Preface and acknowledgements
Data and Methodology 5.1. Data Description
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5. Data and Methodology5.1. Data DescriptionCameron and Schnusenberg (2008) used the Fama-French three factors as obtained from Ken French’s website.The factors from the website represent the US market relative to other markets. Nevertheless, the author argues that it is inappropriate to use these factors from that website since they are collected from US data; therefore the data cannot be representative of Japan’s capital market. Thus, before doing such an analysis, the data used should directly represent Japan’s capital market. Specifically, the Tokyo Stock Exchange can be a representative market because it is the largest stock exchange in Japan.The basic data used is compiled from daily returns on a value weighted portfolio index of all stock listed on the first section of the Tokyo Stock Exchange. Secondly, Daniel et al. (2001) argued that the daily Gensaki rate is used as a benchmark for the risk free rate in the Japanese market since there is no risk free rate in Japan comparable to that of the US Treasury bill rates. Chiao and Hueng (2004) also used a 30-day Gensaki risk free rate as a benchmark for the risk free rate in Japan. Therefore, Gensaki risk free rate is crucial for the financial securities market in Japan. In addition, Nowman (2002) also used a Gensaki rate as a proxy for the Japanese short-term interest rate. All these data are required to calculate the Fama-French three factors that are retrieved from DataStream. In this research, the daily prices are chosen which are better representative for calculating the log returns of auto index, market index, and oil price index, which were included in the Fama-French factors. The proposed period of the daily closing prices started from December 29, 2000 to March 31, 2011. For each of the companies, the data of the daily closing prices are retrieved from DataStream. To analyze the credit crisis event, the daily data are divided into three distinct sub-periods called “pre-crisis”, “crisis”, and “post crisis”. The time frame of the crisis focuses three years before and one year after the crisis. Nevertheless, there are many different opinions about the exact starting date of the credit crisis. Enlightment comes from Manda (2010), who analyzed the US stock volatility during the credit crisis era with the starting point on March 17, 2008, because on that date the US investment bank Bear Stearns & Co was taken by JP Morgan.The crisis ended on April 1, 2009, indicated by the fact that the S&P index has rebounded from its lowest value at the end of March 2009. Similarly, in analyzing the Iraq invasion, the data divided into three phases and the time frame of the war is taken to start from January 1, 2001 and end on July 29, 2005. The time phases for both events are summarized as follows: While analyzing the sales boom of hybrid cars, the research is focused into two distinct sub-periods called “before sales booming” and “after sales booming”. Owing to the data availability on the sales of hybrid cars, the thesis makes some restrictions. The yearly sales data of hybrid cars are collected from the official websites of Toyota and Honda, the Japan Automobile Dealers Association (JADA), and JAMA. From the table 3, it shows that Toyota outperforms its major competitor concerning sales of hybrid cars. The outperforming of Toyota is also caused by introducing many new hybrid vehicles from its Lexus brand for instance the most prominent Lexus RX 400 hybrid that makes sales of hybrid cars become stronger. Moreover, JADA exhibits that Toyota Prius often ranks first in the sales of cars in the Japanese market. Nevertheless, the success of Honda is not followed by Toyota, where the biggest sales of hybrid car were achieved in April 2009 by the third generation of Honda Insight. Hereafter, the method used to determine the time frame ofthe sales boom is by percentage of hybrid car sales. In Japan, the government’s fiscal year runs within the period April 1 to March 31. Table 2 defines the automobile companies’ (Toyota and Honda) percentage of sales and unit sales of hybrid cars in Japan starting from the fiscal year 2000 until 2011. Table 2: Toyota total sales of hybrid cars in Japan during fiscal year 2000–2010 (in thousand)
Source: JADA, JAMA, HONDA, TOYOTA From the above table, the sales percentage of hybrid cars by Toyota and Honda reached its peak by the fiscal year 2009 compared with previous years. This condition is also supported by the hybrid cars website1, which states that 2009 was recorded as the breakthrough year for gas-electric hybrid cars. The website informs that Toyota Prius was Japan’s top selling automobile in earlier 2009 for the first time since its debut in 1997 and Honda Insight ranked fifth with 93,283 units sold since its first production in 1999. Thus, Toyota and Honda start their sales booming of hybrid cars in fiscal year 2009. In conclusion, the time phases for both events are summarized as follows: Table 3 : Time Phases for Iraq war, credit crisis, and booming sales of hybrid car
Source: Manda (2010), EIA 5.2. MethodologyThe Fama-French three factor model has been extensively used as a tool for measuring returns based on the firm’s market capitalization and the BE/ME ratio in the Japanese stock market (for example works see Mohammed et al 2007; Pham 2007). From the OLS estimation model, the excess return of Japanese automobile companies is a dependent variable proxy. The independent variables are excess market return, SMB (small minus big), and HML (high minus low), which are categorized as Fama-French factors. Furthermore, Pennachi (2008) stated that one of the most important anomalies is caused by macro-economic factors that are motivated by the fact that the market portfolio proxy is not perfect, and, hence, the relation between consumption and marginal utility of that consumption is not perfect as the asset pricing model suggests. Therefore, another way to operationalize is by using the commodity