In the stock market, there exists a method to analyze data and achieve desired results. This method, known as data mining, involves extracting patterns or results from various data sets. In fields like economics, where controlled experiments cannot be repeated, data mining is widely used to manipulate data and derive desired outcomes. For example, if one wishes to understand how to make money through stocks, data mining can be employed. By analyzing different trading techniques, such as buying and selling every three days or trading when certain indicators reach specific values, one can identify which methods yield the best returns.
Data Mining and System Trading
The Principle of Data Mining
Data mining involves collecting and analyzing diverse data sets. For instance, if you want to make money from stocks, you can apply different trading techniques to historical stock price movements. By doing so, you can easily determine which method yields the highest returns.
The Popularity of System Trading
System trading, based on data mining, allows computers to execute trades automatically. It gained popularity among Japanese individual investors because of its simplicity and ease of use. However, even models that consistently generated profits for a certain period showed dramatically different results when the application period was slightly altered. This inconsistency led many investors to abandon system trading.
Limitations and Issues of Data Mining
Limitations of Data Mining
A common issue with data mining is the tendency to attribute results to a few causes while ignoring other potential factors. In economics, similar simplifications can lead to flawed models by focusing on a few manageable causes while disregarding more complex, realistic hypotheses.
Investor Misconceptions
Investors using online trading platforms (HTS) often view themselves as geniuses, unlike those who rely on brokerage firms' advice and tend to be more cautious. To satisfy these tech-savvy investors, brokerage firms offer features that allow them to create their own indicators by manipulating data such as opening price, high, low, closing price, and trading volume.
Market Changes and Investor Responses
The Constant Evolution of the Market
The market continuously evolves based on how participants react and which techniques they employ. A previously effective indicator may no longer be reliable. The market's composition changes every moment, making it impossible to measure with a fixed yardstick.
Diverse Investors
Investors in the market are highly diverse, ranging from seasoned traders with decades of experience to elementary school students experimenting with stock trading. They may base their investments on company value, technical charts, or algorithmic programs. Predicting their actions with certainty is challenging.
The Reality of Mysterious Trading Indicators
The So-called "Magic Indicators"
At one point, a "magic indicator" developed by a certain securities firm gained popularity. However, if these indicators were truly profitable, they would be exclusively used by fund managers rather than being disclosed to the public. It's puzzling that some investors trust these indicators without understanding their criteria for generating signals.
The Reality for Individual Investors
Many individual investors initially embraced system trading but eventually gave up. The market is dynamic, and neither data mining nor mysterious trading rules can account for all variables. As such, a careful and diversified approach to investing is essential.
Conclusion
System trading and data mining are attractive tools in stock investment, but it is crucial to recognize their limitations and issues. The market is in constant flux, and simple analyses cannot account for all influencing factors. Therefore, a cautious and varied approach to investment is necessary.
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