Get started

Lossaversion

Discover How Thinking Like a Consultant Can Improve Your Trades█ Self–other decision making and loss aversion You might think that I have discussed this topic in depth before, and you would be right. However, there is still much more to explore. This article delves into an excellent research paper by Evan Polman, which examines changes in decision-making behavior when choices are made for oneself versus for others. By studying self-other decision-making, we can uncover varying degrees of loss aversion and gain insights to enhance trading strategies and risk management practices. █ Results Polman's research reveals that individuals exhibit lower levels of loss aversion when making decisions for others compared to themselves. The study found that people are more willing to take risks and are less sensitive to potential losses when the consequences affect others rather than themselves. This reduction in loss aversion is attributed to increased psychological distance and a more abstract level of thinking when making decisions on behalf of others. █ How Understanding Self–Other Decision Making Can Enhance Your Trading Strategies In the dynamic world of trading, making the right decision at the right time is crucial. Yet, how often do we consider the psychological underpinnings that influence these decisions? Recent research on self-other decision making and loss aversion offers valuable insights that can transform our approach to trading and investment management. █ Making Decisions for Yourself vs. Others A study by Evan Polman from New York University found that people make different decisions for themselves compared to when they make decisions for others. The study showed that we tend to be less afraid of losses when deciding for others. This is known as having less "loss aversion." Loss aversion means that people usually fear losing money more than they enjoy gaining the same amount. For example, losing $100 feels worse than gaining $100 feels good. This fear can make us overly cautious and miss out on good opportunities. █ Psychological Distance and Construal Level Theory According to the construal level theory (CLT) proposed by Trope and Liberman, the psychological distance between an individual and an event affects how they mentally construe that event. Greater psychological distance leads to higher-level, more abstract thinking, while lesser distance results in lower-level, more concrete thinking. When making decisions for others, the increased psychological distance can lead to more abstract thinking, reducing the emotional impact of potential losses. This shift in perspective can decrease loss aversion, as decision-makers focus more on long-term outcomes and broader goals rather than immediate losses. █ What This Means for Traders Less Fear of Losses When Trading for Others: When you trade for someone else, like giving advice to a friend, you’re less likely to be overly cautious. This can help you make more balanced decisions and potentially increase profits. Psychological Distance: When deciding for others, you think more abstractly and are less emotionally involved. Try to create this psychological distance when trading for yourself by imagining you’re making the decision for someone else. This can help you stay calm and make better choices. Better Risk Management: Knowing that you’re less afraid of losses when trading for others can help you manage risks better. Use this awareness to avoid being too conservative and missing out on profitable trades. █ Practical Tips for Traders Think Like a Consultant: When trading for yourself, pretend you’re advising a friend. This can help you stay objective and make better decisions. Collaborate: Discuss your trading ideas with others. Getting different perspectives can help reduce individual biases and improve your strategy. Review Your Trades: Regularly look back at your trades to see if you’re being too cautious. Learn from your mistakes and successes to improve future decisions. Use Tools: Use trading tools and software that help you analyze risks and rewards clearly. These tools can support your decision-making process. █  Reference Polman, E. (2012). Self–other decision making and loss aversion. Organizational Behavior and Human Decision Processes, 119(2), 141-150. doi:10.1016/j.obhdp.2012.06.005 ----------------- Disclaimer This is an educational study for entertainment purposes only. The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Education
by Zeiierman
5
