Author: Sally Shen
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We develop a robust optimal dynamic hedging strategy that takes both downside risks and market incompleteness into account for an agent who fears model misspecification. The robust agent is assumed to minimize the shortfall between the assets and liabilities under an endogenous worst case scenario by means of solving a min-max robust optimization problem. When the funding ratio is low, robustness reduces the demand for risky assets. However, cherishing the hope of covering the liabilities, a substantial risk exposure is still optimal. A longer investment horizon or a higher funding ratio weakens the investor's fear of model misspecification. If the expected equity return is overestimated, the initial capital requirement for hedging can be decreased by following the robust strategy.
Robust Hedging in Incomplete Markets
Author: Sally Shen
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We develop a robust optimal dynamic hedging strategy that takes both downside risks and market incompleteness into account for an agent who fears model misspecification. The robust agent is assumed to minimize the shortfall between the assets and liabilities under an endogenous worst case scenario by means of solving a min-max robust optimization problem. When the funding ratio is low, robustness reduces the demand for risky assets. However, cherishing the hope of covering the liabilities, a substantial risk exposure is still optimal. A longer investment horizon or a higher funding ratio weakens the investor's fear of model misspecification. If the expected equity return is overestimated, the initial capital requirement for hedging can be decreased by following the robust strategy.
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We develop a robust optimal dynamic hedging strategy that takes both downside risks and market incompleteness into account for an agent who fears model misspecification. The robust agent is assumed to minimize the shortfall between the assets and liabilities under an endogenous worst case scenario by means of solving a min-max robust optimization problem. When the funding ratio is low, robustness reduces the demand for risky assets. However, cherishing the hope of covering the liabilities, a substantial risk exposure is still optimal. A longer investment horizon or a higher funding ratio weakens the investor's fear of model misspecification. If the expected equity return is overestimated, the initial capital requirement for hedging can be decreased by following the robust strategy.
Metodika muzykal'nogo vospitanija škol'nikov I-IV klassov
Pricing and Hedging in Incomplete Markets with Model Uncertainty
Author: Anne Balter
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We search for a trading strategy and the associated robust price of unhedgeable assets in incomplete markets under the acknowledgement of model uncertainty. Our set-up is that we postulate an agent who wants to maximise the expected surplus by choosing an optimal investment strategy. Furthermore, we assume that the agent is concerned about model misspecification. This robust optimal control problem under model uncertainty leads to (i) risk-neutral pricing for the traded risky assets, and (ii) adjusting the drift of the nontraded risk drivers in a conservative direction. The direction depends on the agent's long or short position, and the adjustment that ensures a robust strategy leads to what is known as "actuarial" or "prudential" pricing. Our results extend to a multivariate setting. We prove existence and uniqueness of the robust price in an incomplete market via the link between the semilinear partial differential equation and backward stochastic differential equations.
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
Book Description
We search for a trading strategy and the associated robust price of unhedgeable assets in incomplete markets under the acknowledgement of model uncertainty. Our set-up is that we postulate an agent who wants to maximise the expected surplus by choosing an optimal investment strategy. Furthermore, we assume that the agent is concerned about model misspecification. This robust optimal control problem under model uncertainty leads to (i) risk-neutral pricing for the traded risky assets, and (ii) adjusting the drift of the nontraded risk drivers in a conservative direction. The direction depends on the agent's long or short position, and the adjustment that ensures a robust strategy leads to what is known as "actuarial" or "prudential" pricing. Our results extend to a multivariate setting. We prove existence and uniqueness of the robust price in an incomplete market via the link between the semilinear partial differential equation and backward stochastic differential equations.
