A research estimate stated that 95% of traders lose money in the leading virtual currency, bitcoin. Indeed, bitcoin isn’t immune to human motion and the present market forces. A majority of traders are familiar with the statistics from this research. Even when you get deeper into it, you’ll realize the number is probably higher than stated. Most of them end up quitting after losing money, especially beginner traders that find it tough to gain ground in the market. This block contains several reasons why bitcoin day traders lose money. Kindly continue reading to understand better.
Statistics showing traders’ hardships.
Among the most common reasons is the mindset of being your boss. People think it’s all about merely sitting on the couch and making substantial money sums from home. Thoughts of getting easy money and independent wealth is what kills most traders.
You should understand that day trading in bitcoin isn’t a bed of roses. It’s challenging, taxing you emotionally, and may damage your entire life. The online educational resource trade city has the following striking statistics indicating how rough it is for traders. You may learn more here.
- Almost 40% of all day traders try trading for one month.
- 80% quit trading within the first or second year.
- Around 13% keep day trading in the first three years, but 7% will be on after five years.
- Traders recording failure for up to 10 years continues with the trade.
- 5% of active traders underperform annually.
- Average individual investors underperform a market index by 1.5% annually.
Shockingly, most of them make losses and underperform. Still, it never matters. Trading continues despite the negative sign of their ability in the market. These traders are truly underprepared for what should be done. It makes them learn the hard way using their real cash. They fail to rate psychological trading challenges and include emotions in the trade. Most of them forget trading with a defined system—those who fail to use their established rules governing the trade.
Defining random reinforcement
Traders also fail due to the random reinforcement principle. It’s a concept elaborating a reason for traders not quitting even after making several fails. We can describe random reinforcement as seconding a negative or positive behavior from naturally inconsistent outcomes, such as from the financial markets. Did you know that the market has a bad character of rewarding what’s bad and punishing a positive behavior? It mostly happens with a set sample. Look at the following narrative that explains this principle better;
For example, Rose is willing and ready to quit her job and start crypto trading. Having enough capital with little knowledge from big twitter names of people in the cryptocurrency trade, her attention grows. She talks about an altcoin and its rising prices daily and decides to buy. After some time, she sells it for quicker returns. She does this a second and third or fourth time getting successful trades. Her confidence in the trade grows, and she thinks it’s a talent. Do you think there’s any problem?
Rose is trading with no plan or system. She’s getting fooled that two-three successful random trades indicate potential success as time goes by. That’s when we see the market gratifying bad habits. It’s obvious how the final result will be- she’ll keep doing impulsive buying and, at last, lose her capital. The leaf now flips to the other side.
Rose may later learn her lesson after the loss and develops a trading plan in a few months. She comes up with risk management measures, trade rules, and portfolio allocations. She finds out a reasonable trading opportunity, does what’s expected to get started, then stops. She gives it a try once again, and again, failing around seven consecutive times. Here we say the market is punishing her for behaving well. It makes Rose to begin doubting the system and embark on a high-risk plan violating the rules- gains success. She also succeeds after trying a second and third time. This means bad behavior is being rewarded, making her go back to the first square.
Understanding bitcoin trading
Do you want to sustain various consecutive losses? If you do, then don’t allow risking more than one percent risk to any portfolio. A trader needs to test and make adjustments to plans for a long time. You can always identify a good system by its edge over a long period- it should be good. It’s because using randomness grows into a minor factor when a sample enlarges. Please understand that a productive trade isn’t defined by its outcome, but a planned idea by the trader who traded the plan and manages risks that came with it; elements under their control.
On the contrary, a bad trade happens when a trader doesn’t follow the rules as they execute it against their judgment. Be sure it’ll go wrong despite making a profit. If you really want to get counted among the remaining five percent that succeed in day trading, act smart. Start by creating a properly-tested plan to help overcome challenges caused by random reinforcement as we looked earlier. Additionally, get rid of impulse and emotion and gain more knowledge of being profitable. In this way, you’d be sure of joining the remaining part of traders.
The bottom line
Statistics state that 95% of traders lose money in trade, and most of them are aware. Looking deeper into it, you realize the number is likely more than said. It leaves someone wondering why smart people are drawn to a profession with great failure odds. Most traders live thinking it’s a chance to be your boss. They therefore sit and wait to make millions. They’re lured by the false promise of getting easy money plus independent wealth.
The challenge begins with the failure to comprehend that day trading is not as simple as thought. It’s highly taxing and can destroy one’s life than making it better as presumed. Random reinforcement is also another reason giving the wrong mindset in trading. It’s worsened by the market, which rewards bad deeds and rebukes good behavior, like what happened to Rose. Also, it would help to learn about bitcoin scams. You can Learn More Here.
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