Quantitative trading is an algorithmic based effort to capitalize on opportunities in the financial markets with the help of mathematical models. It constitutes a set of quantitative strategies that analyzes historical and current data to identify patterns and predict future performance. Quantitative trading is considered a highly accurate and reliable form of trading as decisions are based on data, as opposed to risk appetite or gut feeling.

Quantitative trading is typically done by professional investors such as hedge funds, banks, or other financial institutions. Sophisticated algorithms are designed to detect inefficiencies in the market, often leveraging data points such as price, volume, returns, open interest, and other analytics. The algorithms then form an automated process which executes the desired trades. Quantitative traders enjoy the advantages of being able to react faster to market movements compared to the manual counterparts, as well as the ability to trade any size or duration.

High Frequency Trading (HFT) is one of the most popular forms of quantitative trading. It is based on sophisticated algorithms that detect price changes in milliseconds and execute trades as soon as signals are detected. It takes advantage of enormous volumes of data and its powerful computing capacity, allowing for large profits in a very short period of time.

Compared to manual trading, quantitative trading presents a unique advantage of its ability to minimize errors due to small factors such as human emotions and bias. Trading decisions are taken objectively and logically from historical and current datasets, without any subjective inputs from the trader. Quantitative traders also enjoy the benefit of being able to test multiple strategies and adjust them quickly to market conditions or to replace outdated ones.

A major drawback associated with quantitative trading is its limited use. Strategies become less effective over time as the market adapts, changes, and competitors start incorporating the same. High Frequency Trading (HFT) also presents challenges related to liquidity issues and market impacts, resulting in increased losses in fast-moving markets.

In conclusion, quantitative trading is a highly popular and reliable form of algorithmic trading which allows for rapid decision making and faster implementation. Its advantages of being objective and minimising errors due to human emotions, as well as its ability to test multiple strategies, makes it attractive among professional traders and investors. However, its limited use and potential challenges that come with HFT, should be considered before a trader embarks on a quantitative trading journey.