Market Efficiency around the Clock some Supporting Evidence Using Foreign-Based Derivatives - Assignment Example

? FINANCE AND ACCOUNTING ASSIGNMENT 2 Table of Contents Question 3 a) 4 b) 5 c) 6 Question 2 8 References 12 Appendices 13 Question The three companies chosen whose stocks are traded on the Australian Securities Exchange (ASX) are Adcorp Australia Limited (AAU.AX), Australian Agriculture Co. Ltd. (AAC.AX) and Activex Limited (AIV.AX). All the three companies have at least five years of historically adjusted closing prices ending on Dec 31, 2012. Australian Agriculture Co. Ltd. is a leading provider of beef and agricultural products operating in over 19 cattle stations. The company owns over 7 million hectares of land across the Northern Territory and Queensland. The company’s strategy is to operate in diversified agribusiness operations and bring innovation in existing business practices in order to achieve long term gains. ActivEX Limited is an Australian mineral and exploration company that specialises in identifying, acquiring, and distribution of minerals. The company aims to increase shareholders’ value by investing into quality projects including minerals such as gold, copper, cobalt, etc. The company is involved in activities such as drilling, soil testing and mapping, data compilation, and reviewing. Adcorp Australia is a leading advertising agency owned locally and offers services including branding, advertising, creative design, event management, media planning and promotions. a) The monthly returns of the three companies are calculated using the following formula: Monthly return = (Current adjusted close price/Previous adjusted close price) – 1 The historical prices of the three companies are obtained from Yahoo Finance and the individual monthly returns of the three chosen stocks are shown in the appendices section. The period under study was for 61 months ending on Dec 31, 2012. The calculations are made in the MS-Excel spreadsheet application using the above formula to calculate monthly returns. Then the average monthly return is calculated using the Excel function AVERAGE that computes the average of given numbers. The standard deviations of adjusted closing prices are calculated using the STDEV function of MS-Excel. Standard deviation is the measure of risk of investment which measures the stock volatility over a given period of time. The expected return from the stock is calculated using the CAPM (Capital Asset Pricing Model) approach, where there is the concept of Beta. From the above summarised risk-return analysis, it can be said that the returns of all the three stocks are equal since beta is very close to zero but it is positive. This means that investment in either of the companies is safe as it is apparent that the standard deviation of market index (AORD) is more volatile than the chosen stocks. From the theory of risk-return, it can be said that the higher the risk, the higher would be potential return. This is true in case of AORD since the risk borne by the investor must be compensated by higher expected returns. When the individual stocks of the companies are compared to AORD, it can be said that all the three stocks have lower standard deviation or risk associated with investment. This would alternatively mean that the returns from these stocks would be lower due to less associated risk. This can be verified from the expected return that calculates the estimated return from the stock using CAPM. In this study it was found that expected return of AORD was higher than the three chosen stocks due to a higher risk. Also, for the given return, the rational investor would select the stock that is least risky and in this study riskiness of