Professional traders often speak of a “fast” market or a “slow” one, depending on how they judge the volatility at that moment. Black Swans are extremely unpredictable events that have massive impacts on human society. These include positive Black Swans, like the invention of the Internet and the discovery of antibiotics, as well as negative Black Swans, like the 2008 recession.
Financial theory, as experts like Markowitz have pointed out, is built on a foundation of assumptions that do not stand up to scrutiny. Employing the bell curve as a measure for stock-market risk is troublesome, as it presumes that such risk correlates with mild, autonomous, and gradually changing price fluctuations. The presumption that price movements are independent and conform to a typical distribution is especially significant, despite a wealth of evidence to the contrary. Abstract A market is said to be efficient with respect to an information set if the price ‘fully reflects’ that information set, ie if the price would be unaffected by revealing the information set to all market participants. The efficient market hypothesis (EMH) asserts that financial markets are efficient. On the one hand, the definitional ‘fully’is an exacting requirement, suggesting that no real market could ever be efficient, implying that the EMH is almost certainly false.
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The concept that financial markets exhibit complexities and behaviors similar to chaotic natural systems was initially introduced through Mandelbrot’s development of fractal finance. Mandelbrot’s theory, which incorporates elements of fractal geometry, has shifted the perspective from a firm belief in entirely rational and orderly markets to a recognition of their unpredictable and volatile nature. This paper presents a basic theory of intelligent¯nance as a new paradigm of¯nancial investment. In stock markets, the theory exhibits itself in the form of an Intelligent Dynamic Portfolio Theory, which integrates predictive modeling of a bullbear market cycle, sector rotation, and portfolio optimization with a reactive trend following trading strategy.
The Misbehavior of Markets: A Fractal View of Financial Turbulence Annotated Edition
- The article underscores the importance of advancing and applying concepts derived from the geometry of fractals to improve the accuracy of models and methods in finance.
- Benoit Mandelbrot, one of the century’s most influential mathematicians, and his co-author, science journalist and former Wall Street Journal editor Richard Hudson reveal what a fractal view of the world of finance looks like.
- They provide examples of how market misbehavior can lead to crashes and other financial disasters.
- The perspective of “close enough” does not adequately capture the complex and diverse characteristics of financial markets.
Furthermore, because of our cognitive biases, we’re more vulnerable than ever to misunderstanding Black Swans and their impact. The theory’s supplementary fundamental premises, particularly the notion that the likelihood distribution of price fluctuations remains constant over time, have been repeatedly proven to be inaccurate. Price changes don’t typically follow the expected normal distribution with most being minute and few large; they are, in reality, far less predictable. Modern finance theory, praised for transforming investing into a scientific discipline, encounters substantial challenges because it is based on flawed assumptions and struggles to predict market movements with precision. Warren Buffett is the world’s most successful investor, but he also thinks of himself as a teacher in the field of investing and economics.
We also classify financial markets of different countries by the level of their efficiency and reaffirm that financial markets of developed countries are more efficient than the developing ones. Based on Ukrainian financial market analysis we show the reasons of inefficiency of financial markets and provide some recommendations on their solution and thus improving the efficiency. Mandelbrot’s innovative use of geometric techniques, which involve fractals and multifractals, has significantly deepened our understanding of the complex characteristics of financial markets. Creating new mathematical tools is essential for uncovering the intrinsic inconsistencies found in real-world financial market data.
Book SummaryThe Misbehavior of Markets, by Benoit B. Mandelbrot and Richard L. Hudson
In this paper, we make a detailed analysis and summary on three main functions, namely multifractal structure diagnosis, tendency and singularity analysis. Finally, some experiments based on oil prices data and spatial physical data are carried out to validate its performance effectively. Multifractal analysis illustrates how different scales of volatility interact, enabling a deeper understanding of market behavior and improving risk assessment beyond traditional models. This paper examines the behavior of financial markets efficiency during the recent financial market crisis. Using the Hurst exponent as a criterion of market efficiency we show that level of market efficiency is different for pre-crisis and crisis periods.
