Quantitative trading model system development strategy consulting [Liu Yi, 46, 36, 992, 653], quantitative trading platform system development and construction, quantitative trading software system development and construction, quantitative trading model system development and design
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"Quantitative trading" has two meanings: First, in a narrow sense, it refers to the content of quantitative trading, which transforms trading conditions into procedures and automatically places orders; the other is, in a broad sense, it refers to a systematic trading method, which is an integration. Trading system. That is, based on a series of trading conditions, an intelligent auxiliary decision-making system, combining rich experience and trading conditions, and managing risk control during the transaction process.
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Quantitative trading should include at least five elements:
(1) The signal system for buying and selling.
(2) Direction guidance for bull market or bear market
(3) Position management and fund management.
(4) Risk control, using signal sources to determine the position of the stop loss, using the asset curve and equity curve to determine and manage.
(5) Investment portfolio, different investment products, different trading systems (different functions and parameters, fast and slow), and different time period combinations. Now decentralized portfolios make trading account fluctuations more stable.
2. Features of quantitative trading
Quantitative trading is a relatively new concept, and its most distinctive feature is the use of models. The main features of quantitative trading are as follows.
(1) Wide investment perspective. Relying on the computer to process the sea star information efficiently and accurately, to find a wider range of investment opportunities in all markets.
(2) Discipline. Strict discipline is an important feature that distinguishes quantitative trading from active investment. Discipline has many benefits. It can overcome the weaknesses of human nature, such as fear, greed, fluke, and cognitive biases.
(3) Systematic. Multi-level models mainly include industry selection models, major asset allocation models, and selected individual stock models. Multi-angle observations mainly include analysis from multiple perspectives such as macro cycle, valuation, growth, earnings quality, market structure, analyst earnings forecasts, and market sentiment.
(4) Timeliness. Track market changes in a timely and rapid manner, constantly discover new statistical models that can provide huge profits, and look for new trading opportunities.
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.