What Is Manual Trading?
Manual trading is a trading method that uses human decision-making to enter and exit transactions.
In contrast, automated trading uses computer algorithms to generate transactions based on algorithmic or human-instructed criteria.
- Manual trading relies on human decision-making to initiate and exit deals rather than computers and algorithms.
- Manual traders are often aided in their trading choices by programs and technology.
- Both manual and automatic trading have advantages and disadvantages, and it is up to the individual to choose whatever works best for them.
Understanding Manual Trading
Manual traders often use computer programs to consolidate information. They may also configure automatic indicators to inform them of prospective trading opportunities in certain circumstances. When manual trading, however, human involvement is necessary in all circumstances to approve deals.
The question of whether automated trading is advisable or not is still being debated. Some traders argue that manual trading is preferable since it requires human judgment to evaluate market movements and limit risk. They believe that monitoring data and combining it for human interpretation is the correct place for automation.
Proponents of automated trading say that it is preferable because it eliminates illogical human behavior from the equation. Manual trading is often based on emotion, while automated trading is based on rules and data. However, this is not always the case, since a manual trader might build their approach on strong reasoning, data, and discipline.
Manual vs. Automated Trading
Automated trading systems, also known as mechanical trading systems, algorithmic trading, automated trading, or system trading, enable traders to create particular rules for trade entry and exit that, once programmed, may be performed automatically by a computer.
Automated systems must still be designed by humans, which implies they are susceptible to human mistake, only the faults occur in the programming code rather than the execution of the code. Although automated trading minimizes the frequency of errors, such as fat finger mistakes that are more common in manual trading, faults do occur when creating or implementing an automated system.
Time will tell if computers outperform humans in capital allocation. In the meantime, many investors prefer to have a person execute buy and sell orders manually. Flash crashes are a sobering reminder that entrusting financial choices to computers is fraught with danger. The most notable example is the May 2010 flash collapse. Popular indices such as the S&P 500, Dow Jones Industrial Average, and Nasdaq Composite fell 5-6% in minutes and rapidly recovered. During the flash collapse, several individual stocks traded for a cent or less, while others traded for $100,000 or more before values returned to normal.
Following this incident, traders and regulators alike accused computer-automated trading systems, which were set up to execute rapid-fire buy and sell orders. Investors and money managers have not forgotten the market-destabilizing potential of computer-driven investing methods since then.
Manual Trading Strategies
A manual trading strategy is any technique that includes a person setting buy and sell orders. Some prominent trading strategies include buy-and-hold. This is when an investor acquires investments that they feel will increase in value over time. Because transactions are uncommon, they are often completed manually when an opportunity occurs. The investor may sell at a set price or when a technical or fundamental indication indicates that it is time to depart.
Swing trading may be done manually or automatically, and it entails making deals that span from a few days to a few months. The fundamental concept is to take advantage of the majority of a predicted price move during a trend or price range, then exit and move on to the next chance.
Day trading may be done manually or automatically, and it entails making many trades each day to capitalize on intraday price changes.
Manual Trading Example
Jim is a trend follower. He seeks chances to enter highly trending equities around the 100-day moving average (MA), and then exits using the 100-day MA. Because there is some subjectivity involved when he initiates a deal, this necessitates manual trading. Subjectivity does not transition well into an automated system.
For example, Jim often loves to see a rising stock dip just below the 100-day MA, then climb back above, triggering his long trade. Once in the trade, he leaves when the price falls below the 100-day moving average. Price cannot also be going sideways. It must be on an upward trend. This helps to prevent whipsaw situations in which the price travels back and forth over the MA while moving laterally.
Netflix (NFLX) was on the rise in 2017. It temporarily fell below the 100-day moving average, providing some gap below the line, before rising back above. Jim made a purchase. Jim sold at the end of the year when the price fell below the 100-day moving average.
Image by Sabrina Jiang © Investopedia2021
Soon after he sold, the price found support at the 100-day moving average and then began to surge off of it. Jim made another purchase. This trade lasted most of the year until the price fell below the 100-day moving average again. Jim resigned from his post.
Soon after, the price, which was still in an uptrend, passed back above the MA, prompting Jim to go long. He was forced to sell a few days later when Netflix stock continued to fall. The uptrend was in doubt at this time, and the price was whipsawing the MA.
This is a predicament Jim prefers to avoid, therefore he chose not to trade any of the crossings that happened in the remaining months of 2018 and 2019. Subjective decision-making is very difficult to program into a machine. As a result, Jim prefers to place all of his transactions by hand.
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