Academic literature on the topic 'Discrete hedging'

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Journal articles on the topic "Discrete hedging"

1

Hussain, Sultan, Salman Zeb, Muhammad Saleem, and Nasir Rehman. "Hedging error estimate of the american put option problem in jump-diffusion processes." Filomat 32, no. 8 (2018): 2813–24. http://dx.doi.org/10.2298/fil1808813h.

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We consider discrete time hedging error of the American put option in case of brusque fluctuations in the price of assets. Since continuous time hedging is not possible in practice so we consider discrete time hedging process. We show that if the proportions of jump sizes in the asset price are identically distributed independent random variables having finite moments then the value process of the discrete time hedging uniformly approximates the value process of the corresponding continuous-time hedging in the sense of L1 and L2-norms under the real world probability measure.
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2

Rémillard, Bruno, and Sylvain Rubenthaler. "Optimal hedging in discrete time." Quantitative Finance 13, no. 6 (2013): 819–25. http://dx.doi.org/10.1080/14697688.2012.745012.

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3

Brealey, R. A., and E. C. Kaplanis. "Discrete exchange rate hedging strategies." Journal of Banking & Finance 19, no. 5 (1995): 765–84. http://dx.doi.org/10.1016/0378-4266(95)00089-y.

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4

BRODÉN, MATS, and PETER TANKOV. "TRACKING ERRORS FROM DISCRETE HEDGING IN EXPONENTIAL LÉVY MODELS." International Journal of Theoretical and Applied Finance 14, no. 06 (2011): 803–37. http://dx.doi.org/10.1142/s0219024911006760.

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We analyze the errors arising from discrete readjustment of the hedging portfolio when hedging options in exponential Lévy models, and establish the rate at which the expected squared error goes to zero when the readjustment frequency increases. We compare the quadratic hedging strategy with the common market practice of delta hedging, and show that for discontinuous option pay-offs the latter strategy may suffer from very large discretization errors. For options with discontinuous pay-offs, the convergence rate depends on the underlying Lévy process, and we give an explicit relation between the rate and the Blumenthal-Getoor index of the process.
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5

Dariane, Alireza B., Mohammad M. Sabokdast, Farzane Karami, Roza Asadi, Kumaraswamy Ponnambalam, and Seyed Jamshid Mousavi. "Integrated Operation of Multi-Reservoir and Many-Objective System Using Fuzzified Hedging Rule and Strength Pareto Evolutionary Optimization Algorithm (SPEA2)." Water 13, no. 15 (2021): 1995. http://dx.doi.org/10.3390/w13151995.

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In this paper, a many-objective optimization algorithm was developed using SPEA2 for a system of four reservoirs in the Karun basin, including hydropower, municipal and industrial, agricultural, and environmental objectives. For this purpose, using 53 years of available data, hedging rules were developed in two modes: with and without applying fuzzy logic. SPEA2 was used to optimize hedging coefficients using the first 43 years of data and the last 10 years of data were used to test the optimized rule curves. The results were compared with those of non-hedging methods, including the standard operating procedures (SOP) and water evaluation and planning (WEAP) model. The results indicate that the combination of fuzzy logic and hedging rules in a many-objectives system is more efficient than the discrete hedging rule alone. For instance, the reliability of the hydropower requirement in the fuzzified discrete hedging method in a drought scenario was found to be 0.68, which is substantially higher than the 0.52 from the discrete hedging method. Moreover, reduction of the maximum monthly shortage is another advantage of this rule. Fuzzy logic reduced 118 million cubic meters (MCM) of deficit in the Karun-3 reservoir alone. Moreover, as expected, the non-hedging SOP and WEAP model produced higher reliabilities, lower average storages, and less water losses through spills.
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6

Hamdi, Haykel, and Jihed Majdoub. "Risk-sharing finance governance: Islamic vs conventional indexes option pricing." Managerial Finance 44, no. 5 (2018): 540–50. http://dx.doi.org/10.1108/mf-05-2017-0199.

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Purpose Risk governance has an important influence on the hedging performances in option pricing and portfolio hedging in both discrete and dynamic case for both conventional and Islamic indexes. The paper aims to discuss these issues. Design/methodology/approach This paper explores option pricing and portfolio hedging in a discrete and dynamic case with transaction costs. Monte Carlo simulations are applied to both conventional and Islamic indexes in US and UK markets. Simulations show that conventional and Islamic assets do not exhibit the same price and portfolio hedging strategy governance. Findings The authors conclude that Islamic assets show different option price and hedging strategy compared to their conventional counterpart. Originality/value The research question of this paper aims at filling the gap in the empirical literature by exploring option price and hedging structure for both conventional and Islamic indexes in US and UK stock markets.
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7

Schweizer, Martin. "Variance-Optimal Hedging in Discrete Time." Mathematics of Operations Research 20, no. 1 (1995): 1–32. http://dx.doi.org/10.1287/moor.20.1.1.

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8

Ku, Hyejin, Kiseop Lee, and Huaiping Zhu. "Discrete time hedging with liquidity risk." Finance Research Letters 9, no. 3 (2012): 135–43. http://dx.doi.org/10.1016/j.frl.2012.02.002.

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9

Park, Sang-Hyeon, and Kiseop Lee. "Hedging with Liquidity Risk under CEV Diffusion." Risks 8, no. 2 (2020): 62. http://dx.doi.org/10.3390/risks8020062.

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We study a discrete time hedging and pricing problem in a market with the liquidity risk. We consider a discrete version of the constant elasticity of variance (CEV) model by applying Leland’s discrete time replication scheme. The pricing equation becomes a nonlinear partial differential equation, and we solve it by a multi scale perturbation method. A numerical example is provided.
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10

Baule, Rainer, and Philip Rosenthal. "Time-Discrete Hedging of Down-and-Out Puts with Overnight Trading Gaps." Journal of Risk and Financial Management 15, no. 1 (2022): 29. http://dx.doi.org/10.3390/jrfm15010029.

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Hedging down-and-out puts (and up-and-out calls), where the maximum payoff is reached just before a barrier is hit that would render the claim worthless afterwards, is challenging. All hedging methods potentially lead to large errors when the underlying is already close to the barrier and the hedge portfolio can only be adjusted in discrete time intervals. In this paper, we analyze this hedging situation, especially the case of overnight trading gaps. We show how a position in a short-term vanilla call option can be used for efficient hedging. Using a mean-variance hedging approach, we calculate optimal hedge ratios for both the underlying and call options as hedge instruments. We derive semi-analytical formulas for optimal hedge ratios in a Black–Scholes setting for continuous trading (as a benchmark) and in the case of trading gaps. For more complex models, we show in a numerical study that the semi-analytical formulas can be used as a sufficient approximation, even when stochastic volatility and jumps are present.
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