prices such as oil prices that can be used as a proxy for consumption. Mathematically, the equation can be written as follows: Ra-Rf = αt + β1(Rm-Rf) + β2(SMB) + β3(HML)+ β4(Oil Price Factor) + εt To carry out the test, the research methodology adopts the same process as Cameron and Schnusenberg (2008) and applies the approach to the automobile manufacturers in Japan with several adjustments considering the compatibility of the data set. Cameron and Schunsenberg (2008) retrieved the data for market index, SMB, and HML from Fama’s website. This sophisticated model is not feasible in this sample case, as the data from the website is solely dictated by the availability of data. Moreover, the details of constructing the data of the automobile index, the Fama-French factors, and the oil price factor are discussed as follows: A. Excess Return on the Auto Index To examine the excess return on the Japanese automobile manufacturers index, the return on auto index is calculated by taking a weighted average of a market capitalization. A stock market portfolio weighted by the market value of the eight automobile companies in the porftolio. Market value is the market share price multiplied by the number shares outstanding. Larger companies have greater portion of the portfolio. The data of the daily market value for each of the eight automobile manufacturers from the period December 29, 2000 until March 31, 2011 are retrieved from DataStream. Further step, the daily market value of all eight companies is summed for the proposed time period and the total market value is chosen to be a divisor. The auto index is calculated by taking the log returns of daily closing prices of automobile manufacturers and multiplied by the weighted average of market capitalization. Moreover, the calculation is repeated every day within the proposed time to compute the auto index. Finally, to obtain the excess return on the auto index, the return on the auto index of Japanese automobile companies should be subtracted by the Gensaki risk free rate. B. Excess Return on the Market Pennachi (2008) argued that market risk premium is computed by subtracting the market index by the risk free rate. Market portfolio is unobservable, therefore, a broad index is needed as an approximation to market portfolio which contains all assets there. To compute Japan’s market return index, the investors could choose whether to use the average price weighted of the Nikkei 225 index or the TOPIX, which are the prominent stock market indexes for the Tokyo Stock Exchange (TSE). The Nikkei 225 is published by newspaper, the so-called Nihon-Keizai Shimbun, and its unit is measured in yen. The Nikkei 225 index has been calculated on a daily basis and it is computed by taking the average price weighted index. Therefore, the Nikkei 225 index is severely affected by high-priced stocks. The TOPIX stock market index is commonly used in Japan’s financial market because it is published by TSE. According to the TSE website, the TOPIX accounts for 1,700 companies listed on the TSE first section and its unit is measured by point. The TOPIX stock market index is computed by taking the fluctuations of adjusted market capitalization weighted index. Therefore, the TOPIX is most affected by issues with high aggregate market value. The calculation method of the world index is often used: the free float adjusted market capitalization weighted. Thus, the TOPIX index has a crucial usage as an assets benchmark to evaluate and standardize asset management. The Japanese government uses the TOPIX as their leading economic indicator. Moreover, pension fund managers and investment fund managers use the TOPIX index as a benchmark to evaluate their Japanese market portfolio. For the purpose of analysis, the TOPIX index seems suitable as a benchmark to calculate the Japanese market return index. As a support, Pham (2007) used the TOPIX index to calculate market index. Furthermore, Japan’s market return index is calculated by taking the log returns of the daily closing price index of the TOPIX index within the period December 29, 2000 to March 31, 2011. To obtain the excess market return, the log returns of the daily closing prices of the TOPIX index should be substracted by a 30-day Gensaki risk free rate. C. The SMB and the HML As discussed in the earlier sub-chapter, the author took the portfolio of the companies that were listed on the Tokyo Stock Exchange as representative of the Japanese financial market. In the Tokyo Stock Exchange, the listed companies are divided into three sections (i.e. first section, second section, and mothers). The first section is for large companies, while the second section is for middle sized companies. The last section is dedicated to small companies that have small growth and emerging stocks. In 2010 there were 1,695 companies listed on the first section of the Tokyo Stock Exchange. However, the number of companies changed slightly owing to the delisting of companies every year (for example in 2009 there were 1,687 companies listed in the first section). We propose to limit the number of selected companies by considering the criteria as mentioned on the TSE website, for instance number of shareholders, market capitalization, shareholder’s equity, and no false statements or fair representations. The website mentions many types of market index (i.e. TOPIX 30, TOPIX 100, TOPIX mid400, etc.). The TOPIX Core 30 contains the most liquid and highly market capitalized stocks in the Japanese capital market. The TOPIX Large 70 serves a data of 70 companies that are the most liquid and highly market capitalized stocks in the Japanese capital market, including the companies listed on the TOPIX Core 30. The TOPIX 100 contains the data of companies from both the TOPIX Core 30 and the TOPIX Large 70. Additionally, the companies listed on the TOPIX 100 are believed to serve financial reports according to Japan’s standard financial reporting system. These companies cover 33 industry sectors (i.e. mining, construction, foods, automotive, etc.) in Japan. Therefore, it