近年來由於市場型式為開放主體，在財務整合，商品區隔的環境下，投資人在進行投資時，應考量全方面的訊息，亦即國家內外部所有會影響股票市場的風險因子。而風險與報酬之間是否存在抵換關係，一直以來皆為備受討論的議題，從過去的文獻當中，研究者多以變異數作為衡量風險的代理，再透過各種不同的研究方法來估計風險報酬係數，但實證上並未獲得一致的結果。本文以1981年1月至2008年7月為研究期間，台灣與韓國之股價指數月資料為樣本，所使用之模型參考Turan G. Bali & Liuren Wu(2010)的研究論文，利用簡化過後的雙變量BEKK-GARCH(1，1)模型進行估計，探討台灣與韓國股票市場跨期收益與風險之關係。本文主要分為三大部分，首先先將台灣及韓國的股價指數以美元計價，針對全球市場觀察其風險以及持續性，並且利用共變異數來判別兩國股市分別為高風險或是低風險，再者，將台灣及韓國的股價指數分別以自己國家之幣別計算，將計算出之殘差估計個別國家股市風險，看是否兩國家內部的非經濟因素，例如:政治及軍事等，會影響股市的表現。最後一部份為前兩部分的整合，比較個別國家風險與全球市場風險對台灣及韓國股市的影響以及超額報酬與風險之間的抵換關係。實證結果顯示，不論就台灣或者是韓國而言，全球市場風險的風險與報酬係數皆為正向顯著，其中又以台灣之係數較為高，透露出若在承擔相同的全球市場風險時，台灣的投資人會較韓國的投資人要求較高的報酬。在匯率風險方面，本文採Turan G. Bali & Liuren Wu(2010)所使用的研究方法，將風險與報酬的抵換關係建立在不同國家的幣別之下進行估計，由結果發現，若以美元為單位來衡量風險報酬係數，則不論是台灣或韓國，在全球市場風險下，係數皆較小；若以個別貨幣來衡量，其台灣的風險與報酬抵換係數較大，韓國之係數則是由正值轉變為負值，代表匯率的確會對市場風險值有所影響，匯率風險是可以被定價的。 / In recent years, due to the opening of the markets, there are more and more choices in the investments. Investors should consider all aspects of information in this world with financial market integration but goods market segmentation. The intertemporal relation between risk and return in the stock market has been one of the most extensively studied topics in financial economics. The risk-return coefficients across different currency denomination change when considering different specification for the conditional covariance process. We used the bivariate BEKK-GARCH (1,1) model as the basic used in the reference by Turan G. Bali & Liuren Wu (2010) estimating the risk-return coefficients and measuring how this risk aversion estimate varies with different currency denominations. We started our analysis using monthly data from January 1981 to July 2008 on the Standard & Poor's 500 index, Taiwan stock exchange corporation and Korea composite stock price index. This article was divided into three parts. First, we computed monthly returns on the indices based on U.S. dollar denomination and calculated the excess returns as the index return minus the short-term interest rate. Second, we estimated the conditional covariances between the excess returns on the world market portfolio and the excess returns on two country indices using a bivariate GARCH specification. Third, we estimated the common relation of the equations implied by the international version of the intertemporal capital asset pricing model between the expected excess returns on those two country indices and the corresponding conditional covariances. After repeating the above procedure and estimating the intertemporal risk-return relation under different currency denomination, the empirical results showed that the risk-return coefficients in the world market portfolio was significantly positive in Taiwan and Korea. We also found that the coefficient was different based on different currency denominations on behalf of the exchange rate risk can be priced.

