The Test of Market Price for Weak Form Efficiency - Assignment Example

The Test of Market Price for Weak Form Efficiency Introduction Market efficiency has been the central point of discussion in finance in the recent times, as experts attempt to ascertain the randomness of prices in the different markets. Market efficiency theory posits that the past market prices can influence the current one, and as a result, the technical analysis might be irrelevant when making a forecast on the future prices (Besley & Brigham, 2012). Theoretically, market efficiency in its weak form is founded on the notion of fundamental analysis, and that the result shows that stocks can either be undervalued or overpriced. The presence of the market efficiency in its weak form when looking at historical prices can be explained through varying statistical tests, and the tests are mainly focused on the notion that the investor might repeatedly make more than the standard returns on the knowledge of the historical price patterns (Timmermann & Granger, 2002). To prove the weak form of market efficiency can often be complicated due to the infinite number of methods to predicting the returns in the future, evaluated against the past and present returns (Hamid et al., 2010). It is also crucial to note that there tests that can show efficiency and with the regard to the provided pattern of prices (Teall, 2012). The investor with intricate knowledge of the test that explains the market inefficiency might utilise the knowledge and obtain high returns, more than the face, or alternatively face a market obstacle that blocks the investor from realising the market efficiency (Botten, 2007). Similarly, tests of efficiency in markets is in reality, the combined tests for the actual inefficiency and a single model that explains the standard profits in an efficient market (Moyer, McGuigan & Rao, 2015). As a result, the market efficiency concept cannot be ignored, unless the investor is aware that the right outlook for standard profits has been chosen for the specific bourse. Moyer, McGuigan & Rao (2015) perceive the presence of costly information in price patterns that are not normal, and in effect, the market cannot be efficient. Consequently, the best benchmark for tests of efficiency in the market will almost certainly not be hypothetically perfectly efficient. Hence, if the efficiency of the market in its weak form is present, therefore, the current prices shows that past information that contains every information might be analysed using the price patterns of the past, as well as the trading volume of the stock (Schubert, 2009). This model can use a number of statistical non-parametric and parametric tests for in proving the efficiency of capital markets, or rather specific efficiency of each price or index. Unit root test, variance ration tests, runs tests, autocorrelation tests are some of the tests that can be used (Bierman, 2010). However, for this paper, the past price data of the market shall be tested for the weak form of market efficiency. Test Design The test to be used in this paper is the runs tests, and the data to be used for this paper shall be sourced from the YahooFinance, and the historical prices shall be the ones for S&P 100 INDEX. The runs test for the data shall tests for randomness, and which if do exist then the hypothesis shall be declared null, and the market would be said to be following the weak form of market efficiency. Otherwise, the prices would not be following the random walk, and the market would be assumed efficient (Abraham Seyyed & Alsakran, 2002). The Runs test This is an important tool for testing for the weak form of market efficiency, the semi strong form of market efficiency, and the strong form of market efficiency, and it would be the best tool for this specific case, testing the market efficiency in its weak form. The formula used for the test is: Z= R- X Σ Note that Σ = √(2M0M1(2M0M1-M)/M2/(M-1) Where M= M0+M1 M0=# of positive runs M1=# of negative runs R= total # of runs Z= this is the normal variate The standard rule for this test is that when the Z value lingers between the region bordering negative one point nine six and positive one point nine six, then the rate is considered as significant, and thus means that the prices for the S&P 100 INDEX follows the random walk. In the value of Z is less than negative one point nine six, while at the same time more than the +1.96, then the prices for the S&P 100 INDEX does not follows the random walk. Test Results The data on the prices for the S&P 100 INDEX are attached to the document in a file labeled Minitab. In testing, it is always proper to show the results of the descriptive statistics from the information gathered when the data were run through the MINITAB software, and the results are shown here in below. A look into