How Prospect Theory and the Disposition Effect Influence Prices█ Prospect theory, the disposition effect, and asset prices In the research paper "Prospect Theory, the Disposition Effect, and Asset Prices," authors Yan Li and Liyan Yang delve into the implications of prospect theory on asset pricing and trading volume through the lens of the disposition effect. The disposition effect, a tendency to sell assets that have increased in value while holding onto assets that have declined, is a well-documented behavioral bias among investors. Results: The study finds that diminishing sensitivity predicts a disposition effect, price momentum, reduced return volatility, and a positive return-volume correlation. Conversely, loss aversion generally predicts opposite outcomes. █ Background and Theory ⚪ Agency theory examines the relationship between principals (owners) and agents (managers), focusing on aligning their interests through contracts and incentives. ⚪ Prospect theory , introduced by Kahneman and Tversky (1979), is a behavioral model that describes how people make decisions involving risk and uncertainty. Unlike traditional utility theory, prospect theory suggests that people value gains and losses differently, leading to risk-averse behavior for gains and risk-seeking behavior for losses. Explanation of Risk Aversion and Loss Aversion Risk aversion is the tendency to prefer certainty over a gamble with a higher or equal expected value. In contrast, loss aversion implies that losses loom larger than gains, making individuals more sensitive to potential losses than to equivalent gains. This phenomenon is captured by the S-shaped value function in prospect theory, which is concave for gains and convex for losses. █ Methodology The research uses a comprehensive model to understand how psychological factors like fear of losses and changing sensitivity to gains and losses affect trading and market behavior. This model looks at both diminishing sensitivity (caring less about bigger changes) and loss aversion (fear of losing money) together. The study's data comes from traders and managers at four big investment banks, including people with different levels of experience and jobs. This gives a broad view of how trading behavior works at these banks. █ Findings Disposition Effect What's Happening: Investors tend to sell stocks that have gone up in value and hold onto stocks that have gone down. Why: Because they are highly sensitive to gains but less sensitive to losses. Evidence: The study shows that people are about 15% more likely to sell stocks that have gone up than those that have gone down. Price Momentum What's Happening: Because of the disposition effect, stock prices keep moving in the same direction for a while before correcting. Why: Investors sell winning stocks quickly and hold onto losing ones, so prices don’t adjust immediately to new information. Evidence: Stocks that performed well continue to do better than those that performed poorly, by about 1% per month over six months to a year. Higher Equity Premium What's Happening: Investors demand higher returns for holding riskier stocks due to fear of losses. Why: Loss aversion makes them want more return to compensate for the risk. Evidence: Historically, stocks have returned about 6% more per year than risk-free assets, which is known as the equity premium puzzle. █ Practical Implications for Retail Traders Retail traders can derive several practical applications from these findings to improve their trading strategies: Risk Management: Understanding that loss aversion may lead to holding losing stocks longer, traders should implement strict stop-loss policies to mitigate this bias. Profit-Taking Strategies: Recognizing the reversed disposition effect, traders should establish clear profit-taking rules to avoid prematurely selling winning stocks. Market Volatility Awareness: Being aware that market volatility can exacerbate loss aversion effects, traders should seek higher returns to compensate for perceived risks. █ Applying Knowledge from the Study Retail traders can apply the knowledge from this study in several effective ways: Implementing Stop-Loss Orders: Setting automatic stop-loss orders helps circumvent the emotional impact of loss aversion, ensuring losses are capped at predetermined levels. Regular Review of Holdings: Periodic reassessment of stock holdings can help overcome the inertia caused by loss aversion, enabling more rational decision-making. Diversification: Diversifying the portfolio can mitigate the impact of loss aversion on individual stock performance, reducing overall portfolio risk. Education on Cognitive Biases: Educating themselves about cognitive biases like loss aversion and the disposition effect can help traders recognize and counteract these biases in their trading behavior. █ Reference Li, Y., & Yang, L. (2013). Prospect theory, the disposition effect, and asset prices. Journal of Financial Economics, 107(3), 715-739. doi:10.1016/j.jfineco.2012.11.002 ----------------- Disclaimer This is an educational study for entertainment purposes only. The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
OANDA:DE30EUREducation
by Zeiierman
