Quantitative trading system development strategy plan

Quantitative trading strategies use computer software programs and spreadsheets to track patterns or trends in trading behavior. Find trends based on the price of securities and the volume or frequency of transactions. Securities such as stocks are often traded in upward and downward cycles. Quantitative methods try to take advantage of these trends.
For example, by separating trend patterns, such as when a stock exhibits a trend rather than seemingly not traded based on any trend behavior, detecting a pattern in the stock. When prices start to show signs of entering a trend based on historical patterns, investment opportunities may take the lead. The investment adviser may decide to enter the trading position in time for profit.
There are several distinguishing features that separate quantitative trading from qualitative strategies. The goal behind the quantitative strategy is to discover investment opportunities in low-priced securities (including stocks and bonds) and to identify assets that are overpriced. These factors will cause investment advisors to make buying and selling decisions in the financial market.
Quantitative trading technology also aims to assess and manage different risk exposures in the trading portfolio. Sometimes there are subtle behaviors in financial security that can be ignored by human eyes. By relying on mathematical formulas, investment advisers can better identify imbalances or vulnerabilities in their portfolios, which could lead to potential losses if not addressed.
Quantitative trading is cost-effective. Investment advisors often diversify in multiple securities in different regions. The quantitative trading style aims to reduce the cost of buying and selling many securities in various transactions by simplifying these transactions.
Although quantitative trading strategies are mainly driven by computer software, they still require human factors. Financial analysts must still conduct scientific research on investment technology, which is the basis of qualitative investment. Nevertheless, quantitative investment managers generally rely less on human recommendation and investment securities evaluation, and rely more on computerized formulas.

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