the descriptive results confirms that the price ranged from 581.6 to 925.5 ad mean of the data was 690.0. Descriptive Statistics: Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Maximum 60 0 690.0 17.5 135.2 467.6 581.6 646.6 822.4 925.5 The Results of Runs Tests Top of Form Bottom of Form Bottom of Form —— 27-Mar-15 11:25:03 PM ———————————————————— Welcome to Minitab, press F1 for help. Results for: Worksheet 2 Runs Test: Close Runs test for Close Runs above and below K = 689.960 The observed number of runs = 3 The expected number of runs = 30.4667 26 observations above K, 34 below P-value = 0.000 Top of Form Bottom of Form Table 2 The S&P 100 INDEX results for monthly prices confirms a p-value of 0.00, and this figure is obviously smaller than the provided alpha, which is usually 0.05. The implication with the value shows that the value of z statistic does not fall within the area that is plus or minus one point nine six, and hence the null hypothesis is rejected. The implication for the market and the prices in particular shows that the prices for the S&P 100 Index are not randomly generated monthly (Shiller, 2003). Reflections on the Results and Suggestions for further Tests Before the running data through tests, it is very important to have sound background knowledge of the topic that is to be tested. The weak form of market of efficiency is rather difficult concept to understand, and this probably is the reason that prompted the writer of this paper to pursue the test, as it presented a challenge. The Results from the data run on the MINITAB implies a weak form of market efficiency This notion is supported by other empirical research, and this is conforms to very security exchange markets throughout the industrialised nations. The presence of the weak form of market efficiency are largely established in the securities exchange markets in the third world countries, including the high rising BRIC nation. A desk top research on empirical literature items reveal several tests carried out on price to prove the weak form of market efficiency in securities exchange markets in both the developed and developing countries. It is through this sea of information that assisted this writer in building a case for the tests and results analysis above. It would have been better to subject this paper to more tests, particularly the variance tests, which is touted as the most reliable in the market. In addition, there has been a thin line separating the forms of market efficiency, and market inefficiency. It can be helpful to tests these other forms of market efficiency, and including market inefficiency. Moreover, may be statistical package might be unreliable, it can be helpful using other statistical packages; such as SPSS and STATA, or even the disparaged EXCEL, which has assisted this writer quite well in the past. When the test is carried out for a single price of stock, or an index or bonds price, it would be improper to indicate that the whole market runs on efficiency based on the single price or index. Rather, a test should be carried out for the entire market using the summary of price index in each category, so that a different result from one price summary invalidates the rest of the prices. Market efficiency is crucial as it reflects the prices in a specific time, ad reflects information from a particular source, and therefore people can get returns relying on information on pricing, but not reflect on the past prices. Reference List Abraham, A., Seyyed, F. J., & Alsakran, S. A. 2002. Testing the Random Walk Behavior and Efficiency of the Gulf Stock Markets. Financial Review. 37, 469-480. Besley, S., & Brigham, E. F. 2012. Principles of finance. Mason, Ohio, South-Western Cengage Learning. Bierman, H. 2010. An introduction to accounting and managerial finance a merger of equals. Singapore, World Scientific. http://public.eblib.com/choice/publicfullrecord.aspx?p=731271. Botten, N. 2007. Management accounting: business strategy. Oxford, CIMA. Hamid K., Suleman M.T., Shah S.Z.A., & Akash R.S.I. 2010. Testing the weak form of efficient market hypothesis: Empirical evidence from Asia-Pacific markets.International Research Journal of Finance and Economics. 58, 121-133. Moyer, R. C., McGuigan, J. R., & Rao, R. P. 2015. Contemporary financial management. Schubert, B. 2009. Weak Form Efficiency Tests. München, GRIN Verlag GmbH. http://nbn- resolving.de/urn:nbn:de:101:1-2010091113076. Shiller, R. J. 2003. From efficient markets theory to behavioral finance. New Haven, CT., Cowles Foundation for Research in Economics. Teall, J. L. 2012. Financial trading and investing. [S.l.], Academic Press. http://www.sciencedirect.com/science/book/9780123918802. Timmermann, A., & Granger, C. W. J. 2002. Efficient market hypothesis and forecasting. London, Centre for Economic Policy Research. Read More