Traders, managers and loss aversion in investment banking█  Traders, managers and loss aversion in investment banking In investment banking institutions, traders and managers exert immense pressure to maximize gains while minimizing losses. In fact, loss aversion, the tendency to prefer avoiding losses over acquiring equivalent gains, is what influences most of their decision-making. If not managed effectively, this bias can lead to suboptimal trading decisions and significantly impact the overall performance of financial institutions. This comprehensive field study by Willmana et al., "Traders, Managers, and Loss Aversion in Investment Banking," examines how loss aversion manifests among traders and managers in four major investment banks. The study integrates insights from agency theory and prospect theory to explore the risk management strategies employed by both groups. █  Background and Theory Two critical theories, agency theory, and prospect theory, help explain how individuals within these institutions make decisions. Agency Theory: This theory deals with the relationship between principals (e.g., shareholders) and agents (e.g., managers and traders). It posits that agents employed to make decisions on behalf of principals may not always act in the principal's best interests due to differing goals and risk appetites. For instance, if you're a trader, you might engage in riskier behavior to maximize your bonuses. At the same time, your managers might prioritize stability and risk mitigation to protect their positions. Prospect Theory: Introduced by Daniel Kahneman and Amos Tversky, prospect theory describes how people choose between probabilistic alternatives that involve risk. It highlights two main biases: loss aversion and the framing effect. Loss aversion is the tendency to prefer avoiding losses over acquiring equivalent gains, and the framing effect shows that the way a problem or decision is presented can significantly impact choices. █  Explanation of Risk Aversion and Loss Aversion Risk Aversion: It is the preference for certainty over uncertainty. In the context of trading, risk-averse individuals prefer investments with lower risk and potentially lower returns over those with higher risk and higher potential returns. Loss Aversion: A central component of prospect theory, loss aversion suggests that the pain of losing is psychologically about twice as powerful as the pleasure of gaining. This bias can lead traders to hold onto losing positions longer than is rational and to sell winning positions too quickly, seeking to lock in gains and avoid realizing losses. █  Methodology The study by Willmana et al. utilizes a qualitative research approach, focusing on detailed interviews to gather insights into the behaviors and attitudes of traders and managers in investment banking. The researchers interviewed 118 traders and managers across four leading investment banks. These interviews included questions about motivations, emotions, trading strategies, organizational culture, and experiences with gains and losses. Additionally, 10 senior managers participated in the management interview section, providing a broader perspective on organizational practices and controls. █  Key Findings Managers are primarily concerned with mitigating losses rather than maximizing gains. Position holders tend to intervene more aggressively when traders experience losses, emphasizing the need to cut losing positions quickly to prevent further deterioration. The study found that managers used veto power primarily to reduce risk. As one manager said, "My veto works only one way—to reduce risk." Managers frequently highlighted the importance of controlling downside risk. One manager noted, "My role as a manager is to cover the downside rather than the upside. I try to enforce the discipline of cutting losses rather than pushing them to add to positions." ⚪ Differences in Risk Management Strategies The study revealed traders often operate with significant autonomy and tend to take on more risk, particularly in pursuing higher bonuses. Conversely, managers focus on ensuring that risk levels remain within acceptable limits, stepping in mainly to curtail losses. The research showed that managers are generally ex-traders who understand the technical complexities of trading. However, their managerial role shifts their focus towards risk containment. One trader mentioned, "95% of the time, managers are traders who have been in the business a long time and they have no real management skills." Traders have a strong ethos of autonomy, with managers intervening only when necessary. A manager noted, "I consider I have a veto on any positions my traders take, even when they are within their limits. But, to give you an idea, I think last year I used it once, the year before twice, and this year, not at all." ⚪ Impact of Bonus Structures and Incentive Systems The study found that these systems often drive traders to take on higher risks to achieve performance targets, especially as the year-end approaches. Over half of the traders in the sample earned over £300,000 per annum, with bonuses constituting a significant portion of their total compensation. The direction of risk-bearing behavior varied among traders toward the end of the compensation year. Some traders became risk-averse to protect their gains, while others increased their risk tolerance. One trader stated, "Risk tolerance becomes infinite at the end of the year because we don't have any personal exposure to our results in the last couple of months; we can almost become less discriminating in the trades we put on." █ Practical Implications for Retail Traders Retail traders can draw several practical implications from the findings of this study: ⚪ Awareness of Loss Aversion: Retail traders should recognize