Lesson 1: Learning Quantitative trading for the first time
1. How does quantitative trading help you catch the opportunity of trading
When many people hear about quantitative trading, their reaction is not "understand". Check it out on a search engine:
"Quantitative trading refers to the advanced mathematical model to replace human subjective judgment, using computer technology from huge historical data audition can bring excess returns in a variety of ' 'big probability events to develop strategy, greatly reduce the effect of investor sentiment volatility, avoid under the condition of the market mania or pessimistic to make irrational investment decisions."
Here's an interesting life scenario to help you understand:
Xiao Ming raised a chicken and discovered one week that if the chicken crowed before dinner in the morning, bitcoin would rise today and fall if the chicken did not crow before dinner tomorrow. Xiao Ming vaguely sensed the relationship between the crow of a rooster and the rise and fall of bitcoin.
Xiao Ming ask neighbors for help to verify his conjecture, want to refine the inspiration into an executable trading strategy. He has kept a chicken all his life and recorded in detail the number of times the chicken crows before eating from birth to the present. Xiao Ming verified the relationship between the number of crowing chickens and the rise and fall of bitcoin in the previous five years through the data of his neighbors. He found that the probability of bitcoin rising was 85% after the crow of a rooster before dinner, but there was also a 15% probability of inaccurate. For example, there are black swan cases, where the dog next door chased the chicken and the chicken barked before eating, and gray rhino cases, where the chicken barked before eating because of courtship.
Xiao Ming thinks the profit probability is very large, decided to seize the opportunity encounter. He wrote a voice-recognition software system that translated the strategy into a program that regularly monitored when the chicken was eating, placing orders to buy bitcoin when the chicken crowed and selling when the chicken didn't. He used real trading and adjust the strategy constantly, it made him have stable income after that,and now his life is very moist.
As can be seen from the above, quantitative trading = quantitative + procedural.All in all, is to convert the trading logic into mathematical model, and realize the corresponding investment needs with the program language.
2. Why need quantitative trading?
Usually an investor making a traditional trade needs to be prepared: Pay attention to the international environment, financial news, securities research report, the company's financial report, K line trends, news and other investment related data, qualitative analysis and quantitative analysis, according to their own investment principle, wait for a signal trading orders manually, if the list is too big need partial buying cost to reduce the impact of market changes.
The process of data acquisition and tracking is as repetitive and exhausting as a farmer's labor. Labor skills to evolve, trading skills to "quantify"!
One of the advantages of quantitative trading is that the efficient execution of computers frees people from simple and repetitive tasks and allows them to focus more on strategy. In terms of information acquisition, quantitative trading not only focuses on historical market data and fundamental indicator data, but also converts some non-traditional data, such as market sentiment and some key words of financial news, into indicators that can be understood by machines.
When trading, we are usually in one of two scenarios:
(1) Plan to catch the bottom of a currency after it falls below a certain price, and buy it after it rebounds from the low level;
(2) Prepare to sell a currency when it is higher than a certain price after successful buying, and sell it when it falls from a high level;
However, if you don't have time to watch, you miss the buy and sell points.
But if we have a quantitative trading system, in scenario 1, when the market has recovered a certain amount from its low and we think it is a buying opportunity, we can do a simple strategy, we can set a baseline price.When the market price triggers the base price, it keeps tracking the low price and the rebound range based on this point. When the rebound range reaches the target, it triggers the purchase and submits the buy order to the exchange. This is a simple bottom-fishing strategy. So the scenario 2 has similar logic.
Quantitative trading, quantitative is the methods, trading results is the end. Quantification aims to free people from repetitive, complex work and focus on more important decisions. Computer-assisted trading, or automated trading, is a big part of the future.
Topic: Vtrading quantitative guides NO.1|Learning quantitative trading (Read 86 times)