• Korean Journal of Mathematics
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• v.13 no.1
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• pp.19-34
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• 2005

Pricing and hedging strategy for European options of jump-type asset models, which are derived from a stochastic differential equations, are discussed.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.293-310
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• 2007

Recently a risk measure pricing and hedging is replacing a utility-based maximization problem in the literature. In this paper, we treat the optimal problem of risk measure pricing and hedging in the friction market, i.e. in the presence of transaction costs. The risk measure pricing is also verified with the contexts in the literature.

• Journal of the Korean Mathematical Society
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• v.41 no.3
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• pp.513-533
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• 2004

We present the pricing and hedging method for options with general payoffs in the presence of transaction costs. The convexity of the payoff function-gamma of the options- is an important issue under transaction costs. When the payoff function is convex, Leland-style pricing and hedging method still works. However, if the payoff function is of general form, additional assumptions on the size of transaction costs or of the hedging interval are needed. We do not assume that the payoff is convex as in Leland 〔11〕 and the value of the Leland number is less (bigger) than 1 as in Hoggard et al. 〔10〕, Avellaneda and Paras 〔1〕. We focus on generally recognized asymmetry between the option sellers and buyers. We decompose an option with general payoff into difference of two options each of which has a convex payoff. This method is consistent with a scheme of separating out the seller's and buyer's position of an option. In this paper, we first present a simple linear valuation method of general payoff options, and also propose in the last section more efficient hedging scheme which costs less to hedge options.

• Bulletin of the Korean Mathematical Society
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• v.56 no.5
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• pp.1129-1141
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• 2019

We propose a stochastic delay financial model which describes influences driven by historical events. The underlying is modeled by stochastic delay differential equation (SDDE), and the delay effect is modeled by a stopping time in coefficient functions. While this model makes good economical sense, it is difficult to mathematically deal with this. Therefore, we circumvent this model with similar delay effects but mathematically more tractable, which is by the backward time integration. We derive the option pricing equation and provide the option price and the perfect hedging portfolio.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.4 no.2
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• pp.77-84
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• 2000

Black-Scholes equation arising from option pricing in the presence of cost in trading the underlying asset is derived. The transaction cost is chosen precisely and generalized to reflect the trade in the real world. Furthermore the concept of the bandwidth is introduced to obtain the better rehedging. The model with bandwidth derived in this paper can be used to calculate the more accurate option price numerically even if it is nonlinear and more complicated than the models shown before.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.227-246
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• 2009

This study examines the dynamic hedging performances of the Black-Scholes model and Heston model when stock prices drift with stochastic volatilities. Using Monte Carlo simulations, stock prices consistent with Heston's(1993) stochastic volatility option pricing model are generated. In this circumstance, option traders are assumed to use the Black- Scholes model and Heston model to implement dynamic hedging strategies for the options written. The results of simulation indicate that the hedging performance of a mis-specified Black-Scholes model is almost as good as that of a fully specified Heston model. The implication of these results is that the efficacy of the dynamic hedging performances on evaluating the specifications of alternative option models can be limited.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.15 no.1
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• pp.1-17
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• 2011

A new method for option pricing based on the trinomial tree method is introduced. The new method calculates the local average of option prices around a node at each time, instead of computing prices at each node of the trinomial tree. Local averaging has a smoothing effect to reduce oscillations of the tree method and to speed up the convergence. The option price and the hedging parameters are then obtained by the compact scheme and the Richardson extrapolation. Computational results for the valuation of European and American vanilla and barrier options show superiority of the proposed scheme to several existing tree methods.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.170-177
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• 2011

We present an improved binomial method for pricing financial deriva-tives by using cell averages. After non-overlapping cells are introduced around each node in the binomial tree, the proposed method calculates cell averages of payoffs at expiry and then performs the backward valuation process. The price of the derivative and its hedging parameters such as Greeks on the valuation date are then computed using the compact scheme and Richardson extrapolation. The simulation results for European and American barrier options show that the pro-posed method gives much more accurate price and Greeks than other recent lattice methods with less computational effort.

• The Pure and Applied Mathematics
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• v.20 no.4
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• pp.287-298
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• 2013

A standard deviation has been a starting point for a mathematical definition of risk. As a remedy for drawbacks such as subadditivity property discouraging the diversification, coherent and convex risk measures are introduced in an axiomatic approach. Choquet expectation and g-expectations, which generalize mathematical expectations, are widely used in hedging and pricing contingent claims in incomplete markets. The each risk measure or expectation give rise to its own pricing rules. In this paper we investigate relationships among dynamic risk measures, Choquet expectation and dynamic g-expectations in the framework of the continuous-time asset pricing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.266-272
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• 2011

Real Time Pricing(RTP) is used not only to stabilize the price volatility in electricity market, but to hedge the price risk for Load Serving Entity(LSE). This paper presents an efficient method to reduce the risk of the price volatility in real-time electricity market. For designing the RTP, load patterns of customer are calculated by applying the demand elasticity and customer's utility is also analyzed to compute the RTP revenue through the risk-attribute of the LSE. In the end, the distribution of the LSE's profits can be evaluated to lead the optimal RTP value, depending on the level of customer's participation. Results from the case study based on PJM data are reported to illustrate the proposed method.