Can Financial Markets be Forecast? You hear through the grapevine that a coworker doubled his money by investing in financial markets. Hence, you decide to do a quick search online and are captivated by leverage and the apparent ease of profiting through trading financial instruments. You see countless stories of apparent geniuses turning tens of thousands into millions. You pull out your phone the next day and perform some simple compound interest calculations. "If I only make 10% a week, I will have millions in a year!" you say to yourself. However, this is rarely the case. Trading is statistically one of the most challenging professions to master, and for good reason. To be successful in trading, one must not only master complicated maths and financial knowledge, but they must also master their psychology and emotions as the price screen and their account balance fluctuates; this is extremely difficult. "A Security and Exchange Commission's (SEC) study found that 70% of foreign exchange traders lose money every quarter, and on average 100% of retail costumer's investment is gone within twelve months," writes CPA and financial consultant Nick Gallo. An average loss of 100% in twelve months means there is an extremely high probability one loses most of their account balance as a retail trader. Still, the question remains – why? One culprit may be technical analysis. Technical analysis is a popular form of financial analysis primarily used by retail traders who utilize market data to identify trends and make predictions. Since retail traders have an astonishingly poor performance record, we aim to determine if technical analysis chart patterns provide signal in financial markets. Common knowledge may lead one to believe that an average loss of 100% with retail traders over time concludes one should avoid the primary method utilized in retail trading activity at all costs, but this is far from what new traders do. Our stance is that technical analysis does not provide a signal in financial markets because chart patterns are visible in random mathematical models, studies prove the invalidity of chart patterns, and the efficient market hypothesis theorizes a random market. Not all evidence for this hypothesis is empirical, but it can be concluded by association; if a gunshot was heard across the street, and you see a man running away from your neighbor's house with a TV in his hands, you can safely assume he is the burglar – if it looks like a duck, swims like a duck, and squawks like a duck, then it probably is a duck. Likewise, if something shows very similar traits while encompassing certain aspects, it can logically be assumed those aspects are encompassing another thing showing similar traits. Most all technical chart patterns can be found in geometric Brownian motion models of stocks, indicating chart patterns are random and lack signal (22). Brownian motion utilizes stochastic calculus to model random motion, like the movement of particles suspended in a liquid or gas medium. Geometric Brownian motion also models random motion but accounts for positive drift, as is typically seen with a stock's tendency to go up and to the right over time. When these models run for a given ticker symbol, countless – so-called – "chart patterns" appear in the data. The logical fallacy amongst retail traders is that they mistakenly use randomly occurring price phenomena to predict future price movement. If chart patterns generate randomly to begin with, there will be an inherently random result in price after the pattern's occurrence. The image below displays a geometric Brownian motion model of price. The typical head and shoulders pattern is seen at one of the three tops, highlighted within a box, along with a reverse head and shoulders pattern at one of the three bottoms. Support and resistance zones are also seen in the image. Remember, this chart does not represent any ticker symbol but is a random mathematical model graphed onto a chart. It looks eerily like most price screens. However, even though this model displays convincing evidence for the randomness of chart patterns, it is not empirical because the pattern is contained within the model and does not represent real stocks. James McCray: Geometric Brownian Motion Evidence must be found in stocks to posit that technical chart patterns truly have no signal. The study, Noise Trading and Illusory Correlations in US Equity Markets, headed by Morgan Stanley's Jennifer Bender, used data sets from all 304 NYSE and AMEX firms from 1962-2002 – some 40.5 years, as well as 373 NASDAQ firms with at least five years of consecutive data (6). The findings empirically prove that the head and shoulders pattern does not profitably predict directional movement; the only thing the head and shoulders pattern is predictive of is volume, indicating that many retail traders take positions after seeing the pattern (2). Unfortunately, retail traders do not readily observe empirical evidence such as this. A reason may be that some brokerage firms issue technical analysis reports. Proponents of technical analysis often cite this as evidence of technical