What Is Quantitative Trading? 什么是量化交易？
Quantitative trading is an area of finance where investment professionals use mathematical models and automated trading strategies to seek profitable opportunities in the financial markets. Quantitative trading plays an important role in proprietary trading, which is undertaken by investment banks and hedge funds for their own accounts. It is also prominent in market making, where participants provide liquidity and are focused on maintaining smooth operations, so that market participants can buy and sell assets in an orderly manner. Quantitative trading holds an advantage over discretionary trading in its data-driven methods and systematic approach to the markets that avoid emotional decision-making. However, quant trading can also be subject to the challenges of sudden market regime changes and crashes.
量化交易是金融领域的一个分支，投资专业人士运用数学模型和自动化交易策略在金融市场中寻找获利机会。量化交易在自营交易中扮演着重要的角色，自营交易通常由投资银行和对冲基金以自有账户进行。量化交易在做市中也发挥着重要作用。做市商提供流动性，并致力于维持市场平稳运行，以确保市场参与者能够有序地买卖资产。相较于主观交易，量化交易的优势在于其以数据为驱动的方法和系统化的市场分析方法，避免了情绪化的决策。然而，量化交易也可能面临市场格局突变和市场崩盘的挑战。
What Does a Quantitative Trader Do? 量化交易员做什么？
Quant traders have expertise in implementing mathematical and statistical models to discover potentially profitable trading strategies and to execute trades.
Quant traders work at investment firms, hedge funds, and banks, often as proprietary traders, or many trade independently for their own accounts. They are active across a wide range of asset classes, including equities, bonds, commodities, currencies, and derivatives. Specific areas of quantitative trading and research include:
量化交易员擅长运用数学和统计模型来发现潜在的盈利交易策略并执行交易。量化交易员在投资公司、对冲基金和银行工作，通常担任自营交易员，也有很多量化交易员独立使用自己的账户进行交易。他们活跃于各种资产类别，包括股票、债券、商品、货币和衍生品。量化交易和研究的具体领域包括：
-
Valuation – where algorithms help determine an appropriate price for an asset based on prior information
估值 ——算法根据先前信息帮助确定资产的适当价格 -
Execution – where algorithms manage buy and sell orders and execute trades
执行 ——算法管理买卖订单并执行交易 -
Position Management – which entails analyzing an inventory of equities and options, for example, and managing the risk of those positions though buying, selling, or hedging.
头寸管理 ——例如，需要分析股票和期权库存，并通过买入、卖出或对冲来管理这些头寸的风险。
The main inputs to quantitative trading systems include trading volume and prices over time, including price data at very small-time increments, known as tick data. In addition, these systems often make use of other types of data, from corporate information to alternative datasets, such as information gleaned from mobile devices, sensors, and satellites. Quant trading strategies are supported by backtesting, which is designed to model various scenarios and help to identify investing opportunities.
量化交易系统的主要输入包括交易量和价格随时间的变化，包括极小时间增量的价格数据，即所谓的“报价数据”。此外，这些系统通常还会利用其他类型的数据，从公司信息到另类数据集，例如从移动设备、传感器和卫星收集的信息。量化交易策略需要回测的支持，回测旨在模拟各种情景并帮助识别投资机会。
Over the past decade, machine learning and data science have had a significant impact on quantitative trading, and Python has become a language of choice for data analysis. span This means that the journey to become a quant trader covers several fields simultaneously: mathematics, finance, and programming.
在过去的十年中，机器学习和数据科学对量化交易产生了重大影响，Python 已成为数据分析的首选语言。这意味着成为一名量化交易员的旅程同时涵盖多个领域：数学、金融和编程。
How to Learn Quantitative Trading 如何学习量化交易
In terms of skills and education, a quant trader will often have a bachelor's degree and sometimes a master’s degree in a quantitative discipline such as mathematics, statistics, physics, computer science, engineering, operations research, or financial engineering. Quant traders also have expertise in the financial markets, and knowledge of research methods based on programming, data mining techniques, and statistical analysis. They will have a practical understanding of automated trading systems and may be capable of building their own systems. Many quant traders pursue professional education in relevant areas through online courses, such as the Certificate in Quantitative Finance (CQF).
在技能和教育方面，量化交易员通常拥有数学、统计学、物理学、计算机科学、工程学、运筹学或金融工程等量化学科的学士学位，有时甚至拥有硕士学位。量化交易员还具备金融市场的专业知识，以及基于编程、数据挖掘技术和统计分析的研究方法。他们对自动交易系统有实际的理解，并且可能能够构建自己的系统。许多量化交易员通过在线课程（例如量化金融证书 (CQF)）攻读相关领域的专业教育。