• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.343-352
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• 2022

We present the user-friendly graphical user interface design and implementation of Monte Carlo simulation (MCS) for computing option price of the four-underlying asset step-down equity linked securities (ELS) using the Android platform. The ELS has been one of the most important and influential financial products in South Korea. Most ELS products are based on one-, two-, and three-underlying assets. However, currently there is a demand for higher coupon payment from ELS products because of the increased interest rate in financial market. In order to allow the investors to have higher coupon payment, it is necessary to design a multi-asset ELS such as four-asset step-down ELS. We conduct the computational experiments to demonstrate the performance of the Android platform for pricing four-asset step-down ELS. Furthermore, we perform a comparison test with a three-asset step-down ELS.

• The Journal of Information Systems
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• v.18 no.3
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• pp.351-373
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• 2009

An index fund is a collective investment scheme that aims to replicate the movements of an index of a specific financial market regardless of market conditions. An index fund is a popular investment alternative because it is much cheaper to run than an active fund and it performs better than actively managed funds. This paper illustrates the usefulness of wavelet analysis in constructing an index fund. The wavelet analysis can decompose the time series data in frequency domain as well as in time domain. The major findings of this paper are as follows. First, the beta coefficient that represents the systematic risk has the scale dependent property. This result can provide important information to the investors with various investment time frequency. Investors can use the betas corresponding to their investment frequencies among the various scale betas estimated by wavelet analysis. Second, we can find the usefulness of wavelet analysis in constructing index fund because the wavelet technique gives less tracking error(difference between the index performance and the index fund performance) than the traditional constructing techniques. The result of this study implies that the wavelet techniques can be an important analytic method to the other financial markets such as option market, futures market, bond markets and currency market.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Journal of Distribution Science
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• v.7 no.1
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• pp.35-53
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• 2009

Sees the market where home appliance and network equipment, the communication service enterprises are new recently the home network market of the most which has an interest in the home network is being activated the newly-built high-class apartment in the center. The company building leads because not being option of the case last customer of newly-built market and must do a business . marketing. So newly-built market the demand grasp which is individual leads sale activation with difficult and that to creates a benefit there is a limit judges and axis market in the object hereafter demand at even the popular house the function to prepare in being magnified is simple and there is a possibility of saying that a more effort is demanded in supply style video phone market opening up where the price is cheap. Saw with like this reason from, analyzes the concept and a market trend of the video phone, grasps distribution channel forms and A/S handling systems and there is the goal finds the video phone sale revitalization plan which is suitable in all market.

• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.735-761
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• 2004

As a possible alternative to Traditional Discounted Cash Flow Method, "Option Pricing Model" has drawn academic attentions for the last a few decades. However, it has failed to replace traditional DCF method practically due to its mathematical complexity. This paper introduces an option pricing valuation model specifically adjusted for the natural resource development projects. We add market information and industry-specific features into the model so that the model remains objective as well as realistic after the adjustment. The following two features of natural resource development projects take central parts in model construction; product price is a unique source of cash flow's uncertainty, and the projects have cost structure from capital-intense industry, in which initial capital cost takes most part of total cost during the projects. To improve the adaptability of Option Pricing Model specifically to the natural resource development projects, we use Two-Factor Model and Long-term Asset Model for the analysis. Although the model introduced in this paper is still simple and reflects limited reality, we expect an improvement in applicability of option pricing method for the evaluation of natural resource development projects can be made through the process taken in this paper.

• Management & Information Systems Review
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• v.28 no.1
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• pp.71-97
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• 2009

In this study, I compare the ability of alternative accounting method for employee stock option to reflect firm value using the Ohlson's(1995) valuation model for 200 firms. The each methods, I compare are employee stock option expense recognition based on the K-GAAP disclosures, and asset recognition at the grant date based on the SFAS No. 123 Exposure Draft: Accounting for stock-based compensation. The model include: (1) a model that uses reported earnings, equity book value, and compensation expense based on the K-GAAP disclosures; (2) a model that uses pro-forma earnings, equity book value and adds a measure of the unrecognized asset arising form granting of employee stock options. Finding form estimating equations that the K-GAAP method for calculating compensation has no explanatory power, and the SFAS No.123 Draft Exposure method for arising asset and fair value compensation better captures than market's perception of the economic impact of stock options on firm values. However, the correlation of employee stock option compensation expense is positive. These results suggest that incentive benefits derived from employee stock option plans outweigh the cost associated with plan. In addition, I couldn't find evidence that company in KOSDAQ that have high growth potential benefit more from employee stock option plan compared to lager, more mature firm in SEC.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.469-476
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• 2009