investment is determined using standard deviation. A higher value of standard deviation means that the stock is more risky and vice versa. From the above table, it can be said that Activex Limited is the least risky (the lowest standard deviation among other two stocks) and Australian Agriculture Co. Ltd is the riskiest (the highest standard deviation among other two stocks). b) In order to estimate the beta for each of three chosen companies from the 60 month adjusted stock close price, the adjusted close price data for a specific market will be required. Such market may be international index including S&P 500, FTSE 100, and so on. In this case, the beta of three companies is calculated relative to All Ordinaries Index. The beta of stock can be then calculated in spreadsheet using the following formula: ? = COVAR (Stock Close Price Array, Market Close Price Array) / VARP (Market Close Price Array) Using the above formula the following results can be summarised: Beta indicates the stock volatility relative to a benchmark or market. The beta of market or benchmark is always one. The value of stock is stated relative to benchmark beta. Consider an example where the chosen benchmark is S&P 500 whose beta is 1 and the beta of particular company’s stock is 1.5 (say). It implies that stock is 50% more volatile compared to benchmark and hence more risky. For risky stocks, the market premium is also higher. Alternatively, the stock would return 15% when the market returns 10%. Similarly, beta less than one implies less volatility, more safety and lower return compared to benchmark. A desirable value of beta would depend upon individual risk tolerance. So, in case the beta is high, it will mean a higher return but at the same time when the market falls, the stock of companies with a higher beta is expected drop much more. From the calculation of beta of the three companies it can be said that the risk of Activex limited is the least. c) The risk free rate of interest is the interest rate that an investor expects from investment after considering sufficient compensation for taking systematic risk that is non-diversifiable. Generally, the domestic government bonds are perceived as a good benchmark for the risk free rate. Such rates will be considered as risk free only if there is no defaulting risk. Hence from the above discussion it can be said that the risk free rate should be equal to a 10 year bond of Australian Government. Risk premium is the minimum return that an investor expects to earn by taking risk beyond risk free assets. The risk premium encourages investors to hold the risky asset in expectation of higher rewards above the risk free rate. Hence, the risk premium should be above the risk free rate or Government bond rate. In the given case, the risk premium should be estimated relative to a 90 day bank acceptance bill or 4.3%. Question 2 The market efficiency test aims to find out whether a market is weak, semi-strong, or strong form of market. Such test is conducted to evaluate whether investment strategies of a firm could earn superior returns from the chosen market. The stock market chosen among Asia-Pacific stock markets was that of Japan’s Nikkei. The Nikkei index is the index for stock markets on the Tokyo Stock Exchange. The components of Nikkei are reviewed once every year. It is the most popular and widely quoted equity indices of Japan. The index is very similar to Dow Jones Industrial Average. The index has been operating since 1950 and is regularly published in newspapers. The special feature about the index is that it is updated during every trading session in a 15 second interval. The stock index reached its peak value of 38,957.44 during intra-day and