Analysis of Financial Article - Essay Example

?Running Head: Analysis of Financial Article Analysis of Financial Article [Institute’s Analysis of Financial Article The article “Chaos in the Capital Markets: A New View of Cycles, Prices, and Market Volatility” by Edgar Peters aims to apply R/S analysis to different capital markets and capital market instruments. The author believes that in all cases, fractal structures and non-periodic cycles were found, which accordingly suggests and provides evidence that capital markets have a non-linear system, which thus makes the EMH doubtful. The author begins the article by asserting that logarithms will be applied to analyze data instead of percentages as logarithms can calculate cumulative returns and percentages cannot. Thus, the steps to analyzing R/S for capital markets include first converting prices into logarithms and then applying the suggested equations. Then each capital market instrument and data is analyzed turn by turn to gauge volatility, cycles, and price changes. The author uses Hurst statistics to analyze various capital market instruments and implies at the end of the article that prices are reflections of investors’ concept of ‘fair value”. While some may believe this to be a single value, this can actually be a range of values which is based on information such as the earnings from an investment, the management system, the new products offered, and the economic environment in that area. After fundamental analysis and technical analysis of what other investors believe their counterparts are willing to pay, the price is automatically adjusted to what is perceived as fair price and thus other investors become attracted to the investment and begin to purchase it. A Hurst statistic of more than 0.5 suggests that new information and previous events may affect the future prices of securities while one, which is lower than 0.5 implies the opposite. The author claims that the capital markets have a fractal nature and thus models such as the CAPM, APT, and Black-Scholes model fail. It is mainly due to their simple assumptions and their lack of acknowledging the importance of time when making vital decisions. Hence, the author believes that fractal analysis is a better measure of the reality of capital markets and the outcomes of human decision making. Fractal analysis is a reflection of the reality of life and how messy and complicated results can be. Thus, while it makes mathematics more difficult, it also explains the qualitative aspects of decision making and capital markets. It also gives capital markets a number of air values, cycles, trends, and recognizes the fact that there are innumerous possibilities. Thus, in the author’s point of view, fractal analysis is a better measure of the capital markets rather than the simple models as it accounts for a number of things, which are not accounted for in simple analysis. Hence, even though it is more complicated, the author encourages its use. The important points in the article are as follows: Logarithm returns are a better measure than percentages when calculating changes in price The author suggests that enough data is collected when the natural period of the system is visible and several cycles are available for analysis The first regression analysis is applied to the S&P 500 from 1950 to July 1958 The high value of H suggests the fractal position of the market The stock market results are not in accordance with the efficient market hypothesis The author suggests that market returns are persistent and have a fractal probability distribution The system is non-periodic and reinforces trends According to CAPM, a higher beta stock value is riskier than a lower beta stock value This is due to higher volatility The author suggests that high H values pose less risk and low H values may pose more risk High H values have less noise in the data while lower H values have more noise High H values may change abruptly Portfolio diversification reduces risk Market efficiency can be determined by the level of noise in the data The article examines a 30-year bond to examine the volatility of the bond market The author observed slightly more noise in the Hurst statistics for Treasury Bills compared to long bonds However, it was difficult to draw any conclusions from the data presented regarding the bonds To analyze currency in the capital market, the Singaporean dollar, US Dollar, Japanese Yen, British Pound, and the German mark. Currency markets may abruptly change due to controls imposed by governments Currencies are not exceptionally persistent Lack of data led to the cycles of currency not being completely visible Currency markets have a fractal structure as well which is confirmed by the occurrence of the values of H R/S analysis shows that economic indicators have very persistent H values Thus, this suggests that economic indicators follow a non-periodic cycle There is too much subjective data, thus it is difficult to analyze data in economic indicators The implications of the study explain that the existence of Hurst statistics is because of investors aiming to set a “ fair value” for a security However, the value does not remain constant New information regarding the security or changes in market conditions can cause a lot of volatility A 0.5 H value suggests that events are unrelated and today’s information does not affect tomorrow However, a value greater than 0.5 suggests that new information will impact the security and present events affect future events The fractal nature of the markets contradicts all simple models such as the CAPM, the APT, and the Black-Scholes option pricing model Simplifying reality and ignoring the influence of time has led to the failure of these models amongst others Fractal analysis may be a cause for more complications and confusion However, the results obtained through fractal analysis are more accurate and practical Fractal analysis considers all the possibilities and returns a multitude of results Cycles, Trends, and a number of fair values are evident from fractal analysis It outlines the qualitative effects of human decision making and gives them a quantitative measurement Thus, such statistics recognize and account for the fact that life may be quite complicated and messy and has innumerous outcomes and possibilities References Peters, Edgar E. n.d. Chaos and Order in the Capital Markets. John Wiley & Sons. Read More