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In the wealth and asset management company, investments are managed by fund managers. They are aided by teams of research analysts in analyzing diverse and voluminous information. Investment strategies are followed in selecting securities and deciding allocations. Though structured, every investment decision has human judgements. 

A quant fund, on the other hand, would have algorithms at its core that drive the investment strategy. A specific framework involving rule engines and predictive models are put together to drive an objective and systematic decision process. Development of quant systems require employing advanced statistical techniques and enabling technologies. The resultant system analyzes complex correlations, identifies hidden patterns and formulates predictive models. 

A quant engine for investment minimizes human judgement and therefore, manages portfolios free of human emotions and biases. These strategies benefit from disciplined, academically researched, objective decision-making systems.

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How Does a Quant Fund Work and What are Its Advantages?

Quant funds can be structured in multiple possible ways to generate returns. 

  • Market trades generate huge volumes of data at very high velocity. One can develop a system to scan such data, analyze patterns, identify available arbitrages and generate returns therefrom. This could involve very short duration trades.
  • On the other hand, one can deploy predictive models and rule-based portfolio creation aimed at generating medium to long term returns
  • One can also build predictive engines modelling movements of different ETFs across sectors, size, geography, etc. Base on directions calls for these assets, a framework can use derivative positions to generate returns

Essentially, quant funds leverage the following key capabilities of machines to drive systematic investment strategies to generate consistent alpha

  • Ability to handle massive computational intensity for asset selection and allocation
  • Enhance predictive power by deploying AI & ML to learn for historic correlations and hidden patterns
  • Objective decision making, free of human emotions and biases
  • Better risk management by reducing errors and focusing on actual source of return rather than on favored asset classes

How Are Machine Learning Technologies Driving Decision Science? 

Artificial intelligence and machine learning technologies are powerful disruptors in today’s businesses.

Many organizations engage complex algorithms and predictive models to continually process and analyze multiple information stream to drive their services and business processes. Map applications that recommend possible routes between two locations and estimate travel time is one such example.

Investments too require predictions that are made basis large and diverse data or information and involve rather complex processing. Basic rules and frameworks for successful wealth management that identify assets that generate potential future returns have been evolving over time. While actively managed funds benefit from human intelligence and judgement, passively managed funds are rule based. These styles have contrasting pros and cons. Artificial intelligence can add a third dimension to these contrasting styles. It can mimic human judgement to a good extent while retaining the benefits of disciplined passive investing. 

For mimicking human judgement, an AI system must process large data sets, build predictive models and then choose the best available option for generating future returns. A fund or scheme constructed in these lines can broadly be called a Quant Fund. These strategies benefit from disciplined, academically researched, objective decision-making systems.

When it comes to quant funds in India, recently, Tata Asset Management Company launched the TATA Quant Fund , which is a  multi-factor systematic mutual fund scheme with embedded AI modules that dynamically choose strategies based on prevailing conditions. For portfolio creation the fund will select from a fixed universe of stocks comprising of BSE 200 and those in the derivatives list.

Read More : NFO Review for Tata Quant Fund

Conclusion 

Quant funds are successful in removing the bias that often accompanies active fund management, thereby creating a certain degree of risk for investors, which quant models are able to mitigate. If the concept of quant funds interests you, make sure to research about these funds in detail and take investment decisions accordingly. 

Happy Investing!

Disclaimer : This blog has been written by the Content Desk at Tata Mutual Fund. The views expressed in this post are that of the author and not those of Groww

Investment in securities market are subject to market risks, read all the related documents carefully before investing. Please read the Risk Disclosure documents carefully before investing in Equity Shares, Derivatives, Mutual fund, and/or other instruments traded on the Stock Exchanges. As investments are subject to market risks and price fluctuation risk, there is no assurance or guarantee that the investment objectives shall be achieved. NBT do not guarantee any assured returns on any investments. Past performance of securities/instruments is not indicative of their future performance.

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