quants

简明释义

英[kwɒnts]美[kwɑnts]

n. 数量化投资；数量分析专家；船篙（quant 的复数）

v. 用篙撑（quant 的三单形式）

英英释义

单词用法

同义词

反义词

例句

1.With the advent of the “peace dividend” (read: Pentagon cuts), many of them headed for Wall Street and became “quants.”

随着“和平股息”的出现这些人大多进入了华尔街，成为数据分析员。

2.But some financial experts wonder whether the quants are weakening whatever contact with reality the street may have had.

但是一些金融专家怀疑，金融工程师们是否正在弱化现实中与华尔街联系着的一切。

3.Banks hired hordes of PhD-wielding “quants” to fine-tune ever more complex risk models.

银行雇佣了一大群图有博士之表的“quants”（译者注：指从事计量金融研究者）对更为复杂的金融模型进行微调。

4.It would, though, be simplistic to blame the crisis solely, or even mainly, on sloppy risk managers or wild-eyed quants.

但是，把危机归咎于危机本身，甚至把主要责任推卸在碌碌无为的风险管理这和狂热激进的quants身上就显得太简单了。

5.For a time, employing quants was trendy: it showed the firm was using science to beat the market.

聘用宽客一度成为时髦做法：它体现出公司正利用科学战胜市场。

6.But the quants are usually pragmatic enough to cope.

不过数量分析师的务实通常足以应付此类问题。

7.In the world of finance, quants are highly sought after for their analytical skills.

在金融界，量化分析师因其分析能力而备受追捧。

8.The financial firm hired several quants to develop new trading algorithms.

这家金融公司雇佣了几位量化分析师来开发新的交易算法。

9.Many quants use statistical models to predict market trends.

许多量化分析师使用统计模型来预测市场趋势。

10.She decided to pursue a career as a quant after studying applied mathematics.

她在学习应用数学后决定追求成为一名量化分析师的职业。

11.The job of a quant often requires advanced knowledge of mathematics and programming.

一个量化分析师的工作通常需要高级数学和编程知识。

作文

In the world of finance and investment, the term quants (量化分析师) has become increasingly prominent. These professionals utilize mathematical models and computational techniques to analyze financial data, identify trends, and make informed investment decisions. The rise of technology in finance has transformed traditional investment strategies, leading to the emergence of a new breed of analysts known as quants. Their ability to leverage complex algorithms and statistical methods allows them to uncover opportunities that may not be visible through conventional analysis. One of the key aspects of being a quant is the proficiency in programming languages such as Python, R, or MATLAB. These tools enable quants to manipulate large datasets and implement sophisticated models that can predict market movements. For instance, a quant might develop a trading algorithm that analyzes historical price data to forecast future stock prices. This quantitative approach minimizes emotional biases often associated with trading, relying instead on data-driven insights.Moreover, quants play a crucial role in risk management. They assess the potential risks associated with various investment strategies and help firms allocate resources effectively. By employing techniques such as Value at Risk (VaR) and Monte Carlo simulations, quants can quantify the likelihood of adverse outcomes and devise strategies to mitigate those risks. This analytical rigor is essential in today’s volatile markets, where unforeseen events can have significant impacts on investments.The collaboration between quants and traditional financial analysts is also noteworthy. While quants focus on numerical data and models, traditional analysts may emphasize qualitative factors such as company management and industry trends. Together, they create a more comprehensive view of the market, allowing for better-informed decision-making. This synergy highlights the importance of interdisciplinary knowledge in finance, bridging the gap between mathematics and business acumen.However, the rise of quants has not been without challenges. The increasing reliance on quantitative models can lead to overfitting, where a model performs well on historical data but fails to predict future outcomes accurately. Additionally, during times of market stress, many quantitative strategies may correlate, leading to systemic risks. Therefore, it is vital for quants to remain vigilant and continuously refine their models to adapt to changing market conditions.In conclusion, quants are reshaping the landscape of finance with their analytical prowess and technological expertise. As the financial industry continues to evolve, the demand for skilled quants is likely to grow. Their ability to combine mathematics, programming, and financial theory positions them as invaluable assets in navigating the complexities of modern markets. Understanding the role of quants not only enhances our appreciation for quantitative analysis but also underscores the importance of innovation in driving financial success.

在金融和投资的世界中，术语quants（量化分析师）变得越来越突出。这些专业人士利用数学模型和计算技术来分析金融数据、识别趋势并做出明智的投资决策。技术在金融领域的崛起已经改变了传统的投资策略，导致了一种新的分析师群体的出现，称为quants。他们利用复杂的算法和统计方法的能力使他们能够发现通过传统分析可能看不到的机会。成为quant的关键方面之一是熟练掌握编程语言，如Python、R或MATLAB。这些工具使quants能够操作大型数据集并实施复杂的模型，以预测市场动向。例如，一个quant可能开发一个交易算法，分析历史价格数据以预测未来的股票价格。这种定量的方法最小化了与交易相关的情感偏见，而是依赖于数据驱动的见解。此外，quants在风险管理中发挥着至关重要的作用。他们评估与各种投资策略相关的潜在风险，并帮助公司有效分配资源。通过采用如风险价值（VaR）和蒙特卡罗模拟等技术，quants可以量化不利结果的可能性，并制定减轻这些风险的策略。这种分析的严谨性在今天动荡的市场中至关重要，因为不可预见的事件可能对投资产生重大影响。quants与传统金融分析师之间的协作也值得注意。虽然quants专注于数字数据和模型，但传统分析师可能更强调定性因素，如公司管理和行业趋势。两者共同创造了对市场的更全面的视角，使决策更加明智。这种协同作用突显了金融中跨学科知识的重要性，弥合了数学与商业智慧之间的差距。然而，quants的崛起并非没有挑战。对定量模型的日益依赖可能导致过拟合，即模型在历史数据上表现良好，但未能准确预测未来结果。此外，在市场压力时期，许多定量策略可能会相关，从而导致系统性风险。因此，对于quants而言，保持警惕并不断完善他们的模型以适应变化的市场条件至关重要。总之，quants凭借其分析能力和技术专长正在重塑金融领域。随着金融行业的不断发展，对熟练quants的需求可能会增长。他们将数学、编程和金融理论结合的能力使他们成为驾驭现代市场复杂性的宝贵资产。理解quants的角色不仅增强了我们对定量分析的欣赏，还强调了创新在推动金融成功中的重要性。