closed at 38,915.87 on Dec 29, 1989. This was the time during which the Japanese asset prices were growing exponentially and were six times more than historic high yields. On March 10, 2009, the stock index lost all its previous gains and closed at 7,054.88 declining over 81% below its peak value twenty years ago. The stocks or components of Nikkei are calculated on the basis of par value. There is equal weight age given to stocks at 50 Yen per share. The Nikkei 225 is computed so as to reflect the performance of overall market and hence there is no specific weight age given to a particular industry. The stocks are reviewed every September and the changes due to removals, additions and stock splits are generally introduced at the beginning of October. An empirical study research on the market efficiency of Nikkei index was conducted by Alastair, Dravid and Richardson in 1993. Their reports were published in the Journal of Financial Economics in 1995. Their research paper aimed to find out whether the information across various markets is reflected in stock prices. In order to test market efficiency, the market chosen in their study was Nikkei index futures. Their study provides sufficient information regarding cross-dependence between Japanese stock index and US stock index. The study conducted by Alastair, Dravid and Richardson investigates how the stock markets incorporate information relative to international indices such as S&P 500, CME (Chicago Mercantile Exchange) or NYSE (New York Stock Exchange). The theory of the study states that in an efficient market, the changes in the implied market index of Nikkei will be the same as actual changes over a chosen time interval. Alternatively, international indices such as S&P 500 should not change marginally relative to Nikkei. Their studies, however, revealed that there is a relation between implied changes and actual change in Nikkei. Their findings also suggest that the international indices do not provide additional information for overnight returns in Japanese stock markets. In order to calculate implied changes in Nikkei during US trading hours, the stock volatility was calculated during the period under observation in addition to calculation of stock volatility of international indices. The paper primarily investigates the relation between the Japanese stock market and US stock markets in order to check the market efficiency. The first task in their methodology was to set a specific time line that would be consistent with these markets trading time. This is because the trading time in the Japanese stock market is different from that of US stock markets. For instance, when it is 8 pm in New, York it is 10 am in Tokyo. Then the overnight log returns on Nikkei index can be calculated by finding out the sum of log returns during the chosen period. The daily returns or overnight returns are converted into lognormal returns in order to bring consistency and remove overlapping values for different trading periods. A correlation test was conducted on the stock indices to determine whether there is a pattern in the stock returns between the international index and Nikkei. The objective of the correlation test is to find out whether international news has any effect on Nikkei’s movement of stock prices. For instance, the correlation analysis will help to analyse the impact of news such as US trade or budget deficit, interest rates, employment data, etc in the Japanese stock markets. Conversely, Japanese trade related information released in US markets during trading hours should also reflect the overnight price changes of the Japanese economy and hence test the market efficiency of Nikkei. The implied level of Nikkei index can be