Written by: Chenzi McLoyd
In an age where short-form content platforms such as TikTok and Instagram are becoming increasingly popular, accessing a vast quantity of information within a short timeframe has never been easier. From productivity hacks to workout advice, there are videos on virtually every topic imaginable, all accessible with a quick search or a swipe of the finger. Out of these, one content area that has blown up especially in recent years is financial investment, particularly the practice of daytrading. Content creators will post videos of them making hundreds to thousands of dollars at a time by rapidly buying and selling financial security, such as stocks, within a single day on their at-home monitors. These videos appeal to viewers because they present day trading as an easy, accessible side-hustle that allows people to make large sums of money from the comfort of one’s own home. While daytrading is technically accessible to anyone through popular brokerage firms like Charles Schwab and Robinhood, it is far from easy, and typically not the reliable source of income that it is made out to be (Hayes, 2025).
While there are success stories of daytraders making significant earnings, these occurrences are few and far between; according to financial analyst and investor Othmane Bennis (2026), a mere 3% of daytraders make a profit, and only 1% are able to do so predictably. Thus, the majority of traders within this small fraction are essentially just lucky, as they win through guesswork as opposed to using data-backed strategies. Supporting these statistics, a 2019 study by Brad Barber (2019), a professor of finance at the University of California Davis, found that 97% of traders lost money. Additionally, a professor named Fernando Chague (2020) at the São Paulo School of Economics found the same result while studying over 20,000 traders over a period of 300 days.
There are a variety of reasons as to why daytrading is widely unprofitable. Firstly, in order to achieve success, one needs experience, as demonstrated by the fact that traders with over 400 days of experience are three times more likely to be profitable (Bennis, 2026). Although this percentage is still quite small, it is measurably higher than that of the general population of day traders. Due to discouragement from early losses, however, the vast majority of people quit too early to take advantage of this; about 40% of traders quit after 30 days, with only 13% remaining after 3 years (Groette, 2026).
Even those persistent enough to continue trading past this mark still tend to fail because they are unaware that the majority of successful traders are professionals working for financial institutions with access to technology that the average person does not possess. Because day trading entails buying and selling assets multiple times a day in rapid succession, complex technical analysis and charting is required to predict price movements. Conversely, long-term investment involves holding positions for months to years based on fundamental economic knowledge and market reports, allowing more time for good decision-making without relying on advanced technology (Kuepper, 2025). A common tool utilized by institutional traders is High-Frequency Trading (HFT), which uses high-caliber computer algorithms to execute a large quantity of trades in fractions of a second. This strategy increases profitability by taking advantage of the many small price movements that are missed by humans. HFT essentially removes all human interaction from trading, which has actually become a source of criticism. Although, the tool has many benefits, primarily its ability to increase market liquidity, which is the ease at which securities can be bought and sold without drastically changing in price. This result is due to its high-volume, high-frequency trading algorithms (Chen, 2025). Without the precision that HFT provides, it is much harder to be predictably profitable while executing trades. Still, those without the technology can still take advantage of two primary types of security analysis: fundamental analysis and technical analysis. Fundamental analysis focuses on a security’s value through understanding the underlying financial and economic factors that may influence it. This includes assessing individual company financial statements as well as wider industry trends. Technical analysis, on the other hand, looks at historical data such as stock price and trading volume to establish trends that can be used to predict a security’s future movement. Because the latter focuses more on gaining insight into potential short-term price movements, it is more prevalent in day trading, although fundamental analysis is still critical in understanding a security’s long-term potential (Horton, 2025; Bush, 2023). Thus, a combination of both methods may be most effective in order to achieve profitability over many years.
With these strategies in place, traders are able to increase their odds of becoming successful considerably. Although, the majority find it difficult to stay consistent with their approach and ultimately ditch it for impulsive decision-making, a common pitfall known as emotional trading (Cabana, 2026). Emotional trading is largely a result of the stressful nature of continuously wagering one’s money; high stress weakens the prefrontal cortex, which is the part of the brain responsible for decision making and impulse control. This occurs because the amygdala, which treats financial loss as a biological threat, triggers the release of various stress chemicals that negatively impact how the prefrontal cortex functions. Because emotional trading thus stems from the brain’s natural functionality, it is very hard to avoid and cannot be solved by simply improving discipline, a prevalent myth (Curtin, 2026).
Research suggests that the best way to mitigate this problem is by setting concrete plans before trading commences, such as deciding the exact amount of total money lost that marks when you will stop trading. This works by forcing the majority of decision making to occur before your brain enters a stressful state, preventing a large portion of impulsive action (Curtin, 2026).
With the widespread marketing of day trading on social media, many people are led to believe that this form of short-term investment is a quick and easy way to make a few bucks. This idea, however, is merely a misconception that fails to take into account the many factors that make it a generally unprofitable undertaking; the competition provided by institutional traders, the technological limitations for the average person, and the complex strategies required to succeed all make it incredibly difficult for the majority to benefit from it. Still, as technology becomes increasingly advanced and more studies are conducted on the possibilities surrounding day trading success and effective approaches, there is hope that this domain will become a prosperous one for the general population, providing a novel pathway to economic success for everyone.
References
Barber, B. M., Lee, Y.-T., Liu, Y.-J., Odean, T., & Zhang, K. (2019). Learning fast or slow? Social Science Research Network. https://doi.org/10.2139/ssrn.2535636
Bennis, O. (2024, November 20). Is Day Trading Profitable? Here’s What Statistics Say. NewTrading. https://www.newtrading.io/is-day-trading-profitable/
Bush, J. (2023, December 19). The Ultimate Day Trading Beginner’s Guide: Mastering the Art of Trading. (2023, December 19). The Chart Guys. https://www.chartguys.com/articles/the-ultimate-day-trading-beginners-guide-mastering-the-art-of-trading
Cabana, K. (2026, March 11). Emotional Trading: How to Recognize It and Stop It From Destroying Your Account. (2026). Trademomentum.org. https://www.trademomentum.org/blog/emotional-trading
Chague, F., De-Losso, R., & Giovannetti, B. (2020). Day trading for a living? Social Science Research Network. https://doi.org/10.2139/ssrn.3423101
Chen, J. (2021, August 25). High-Frequency Trading – HFT. Investopedia. https://www.investopedia.com/terms/h/high-frequency-trading.asp
Groette, O. (2024, February 10). Day Trading Statistics 2024: The Hard Truth – Quantified Trading Strategies. Quantified Strategies. https://www.quantifiedstrategies.com/day-trading-statistics/
Hayes, A. (2020). How Brokerage Companies Work. Investopedia. https://www.investopedia.com/terms/b/brokerage-company.asp
Horton, M. (2021, December 1). Is it better to use fundamental analysis, technical analysis, or quantitative analysis to evaluate long-term investments? Investopedia. https://www.investopedia.com/ask/answers/050515/it-better-use-fundamental-analysis-technical-analysis-or-quantitative-analysis-evaluate-longterm.asp
Kuepper, J. (2019). An introduction to day trading. Investopedia. https://www.investopedia.com/articles/trading/05/011705.asp
Kurtin, K.A. (2026, March 2026). How to Control Your Emotions While Trading (What Neuroscience Actually Says). (2026, March 26). Thewallstreetcoach.com. https://thewallstreetcoach.com/blog/how-to-control-emotions-while-trading/