• The Pure and Applied Mathematics
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• v.21 no.4
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• pp.295-305
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• 2014

Yan & Hanson [8] and Makate & Sattayatham [6] extended Bates' model to the stochastic volatility model with jumps in both the stock price and the variance processes. As the solution processes of finding the characteristic function, they sought such a function f satisfying $$f({\ell},{\nu},t;k,T)=exp\;(g({\tau})+{\nu}h({\tau})+ix{\ell})$$. We add the term of order ${\nu}^{1/2}$ to the exponent in the above equation and seek the explicit solution of f.

• The Korean Journal of Financial Management
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• v.15 no.1
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• pp.73-94
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• 1998

This paper contributes to the ongoing controversy over price and volatility spillovers across countries by providing new evidence with the futures data of the S&P 500 and Nikkei 225 index futures contacts from January 3, 1990 to April 16, 1996. Based on the two-stage symmetric and asymmetric GARCH models we document that both the U.S. and the Japanese daytime returns significantly influence the subsequent overnight returns of the other market. We find no signs of volatility spillovers between two international markets with the symmetric model. However, with the asymmetric models, we find that the magnitude of foreign negative shocks are different from the positive ones. The findings generally suggest that the two markets are more sensitive to the bad news originating in the other market. This nature of transmission between two markets would have important implications to the arbitragers who are trying to exploit the short-term dynamics of price and volatility movements across two security markets.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.159-166
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• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.41-49
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• 2020

This study investigates the short-run and long-run causal behavior of the Philippine stock market index volatility under vector error correction environment. The variables were tested first for stationarity and then long-run equilibrium relationship. Moreover, an impulse response function was estimated to examine the extent of innovations in the independent variables in explaining the Philippine stock market index volatility. The results reveal that the volatility of the Philippine stock market index exhibit long-run equilibrium relationship with Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil prices. The short-run dynamics-based VECM estimates indicate that in the short-run, increases (i.e., depreciation) in Peso-Dollar exchange rate cause PSEI volatility to increase. As for the London Interbank Offered Rate, it causes increases in PSEI volatility in the short-run. The adjustment coefficients used with the long-run dynamics validates the presence of unidirectional causal long-run relationship from Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil prices to PSEI volatility, and bidirectional causal long-run relationship between PSEI volatility and London Interbank Offered Rate. The impulse response functions developed within the VECM framework demonstrate the positive and negative reactions of PSEI volatility to unanticipated Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil price shocks.

• Korean Journal of Construction Engineering and Management
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• v.17 no.1
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• pp.76-82
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• 2016

Decision-making in construction projects often include options features. Such embedded options are difficult to value properly and many decision makers do not have experience in option analysis. The purpose of this paper is to demonstrate how real option analysis can be used to value capital expenditures on construction materials. We propose a real option framework to evaluate decision-making processes involving the purchase of construction materials. A case study was conducted by evaluating the purchase decision-making of solar cells, a good with high price volatility. Using real option analysis two strategies to improve the financial feasibility of installing a solar panel system were derived. The first strategy involves using a price cap that gives the project manager the right, but not obligation, to buy the modules for a predefined price during the next year. The second strategy is to defer the purchase of the solar cells until future price information becomes clearer. Both of the strategies in the case study were valued using the binominal model. This study will help to improve the financial feasibility of purchasing construction materials with high price volatility by including the value of managerial flexibility.

• Communications of the Korean Mathematical Society
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• v.28 no.3
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• pp.615-633
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• 2013

We use a power series expansion method to get an analytic approximation value for the quanto option price under the Hull and White stochastic volatility model, which turns out to be accurate enough by comparing with the simulation prices using Monte Carlo method.

• Korean Management Science Review
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• v.28 no.3
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• pp.61-72
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• 2011

This study suggests a DEA(Data Envelopment Analysis) based model to evaluate the value of corporate stock. The model integrating PER(Price-Earning Ratio), PBR(Price-BookValue Ratio), PSR(Price-Sales Ratio) and volatility in DEA structure has an advantage of overcome the limitation of traditional financial ratio based models. In order to show the effectiveness of the suggested model. we compare the performance of portfolio composed by DEA approach with those of portfolios made by traditional approaches such as PER, PBR, and PSR in terms of stock return and volatility. Specifically, we use the data of all the enterprises listed on the S&P 500 in the U.S. in 2007 and 2009 as the sample data for the experiments. The results of the experiments show that the performance of the DEA approach is clearly better than those of other approaches. Particularly, in sharply plummeting market, the performance of the DEA approach is shown to be prominently better than those of other approaches as the DEA approach reflects investment risk as well as profitability and growth. The DEA score combining the existing investment indices may serve as a useful barometer for selecting a stable and profitable portfolio.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.455-475
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• 2009

According to the returns of Housing and business cycle over the period 1992 to 2007, it is a measure of the total volatility faced by investors in Housing properties. First, it isn't a distinct difference from business cycle contrary to U.S. Second, the rise of purchase price in total apartments moves up the consumer price index. According to the cross-sectional dispersion of returns and growth in net operating income (NOI) of apartments, industrial, retail and office properties using panel data for U.S. metropolitan areas over the period 1986 to 2002, it is a measure of the total volatility faced by investors in commercial real estate. To the extent that most of that volatility is difficult to diversify, cross-sectional dispersion may be an appropriate measure of risk.

• Journal of Distribution Science
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• v.7 no.1
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• pp.91-104
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• 2009

The Purpose of this study is to reveal interactive relation between Product Life Cycle and Market Risk Management. PLC analyzes consumer buying behavior, volatility of price and sales at market place from the viewpoint of Marketing so that company can improve management result. This study is attempt to analyze PLC from a comprehensive and integrating angle by using MRM. In order to find out relationship between two theories, this study is an extraction of the factors that affects the management result commonly on PLC and MRM. Then, this study analyzes the factors of PLC from the viewpoint of MRM. The result shows that the factors of PLC and MRM have relation with in terms of volatility of price, trade risk and market share.

• Korean Business Review
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• v.19 no.1
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• pp.81-92
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• 2006

This study investigates the relation between institutional investor's net purchase and the volatility of KOSPI. Some portion of volatility in stock prices comes from noise trading of irrational traders. Observed volatility may be defined as the sum of the portion caused by information arrival, fundamental volatility, and the portion caused by noise trading, transitory volatility. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. Most studies investigates the effect on the observed volatility. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Estimation results show that institutional investor's net purchase was not significantly related to all kinds of volatility(observed volatility, fundamental volatility and transitory volatility). This means that institutional investor's net purchase did not increase noise trading.