is wisely to use the companies listed on the TOPIX 100 as an indicator to represent the Japanese stock market. The CAPM model only uses a single factor, beta, to compare market portfolio as a whole. The beta explains the causality between market risk premium and excess return. As an extension, the Fama-French three factor model introduces SMB (small minus big) and HML (high minus low) factors. They provide how to compute these variables on their website. According to Cameron and Schnusenberg (2008), as cited from French (1993), the SMB and HML factors are constructed using the six valueweighted stock portfolio formed by two market equity (e.g. size of the equity market and book-to-market benchmark porftolios) whereas there are any distortion from costs, transaction fees, or taxes. The SMB factor attempts to explain excess returns made by the portfolio manager. The portfolio manager divides the portfolio of companies based on their size of equity market. Therefore, market value is used to compute the size of the equity market. This thesis uses the same methodology according to the Fama-French website to obtain SMB and HML. The market capitalization (size of equity market) breakpoint determines the buy range for the “small” and “big” portfolios. The SMB denotes the first 50 percent of companies as “small” size companies and the other 50 percent as “big” size companies. Another factor, HML, shows the spread in excess returns between value and growth stocks. HML accounts that companies with value stocks (high book value relative to their book value) seem to earn excess returns over growth stocks. Therefore, HML is calculated by B/M ratios by dividing the book value by the market value. For each of the companies, the author retrieves the market value and book value data of each of the companies from DataStream within the period December 29, 2000 to March 31, 2011. A portfolio of companies is divided using the B/M ratios as the benchmark, with the criteria on the basis of 30:40:30 percentiles. The first 30 percent of the companies are called “low stocks”, the next 40 percent “medium stocks”, and the last 30 percent “high stocks”. Furthermore, these steps created the six portfolios divided into building blocks; small-low, small-medium, and small-high, and value stocks; big-low, big-medium, and big-high. Further step, the daily log returns of those companies that constituted the value and growth portfolios of each year were calculated. The daily log returns were calculated by taking the daily closing prices of each of the companies under scrutiny. The method used to determine daily SMB and HML is to take the average daily log returns of each companies under portfolios made within the proposed time period. Furthermore, the Fama-French (1993) determination of small minus big (SMB) and high minus low (HML) were obtained by applying the following formulas: SMB = 1/3*(Small/Low + Small/Medium + Small/High) – 1/3*(Big/Low + Big/Medium + Big/High) HML = ½*(Small/High + Big/High) – ½*(Small/Low + Big/Low) D. Oil factor Ono (2004) stated that Japan imports crude oil mainly from the Middle East which costs less than from West Texas Intermediate (WTI) and Brent Crude. The WTI is well known as a benchmark of the US market.The Brent Crude is used as a benchmark of the European market and Dubai Crude oil as a benchmark of crude oil price for the Asian market. Ono (2004) also stated that Middle-East crude oil accounts for almost 90% of crude oil imports in Japan. Koyama (2011) argued that the Middle-East countries who are oil producers determine the export price of crude oil for Asia on the basis average spot price of Dubai Crude price. As a consequence, the import price of crude oil in Japan is based on Dubai Crude price. Therefore, we have to pay attention to the fact that the Asian market is more dependent on Middle East oil than Europe and North America. Figure 2 shows the price of Dubai crude oil. Dubai Crude oil, so-called Dubai Fateh, is heavy oil with a high content of sulfur. In contrast, Both WTI and Brent are light and sweet crude oil. However, regarding specific quality data, WTI is lighter than Brent. That is why the WTI price is higher than the Brent price and the Dubai Fateh price. Ono (2004) stated the difference price between WTI and Dubai crude oil has been US$3 to US$6 per barrel. Figure 2: Dubai crude oil price from 2001-2011 
Market participants have made successful efforts to set the Dubai Crude price as a benchmark, for example utilize Upper Zakum crude oil as an alternative to Dubai Crude oil because of the declining production of Dubai Crude oil, listed as Oman Crude oil on the Dubai Merchantile Exchange since the middle 2007. In short, Dubai Crude oil is more suitable as a benchmark for the computation of oil factors in the Japanese capital market. The daily closing prices of Dubai Fateh crude oil are retrieved from DataStream within the proposed period. Furthermore, because crude oil price is based on the US dollars, hence, these prices were converted to Japanese yen by using the daily yen–US dollar exchange rate to give the reflection in the import price of crude oil in Japan. Furthermore, after computing the log returns of the daily closing prices, the daily log returns are subtracted by the daily Gensaki risk free rate to obtain the excess return of oil. Directory: pub pub -> Project Scoring Template Pre-Construction Phase New Core/Branch Campus Projects pub -> Acm word Template for sig site pub -> The german unification, 1815-1870 pub -> Baltic Olympiads in Informatics: Challenges for Training Together pub -> Preparation of Papers for ieee transactions on medical imaging pub -> Forthcoming meetings and conferences pub -> Asilomar Conference on Circuits, Systems & Computers, Pacific Grove, ca, November 1978, pp. 55 58 pub -> Forthcoming meetings and conferences pub -> Harmonised compatibility and sharing conditions for video pmse in the 7 9 ghz frequency band, taking into account radar use Download 420.96 Kb. Share with your friends:
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