Behavioral Finance in Books' Benoit Mandelbrot and Edgar Peters - Book Report/Review Example

Behavioral Finance By 5th, September, Article Fractals and scaling in finance by Benoit Mandelbrot This book discusses the major contributions of finance, which helps readers to understand how speculative prices fluctuate in time. Mandelbrot (1997) is famous for his great thoughts of fractal and scaling in finance whereby he discusses the following subjects. Financial and econometrics models Applying the concept of scaling to data generated by financial analyses. Highlighting risks in trading strategies. Distribution of income. Methods in statistical economics. Proportional growth as well as other explanations of scaling. 1. Financial and Econometrics Models In discussing, the book highlights financial and econometrics models, the book create a strong platform for readers to understand economics weightily. The following follows in this discussion. Brownian motion is a model which explores that financial market operates like a random walk that can be summarized in standard probability calculus. From Brownian motion, learners can comprehend how economies and markets operate. This discussion assists those in the financial industry to develop assess and strategies risks that helps to stabilize the market. This book outline that the Brownian motion is associated with the Wiener process. By taking this model into consideration, one can conclude that it is applicable in tracking stocks prices since it comprises of degree of randomness which tends to be steady with the instability of commodity. Wiener Brownian Motion This model can be applied in finance and physics via modeling random behavior, which exists over a time. Louis Bachelier established this model in 1900 with an aim of understanding modeling fluctuations of prices in the financial markets. Still, Albert Einstein gave his contribution towards this arithmetical model, which was first established by Robert Brown in 1827. “The Ordinary Wiener Brownian motion” Wiener Brownian motion has two properties, which are Scaling of price: This property regards that the amplitude with the rate of change, the principles of lower and higher frequency variation are similar to the rules of mid-speed frequency variation. Statistical aspect of price increments: Brownian motion displayed over equal time increase can be overlaid statistically. Brownian Motion In this case, the author highlights points that relate with “Random walk down the street” as follows. Scaling models should replace model of price variation referred as “Random walk down the street”. This model presupposes that prices adjust randomly and each is statistically independent from the past one. It proceeds in up or down scale, equally spaced in steps and time as indicated in the following diagram. Brownian motion’s insufficiencies as a model of price variation As discussed in the article, this model has inadequacies of price variation. One of his cons is that; it is a poor estimation to financial reality. 2. Applying The Concept Of Scaling To Data Generated By Financial Analyses The fractal aspect to economics and finance rests on two factors Identifying scaling and stationarity as invariance factors in economics. Identifying that probability model is more resourceful than willingness to face different states of randomness. 3. Highlighting Risks in Trading Strategies. As argued, it is important to highlight risks in trading strategies as it guarantees productivity and success. This can be achieved by understanding behavioral finance as described by models in this book. From this book, readers can comprehend that Brownian motion that analyses the impact of price stabilization on investment when the demand is doubtful. This model creates a platform to understand how economies and markets functions thus, making it easier to make money and better develop strategies that assess risks. 4. Distribution of Income. Brownian motion is important in understanding the concept of distribution of income in a nation. This model assists in distribution of income due to the following factors. It is one of the econometric models which economists use as a tool to predict future economy development. Through this model, econometricians can access past relationships and various variable such as consumer spending, tax rates, employment, household income, and interest rates. At this point, economists predict how such variable affect the future course of an economy development. 5. Methods in Statistical Economics. At this point, the author proposes that Wiener Brownian motion as the model which preserve scaling and stationarity as the basic principle of economics. 6. Proportional Growth As Well As Other Explanations Of Scaling Given fractals in finance, the model of Tail-Driven variability outline that changes of successive price are usually independent and non-Gaussian but scaling and stationary. This assists to explain proportional growth which is attributed by the economy development. It is worth noting that, economic development enhance better living, creates job opportunities, and better chances for investment. This book is useful as it lays a strong foundation for learners to comprehend economic facts that affect the market. Therefore, students can use this book to understand in depth about what attributes to economy development. The significance of reading this book is that it has great insights on the following. Financial and econometrics models Scaling as generated by financial analyses. Assessing and understanding risks in trading strategies. The concept of income distribution Methods in statistical economics. Proportional growth of an economy. The concluding remarks are based on graphs analogous, which are explained in the fractal context. In explaining, the author presents graphs as that indicated in figure E1-5 that illustrate the multifractal aspect of fractal context. As intended, the author reveals the deep link between the fractal approach and finance. Therefore, from this article, readers can comprehend the following. The concept of behavioural finance that has a fundamental application in the field of economics. Understand the Brownian model, which is widely used in finance and physics. The book gives the background information of the model in that, it outlines how Louis Bachelier it in 1900 with an aim of understanding modeling fluctuations of prices in financial