Tata Mutual Fund launches AI driven fund - Tata Quant Fund
In this digital age, ‘Machine Learning’ & ‘Artificial Intelligence’ drive innovations as ‘product recommendations on e-commerce platforms’, ‘a maps app recommending the best route’ and the estimated time to reach the destination’ or ‘a music app knowing our favorite songs.’
Despite its pitfalls, AI has given us great tools and resources to lead more informed and convenient lives, with a lot of information at our fingertips.
TATA Quant Fund (Open Ended Equity Scheme): AI & ML driven mutual fund scheme - Stock Selection (market driven) Optimal Portfolio (weightage, eliminated) with efficiency of investing decisions. This Model has factors “Value, Quality, Alpha” for objective stock selection & portfolio allocation and analyze dynamically change based on Macro-economic indicators & market valuations such as GDP, Inflation, Interest Rate, Market Index and aims to create a momentum, quality, value, market capitalization of stocks from the Stock Universe (S&P BSE 200 Index & Equity derivatives) to perform well under prevailing market conditions .
Then, using machine learning algorithms, create an optimal portfolio & allocate stock weightage protect the downside risk and rebalance the portfolio based on the market optimizing the stock selection & accuracy over time, remove human biases & help in emotion free investing , follow fund mandate (Factor based Mandate, S&P BSE 200 Index Stock Universe, Market direction based portfolio management, well diversified ) Learn -> Unlearn-> Adapt back tested over the last 8 years data to understand the response to historical market situations & analyse resultant performance & has a potential to outperform S&P BSE 200 TRI Index over time.
However under certain circumstances as unforeseen market events, political instability, sudden policy changes , the model may under perform the benchmark Index.
Tata Quant Fund is an 'open ended equity mutual fund scheme’ following quant-based investing theme. The fund would invest in equity and equity related instruments which form part of S&P BSE 200 and Equity Derivative Segment.
NFO opens on 03 January 2020 and closes on 17 January 2020 Fund Manager: Sailesh Jain. Benchmark: S&P BSE 200 TRI.
The predictive engines use more than past 20 years of market and macro-economic data to analyse hidden relationships and patterns. These correlations along with prevailing market and macro-economic data are then used by the engines for making monthly predictions. Thus, the investment decision making process of the fund is fully machine driven and free of human judgement. The machine learning framework predictive models also recalibrate and re-adjust at a fixed periodicity by using new and incremental data. This enables the models to factor in emerging patterns and relationships.
Future of Personal Finance & Investing
AI and Machine driven financial apps analyse data on spending patterns, how customers use their accounts and are getting smart to spot a potential fraudulent behavior and have the ability to build a relationship of trust. Nevertheless, companies are excited and constantly exploring the possibilities of Artificial Intelligence and Machine Learning
Despite its pitfalls, AI has given us great tools and resources to lead more informed and convenient lives, with a lot of information at our fingertips.
TATA Quant Fund- Strategy Landscape
TATA Quant Fund (Open Ended Equity Scheme): AI & ML driven mutual fund scheme - Stock Selection (market driven) Optimal Portfolio (weightage, eliminated) with efficiency of investing decisions. This Model has factors “Value, Quality, Alpha” for objective stock selection & portfolio allocation and analyze dynamically change based on Macro-economic indicators & market valuations such as GDP, Inflation, Interest Rate, Market Index and aims to create a momentum, quality, value, market capitalization of stocks from the Stock Universe (S&P BSE 200 Index & Equity derivatives) to perform well under prevailing market conditions .
Then, using machine learning algorithms, create an optimal portfolio & allocate stock weightage protect the downside risk and rebalance the portfolio based on the market optimizing the stock selection & accuracy over time, remove human biases & help in emotion free investing , follow fund mandate (Factor based Mandate, S&P BSE 200 Index Stock Universe, Market direction based portfolio management, well diversified ) Learn -> Unlearn-> Adapt back tested over the last 8 years data to understand the response to historical market situations & analyse resultant performance & has a potential to outperform S&P BSE 200 TRI Index over time.
However under certain circumstances as unforeseen market events, political instability, sudden policy changes , the model may under perform the benchmark Index.
Tata Quant Fund is an 'open ended equity mutual fund scheme’ following quant-based investing theme. The fund would invest in equity and equity related instruments which form part of S&P BSE 200 and Equity Derivative Segment.
NFO opens on 03 January 2020 and closes on 17 January 2020 Fund Manager: Sailesh Jain. Benchmark: S&P BSE 200 TRI.
Tata Quant Fund is available with digital channel partners Paytm Money & Groww App.
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| (Courtesy – Tata Mutual Fund) |
Artificial Intelligence & Machine Learning driven Advisor
The predictive engines use more than past 20 years of market and macro-economic data to analyse hidden relationships and patterns. These correlations along with prevailing market and macro-economic data are then used by the engines for making monthly predictions. Thus, the investment decision making process of the fund is fully machine driven and free of human judgement. The machine learning framework predictive models also recalibrate and re-adjust at a fixed periodicity by using new and incremental data. This enables the models to factor in emerging patterns and relationships.
Future of Personal Finance & Investing
AI and Machine driven financial apps analyse data on spending patterns, how customers use their accounts and are getting smart to spot a potential fraudulent behavior and have the ability to build a relationship of trust. Nevertheless, companies are excited and constantly exploring the possibilities of Artificial Intelligence and Machine Learning
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