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Understanding NSE Strategy Indices and the Basics of Factor Investing

The NSE site describes Strategy Indices as "designed based on quantitative models/investment strategies to provide a single value for the aggregate performance of a number of companies." This style of identifying companies is known as factor investing, which includes target factors like momentum, quality, value, low volatility, and more. Capitalmind PMS, with the longest-running and best-performing real-world track record in factor strategies in India, offers an in-depth understanding of this approach. In this post, we provide an easy-to-understand explanation of Factor Investing and examine the performance of various Nifty Strategy Indices since their inception.

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Understanding NSE Strategy Indices and the basics of Factor Investing

NSE Factor Indices and their performance


The NSE site describes Strategy Indices as “designed based on quantitative models/investment strategies to provide a single value for the aggregate performance of a number of companies.” That is close to how we think about “Factor Investing”. A more straightforward way of thinking about factor or quantitative investing is

Factor Investing is about defining a characteristic (also called a factor or set of factors) and consistently applying a set of criteria to buy a diversified portfolio of stocks that share that characteristic.

A common-sense understanding of Factor Investing

The no-jargon version:

Let’s say you were tasked with constructing a high-quality basketball team.

One way you might go about it is to ask around for the best basketball players, the folks with pedigree colleges with track records of producing great players, those who have scored the most points or been in the most winning games. Then look at recorded footage, observe them in live practice. You might even meet them in person, talk to their trainers. And only then decide whether to have them on your team.

You might be thinking “Wait, I don’t know anything about basketball.” The approach will be similar for any other team sport. In fact, it holds for other fields like how big companies recruit, how VCs fund start-ups

An alternate approach in our basketball team hypothetical would be to come up with a set of characteristics that might represent good basketball players. Thinking intuitively, you start with height. You’d go back into the past, and create teams of the tallest available players. Then you’d see how many points those teams scored and whether they outperformed the average team. If the data says a team of the tallest available players consistently scored 3 extra points per game compared to the average team, you could conclude that it might continue to work in the future.

Note how both approaches are rooted in pattern recognition. Relying on the past to tell you what might work in the future. The first is largely subjective but considers a broad set of hard and soft aspects. The second is objective and only considers what can be quantified and can be tested with historical data.

It’s probably apparent that the first approach is the investing equivalent of fundamental stock selection, and the second approach is the analogy to factor investing.

Factor Investing is about defining a characteristic (also called factor), and consistently applying a set of criteria to buy a diversified portfolio of stocks that share that characteristic.

What factors offer the potential to beat the market?

Bangladesh Butter Production and the S&P 500

In our illustration above, we picked height as the “factor” for exploration. But what if there were other factors more effective at predicting outperformance?

Speed for instance. Or Age. How about Place of birth? Relationship status? You quickly realise the possibilities are endless. After all, all kinds of things could impact the performance of professional athletes.

For example, if you were considering NBA data from the 1990s, picking players from teams with domesticated agricultural animals in their names would deliver many points in excess of the average team. Wait, what?

Fact: The Chicago Bulls won the NBA championship 6 years out of the 10 between 1991 and 2000.

This brings us to the Bangladesh Butter Production problem. In 1995, David Leinweber, now the head of  the Center for Innovative Financial Technology, Lawrence Berkley National Lab, examined over 150 macro-economic indicators to find statistically significant relationships with the S&P500.

His intent was to identify any indicators that could predict the market. The butter production in our neighbouring country showed the tightest relationship with the US Equity Index. Leinweber published this finding as a joke which has since been part of most “correlation is not causation” lessons in courses the world over.

The simple takeaway for factor investors is that if a factor does not make intuitive sense, it probably is a chance relationship applicable only to the historical data in question and, therefore, unlikely to deliver excess return in the future.

In their book Your Complete Guide to Factor-Based Investing, the authors lay out five tests to determine whether a factor offers the promise of superior returns. To merit consideration, a factor should be:

  1. Persistent – over long periods of time and regimes
  2. Pervasive – across countries, sectors and asset classes
  3. Robust – for various definitions (e.g. there is a value premium whether measured by Price-to-Book, Earnings Yield, Price-to-CashFlow etc)
  4. Investable – not just on paper, but after considering actual implementation issues
  5. Intuitive – has logical risk-based or behavioural-based explanations on why it might continue to exist

The more of the above five conditions a factor checks, the more likely it is to offer the potential for outperformance in the future.

Nifty 50

Nifty 200 Momentum 30 Index

Nifty200 Momentum 30 Index aims to track the performance of the top 30 companies within the Nifty 200 selected based on their Normalised Momentum Score. The Normalised Momentum Score for each company is determined based on its 6-month and 12-month price return, adjusted for volatility. Stock weights are based on a combination of the stock's Normalised Momentum Score and its free-float market capitalisation.

 

Nifty Midcap150 Momentum 50 Index

Nifty Midcap150 Momentum 50 Index aims to track the performance of the top 50 companies within the Nifty Midcap 150 selected based on their Normalised Momentum Score. The Normalised Momentum Score for each company is determined based on its 6-month and 12-month price return, adjusted for volatility. Stock weights are based on a combination of the stock's Normalised Momentum Score and its free-float market capitalisation.

