• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.755-763
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• 2008

This paper approaches the problem of option pricing in an incomplete market, where the underlying asset price process follows a compound Poisson model. We assume that the price process follows a compound Poisson model under an equivalent martingale measure and it converges weakly to the Black-Scholes model. First, we express the option price as the expectation of the discounted payoff and expand it at the Black-Scholes price to obtain a pricing formula with three unknown parameters. Then we estimate those parameters using the market option data. This method can use the option data on the same stock with different expiration dates and different strike prices.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.25-39
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• 2016

Asset prices decline sharply and stock markets collapse when financial crisis happens. Recently we have encountered more frequent financial crises than ever. 1998 currency crisis and 2008 global financial crisis triggered academic researches on early warning systems that aim to detect the symptom of financial crisis in advance. This study proposes a risk recovery index for detection of good opportunities from financial market instability. We use SVM classifier algorithms to separate recovery period from unstable financial market data. Input variables are KOSPI index and V-KOSPI200 index. Our SVM algorithms show highly accurate forecasting results on testing data as well as training data. Risk recovery index is derived from our SVM-trained outputs. We develop a trading system that utilizes the suggested risk recovery index. The trading result records very high profit, that is, its annual return runs to 121%.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.721-733
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• 2011

We consider the state price densities that are implicit in financial asset prices. In the pricing of an option, the state price density is proportional to the second derivative of the option pricing function and this relationship together with no arbitrage principle imposes restrictions on the pricing function such as monotonicity and convexity. Since the state price density is a proper density function and most of the shape constraints are caused by this, we propose to estimate the state price density directly by specifying candidate densities in a flexible nonparametric way and applying methods of regularization under extra constraints. The problem is easy to solve and the resulting state price density estimates satisfy all the restrictions required by economic theory.

• The Pure and Applied Mathematics
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• v.27 no.1
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• pp.43-50
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• 2020

We investigate the domain of influence of the local volatility function on the solutions of the general Black-Scholes model. First, we generate the sample paths of underlying asset using the Monte Carlo simulation. Next, we define the inner and outer domains to find the effective volatility region. To confirm the effect of the inner domain, we use the root mean square error for the European call option prices, and then change the values of volatility in the proposed domain. The computational experiments confirm that there is an effective region which dominates the option pricing.

• Management & Information Systems Review
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• v.26
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• pp.1-26
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• 2008

Since Capital Asset Pricing Model(CAPM) was proposed in the early 1960s by William Sharpe(1964) and John Lintner(1965) researchers have investigated the validity of the model. The results of empirical researches do not show that expected returns of stocks seem to be determined solely by systematic risk of the stocks as precicted by CAPM. In this paper the relationship between transaction volume and expected returns of stocks was investigated. Empirical cross-sectional analysis about the data collected from Stock Market of Korea Exchange shows transaction volume and variability of stock returns play an important role in pricing assets. The well-known variables which were used traditionally to explain the differences of expected returns among stocks such as the size and beta of a stock seems to be unimportant in pricing assets.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.45-57
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• 2004

The purpose of this paper is studying the valuation of option prices in Incomplete markets. A market is said to be incomplete if the given traded assets are insufficient to hedge a contingent claim. This situation occurs, for example, when the underlying stock process follows jump-diffusion processes. Due to the jump part, it is impossible to construct a hedging portfolio with stocks and riskless assets. Contrary to the case of a complete market in which only one equivalent martingale measure exists, there are infinite numbers of equivalent martingale measures in an incomplete market. Our research here is focusing on risk minimizing hedging strategy and its associated minimal martingale measure under the jump-diffusion processes. Based on this risk minimizing hedging strategy, we characterize the dynamics of a risky asset and derive the valuation formula for an option price. The main contribution of this paper is to obtain an analytical formula for a European option price under the jump-diffusion processes using the minimal martingale measure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.261-262
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• 2013

In this paper, we subject to MA area to identifying improve the performance of equipment and prices down. When we replace the equipment, the cost savings available area, servers, storage, the As-is vs To-be of software compared to the cost. Thus, based decision-making is utilized.

• Journal of Navigation and Port Research
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• v.43 no.2
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• pp.134-141
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• 2019

The objective of this study was to establish whether global macroeconomic indicators affect the profitability of Korean shipping companies by using panel regression analysis. OROA (operating return on assets) and ROA (ratio of net profit to assets) were selected as proxy variables for profitability. OROA and ROA were used as dependent variables. The world GDP growth rate, interest rate, exchange rate, stock index, bunker price, freight, demand and supply of the world shipping market were set as independent variables. The size of the firm was added to the control variable. For small-sized firms, OROA was not affect by macroeconomic indicators. However, ROA was affected by variables such as interest rates, bunker prices, and size of firms. For medium-sized firms, OROA was affected by demand, supply, GDP, freight, and asset variables. However, macroeconomic indicators did not affect ROA. For large-sized firms, freight, GDP, and stock index (SCI; Shanghai Composite Index) have an effect on OROA. ROA was analyzed to be influenced by bunker price and SCI.

• Journal of Information Technology Applications and Management
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• v.29 no.2
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• pp.17-25
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• 2022

Although the two types of currencies compete, the possibility of a virtual currency price bubble is diagnosed by assuming an economic model with currencies (won, virtual currency) that are intrinsically worthless. The won is supplied by the central bank to achieve the price stability target, while the supply of virtual currency increases by a fixed number. According to the basic price theory equation, as a simple proposition, cryptocurrency prices form a Martin Gale process [Schilling and Uhlig, 2019, p.20]. Based on the existing theoretical proposition, we applied the variance ratio verification method [Linton and Smetanina, 2016] and a simple technical chart method for empirical analysis. For the purpose of this study, the possibility of a bubble was empirically analyzed by analyzing the price volatility formed in the Korean virtual currency market over the past year, and brief policy implications for this were presented.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.