In this section, we will talk briefly about the different parts of the quant universe.
    Quantitative trading is a family of analytical methods and execution strategies that comprise the quant universe(量化交易是一系列分析方法和执行策略，他们构成了量子宇宙).

    Quantitative trading is gradually taking over the world and now counts for almost 90 percent of trading volume overall. I began my trading career about 20 years ago in a proprietary trading group within a global bank. The group traded options, forwards, and futures based on foreign exchange rates and interest rates. It was separate from the bank’s risk management function which use the same derivatives but only to hedge the risk and the bank’s lending and investment portfolio（使用相同的衍生工具，用于对冲风险和银行的贷款和投资组合）. Initially, it was my responsibility to create pricing and risk management models within the trading group. My primary focus was to create a model of the behavior volatility in exchange rates and short-term interest rates.
    A successful quantitative strategy depends on good quality data which you can analyze statistically to uncover potentially profitable patterns and behaviors（发现潜在的盈利模式和行为）. Algorithmic trading is a type of quant trading that uses pre-specified machine executable instructions to determine the size and timing of trades based on a quantitative model of an asset’s price behavior. Over 70 percent of US trading volume is algorithmic.

    Most of this volume is high-frequency trading which we will discuss next. High-frequency trading is a subset of algo trading, focuses on the rapid execution of short term trading strategies at the millisecond and sub-millisecond timescale（专注在毫秒和亚毫秒上快速执行短期交易策略）.

    We base or high-frequency trading strategies on quant models and market micro-structure features such as liquidity and latency which we will talk about in a later section covering arbitrage strategies.