• Korean Journal of Mathematics
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• 제13권1호
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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.

• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.1-10
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• 2021

This paper compares the performance of Fama-French three-factor and five-factor models using a dataset of 20 Pakistani commercial banks for the period 2011 to 2020. We focus on an emerging economy as the findings from earlier studies on developed countries cannot be generalized in emerging markets. For empirical analysis, twelve portfolios were developed based on size, market capitalization, investment strategy, and growth. Subsequently, we constructed five Fama-French factors namely, R_M, SMB, HML, RMW, and CMA. The OLS regression technique with robust standard errors was applied to compare the predictive power of both the Fama-French models. Further, we also compared the mean-variance efficiency of the Fama-French models through the GRS test. Our empirical analysis provides three unique and interesting findings. First, both asset pricing models have similar predictive power to explain the expected portfolio returns in most cases. Second, our results from the GRS test suggest that there is no noticeable difference in the mean-variance efficiency of one asset pricing model over the other. Third, we find that all factors of both Fama-French models are statistically significant and are important for explaining the volatility of expected commercial bank returns in the context of Pakistan.

• The Journal of Asian Finance, Economics and Business
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• 제7권8호
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• 재무관리논총
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• 제2권2호
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• pp.171-211
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• 1995

Relatively little is known about the relationship between taxes and asset prices. Differential tax treatment of assets in the same risk class implies differential pricing. Conversely, the ability of tax-exempt investors to engage in tax arbitrage should drive any pricing differences away. The differential tax treatment of classes of US Treasury securities provides a straightforward setting for the examination of possible tax-effects in asset prices. Using the Cox-Ingersoll-Ross Term Structure Model as our framework, we examine the pricing of US Treasury securities over two distinct tax regimes. Evidence that tax effects are not arbitraged away is presented.

• 아태비즈니스연구
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• 제11권3호
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• pp.199-215
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• 2020

Purpose - This article tries to test if the conditional consumption capital asset pricing model (CCAPM) with bank credit for household as a conditional variable can explain the cross-sectional variation of stock returns in Korea. The performance of conditional CCAPM is compared to that of multifactor asset pricing models based on Arbitrage Pricing Theory. Design/methodology/approach - This paper extends the simple CCAPM to the conditional version of CCAPM by using bank credit for household as conditioning information. By employing KOSPI and KOSDAQ stocks as test assets from the second quarter of 2003 to the first quarter of 2018, this paper estimates risk premiums of conditional CCAPM and a variety of multifactor linear models such as Fama-French three and five-factor models. The significance of risk factors and the adjusted coefficient of determination are the basis for the comparison in models' performances. Findings - First, the paper finds that conditional CCAPM with bank credit performs as well as the multifactor linear models from Arbitrage Pricing theory on 25 test assets sorted by size and book-to-market. When using long-term consumption growth, the conditional CCAPM explains the cross-sectional variation of stock returns far better than multifactor models. Not only that, although the performances of multifactor models decrease on 75 test assets, conditional CCAPM's performance is well maintained. Research implications or Originality - This paper proposes bank credit for household as a conditional variable for CCAPM. This enables CCAPM, one of the most famous economic asset pricing models, to conform with the empirical data. In light of this, we can now explain the cross-sectional variation of stock returns from an economic perspective: Asset's riskiness is determined by its correlation with consumption growth conditional on bank credit for household.

• 응용통계연구
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• 제24권1호
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• pp.83-92
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• 2011

주식은 그 자체로도 투자의 대상이며, 또한 옵션의 기초자산으로서 옵션의 가격을 평가하는 기본도구로 사용되고 있기에, 주식에 대한 정확한 예측값 도출은 매우 중요하다고 불 수 있다.주식의 가치평가를 위하여 기존 연구들은 대표적으로 GARCH 류의 모형과 SV(stochastic volatility, 확률변동성)류의 모형을 사용하였다. 본 연구에서는 SV 모형에 대해서 초점을 맞추어 KOSPI200 지수를 실증분석하였다. 특히 Durham (2008)의 방법론에 따라서 로그 SV 모델에 변동성지수(VKOSPI 지수)를 추가로 고려하여 모델의 정확도 향상을 기대하였다. VKOSPI 지수는 KOSPI200의 옵션으로부터 계산된 미래에 대한 기대 변동성으로, 주식과 옵션간의 유기적 관련성을 바탕으로 추정하기에 그 의미가 있다. 자료는 2003년 1월2일부터 2010년 9월 24일을 기간으로 사용하였다.

• 경영과정보연구
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• 제26권
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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.

• East Asian Economic Review
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• 제18권3호
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• pp.253-276
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• 2014

We examine which traditional asset pricing variables together with bank-specific accounting variables explain the cross-sectional variation of future bank stock returns, using a firm-level data of eight Asian countries. Our empirical evidence shows that exchange rate risk, firm size, the book-to-market ratio, and the net income ratio are important in explaining future bank stock returns during normal times. However, during the Global Financial Crisis period, different variables such as local market beta, illiquidity risk, equity ratio, and off-balance sheets ratio were statistically significant. Thus, researchers and policy practitioners should monitor these variables during normal times as well as during times of crisis.

• The Journal of Asian Finance, Economics and Business
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• 제5권1호
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• pp.11-16
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• 2018

This research examines the alternative ways of estimating the coefficient of non-diversifiable risk, namely beta coefficient, in Capital Asset Pricing Model (CAPM) introduced by Sharpe (1964) that is an essential element of assessing the value of diverse assets. The non-parametric methods used in this research are the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator). The Jackknife, the resampling technique, is also employed to validate the results. According to finance literature and common practices, these coecients have often been estimated using Ordinary Least Square (LS) regression method and monthly return data set. The empirical results of this research pointed out that the robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) performed much better than Ordinary Least Square (LS) in terms of eciency for large-cap stocks trading actively in the United States markets. Interestingly, the empirical results also showed that daily return data would give more accurate estimation than monthly return data in both Ordinary Least Square (LS) and robust Least Trimmed Square (LTS) and Maximum likelihood type of M-estimator (MM-estimator) regressions.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.117-123
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• 2020

The objective of this study is to examine whether the four-factor model explains variation in the expected return of stocks on the Stock Exchange of Thailand. The study used individual monthly data for all stock with continuous trading on the Stock Exchange of Thailand. The study used sample data of 429 listed stocks to construct 8 portfolios bases on the industries. In this study, subject to market factors such as size, the book-to-market ratio, the market beta, and stock liquidity are taken into account. The Empirical analysis reveals that not all of the variables included in the four-factor asset pricing model are statistically significant to do affect the formation of the rate of return on stocks calculated on a monthly basis. The result shows that market beta, stock liquidity, and the book-to-market ratio has a significant increase in the rate of return on shares listed on the Consumer Products. It is therefore apparent that at least in respect of monthly analysis, the predictions of bass models in the field of modern finance theory systematic risk measured by the beta coefficient did play a significantly important role in the formation of the rate of return on the Stock Exchange of Thailand.