Recent collapse of shipping market right after unprecedent surge clearly demonstrates that shipping industry is extremely risky. Due to the volatile movements of the freight rates, investors tend to ask higher rate of return; higher required return reduces the total net present value of the investment project. For several decades, the Discounted Cash Flow(DCF hereafter) analysis has been the most frequently used valuation technique. However, the main problem of the DCF analysis is its assumption that the discount rate would stay the same during the project life. In other words, it usually does not address the decisions that managers have after a project has been accepted. The purpose of this study is investigate a new valuation method of investment: the Real Option Analysis(ROA hereafter) on ship investment. By replacing the existing valuation methods with the new one, the research will present a new perspective on investment with uncertainty. While uncertainty increases risk of investment and consequently discounts the value of it in the traditional feasibility analysis, in the ROA, a new valuation method which will be addressed in the research, uncertainty means some additional value of flexibility so that the tool can help investors produce more accurate decisions. Contrary to the DCF analysis, the ROA takes managerial flexibilities into account. In reality, capital budgeting and project management is typically dynamic, rather than static in nature. The ROA finds and assesses the values of managerial flexibilities or real options in the investments. The main structures of the research will be as follows: (1) overview of the ship investment project, (2) evaluation of the project by the Net Present Value analysis, (3) evaluation of the same project by the Real Option Analysis, (4) comparision of the two techniques.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.272-275
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• 2009

Carbon finance is the investment in Greenhouse Gas (GHG) emission reduction projects in developing countries and countries with economies in transition within the framework of the Kyoto Protocol's Clean Development Mechanism (CDM) or Joint Implementation (JI) and with creation of financial instruments, i.e., carbon credits, which are tradable in carbon market. The additional revenue generated from carbon credits will increase the bankability of projects by reducing the risks of commercial lending or grant finance. Meantime, it has also demonstrated numerous opportunities for collaborating across sectors, and has served as a catalyst in bringing climate issues to bear in projects relating to rural electrification, renewable energy, energy efficiency, urban infrastructure, waste management, pollution abatement, forestry, and water resource management. Establishing additionality is essential for successful CDM project development. One of the key steps is the investment analysis. As guided by UNFCCC, financial indicators such as IRR, NPV, DSCR etc are most commonly used in both Option II & Option III. However, economic indicator such as Economic Internal Rate of Return(EIRR) are often overlooked in Option III even it might be more suitable for the project. This could be due to the difficulties in economic analysis. Although Asian Development Bank(ADB) has given guidelines in evaluating EIRR, there are still large amount of works have to be carried out in estimating the economic, financial, social and environmental benefits in the host country. This paper will present a case study of a CDM development of a 18 MW hydro power plant with carbon finance option in central Vietnam. The estimation of respective factors in EIRR, such as Willingness to Pay(WTP), shadow price etc, will be addressed with the adjustment to Vietnam local provincial factors. The significance of carbon finance to Vietnam renewable energy development will also be addressed.

• Journal of Distribution Science
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• v.14 no.11
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• pp.29-36
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• 2016

Purpose - Intense debate is occurring over support for farmers in Korea, specifically on the justification, policy design, and equality issues of the farm support programs. Given this debate, a new type of farm program in the US, a market flexible revenue program(the Average Crop Revenue Election, ACRE), is examined. ACRE stands in contrast to traditional programs that tie payments to price and have parameters that are fixed or change only infrequently. Research design, data, and methodology - Based on the ACRE program formulas, the potential payments are estimated by crop year, program crop and geographical area using the FSA acreage and payment rate data. Results - If all US farm program acres were in ACRE over the 2009-2013 crop years, payments would have totaled $7.95 billion or 1.2 percent of average market receipts for US crops. Enacting ACRE as a revenue program instead of a similarly-structured price-only program increased payments by $1.75 billion or 28 percent. Conclusions - Potential payments by ACRE largely reflected the distribution of the value of production across the program crops eligible for ACRE as well as across state geographical areas. If program parameters can be made acceptable and if data availability issues can be addressed, market flexible revenue programs offer a farm policy option that can address many of the concerns that have arisen over farm policy in Korea.

• International Journal of Contents
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• v.17 no.2
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• pp.1-8
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• 2021

Online streaming wars are intensifying. Netflix is known as the market leader in the streaming business. However, since 2019, Netflix has been losing subscribers in the United States and is at a turning point where it needs to reassess its current position in the market. While Netflix is losing dominance, rivals Amazon Prime and Hulu continue to gain market shares. Studies from Deloitte and PricewaterhouseCoopers indicated a new shift in the streaming landscape caused by the abundance of streaming options and rising subscription costs. Recent surveys showed that consumers are excited about new streaming services, such as Disney +. Nearly two-thirds of consumers intend to terminate or downgrade one or more of their current subscriptions to make room for a new service. Moreover, it seems that consumers want ad-supported options. In Deloitte's latest Digital Media Trends survey, 65% responded that they would watch ads to eliminate or reduce subscription costs. Seventy percent of Hulu's subscribers choose its lower-priced ad-supported plan. NBC recently launched its own streaming service, Peacock, with a free ad-supported option. This opposes Netflix's brand identity of "no ads" and premium differentiation. With increasing pressure from competition and the growing risk of subscriber loss, Netflix needs to diversify its price plans. The company could try implementing the lower-priced mobile-only plan they are currently testing or plan to test in other regions. Netflix should also consider features or benefits for loyal subscribers to maintain a stronger consumer base.