Pre-Foreclosure List📝| October 27, 2024

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[.]( 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](. [logo]( [Privacy Policy]( [Terms & Conditions]( [Unsubscribe]( Bullish Stock Trader sending this newsletter on behalf of Event Horizon LLC. Copyright © 2024. All Rights Reserved. Stock traders can trade on their own account, called proprietary trading or self-directed trading, or through an agent authorized to buy and sell on the owner's behalf. That agent is referred to as a stockbroker. Agents are paid a commission for performing the trade. Major stock exchanges have market makers who help limit price variation (volatility) by buying and selling a particular company's shares on their own behalf and also on behalf of other clients. Proprietary or self-directed traders who use online brokerages (e.g., Fidelity, Interactive Brokers, Schwab, tastytrade) benefit from commission-free trades. A stock trader or equity trader or share trader, also called a stock investor, is a person or company involved in trading equity securities and attempting to profit from the purchase and sale of those securities.[1][2] Stock traders may be an investor, agent, hedger, arbitrageur, speculator, or stockbroker. Such equity trading in large publicly traded companies may be through a stock exchange. Stock shares in smaller public companies may be bought and sold in over-the-counter (OTC) markets or in some instances in equity crowdfunding platforms. Both self-styled innovative fintech and traditional banking apps offer stock trading and investing tools to their customers. Stock speculators and investors usually need a stock broker such as a bank or a brokerage firm to access the stock market. Since the advent of Internet banking, an Internet connection is commonly used to manage positions. Using the Internet, specialized software, a personal computer or a smartphone, stock speculators/investors make use of technical and fundamental analysis to help them in making decisions. They may use several information resources, some of which are strictly technical. Using the pivot points calculated from a previous day's trading, they attempt to predict the buy and sell points of the current day's trading session. These points give a cue to speculators, as to where prices will head for the day, prompting each speculator where to enter his trade, and where to exit. An added tool for the stock picker is the use of stock screens. Stock screens allow the user to input specific parameters, based on technical and/or fundamental conditions, that he or she deems desirable. Primary benefit associated with stock screens is its ability to return a small group of stocks for further analysis, among tens of thousands, that fit the requirements requested. There is criticism on the validity of using these technical indicators in analysis, and many professional stock speculators do not use them.[citation needed] Many full-time stock speculators and stock investors, as well as most other people in finance, traditionally have a formal education and training in fields such as economics, finance, mathematics and computer science, which may be particularly relevant to this occupation – since stock trading is not an exact science, stock prices have in general a random or chaotic[3] behaviour and there is no proven technique for trading stocks profitably, the degree of knowledge in those fields is ultimately neglectable. U.S. Securities and Exchange Commission headquarters in Washington, D.C. Technical analysis is the use of graphical and analytical patterns and data to attempt to predict future prices. Although many companies offer courses in stock picking, and numerous experts report success through technical analysis and fundamental analysis, many economists and academics state that because of the efficient-market hypothesis (EMH) it is unlikely that any amount of analysis can help an investor make any gains above the stock market itself. In the distribution of investors, many academics believe that the richest are simply outliers in such a distribution (i.e. in a game of chance, they have flipped heads twenty times in a row). When money is put into the stock market, it is done with the aim of generating a return on the capital invested. Professional stock traders who work for a financial company are required to complete an internship of up to four months before becoming established in their career field. In the United States, for example, internship is followed up by taking and passing a Financial Industry Regulatory Authority-administered Series 63 or 65 exam. Stock traders who pass demonstrate familiarity with U.S. Securities and Exchange Commission (SEC) compliant practices and regulation. Stock traders with experience usually obtain a four-year degree in a financial, accounting or economics field after licensure. Supervisory positions as a trader may usually require an MBA for advanced stock market analysis. Many investors try not only to make a profitable return, but also to outperform, or beat, the market. However, market efficiency, championed in the EMH formulated by Eugene Fama in 1970, suggests that at any given time, prices fully reflect all available information on a particular stock and/or market. Thus, according to the EMH, no investor has an advantage in predicting a return on a stock price because no one has access to information not already available to everyone else. In efficient markets, prices become not predictable but random, so no investment pattern can be discerned. A planned approach to investment, therefore, cannot be successful. This "random walk" of prices, commonly spoken about in the EMH school of thought, results in the failure of any investment strategy that aims to beat the market consistently. In fact, the EMH suggests that given the transaction costs involved in portfolio management, it would be more profitable for an investor to put his or her money into an index fund. 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] Mandelbrot's fractal theory 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. Throughout the stock markets history, there have been dozens of scandals involving listed companies, stock investing methods and brokerage. Mandelbrot delves into several key principles of fractal finance in The Misbehavior of Markets: A Fractal View of Financial Turbulence: 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. "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." A classical case related to insider trading of listed companies involved Raj Rajaratnam and its hedge fund management firm, the Galleon Group. On Friday October 16, 2009, he was arrested by the FBI and accused of conspiring with others in insider trading in several publicly traded companies. U.S. Attorney Preet Bharara put the total profits in the scheme at over $60 million, telling a news conference it was the largest hedge fund insider trading case in United States history.[5] A well publicized accounting fraud of a listed company involved Satyam. On January 7, 2009, its Chairman Raju resigned after publicly announcing his involvement in a massive accounting fraud. Ramalinga Raju was sent to the Hyderabad prison along with his brother and former board member Rama Raju, and the former CFO Vadlamani Srinivas. In Italy, Parmalat's Calisto Tanzi was charged with financial fraud and money laundering in 2008. Italians were shocked that such a vast and established empire could crumble so quickly. When the scandal was made known, the share price of Parmalat in the Milan Stock Exchange tumbled. Parmalat had sold itself credit-linked notes, in effect placing a bet on its own credit worthiness in order to conjure up an asset out of thin air. After his arrest, Tanzi reportedly admitted during questioning at Milan's San Vittore prison, that he diverted funds from Parmalat into Parmatour and elsewhere. The family football and tourism enterprises were financial disasters; as well as Tanzi's attempt to rival Berlusconi by buying Odeon TV, only to sell it at a loss of about €45 million. Tanzi was sentenced to 10 years in prison for fraud relating to the collapse of the dairy group. The other seven defendants, including executives and bankers, were acquitted. Another eight defendants settled out of court in September 2008.[6] Masayoshi Son achieved fame as a stock investor after a successful and very profitable early-stage investment in Alibaba Group and the subsequent morphing of his own telecom company Softbank Corp into an investment management firm called Softbank Group.[8] However, a series of failed high-profile investments prompted criticism on him.[9][10] The problems with mutual fund trading that cast market timing in a negative light occurred because the prospectuses written by the mutual fund companies strictly forbid short-term trading. Despite this prohibition, special clients were allowed to do it anyway. So, the problem was not with the trading strategy but rather with the unethical and unfair implementation of that strategy, which permitted some investors to engage in it while excluding others. All of the world's greatest investors rely, to some extent, on market timing for their success. Whether they base their buy-sell decisions on fundamental analysis of the markets, technical analysis of individual companies, personal intuition, or all of the above, the ultimate reason for their success involves making the right trades at the right time. In most cases, those decisions involve extended periods of time and are based on buy-and-hold investment strategies. Value investing is a clear example, as the strategy is based on buying stocks that trade for less than their intrinsic values and selling them when their value is recognized in the marketplace. Most value investors are known for their patience, as undervalued stocks often remain undervalued for significant periods of time. Some investors choose a blend of technical, fundamental and environmental factors to influence where and when they invest. These strategists reject the 'chance' theory of investing, and attribute their higher level of returns to both insight and discipline