American Options in Incomplete Markets
Author: Erick Treviño Aguilar
Publisher:
ISBN:
Category :
Languages : en
Pages : 151
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 151
Book Description
Hedging in incomplete markets and optimal control
The Cost of Risk and Option Hedging in Incomplete Markets
Author: Vera Minina
Publisher:
ISBN: 9789036526111
Category :
Languages : en
Pages : 110
Book Description
Publisher:
ISBN: 9789036526111
Category :
Languages : en
Pages : 110
Book Description
Pricing and Hedging Derivative Securities in Incomplete Markets
Author: Dimitris Bertsimas
Publisher:
ISBN:
Category : Arbitrage
Languages : en
Pages : 80
Book Description
Publisher:
ISBN:
Category : Arbitrage
Languages : en
Pages : 80
Book Description
Robust Long-Term Interest Rate Risk Hedging in Incomplete Bond Markets
Author: Sally Shen
Publisher:
ISBN:
Category :
Languages : en
Pages : 29
Book Description
We introduce a robust investment strategy to hedge long dated liabilities under model misspecification and incomplete bond markets. A robust agent who worries about misspecified bond premia follows a min-max expected shortfall criterion to protect against model uncertainty. We employ a backward least squares Monte Carlo method to solve this dynamic robust optimization problem. We find that both naive and robust optimal portfolios depend on the hedging horizon and current funding ratio. The robust policy suggests to take more risk when the current funding ratio is low. The robust yield curve derived through the minimum assets required to eliminate shortfall risk is lower than the naive one.
Publisher:
ISBN:
Category :
Languages : en
Pages : 29
Book Description
We introduce a robust investment strategy to hedge long dated liabilities under model misspecification and incomplete bond markets. A robust agent who worries about misspecified bond premia follows a min-max expected shortfall criterion to protect against model uncertainty. We employ a backward least squares Monte Carlo method to solve this dynamic robust optimization problem. We find that both naive and robust optimal portfolios depend on the hedging horizon and current funding ratio. The robust policy suggests to take more risk when the current funding ratio is low. The robust yield curve derived through the minimum assets required to eliminate shortfall risk is lower than the naive one.
Dynamic Hedging in Incomplete Markets
Author: Suleyman Basak
Publisher:
ISBN:
Category : Financial futures
Languages : en
Pages : 0
Book Description
Despite much work on hedging in incomplete markets, the literature still lacks tractable dynamic hedges in plausible environments. In this article, we provide a simple solution to this problem in a general incomplete-market economy in which a hedger, guided by the traditional minimum-variance criterion, aims at reducing the risk of a non-tradable asset or a contingent claim. We derive fully analytical optimal hedges and demonstrate that they can easily be computed in various stochastic environments. Our dynamic hedges preserve the simple structure of complete-market perfect hedges and are in terms of generalized "Greeks," familiar in risk management applications, as well as retaining the intuitive features of their static counterparts. We obtain our time-consistent hedges by dynamic programming, while the extant literature characterizes either static or myopic hedges, or dynamic ones that minimize the variance criterion at an initial date and from which the hedger may deviate unless she can pre-commit to follow them. We apply our results to the discrete hedging problem of derivatives when trading occurs infrequently. We determine the corresponding optimal hedge and replicating portfolio value, and show that they have structure similar to their complete-market counterparts and reduce to generalized Black-Scholes expressions when specialized to the Black-Scholes setting. We also generalize our results to richer settings to study dynamic hedging with Poisson jumps, stochastic correlation and portfolio management with benchmarking.
Publisher:
ISBN:
Category : Financial futures
Languages : en
Pages : 0
Book Description
Despite much work on hedging in incomplete markets, the literature still lacks tractable dynamic hedges in plausible environments. In this article, we provide a simple solution to this problem in a general incomplete-market economy in which a hedger, guided by the traditional minimum-variance criterion, aims at reducing the risk of a non-tradable asset or a contingent claim. We derive fully analytical optimal hedges and demonstrate that they can easily be computed in various stochastic environments. Our dynamic hedges preserve the simple structure of complete-market perfect hedges and are in terms of generalized "Greeks," familiar in risk management applications, as well as retaining the intuitive features of their static counterparts. We obtain our time-consistent hedges by dynamic programming, while the extant literature characterizes either static or myopic hedges, or dynamic ones that minimize the variance criterion at an initial date and from which the hedger may deviate unless she can pre-commit to follow them. We apply our results to the discrete hedging problem of derivatives when trading occurs infrequently. We determine the corresponding optimal hedge and replicating portfolio value, and show that they have structure similar to their complete-market counterparts and reduce to generalized Black-Scholes expressions when specialized to the Black-Scholes setting. We also generalize our results to richer settings to study dynamic hedging with Poisson jumps, stochastic correlation and portfolio management with benchmarking.