Rapid advancements in technology are transforming industries and people’s lives around the world. Technology in the conventional sense has been used to automate manual processes and improve productivity. However, development in information technology in the last 20 years or so, particularly artificial intelligence (AI) and data science has brought about a paradigm shift in how we use technology. Apart from improving efficiency and reducing defects related to human errors, technology is increasingly being used to make better and smarter decisions.
Like many other industries, the financial services industry including asset management, are adopting technology in order to meet their client’s (investor’s) needs. In asset management, technology is being increasingly used to provide better outcomes for investors. Quant (shortened form of quantitative) funds are a great use case of technology in the investment management. Though fund managers look at many analytical factors and use quantitative techniques, there is always human judgement involved in conventional actively managed funds. To err is human and despite best intentions, you can have errors in judgements in investments.
Quant Funds build their portfolios by following fundamental rules of investing using mathematical algorithms with little human interference. This reduces errors of judgement and provides a better chance to meet investment goals.
In India quant investing is still a relatively new concept; only a few Portfolio Management Services and mutual funds offer quant products. However, quant funds are very popular in the West; nearly a quarter of all stock trades in the US comprise of quantitative or algorithmic investments. Many quant hedge funds and mutual funds are now also using Artificial Intelligence (AI) and Machine Learning to improve the way they analyze securities and make investment decisions.
Tata Mutual Fund has launched Tata Quant Fund which uses an active multi-factor quantitative investment model, embedded with AI modules that dynamically change factor strategies basis prevailing market conditions.
AI in Investing
Many people are not aware of the extent of AI penetration in our lives. Have you ever wondered how Google Maps is able to give fairly accurate estimation of the driving time between two locations? Have you wondered how some of your social media apps (e.g. twitter, YouTube etc.) are able to show content that are likely of interest to you? They use AI. Likewise, AI can be used in investment process for consistent, high velocity information processing and structured decisioning which human brain may not capable of.
Quant funds use AI in the following way:-
- Secure large market impacting datasets
- Build statistical models to drive Quant investment strategy
- Run comprehensive model testing for different real life scenarios
- Create framework that evaluates and manages Quant Model’s prediction accuracy over time
- Employ statistics to identify hidden patterns and correlations that would be difficult to spot otherwise
All of this is done with the objective of making better predictions, fewer errors, and greater efficiency. Tata Quant Fund’s algorithmic investment strategy using AI is accordingly, expected to achieve better returns than the index on a consistent basis and avoid negative absolute returns.
Tata Quant Fund Investment Process - Overview
The schematic below depicts Tata Quant Fund investment process at a high level. You can see that fund has a very structured and highly analytical (data driven) approach for portfolio construction and management. The stock selection approach focuses on generating superior long term returns and reducing portfolio risks. The AI algorithms aim at providing stability and performance consistency over time.
Tata Quant Fund - Stock Selection Strategy
Many investors tend to focus on individual stocks, hoping that they turn out to be multi-baggers rather than take a portfolio view. Portfolio investment, on the other hand, is a diversified approach to investing that seeks to meet the investment objectives, irrespective of market conditions. Building a portfolio is like selecting a cricket team; different members of the team have roles to play e.g. you cannot have a winning team by having 11 batsmen; you need to have the optimal combination of players (batsmen, bowlers, wicket keeper etc.). Similarly, Tata Quant Fund aims to select optimal portfolio combination of Alpha, Value and Quality stocks. The fund will use a quant model to build its portfolio (see below).
The fund will use AI / machine learning to:-
- Evaluates which factor Strategy (Alpha, Value & Quality etc.) worked in a Macro scenario and select an optimal portfolio with a combination of top ranked stocks within the factor strategy
- Evaluates whether the Macro conditions and various strategy scenarios favour factor strategy investment or may lead to fall in portfolio performance
- Based on the evaluation, the Model makes the Buy or Hedge (Current portfolio) decision
Why invest in Tata Quant Fund?
- Quant based disciplined investment approach devoid of human errors of judgement
- Machine Learning enabled investing for superior outcomes without taking too much risk to get higher returns
- Suitable for long term investing as Model learns from new economic and market conditions for making investment decisions
Who should invest in Tata Quant Fund?
- Investors who have disciplined approach to investing
- Investors who are patient and can remain invested for the long term (at least 5 years)
- Investors with moderately high to high risk appetites
Tata Quant Fund provides an opportunity for you to invest in machine drive investment strategy which can provide superior risk adjusted returns in the long term. For scheme information document of Tata Quant Fund, please click here. The NFO closes on 17th January 2020. Read the scheme related documents before investing. You should consult with your financial advisor if Tata Quant Fund is suitable for your investment needs or contact Tata Mutual Funds at firstname.lastname@example.org / 022 - 62827777.
Mutual Fund Investments are subject to market risk, read all scheme related documents carefully.