首先向大家介绍一下Robert Carver的背景。Carver目前是一位自雇人士，专业在自己家里做量化投资。在辞职自己干之前，他曾经是英世曼AHL（Man AHL）基金中的基金经理，管理十亿美元以上的固定收益投资策略。
【笔者注：Man AHL是一家历史悠久的量化对冲基金。AHL的交易策略以Trend Following为主，涉足的市场主要包括全球成百上千的期货交易市场。】
Robert Carver曾经出版过两本关于量化交易的书籍，分别为：Systematic Trading（《系统化交易》）和Smart 量化交易是什麼？ Portfolios（《智慧投资组合》）。在这两本书中，Carver介绍了不少关于量化投资方面的方法和技巧，因此我觉得和他的访谈，能够为那些对量化投资感兴趣的朋友带来一些价值。
通过了解传统投资和量化投资的区别我们不难看出， 量化投资区别于传统投资的鲜明特征就是 模型 ，投资成功的关键也在于这个模型是不是正确的。
For example,you may find that after the number of Apple shares soared,the price fluctuated rapidly.Therefore,you have built a program to find this pattern in Apple’s entire market history.
If it finds that this pattern has caused upward movement in the past 95%of the time,then your model will predict that the probability of similar pattern happening in the future is 95%.
Algorithms traders use automated systems to analyze chart patterns and then open and close positions on their behalf.Quantitative traders use statistical methods to identify but not necessarily execute opportunities.Although they overlap each other,they are two independent technologies that should not be confused.
Any kind of transaction needs risk management,and the quantity is the same.Risk refers to any factor that may interfere with the success of the strategy.
Capital allocation is an important area of risk management,covering the scale of each transaction–if multiple systems are used for quantitative tools,how much capital should be invested in each model.This is a complicated field,especially when dealing with the strategy of leveraging.
A completely automated strategy should not be influenced by human bias,but only if its creators ignore it.For retail 量化交易是什麼？ traders,keeping the system running without excessive patching may be 量化交易是什麼？ the main part of risk management.
There are many different ways to discover emerging trends through quantitative analysis.For example,you can monitor the mood of traders in large companies to build models to predict when institutional investors are likely to buy or sell stocks in large quantities.In addition,you can find a pattern between volatility breakthroughs and new trends.
Statistical arbitrage is based on the mean regression theory.Its working principle is that a group of similar stocks should behave similarly in the market.If any stocks in this group outperform or are below average,then they represent an opportunity to make 量化交易是什麼？ a profit.
Statistical arbitrage strategy will find a group of stocks with similar characteristics.For example,the stocks of American automobile companies are all in the same exchange,the same department and subject to the same market conditions.Then,the model will calculate the average"fair price"of each stock.
然后，You will short any company in this group that exceeds the fair price,and buy all companies of this company that have not reached their reasonable price.When the stock returns to the average price,both positions are closed for profit.
The core value of the Internet of things is to capture and analyze the sensing data of devices,and to identify and separate the most important data from a large amount of information and noise.Therefore,based on the development of sensors and other hardware,the maturity of big data analysis technology largely determines the development speed of the Internet of things.