calculated either in the market based method or in the model based method. The market based approach assumes that all relevant parameters are constant and hence, according to this model, the price of US derivative should be the benchmark for changes in Nikkei’s derivatives instrument. If this is true, then the Japanese market can be considered as efficient. According to the model based approach, derivatives prices in Japanese markets can be determined from the stochastic process using the US and Japan interest rates, exchange rates between the countries and so on. After determining all key parameters, the derivative prices of Japanese stock markets can be inverted to find out the implied level of prices changes. Now for the period under observation, the implied level price changes calculated earlier have to be compared with actual price changes. When the implied level price changes are equal to the actual price changes, then the market is efficient, otherwise the market efficiency should be rejected. The sample period chosen by Alastair, Dravid and Richardson in their study in 1993 was of 13 months extending from Nov 1991 to Dec 1992. At that time the data was calculated manually from Bloomberg Financial Markets Quotes (Alastair, Dravid and Richardson, 1995, pp.162-179). Various hypotheses were formulated with regards to the market efficiency and the results were collected on the basis of regression models, correlation analysis, run-test, and so on. From the findings of their research it can be said that the research provides a useful benchmark to evaluate the rationality of information processing across various stock markets. In order to test the market efficiency, overnight returns from Japanese stock markets were measured for the derivatives that were traded in Nikkei as well as international indices. The empirical research conducted reveals the relation between the US stock markets and the Japanese stock markets. The findings of the study state that there is relevant relation between overnight returns in Nikkei and international indices. Alternatively, their findings suggest that the market is efficient and information is reflected not only in domestic index but international indices as well. References Alastair, C., Dravid, A. & Richardson, M. (1995). Market efficiency around the clock some supporting evidence using foreign-based derivatives. Journal of Financial Economics, 39. Appendices Table 1 – Computation of Monthly Returns of Activex Limited Date Adjusted Close Price of Activex Ltd. Monthly Returns 1/2/2007 0.08 n/a 2/1/2007 0.06 -25.00% 3/1/2007 0.07 16.67% 4/2/2007 0.08 14.29% 5/1/2007 0.09 12.50% 6/1/2007 0.07 -22.22% 7/2/2007 0.07 0.00% 8/1/2007 0.05 -28.57% 9/3/2007 0.06 20.00% 10/1/2007 0.07 16.67% 11/1/2007 0.08 14.29% 12/3/2007 0.07 -12.50% 1/2/2008 0.06 -14.29% 2/1/2008 0.05 -16.67% 3/3/2008 0.05 0.00% 4/1/2008 0.05 0.00% 5/1/2008 0.05 0.00% 6/2/2008 0.04 -20.00% 7/1/2008 0.03 -25.00% 8/1/2008 0.03 0.00% 9/1/2008 0.05 66.67% 10/1/2008 0.02 -60.00% 11/3/2008 0.03 50.00% 12/1/2008 0.02 -33.33% 1/2/2009 0.03 50.00% 2/2/2009 0.03 0.00% 3/2/2009 0.03 0.00% 4/1/2009 0.03 0.00% 5/1/2009 0.04 33.33% 6/1/2009 0.04 0.00% 7/1/2009 0.04 0.00% 8/3/2009 0.05 25.00% 9/1/2009 0.05 0.00% 10/1/2009 0.06 20.00% 11/2/2009 0.06 0.00% 12/1/2009 0.05 -16.67% 1/4/2010 0.06 20.00% 2/1/2010 0.05 -16.67% 3/1/2010 0.07 40.00% 4/1/2010 0.07 0.00% 5/3/2010 0.05 -28.57% 6/1/2010 0.04 -20.00% 7/5/2010 0.06 50.00% 8/3/2010 0.05 -16.67% 9/1/2010 0.04 -20.00% 10/1/2010 0.04 0.00% 11/1/2010 0.04 0.00% 12/2/2010 0.04 0.00% 1/4/2011 0.04 0.00% 2/1/2011 0.05 25.00% 3/1/2011 0.04 -20.00% 4/1/2011 0.03 -25.00% 5/2/2011 0.03 0.00% 6/1/2011 0.05 66.67% 7/1/2011 0.04 -20.00% 8/1/2011 0.03 -25.00% 