their own tendencies towards loss aversion and implement strategies to manage this bias. This might include setting predefined stop-loss limits and adhering to them strictly to avoid letting losses run. ⚪ Structured Risk Management: Just as investment bank managers focus on controlling downside risk, retail traders should establish clear risk management frameworks. This includes setting risk limits for each trade and not deviating from these limits based on emotional responses. ⚪ Balanced Focus on Gains and Losses: While avoiding losses is crucial, retail traders should also develop strategies to maximize gains. This involves identifying opportunities for larger positions when the probability of success is high, without succumbing to undue caution after achieving small gains. ⚪ Bonus and Reward Systems: Retail traders should design their own reward systems to align with their trading goals. For instance, setting incremental performance targets and rewarding themselves upon achieving these can help maintain motivation and discipline. ⚪ Continuous Learning and Adaptation: Managers in investment banks often act as mentors, providing guidance based on their experience. Retail traders should seek out mentorship or peer support to learn from more experienced traders. Participating in trading communities and continuous education can help improve trading performance over time. █ Applying Knowledge from the Study Retail traders can apply the knowledge derived from this study in several ways: ⚪ Develop a Trading Plan: Create a comprehensive trading plan that includes risk management rules, entry and exit strategies, and guidelines for handling losses. Regularly review and update this plan based on trading performance and market conditions. ⚪ Implement Risk Controls: Use tools such as stop-loss orders, position sizing strategies, and diversification to manage risk effectively. Ensure that these controls are strictly followed to prevent emotional trading decisions. ⚪ Monitor Performance and Adjust: Regularly review trading performance to identify patterns of loss aversion or risk-seeking behavior. Use this analysis to adjust trading strategies and improve decision-making processes. ⚪ Seek Continuous Improvement: Engage in ongoing education through books, courses, and trading simulations. Stay updated on market trends and behavioral finance insights to refine trading strategies continuously. By understanding the dynamics of loss aversion and the importance of structured risk management, retail traders can enhance their trading discipline and improve their chances of long-term success. █  Reference Willman, P., Fenton-O’Creevy, M., Nicholson, N., & Soane, E. (2002). Traders, managers and loss aversion in investment banking: A field study. Accounting, Organizations and Society, 27(1-2), 85-98. doi:10.1016/S0361-3682(01)00029-0. ----------------- Disclaimer This is an educational study for entertainment purposes only. The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
OANDA:BCOUSDEducation
by Zeiierman
Myopic loss aversion and market experience█  Myopic loss aversion and market experience Myopic Loss Aversion (MLA) is a behavioral bias that severely affects trading behavior, particularly the tendency to avoid losses more aggressively than to pursue equivalent gains. This bias can lead you to make suboptimal decisions, such as selling winning assets too quickly or holding onto losing assets for too long. Today, we're exploring a study by Mayhewa et al. that explores the interaction between MLA and market experience. Quick Results: Remarkably, experienced traders showed significantly reduced signs of MLA when operating in familiar market environments or under conditions of low-frequency information updates. This suggests that both familiarity with market dynamics and a strategic reduction in the overload of market information can help temper emotional, short-sighted decision-making. █  Study Overview ⚪ Methodology and Participant Structure The research, conducted by leading economists, employed an experimental market setup where participants engaged in trading sessions under controlled conditions. The study distinguished between inexperienced and experienced traders to gauge how repeated market exposure influences MLA. Participants were divided into two main groups based on their trading experience, with further subdivisions based on the frequency of financial information they received. One group received continuous updates (high-frequency information), while another received less frequent updates (low-frequency information), allowing the study to isolate the impact of information frequency on trading behavior. ⚪ Experimental Design The core of the experimental design involved a series of trading tasks where participants were required to make investment decisions across several trading periods. The study introduced a key modification from previous research by incorporating a 'moving average' display—showing the average asset values alongside real-time prices. This addition was intended to reduce cognitive load and help participants make more informed decisions by providing a clearer context for the asset's performance