Elon Musk’s Secret Facility: What You Need to Know🎯 | November 10, 2024

Apple and Amazon are investing big, and it’s not about AI or self-driving cars. [---] [logo]( with L. Davidson [L. Davidson] November 10, 2024 Elon Musk just dropped a bombshell: A hidden Tesla facility is growing faster than Tesla’s car business! [Click here]( Apple and Amazon are investing big, and it’s not about AI or self-driving cars. Discover why these 5 secretive companies could be the next big thing. [Click here to see the shocking details!]( Best, Tim Bohen Bullish Stock Trader is dedicated to bringing exclusive opportunities to our esteemed readers. We highly encourage you to carefully consider the message above from one of our trusted business partners. [.]( For personalized assistance or inquiries, kindly respond to this email for a prompt reply. For non urgent questions, reach out to us at support@bullishstocktrader.com This offer is brought to you by Bullish Stock Trader, 435 N Dupont Hwy, Dover, DE 19901, United States. If you would like to unsubscribe from receiving offers brought to you by Bullish Stock Trader [click here](. Bullish Stock Trader sending this newsletter on behalf of Event Horizon LLC. Copyright © 2024. All Rights Reserved. [Privacy Policy]( [Terms & Conditions]( [Unsubscribe]( [logo]( 2024-03-04 13:03:59 +00:00 Nov 10, 2024 Risks and other costs Stock market volatility can trigger mental health issues such as anxiety and depression. This fits in with research on the long term effects of the stock market on a person's mental health. Seasoned, experienced stock traders and investors generally achieve a level of psychological resilience able to deal with these detrimental factors in the long run or otherwise risk continuous suffering from some type of mental health issue during the course of their careers or financial activities which are dependent on the stock market. Mandelbrot's fractal theory Crowd gathering on Wall Street after the Wall Street Crash of 1929 Contrary to a stockbroker, a professional who arranges transactions between a buyer and a seller, and gets a guaranteed commission for every deal executed, a professional trader may have a steep learning curve and his ultra-competitive performance based career may be cut short, especially during generalized stock market crashes. Stock market trading operations have a considerably high level of risk, uncertainty and complexity, especially for unwise and inexperienced stock traders/investors seeking an easy way to make money quickly. In addition, trading activities are not free. Stock speculators/investors face several costs such as commissions, taxes and fees to be paid for the brokerage and other services, like the buying/selling orders placed through a stock broker stock exchange. Depending on the nature of each national or state legislation involved, a large array of fiscal obligations must be respected, and taxes are charged by jurisdictions over those transactions, dividends and capital gains that fall within their scope. However, these fiscal obligations will vary from jurisdiction to jurisdiction. Among other reasons, there could be some instances where taxation is already incorporated into the stock price through the differing legislation that companies have to comply with in their respective jurisdictions; or that tax free stock market operations are useful to boost economic growth. In the United States, for example, stock gains are generally taxed at two levels: For long-term capital gains (stocks sold after a minimum of one year's ownership, the tax rate currently (2024) is 20%. For short-term trades (stocks bought and sold within a 12-month period, capital gains are taxed at one's ordinary tax rate (e.g., 28%, 30%, 35%). Beyond these costs are the opportunity costs of money and time, currency risk, financial risk, and Internet, data and news agency services and electricity consumption expenses—all of which must be accounted for. These models rely on the assumption that asset price fluctuations are the result of a well-behaved random or stochastic process. This is why mainstream models (such as the famous Black–Scholes model) use normal probabilistic distributions to describe price movements. For all practical purposes, extreme variations can be ignored. Mandelbrot thought this was an awful way to look at financial markets. For him, the distribution of price movements is not normal and has the property of kurtosis, where fat tails abound. This is a more faithful representation of financial markets: the movements of the Dow index for the past hundred years reveals a troubling frequency of violent movements. Still, conventional models used by the time of the 2008 financial crisis ruled out these extreme variations and considered they can only happen every 10,000 years[citation needed]. An obvious conclusion from Mandelbrot's work is that greater regulation in financial markets is indispensable. Other contributions of his work for the study of stock market behaviour are the creation of new approaches to evaluate risk and avoid unanticipated financial collapses.[3] Benoît Mandelbrot during his speech at the ceremony when he was made an officer of the Legion of Honour on September 11, 2006, at the École Polytechnique; here, with a display of the Mandelbrot set. In 1963 Benoit Mandelbrot analyzed the variations of cotton prices on a time series starting in 1900. There were two important findings. First, price movements had very little to do with a normal distribution in which the bulk of the observations lies close to the mean (68% of the data are within one standard deviation). Instead, the data showed a great frequency of extreme variations. Second, price variations followed patterns that were indifferent to scale: the curve described by price changes for a single day was similar to a month's curve. Surprisingly, these patterns of self-similarity were present during the entire period from 1900 to 1960, a violent epoch that had seen a Great Depression and two world wars. Mandelbrot used his fractal theory to explain the presence of extreme events in Wall Street. In 2004 he published his book on the "misbehavior" of financial markets The (Mis)behavior of Markets: A Fractal View of Risk, Ruin, and Reward. The basic idea that relates fractals to financial markets is that the probability of experiencing extreme fluctuations (like the ones triggered by herd behavior) is greater than what conventional wisdom wants us to believe. This of course delivers a more accurate vision of risk in the world of finance. The central objective in financial markets is to maximize income for a given level of risk. Standard models for this are based on the premise that the probability of extreme variations of asset prices is very low. "Inherent Market Turbulence: Markets are described as chaotic with price fluctuations at different time scales, contrary to the conventional view of market stability. Increased Market Risk: The authors show that markets are riskier than standard theories suggest, with frequent extreme events (“black swans”). Market Memory: Contradicting the efficient market hypothesis, the authors claim that markets have memory, affecting future price movements. Self-Similarity Across Time Scales: Financial markets exhibit similar patterns at different levels. Nonlinearity of Markets: Small changes can lead to large, unpredictable outcomes. Human Behavior in Markets: Human emotions and behaviors significantly influence market dynamics." Beating the market, fraud and scams Outside of academia, the controversy surrounding market timing is primarily focused on day trading conducted by individual investors and the mutual fund trading scandals perpetrated by institutional investors in 2003. Media coverage of these issues has been so prevalent that many investors now dismiss market timing as a credible investment strategy. Unexposed insider trading, accounting fraud, embezzlement and pump and dump strategies are factors that hamper an efficient, rational, fair and transparent investing, because they may create fictitious company's financial statements and data, leading to inconsistent stock prices.