markets. It makes readers to articulate Albert Einstein contribution in mathematical model, which was first established by Robert Brown in 1827. Article 2 Chaos and Order in the Capital Market by Edgar Peters This is a book by Peter (1996), who in great thoughts outlines facts of behavioural finance. While reading this article, the following comes into conclusion. For one to be successful, one should master marketing predicting: This is paramount as it creates a platform to comprehend what is required to enhance success. Market prices are usually high with the trend component which varies from market to market and time to time. While it is possible to measure markets’ tendency, one cannot predict which market trend the most in the future. In great thoughts, Edgar Peter covers the following topics, which assists learners to articulate in depth about behavioural finance. In Brief, the book covers the following topics. Ratio analysis of the capital markets The stock market The Bond Market Markets with Chaos. Fractal dimension. Fractal statistics Economic indicators. Dynamic scrutiny of the capital markets. 1. Ratio analysis of the capital markets The author describes ways of applying Ratio analysis in various markets. In his research, he found out that non-periodic cycles and fractal structure outlay evidence of the fact that the capital markets being nonlinear systems. Basically, they are two fundamental aspect of financial ratio analysis. It assists to evaluate a firm performance over a time: This may be used to track trends of concern such a decline of the firm liquidity’s status. It can be used to judge how the firm progress such as liquidity status or increasing revenues: For instance, it can be effective in making the relative performance comparisons such as the firm’s productivity with that of the competitors Following the above discussion, analysing ratio analysis is paramount in the capital market. In analysing, the following logarithmic is used; St=In (Pt/P (t-1). Typically, “The St is the logarithmic return at time t” (Peter, 1996). The following steps are considered in the calculation. One should convert yield or price series into logarithmic returns. Should apply equations for different increments of time, which may differ according to the period of time. 2. The stock market This article describes the ratio analysis for a monthly data for a period of over 38 years from January 1950 to July 1988 where there was a long memory process of approximately 2 years. The graph followed the random walk of the line H=0.50. The peak occurred after 4 years which estimated to a Hurst exponent of the S&P 500. The high value of H indicates a concern of the stock market being fractal and not in the random walk. It is worth noting that, changes of price sequence is paramount as it preserves the scaling of series features. 3. Markets with Chaos As indicated in the article, the sequence of changes is paramount as it preserves the scaling features of the series. However, the result is incompatible as a time it leads to underlying market disorder. In explaining, there are various exhibits that indicate a trend reinforcing behaviour. 4. Fractal dimension This is also referred as capacity dimension of the fractal that is usually calculated via box counting method. In this case, this book shows results with some individual stocks that give an assumption that. Firms with high innovation of technology tend to have a high number of investors as many regard the need of being identified with its progress. However, those with low level of innovation often have few investors as many fails to recognize the importance of the industry. 5. Economic Indicators Ratio analysis shows high persistent values of index of industrial production and the new business configuration. From this discussion, one can summarize that analysts, individual investors, and economists need to understand economic indicators to excel in the market place. Among the vital economic indicators discussed in this paper is Gross Domestic Product that measures the society’s wealth. In explaining, this book presents different exhibits that indicate economic indicators whereby each is analysed in depth. Typically the economic implication as discussed in the book is that price range is affected by the following. The investors’ perception of the fair value: This is determined by the four fundamental factors as discussed below. Investors’ perception towards what other investors will pay: When investors view the trend verifying their positive outlook of the security, they in turn begin to purchase as well It is worth noting that, investors’ value securities as per the range of prices, which is influenced by the following. Management of any given institution, firm or an organization. Earnings Current economic environment New products in the market Concluding remarks are outline as, fractal analysis in the capital market is fundamental as it gives us trend, cycles, and many other possible fair aspects of money circulation. In other words, it is a core field of economic application as it dictates the operation of the capital market. The less an exchange rate is, the less stable an economy is as it hinders many to investment. Indeed, Edgar Peter uses dynamical model, rescaled range, and fractals analysis to describe the price movements. These tools enable readers to understand the economic phenomena. Conclusion of the two articles Following the above discussion, the two articles discuss the subject Behavioural finance, which has effect on markets operation. The two articles have the following similarities. They combine the two aspects of economics and psychology to indicate how and why people make illogical or irrational decision in saving, investing, borrowing money, and spending. The discussion is based on fundamental economic models that portray behavioural financial changes, which are likely to be adopted. With this in mind, I would recommend many to read the two books as they present insightful thoughts about behavioural finance as discussed in the Brownian model and factual approach. Still, the two books are helpful to students desiring to understand economics in depth. Works Cited Mandelbrot, B. B, 1997, Fractals and Scaling In Finance: Discontinuity, Concentration, Risk, New York, Springer Peters, E. E, 1996, Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility, New York, John Wiley and Sons. Read More