over time. ⚪ Initial Hypotheses The researchers hypothesized that: Traders with more market experience would exhibit less myopic loss aversion than their less experienced counterparts. Providing a moving average of asset values would help mitigate the MLA effect by smoothing out the emotional impact of short-term price fluctuations and emphasizing longer-term trends. Less frequent information updates might reduce MLA by limiting the 'noise' or emotional reaction to price movements, thus encouraging more rational, long-term thinking. █  Key Findings ⚪ Impact of Information Frequency The frequency at which traders receive market information plays a crucial role in shaping their trading decisions and susceptibility to Myopic Loss Aversion (MLA). The study found that high-frequency information updates, which provide continuous price data, tend to exacerbate MLA. This is because constant exposure to market fluctuations heightens emotional responses, leading traders to make more short-term decisions to avoid perceived losses. Conversely, less frequent information updates can help mitigate MLA. By reducing the noise from constant price movements, traders are encouraged to focus on longer-term trends rather than reacting to short-term volatility. ⚪ Role of Market Experience The study revealed that experienced traders with substantial exposure to market dynamics show markedly reduced signs of MLA in familiar trading environments. These traders may be better equipped to handle the emotional pressures of trading, well not so much. The research also indicated that experienced traders might revert to MLA behaviors in different trading setups or allocation tasks with which they are less familiar. ⚪ Moving Averages and Cognitive Effects The findings suggest that displaying moving averages is effective in reducing MLA. Traders with access to moving averages were less likely to make impulsive decisions based on short-term losses. Instead, they were more inclined to consider the overall trend and value of the asset over time. This cognitive tool helps traders maintain a broader perspective, which is crucial for mitigating emotional biases and making more informed, strategic decisions. █  Conclusion Understanding and mitigating Myopic Loss Aversion (MLA) is crucial for improving trading outcomes, particularly in the volatile and fast-paced markets. Experienced traders tend to exhibit lower levels of MLA in familiar environments, but they are not entirely immune to it. The context-dependent nature of MLA reduction among experienced traders highlights the importance of continuous adaptation and learning. Additionally, reducing the frequency of information updates and utilizing moving averages can help traders maintain a broader perspective, further mitigating the impact of MLA. █  Reference Mayhew, B. W., & Vitalis, A. (2014). Myopic loss aversion and market experience. Journal of Economic Behavior & Organization, 97, 113-125. doi:10.1016/j.jebo.2013.10.007 ----------------- Disclaimer This is an educational study for entertainment purposes only. The information in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell securities. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on evaluating their financial circumstances, investment objectives, risk tolerance, and liquidity needs. My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Education
by Zeiierman
1
Why using automated trading? #1There are a couple of reasons why to use automated trading, like better risk management, human error, easier to diversify, and Psychology In this post, the focus is on psychology. Here are some of the cognitive biases that affect trading: Loss aversion - the tendency to prefer avoiding losses to acquiring equivalent gains. It feels much worse losing $100 than the joy from earning $100. (A huge topic, the researchers got the Nobel prize for this) Sunk cost - the tendency to treat money that already has been committed or spent as more valuable than money that may be spent in the future. In trading, this effect with loss aversion making people not cut their losses. When we enter a trade we know that a loss can happen, if the losses are not cut the rest of the money in the account can be lost too. The disposition effect - is an anomaly discovered in behavioral finance. It relates to the tendency of investors to sell assets that have increased in value while keeping assets that have dropped in value. Traders tend to lock in gains and ride losses. Recency bias - a cognitive bias that favors recent events over historic ones, in trading, a streak of losses can demoralize a trader even if he had a good run for a long time. I don't know of a system that works 100% of the time. There are more psychological effects, but those are the main ones. Using automated trading, allows traders to reduce these effects on trading because the stocks are chosen in advance, the risk is defined, the entry and exit are calculated and executed by the algorithm (Unless rare events are happening). In the past, I was sometimes afraid of entering a good trade or cut my loss quickly, due to these effects and wishful thinking that the price will do what I want.