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Discontinuity, far from being an anomaly best ignored, is an essential ingredient of markets that helps set finance apart from the natural sciences. This sounds sort of weird, but the history of early financial and economic theory is closely tied in with physics. Black Swans compel people to explain why they happened—to show, after the fact, that they were indeed predictable. Taleb’s thesis, however, is that Black Swans, by their very nature, are always unpredictable.
The perspective of “close enough” does not adequately capture the complex and diverse characteristics of financial markets. The article underscores the importance of advancing and applying concepts derived from the geometry of fractals to improve the accuracy of models and methods in finance. Evidence shows that extreme price movements occur more frequently than predicted by the normal distribution, indicating that financial markets exhibit ‘fat tails’ that lead to underestimation of risk. The extraction of interesting information from enormous and irregular datasets has always been a significant research topic. For the datasets with irregular distribution and the misbehavior of markets selfsimilarity, multifractal theory is the most appreciated approach and has been successfully applied in many fields, such as financial analysis, image processing, medical diagnosis, earthquake study, etc.
The text argues that fractal models map pricing data more accurately than bell curve models, allowing for superior risk assessment and investment strategies. As the financial world recognizes the limitations of current methods, Mandelbrot’s fractal approach offers an alternative path toward market regulation and economic stability. The third chapter of The Misbehavior of Markets focuses on the unpredictable nature of markets. Mandelbrot and Hudson argue that markets are not always rational and can be influenced by a variety of factors, including emotions, rumors, and other external events. They provide examples of how market misbehavior can lead to crashes and other financial disasters. The fifth chapter of The Misbehavior of Markets explores the role of government in regulating financial markets.
- When your neighbor starts getting rich investing in tech stocks, it may influence you to do the same.
- We can see what goes into the box and what comes out of it, but not what happens inside; we can only draw inferences about the odds of input A producing output Z.
- Employing the bell curve as a measure for stock-market risk is troublesome, as it presumes that such risk correlates with mild, autonomous, and gradually changing price fluctuations.
- Mandelbrot’s pioneering work laid the groundwork for a mathematical field that uncovers hidden patterns in seemingly disordered systems, including the variability observed in stock market movements.
- These include positive Black Swans, like the invention of the Internet and the discovery of antibiotics, as well as negative Black Swans, like the 2008 recession.
About this book
We discuss how multiplicative cascades and related multifractal ideas might be relevant to model the main statistical features of financial time series, in particular the intermit-tent, … A massive bestseller now in its 12th edition, Burton Malkiel’s A Random Walk Down Wall Street provides a comprehensive and entertaining introduction to the world of finance. Malkiel leverages his experience as an academic economist and former Wall Street portfolio manager to explain for the lay reader the intricacies of security analysis, asset valuation, and investment theory.
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We study the multifractal nature of daily price and volatility returns of Latin-American stock markets employing the multifractal detrended fluctuation analysis. Comparing with the results obtained for a developed country (US) we conclude that the multifractality degree is higher for emerging markets. Moreover, we propose a stock market inefficiency ranking by considering the multifractality degree as a measure of inefficiency. Finally, we analyze the sources of multifractality quantifying the contributions of two factors, the long-range correlations of the time series and the broad fat-tail distributions. We find that the multifractal structure of Latin-American market indices can be mainly attributed to the latter.
Mandelbrot is legendary. The reader is out of his depth.
Seeing nature through the lens of probability theory is what mathematicians call the stochastic view. The word comes from the Greek stochastes, a diviner, which in turn comes from stokhos, a pointed stake used as a target by archers. We cannot follow the path of every molecule in a gas; but we can work out its average energy and probable behavior, and thereby design a very useful pipeline to transport natural gas across a continent to fuel a city of millions. This study analyses the multifractal properties of the most prominent oil-related derivative which is ‘‘WTI’’ since the West Texas Intermediate grade of crude oil for delivery at Cushing, Oklahoma. To be able to test multifractality of the WTI prices, we used two different methodologies which are multifractal detrended fluctuation analysis (MF – DFA) and wavelet transform modulus maxima (WTMM).