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Barrier Option Pricing with Model Averaging Methods under Local Volatility Models
Namhyoung Kim,Kyu-Hwan Jung,Jaewook Lee,Gyu-Sik Han 대한산업공학회 2011 Industrial Engineeering & Management Systems Vol.10 No.1
In this paper, we propose a method to provide the distribution of option price under local volatility model when market-provided implied volatility data are given. The local volatility model is one of the most widely used smile-consistent models. In local volatility model, the volatility is a deterministic function of the random stock price. Before estimating local volatility surface (LVS), we need to estimate implied volatility surfaces (IVS) from market data. To do this we use local polynomial smoothing method. Then we apply the Dupire formula to estimate the resulting LVS. However, the result is dependent on the bandwidth of kernel function employed in local polynomial smoothing method and to solve this problem, the proposed method in this paper makes use of model averaging approach by means of bandwidth priors, and then produces a robust local volatility surface estimation with a confidence interval. After constructing LVS, we price barrier option with the LVS estimation through Monte Carlo simulation. To show the merits of our proposed method, we have conducted experiments on simulated and market data which are relevant to KOSPI200 call equity linked warrants (ELWs.) We could show by these experiments that the results of the proposed method are quite reasonable and acceptable when compared to the previous works.
Portfolio Optimization with Groupwise Selection
Namhyoung Kim,Suvrit Sra 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.4
Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.
Model Averaging Methods for Estimating Implied and Local Volatility Surfaces
Namhyoung Kim,Jaewook Lee,Gyu-Sik Han 대한산업공학회 2009 Industrial Engineeering & Management Systems Vol.8 No.2
In this paper, we review widely used methods to extract local volatility surfaces (LVSs) from implied volatility surfaces (IVSs) and suggest a model averaging method for constructing implied and local volatility surfaces weighted by trading volumes. It makes use of model averaging method by means of bandwidth priors, and then produces a robust LVS estimation. The method is shown to provide the information about the confidence interval of estimators as well as a rather less variable weighted mean value for the IVS and LVS. To show the merits of our proposed method, we conduct simulations on equity-linked warrants (ELWs) with reasonable and acceptable results.
A Multivariate GARCH Analysis on International Stock Market Integration
Namhyoung Kim 한국경영과학회 2015 Management Science and Financial Engineering Vol.21 No.1
Financial integration is a phenomenon in which global financial markets are closely connected with each other. This article investigates the integration of Korean stock market with other stock markets using a multivariate GARCH analysis. We chose total seven countries including Korea for this paper based on the amount of export and then we chose major stock indices which can be thought as representative stock markets of those countries. The empirical analysis has shown that countries’ financial integration.
Estimation and prediction under local volatility jump–diffusion model
Kim, Namhyoung,Lee, Younhee Elsevier 2018 PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIO Vol.491 No.-
<P><B>Abstract</B></P> <P>Volatility is an important factor in operating a company and managing risk. In the portfolio optimization and risk hedging using the option, the value of the option is evaluated using the volatility model. Various attempts have been made to predict option value. Recent studies have shown that stochastic volatility models and jump–diffusion models reflect stock price movements accurately. However, these models have practical limitations. Combining them with the local volatility model, which is widely used among practitioners, may lead to better performance. In this study, we propose a more effective and efficient method of estimating option prices by combining the local volatility model with the jump–diffusion model and apply it using both artificial and actual market data to evaluate its performance. The calibration process for estimating the jump parameters and local volatility surfaces is divided into three stages. We apply the local volatility model, stochastic volatility model, and local volatility jump–diffusion model estimated by the proposed method to KOSPI 200 index option pricing. The proposed method displays good estimation and prediction performance.</P>
Portfolio Optimization with Groupwise Selection
Kim, Namhyoung,Sra, Suvrit Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.4
Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.
박남형(Namhyoung Park),오장훈(Janghoon Oh),윤동원(Dongweon Yoon),송영준(Young-Joon Song),김종성(Jong-Sung Kim),신경찬(Kyung-Chan Shin) 한국정보기술학회 2016 한국정보기술학회논문지 Vol.14 No.4
In modern electronic warfare, because a variety of electronic devices are being used in the fields, TDL(Tactical Data Link) protocols such as Link-16 are receiving more attention as not only a communication technology but also a real-time command and control system. However, interference may occur if wireless communication and surveillance devices operate simultaneously in a same band. Therefore, it is needed to analyse system performance in in-band interference based on actual measurement data for operation of Link-16 TDL. In this paper, we propose a method to calculate the probability of successful communication of Link-16 system in an interference-rich L-band frequency using actual measurement data. The calculated values are used to analyse the BER(Bit Error Rate) and PER(Packet Error Rate) performance of Link-16 system in the L-band using a software simulator.