Baptiste Pomet. Asymptotic behavior of time optimal orbital transfer for low thrust 2-body control system. Conference Publications, 2007, 2007 (Special) : 122-129. doi: 10.3934/proc.2007.2007.122 [10] Dingjun Yao, Rongming Wang, Lin Xu. Optimal asset control of a geometric Brownian motion with the transaction costs and bankruptcy permission. Journal of Industrial & Management Optimization, 2015, 11 (2) : 461-478. doi: 10.3934/jimo.2015.11.461 [11] Marcus Wagner. A direct method for the solution of an optimal control problem arising from image registration. Numerical Algebra, Control & Optimization, 2012, 2 (3) : 487-510. doi: 10.3934/naco.2012.2.487 [12] Alexander Tyatyushkin, Tatiana Zarodnyuk. Numerical method for solving optimal control problems with phase constraints. Numerical Algebra, Control & Optimization, 2017, 7 (4) : 481-492. doi: 10.3934/naco.2017030 [13] Nan Li, Song Wang, Shuhua Zhang. Pricing options on investment project contraction and ownership transfer using a finite volume scheme and an interior penalty method. Journal of Industrial & Management Optimization, 2020, 16 (3) : 1349-1368. doi: 10.3934/jimo.2019006 [14] Jiongmin Yong. Stochastic optimal control — A concise introduction. Mathematical Control & Related Fields, 2020  doi: 10.3934/mcrf.2020027 [15] Ka Wo Lau, Yue Kuen Kwok. Optimal execution strategy of liquidation. Journal of Industrial & Management Optimization, 2006, 2 (2) : 135-144. doi: 10.3934/jimo.2006.2.135 [16] Yujing Wang, Changjun Yu, Kok Lay Teo. A new computational strategy for optimal control problem with a cost on changing control. Numerical Algebra, Control & Optimization, 2016, 6 (3) : 339-364. doi: 10.3934/naco.2016016 [17] Siyu Liu, Xue Yang, Yingjie Bi, Yong Li. Dynamic behavior and optimal scheduling for mixed vaccination strategy with temporary immunity. Discrete & Continuous Dynamical Systems - B, 2019, 24 (4) : 1469-1483. doi: 10.3934/dcdsb.2018216 [18] Zhengyan Wang, Guanghua Xu, Peibiao Zhao, Zudi Lu. The optimal cash holding models for stochastic cash management of continuous time. Journal of Industrial & Management Optimization, 2018, 14 (1) : 1-17. doi: 10.3934/jimo.2017034 [19] C.E.M. Pearce, J. Piantadosi, P.G. Howlett. On an optimal control policy for stormwater management in two connected dams. Journal of Industrial & Management Optimization, 2007, 3 (2) : 313-320. doi: 10.3934/jimo.2007.3.313 [20] Simone Göttlich, Patrick Schindler. Optimal inflow control of production systems with finite buffers. Discrete & Continuous Dynamical Systems - B, 2015, 20 (1) : 107-127. doi: 10.3934/dcdsb.2015.20.107

2019 Impact Factor: 1.366