AMEX:SPYEducation
by ZoharCho
Irrational behavior: Victim mentality, risk & loss aversionPeople that call themselves neuro-economists make all sorts of experiments, the ABCD questions are from Kahneman and Tversky from 40 years ago, I found these examples on stanford website. There was another similar study, or series of studies in Lyon, France. They got people to speculate and when they dangled the carrot in front of them they basically created Bitcoin: Some researchers looked at institution traders and found the ones taking the most risks had the highest male hormones. I wonder how it is for the girls? They sometimes take big risks I'm sure, and let's ignore the dumb gambling mentality ones that's not who I mean. Maybe they rather get into bonds and stick to small risks safe returns? Any degen out there? All the big losing (famous) rogue traders are boys, so maybe there is something here, still I think the main reason is they hold bags and add to them. Nick Lesson is a legend, a superhero, he turned a 20 thousand loss into an 800 million one, why aren't people fighting to hire him? Can I hire the guy? Going to take his valuable advice and do the opposite. 20k into 800,000k! Another legend is Karen the supertrader, I don't think her high T made her lose millions. Just loss aversion and being a complete psychopath. I guess at some point it's not risk taking but loss aversion, technically/logically they are taking enormous risks out of fear of losing, but they are not logical so... Markets have been around 4000 years and derivatives at least 10,000. And people still don't get why. It is a place for risk averse persons yes, but they are the end user, the "client", the markets help out people get rid of their risk at a price. Once again, 0 logic: It makes absolutely no sense that risk-averse and loss-averse players would try to make money in the markets. The subject is fascinating to me, I have this impression I have dropped on an alien planet where nothing makes sense and it feels so fantastic, like I am in a Star Trek episode. I think (I am quite certain of it) we can see this in full display with Bitcoin: These are not winning odds... Also notice all these Bitcoin baghodlers that like to talk a lot in hindsight NEVER tell anyone what their position is and NEVER have an idea on their profile. Emotional (illogical) brain and low hormones (even moar risk aversion) is a bad combination... You look at some people that lied to police to avoid losing their job or reputation and that would never have lied to get the job in the first place... The majority always runs away from profit when it is objectively much better, and instead chooses the much smaller but guaranteed reward. And the majority will choose taking huge not worth it risks to avoid a loss, rather than just take a small loss and be on their merry way. I find it stunning than the majority of people could literally have the holy grail, and they would still mess it up because they are scared. This game (obviously) is not about changing and managing your emotions. Or autists would all be billionaires it's so obvious... Guess who these "it's easy it's all about emotions" ads are targetted to? What it takes is thousands of hours of screen time, practice, backtesting, reading, number crunching. The emotion stuff everyone learns about at the start is just a way to weed out the ones not meant to play this game. There are plenty other activities out there. As far as I am concerned if an individual has it deeply rooted in their subconscious this "bug", there is no way to rewire the brain this deep. For the (13% according to these questions lol) that have the ability to compete, it's a matter of spending the time getting good and rub hands when noobs cheerfully pile in, in a bubble or when trading gets popular in general (and then they create bubbles). The predators can abuse these cheerful greedy noobs and have a huge feast. When they baghold for ages or keep holding the price down it's less interesting though. But part of me wants to have this image of stomping noobs. Well Bitcoin was bagheld more than usual because they saw it go up so many times before (still super irrational and still sold the bottom for the most part, somehow XD), but hey they are pumping the S&P like the Nasdaq in 2000 right? The noobs are also going to sell GME fast right? After buying it up fast. (Sad I can't short). I don't think this info is really useful to be honest, the people without the illogical bug won't get much out of it (it's cool to know where the illogical as regulators say "inefficient" patterns come from), the people with the illogical bug will be in denial and convinced they are part of the winners. Is this anything more than an ego stroke and having a laugh while belittling illogical risk averse people? Well I think it's interesting, and plenty of scientists do too.
Education
by MrRenev