9/1/2011 0.03 0.00% 10/3/2011 0.03 0.00% 11/1/2011 0.03 0.00% 12/1/2011 0.02 -33.33% 1/2/2012 0.03 50.00% 2/1/2012 0.02 -33.33% 3/1/2012 0.02 0.00% 4/2/2012 0.03 50.00% 5/1/2012 0.02 -33.33% 6/1/2012 0.02 0.00% 7/2/2012 0.02 0.00% 8/1/2012 0.02 0.00% 9/3/2012 0.02 0.00% 10/1/2012 0.02 0.00% 11/1/2012 0.02 0.00% 12/3/2012 0.02 0.00% Table 2 – Computation of Monthly Returns of Australian Agriculture Co. Limited Date Adjusted Close Price of Australian Agriculture Co. Ltd. Monthly Return 1/1/2007 2.03 n/a 2/1/2007 2.23 9.85% 3/1/2007 2.26 1.35% 4/2/2007 2.44 7.96% 5/1/2007 2.47 1.23% 6/1/2007 2.8 13.36% 7/2/2007 2.92 4.29% 8/1/2007 2.55 -12.67% 9/3/2007 2.81 10.20% 10/1/2007 3.14 11.74% 11/1/2007 3.29 4.78% 12/3/2007 3.12 -5.17% 1/1/2008 2.94 -5.77% 2/1/2008 3.02 2.72% 3/3/2008 2.55 -15.56% 4/1/2008 2.95 15.69% 5/1/2008 3.14 6.44% 6/2/2008 2.66 -15.29% 7/1/2008 2.77 4.14% 8/1/2008 3.06 10.47% 9/1/2008 2.7 -11.76% 10/1/2008 1.9 -29.63% 11/3/2008 1.37 -27.89% 12/1/2008 1.88 37.23% 1/1/2009 1.8 -4.26% 2/2/2009 1.52 -15.56% 3/2/2009 1.56 2.63% 4/1/2009 1.8 15.38% 5/1/2009 1.59 -11.67% 6/1/2009 1.36 -14.47% 7/1/2009 1.31 -3.68% 8/3/2009 1.56 19.08% 9/1/2009 1.45 -7.05% 10/1/2009 1.46 0.69% 11/2/2009 1.4 -4.11% 12/1/2009 1.5 7.14% 1/4/2010 1.27 -15.33% 2/1/2010 1.29 1.57% 3/1/2010 1.4 8.53% 4/1/2010 1.29 -7.86% 5/3/2010 1.49 15.50% 6/1/2010 1.5 0.67% 7/1/2010 1.5 0.00% 8/2/2010 1.63 8.67% 9/1/2010 1.54 -5.52% 10/1/2010 1.6 3.90% 11/1/2010 1.48 -7.50% 12/1/2010 1.42 -4.05% 1/3/2011 1.52 7.04% 2/1/2011 1.64 7.89% 3/1/2011 1.61 -1.83% 4/1/2011 1.59 -1.24% 5/2/2011 1.46 -8.18% 6/1/2011 1.38 -5.48% 7/1/2011 1.38 0.00% 8/1/2011 1.35 -2.17% 9/1/2011 1.36 0.74% 10/3/2011 1.4 2.94% 11/1/2011 1.39 -0.71% 12/1/2011 1.33 -4.32% 1/2/2012 1.39 4.51% 2/1/2012 1.36 -2.16% 3/1/2012 1.3 -4.41% 4/2/2012 1.28 -1.54% 5/1/2012 1.15 -10.16% 6/1/2012 1.12 -2.61% 7/2/2012 1.11 -0.89% 8/1/2012 1.29 16.22% 9/3/2012 1.28 -0.78% 10/1/2012 1.3 1.56% 11/1/2012 1.27 -2.31% 12/3/2012 1.17 -7.87% Table 3 – Computation of Monthly Returns of Adcorp Australia Limited Date Adjusted Close of Adcorp Australia Ltd. Monthly Returns 1/1/2007 0.4 n/a 2/1/2007 0.32 -20.00% 3/1/2007 0.29 -9.38% 4/2/2007 0.25 -13.79% 5/1/2007 0.21 -16.00% 6/1/2007 0.22 4.76% 7/2/2007 0.25 13.64% 8/1/2007 0.2 -20.00% 9/3/2007 0.19 -5.00% 10/1/2007 0.18 -5.26% 11/1/2007 0.26 44.44% 12/3/2007 0.26 0.00% 1/1/2008 0.23 -11.54% 2/1/2008 0.28 21.74% 3/3/2008 0.26 -7.14% 4/1/2008 0.26 0.00% 5/1/2008 0.25 -3.85% 6/2/2008 0.25 0.00% 7/1/2008 0.3 20.00% 8/1/2008 0.32 6.67% 9/1/2008 0.28 -12.50% 10/1/2008 0.23 -17.86% 11/3/2008 0.22 -4.35% 12/1/2008 0.22 0.00% 1/1/2009 0.21 -4.55% 2/2/2009 0.14 -33.33% 3/2/2009 0.18 28.57% 4/1/2009 0.17 -5.56% 5/1/2009 0.17 0.00% 6/1/2009 0.18 5.88% 7/1/2009 0.2 11.11% 8/3/2009 0.19 -5.00% 9/1/2009 0.2 5.26% 10/1/2009 0.24 20.00% 11/2/2009 0.2 -16.67% 12/1/2009 0.19 -5.00% 1/4/2010 0.16 -15.79% 2/1/2010 0.14 -12.50% 3/1/2010 0.15 7.14% 4/1/2010 0.14 -6.67% 5/3/2010 0.15 7.14% 6/1/2010 0.12 -20.00% 7/6/2010 0.15 25.00% 8/2/2010 0.15 0.00% 9/1/2010 0.15 0.00% 10/4/2010 0.16 6.67% 11/1/2010 0.17 6.25% 12/3/2010 0.16 -5.88% 1/3/2011 0.16 0.00% 2/2/2011 0.16 0.00% 3/1/2011 0.18 12.50% 4/1/2011 0.14 -22.22% 5/5/2011 0.13 -7.14% 6/1/2011 0.12 -7.69% 7/4/2011 0.11 -8.33% 8/1/2011 0.14 27.27% 9/5/2011 0.17 21.43% 10/6/2011 0.15 -11.76% 11/3/2011 0.16 6.67% 12/1/2011 0.15 -6.25% 1/2/2012 0.15 0.00% 2/1/2012 0.17 13.33% 3/1/2012 0.17 0.00% 4/2/2012 0.19 11.76% 5/1/2012 0.17 -10.53% 6/1/2012 0.16 -5.88% 7/2/2012 0.18 12.50% 8/1/2012 0.21 16.67% 9/3/2012 0.16 -23.81% 10/1/2012 0.11 -31.25% 11/1/2012 0.12 9.09% 12/3/2012 0.12 0.00% Table 4 – Summary of Risk-Return Analysis Table 5 – Summary of Expected Returns Using CAPM Approach Read More