研發支出之會計處理，一直以來，因著研究發展之特性，始終有著相當分歧的看法。由於研究發展支出具有長期性及未來的經濟效益，有人主張將其以「資本化」方式處理；亦由於研究發展支出具有高度的風險與不確定性，有人主張將其以「費用化」方式處理。 Shi(2003)認為研究發展支出資本化與費用化之爭論，正反映了研發支出未來效益及其風險間之抵換關係(trade-off)，亦即，若研發支出之未來效益大於其風險，則較傾向將其資本化，其會計處理同於一般的無形資產；相反地，若研發之風險大於其未來效益，則較傾向將其以費用化方式處理，於發生當期即以費用入帳。 本研究以台灣債券市場為研究對象，探討研發支出未來效益與風險間之抵換關係，文中檢視「債券風險衡量因子」(bond risk measures)與「研究發展支出」之相關性，並以「債信評等等級」與「債券風險溢酬」為債券風險衡量因子，決定平均數效果(預期未來效益)與變異數效果(風險)於債券的評價上何者較為顯著。 一般而言，以債券投資者的角度觀之，若「債券風險衡量因子」與「研究發展支出」兩者呈現負相關，亦即平均數效果較強，則代表研究發展之未來預期效益大於研究發展之風險；若此兩者呈現正相關，亦即變異數效果較強，則代表研究發展之風險大於研究發展之未來預期效益。本研究之實證結果與發現如下： 1.對全體樣本而言，研發支出與債信評等等級呈顯著之正相關(本研究採用TCRI為債信評等衡量變數，等級愈高，風險愈大)，代表研發支出之風險大於其未來效益。然研發支出與債券風險溢酬之關係未達統計顯著水準，無法再次驗證上述結果。 2.對電子業樣本而言，與上述對全體樣本之結論相同。 3.對非電子業樣本而言，研發支出與債券風險溢酬為顯著之負相關，代表研發支出之未來效益大於其風險。然研發支出與債信評等等級之關係未達統計顯著水準，無法再次驗證上述結果。 4.在全體樣本、電子業樣本、及非電子業樣本中，將研發支出以費用化或資本化方式予以衡量，兩者之實證結果並無不同，顯示兩者對研發支出未來效益與風險間之抵換關係並無顯著差異存在。 5.電子業與非電子業所獲之結論不同，再次驗證產業別對於研發支出之效果確實有其差異性。 6.針對電子業而言，本研究之實證結果較傾向以費用化之方式處理其研發支出；然針對非電子業而言，較傾向以資本化之方式處理之。 / The debate about the alternative accounting treatments of R&D expenditures reflects trade-offs between the future benefits of R&D and its risk. In general, if the uncertainty regarding future benefits is not so high that it disqualifies the measurability criterion of asset recognition, then one may argue in favor of capitalizing R&D expenditures (as is typical for intangible investment). Conversely, if future outcomes are risky and unpredictable, the expensing treatment may be warranted. This is study examines the associations among bond risk measures (bond rating and risk premium) and R&D expenditures to determine whether their mean effect (expected future benefits) or their variance effect (risk) is more significant in pricing bonds. In general, from the perspective of bondholders, a negative correlation between bond risk parameter and R&D expenditures would indicate a stronger mean effect; that is, the expected future benefits of R&D expenditures are more than enough to compensate for the added risk of R&D. Conversely, a positive correlation would imply a stronger variance effect that swamps the mean effect of future benefits from R&D expenditures. The empirical results indicate follows: (1) For all samples, R&D expenditures are significantly positively associated with bond rating. The evidence suggests that, from the perspective of bondholders, the risk and uncertainties of R&D appear to dominate its expected future benefits. However, R&D expenditures have no significant effect on risk premium. (2) For electronic industry samples, the empirical results are the same with all samples. (3) For nonelectronic industry samples, R&D expenditures are significantly negatively associated with risk premium. The evidence suggests that, from the perspective of bondholders, the expected future benefits of R&D appear to dominate its risk. However R&D expenditures have no significant effect on bond rating. (4) The interpretation of this issue are not significant different through the expensing and capitalizing of R&D expenditures. (5) The industry effect is supported by the empirical results that show different effects of R&D on the bond risk measures between electronic industry and the nonelectronic industry. (6) The results indicate that it may be in favor of expensing R&D expenditures for electronic industry and capitalizing R&D expenditures for nonelectronic industry.