Systemic Risk and Interbank Lending

Sun, Li-Hsien

doi:10.48550/arxiv.1611.06672

Cited by 3 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Notice that this HJB equation is random, because of its dependence on the F MF 0 -measurable type parameters. Applying the first order conditions, the maximum in (53)…”

Section: 2mentioning

confidence: 99%

“…Beyond the linear quadratic models of [5,15,17], such examples are scarce, especially in the presence of common noise. The only other examples we know of are those in [29,Sections 5 and 7] as well as the more recent [53], which is linear-quadratic aside from a square root diffusion term. In fact, our models permit an explicit solution of the so-called master equation (cf.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mean field and n‐agent games for optimal investment under relative performance criteria

Lacker

Zariphopoulou

2019

Mathematical Finance

134

View full text Add to dashboard Cite

We analyze a family of portfolio management problems under relative performance criteria, for fund managers having CARA or CRRA utilities and trading in a common investment horizon in log‐normal markets. We construct explicit constant equilibrium strategies for both the finite population games and the corresponding mean field games, which we show are unique in the class of constant equilibria. In the CARA case, competition drives agents to invest more in the risky asset than they would otherwise, while in the CRRA case competitive agents may over‐ or underinvest, depending on their levels of risk tolerance.

show abstract

“…Notice that this HJB equation is random, because of its dependence on the F MF 0 -measurable type parameters. Applying the first order conditions, the maximum in (53)…”

Section: 2mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mean field and n‐agent games for optimal investment under relative performance criteria

Lacker

Zariphopoulou

2019

Mathematical Finance

134

View full text Add to dashboard Cite

show abstract

“…Mean field games, introduced in [17,22], are rarely explicitly solvable outside of linearquadratic examples. See [4,6,16,21,29] for some notable exceptions and the book [7] for further background on the active area of mean field games. From a mean field game perspective, our model is rather complex: It involves common noise, degenerate volatility coefficients, singular objective functions, and a mean field interaction through both the states and controls (i.e., an extended mean field game [7,Chapter I.4.6]).…”

Section: Introductionmentioning

confidence: 99%

Many-player games of optimal consumption and investment under relative performance criteria

Lacker

Soret

2020

Math Finan Econ

View full text Add to dashboard Cite

We study a portfolio optimization problem for competitive agents with CRRA utilities and a common finite time horizon. The utility of an agent depends not only on her absolute wealth and consumption but also on her relative wealth and consumption when compared to the averages among the other agents. We derive a closed form solution for the n-player game and the corresponding mean field game. This solution is unique in the class of equilibria with constant investment and continuous time-dependent consumption, both independent of the wealth of the agent. Compared to the classical Merton problem with one agent, the competitive model exhibits a wide range of highly nonlinear and non-monotone dependence on the agents' risk tolerance and competitiveness parameters. Counter-intuitively, competitive agents with high risk tolerance may behave like noncompetitive agents with low risk tolerance.

show abstract

“…[14] use a system of stochastic differential equations with Bessel-type diffusion coefficients to model simultaneous defaults (in this model, a default is when the capital reaches zero). Authors in [3,27] combine such Bessel-type diffusion coefficients with a mean-fieldtype drift term, with [3] having an additional jump term (therefore the processes there are jump-diffusions).…”

Section: Introductionmentioning

confidence: 99%

Modeling Financial System with Interbank Flows, Borrowing, and Investing

Maheshwari

Sarantsev

2018

Risks

View full text Add to dashboard Cite

In our model, private actors with interbank cash flows similar to, but nore general than (Carmona, Fouque, Sun, 2013) borrow from the outside economy at a certain interest rate, controlled by the central bank, and invest in risky assets. Each private actor aims to maximize its expected terminal logarithmic utility. The central bank, in turn, aims to control the overall economy by means of an exponential utility function. We solve all stochastic optimal control problems explicitly. We are able to recreate occasions such as liquidity trap. We study distribution of the number of defaults (net worth of a private actor going below a certain threshold).Date: October 9, 2018. Version 26. 2010 Mathematics Subject Classification. 60H10, 60H30, 60J60, 60K35, 91A15, 91B70, 91G80, 93E15.

show abstract

Systemic Risk and Interbank Lending

Cited by 3 publications

References 0 publications

Mean field and n‐agent games for optimal investment under relative performance criteria

Mean field and n‐agent games for optimal investment under relative performance criteria

Many-player games of optimal consumption and investment under relative performance criteria

Modeling Financial System with Interbank Flows, Borrowing, and Investing

Contact Info

Product

Resources

About