analysis's validity. However, some brokerage firms issuing a technical analysis report does not vindicate it since there is a conflict of interest in its promotion. Brokerage firms want the highest liquidity, and the tightest bid/ask spreads. In addition, they want to generate the most volume so they can collect as many fees as possible, so they may be willing to feed retail traders whatever is necessary to produce these results. "It is in the best interest of some firms to exploit overly optimistic noise traders (1567), says USC Marshall, School of Business professor David Hirshleifer. Suppose brokerage firms provided retail traders with real ways to extract money from markets. In that case, they would be driving away business since telling customers to learn stochastic calculus or how to read financial statements is not very popular. The root of technical analysis's popularity, however, lies in the belief that markets are not random, which is a heavily debated topic. The efficient market hypothesis states that price reflects all knowledge known by all market participants, thereby making consistent alpha generation or predictability of the market impossible. I.e., price and value are the same. The theory gained notoriety after the release of the 1973 book, "A Random Walk Down Wallstreet," where author Burton Malkiel first posited the idea. If all market participants know all the information available and direct their buy and sell decisions as a result, the current price of any tradable instrument is an accurate representation of the efficient distribution of knowledge in the market. There is no "hidden" knowledge one can acquire to capitalize on trading decisions, except by illegal insider trading. However, the efficient market hypothesis may not be entirely accurate since market bubbles such as the Dutch tulip mania and dotcom bubble would conclude fair value at their extremes. In addition, value investors that deforciant a company's quoted stock price from its fair value would also be unable to generate alpha over time, such as the Warren Buffets of the world. Most of the time, however, the efficient market hypothesis is a much more accurate outlook on financial markets than believing chart patterns provide signal within a random environment. Market inefficiencies are seldom but may be found on occasion, but not by technical analysis. Fundamental analysis and quantitative trading strategies have a much higher win rate and are more successful. In addition, highly specialized knowledge that is hard to understand, and requires deep insight, may provide a noticeable edge in financial markets. Even though the information is available to all market participants, not all market participants have the education to understand or glean insight from the information. "There is evidence that information that is presented in a cognitively costly form is weighed less," says David Hirshleifer, speaking of market participants (1546). He says that abstract and statistical information such as sample size and probabilistic base rates have similar reactions, while easily processed information may have an overreaction by market participants (1546). This makes sense because most participants don’t have the understanding to glean insight from highly technical information. Put another way, there is an inefficiency of digestible knowledge in the market, which leaves room for exploitation by knowledgeable persons, such as the Michael Burrys' that called the 2008 housing crisis. While there may be rare situations of market inefficiencies, the geometric Brownian motion, head and shoulder studies, and efficient market hypothesis all confirm a random market, which concludes that most folks will statistically be much better off investing in conservative investment funds. As the adage goes, "it is not timing the market, but time in the market that prevails." This is easier said than done because most people's greed and desire for riches are the very traits that cause them to overtrade, take on too much leverage, and blow up their accounts. This is not to say profitable trading is impossible, but it is hard, as most things worthwhile are; "all things excellent are as difficult as they are rare." – Baruch Spinoza. Works Cited: Bender Jennifer C. et al. “Noise Trading and Illusory Correlations in US Equity Markets.” https://www.bayes.city.ac.uk/__data/assets/pdf_file/0006/79953/Simon.pdf Lidén Joel, “Stock Price Predictions using a Geometric Brownian Motion.” Department of Mathematics, Uppsala University. June 2018. https://uu.diva- portal.org/smash/get/diva2:1218088/FULLTEXT01.pdf Malkiel, Burton Gordon. A Random Walk down Wall Street : the Time-Tested Strategy for Successful Investing. New York :W.W. Norton, 2003. Hirshleifer, David. “Investor Psychology and Asset Pricing.” The Journal of Finance, vol. 56, no. 4, 2001, pp. 1533–97. JSTOR, http://www.jstor.org/stable/2697808. Accessed 21 Jul. 2022. Gallo, Nick. “Why Do Stock Traders Lose Money.” Finmasters.com. June 29, 2022. https://finmasters.com/why-traders-lose- money/#:~:text=A%20Securities%20and%20Exchange%20Commission,gone%20within %2012%20months3.