Nifty200 Quality 30 Index

The Nifty200 Quality 30 index includes the top 30 companies from its parent Nifty 200 index, selected based on their 'quality' scores. The quality score for each company is determined based on return on equity (ROE), financial leverage (Debt/Equity Ratio) and earning (EPS) growth variability analysed during the previous five years.

Nifty500 Value 50 Index

The Nifty500 Value 50 index consists of 50 companies from its parent Nifty 500 index, selected based on their 'value' scores. The value score of each company is determined based on the Earnings to Price ratio (E/P), Book Value to Price ratio (B/P), Sales to Price ratio (S/P) and Dividend Yield.

Nifty 50 Value 20 Index

The Nifty50 Value 20 Index reflects the behaviour and performance of a diversified portfolio of value companies forming a part of the Nifty 50 Index. It consists of the most liquid value blue chip companies. The Nifty50 Value 20 Index comprises 20 National Stock Exchange (NSE) companies. Value companies are generally perceived as companies with low PE (Price to Earning), low PB (Price to Book) and high DY (Dividend Yield).

Nifty100 Low Volatility 30 Index

Nifty100 Low Volatility 30 Index aims to measure the performance of the low volatile securities in the large market capitalisation segment. The selection of securities and their weights in Nifty100 Low Volatility 30 is based on volatility.

Nifty Low Volatility 50 Index

The index measures the performance of the least volatile securities listed on the NSE. To make the 50 stocks index investible and replicable, criteria such as turnover and market capitalisation are applied when selecting securities. Weights of securities in the index are assigned based on the volatility values. The least volatile security in the index gets the highest weight. To derive the volatility of the securities, the standard deviation of daily price returns (log-normal) for the last year is considered.

Nifty High Beta 50

The index aims to measure the performance of the stocks listed on the NSE with High Beta. Beta can be referred to as a measure of the sensitivity of stock returns to market returns. The market is represented by the performance of the Nifty 50 index. To make the 50 stocks index investible and replicable, criteria such as turnover and market capitalisation are applied when selecting securities. Weights of securities in the index are assigned based on the beta values. Security with the highest Beta in the index gets the highest weight.

Nifty Dividend Opportunities 50

The Nifty Dividend Opportunities 50 Index is designed to provide exposure to high-yielding companies listed on NSE while meeting stability and tradability requirements. The index comprises 50 companies. A key feature of the index is the methodology of selection of stocks, i.e. the method employs a yield-driven selection criterion that aims to maximise yield while providing stability and tradability.


Capitalmind PMS Factor Strategies and How Are They Better than Other Factor Strategies

Capitalmind PMS is a top-performing Portfolio Management Service in India with a track record of sustained returns for its investors. It's mix of data-driven quantitative and fundamentally driven investment strategies with the ability for investors to allocate across strategies makes it one of the best PMS in 2024.

Capitalmind Adaptive Momentum

Capitalmind’s flagship Quantitative Strategy is proven and battle-tested. It has the longest-running and best-performing track record for PMS Investors in India.

Key Features of Capitalmind Adaptive Momentum:

  1. Quantitative Portfolio Selection: Our algorithm scores and ranks the universe of investable stocks on a composite metric, quantifying price momentum and allocating to the stocks in the top-decile, repeating this process at regular intervals.
  2. Waters the flowers, Pulls the weeds: Objective set of rules that continue holding stocks that show continued price momentum while exiting those that fade. Ensures only the strongest stocks stay in the portfolio with a consistent rebalance frequency.
  3. Fluid across Market Caps and Sectors: Sector and market-cap agnostic strategy that allocates to the pockets showing strongest relative price momentum with robust risk-management built in that goes fully or partially to cash when market conditions dictate.
  4. Risk-Management, a key part of its design: Quantitative filters that shift the portfolio partially or fully out of equities into alternate assets or cash when market weaken, for effective risk-management.

How Capitalmind PMS Adaptive Momentum differs from typical Quantitative Portfolios

Robust Momentum Methodology

Conventional momentum investing uses discrete point-to-point returns to score and rank stocks. Adaptive Momentum utilises a composite return metric adjusted for volatility.

More selective Entry filters

Adaptive Momentum incorporates short-term price and volume criteria that improve downside volatility by reducing probability of sharp reversals soon after entry

Portfolio-level Risk Management

Most Momentum Factor portfolios rely purely on relative momentum and tend to stay invested irrespective of broader market conditions making them particularly vulnerable in broad and sharp market corrections. Also, the rebalance frequency determines the agility of the strategy. Capitalmind Adaptive Momentum has defined rules to shift partially or fully to cash in broad market declines to reduce downside volatility. Capped exposure to sectors and business groups reduces concentration risk.

Iterative Review & Improvement Process

Adaptive Momentum continues to evolve to improve its risk-reward characteristics through a rigorous quantitative backetsting process that simulates real-world implementation challenges

Learn More and Invest in Capitalmind Adaptive Momentum.

Capitalmind Resilient

A quantitative portfolio approach built by combining profitability and price volatility factors, rebalanced quarterly to hold a set of low-surprise companies with solid fundamentals.

Key Features of Capitalmind Resilient:

  1. Quantitative Portfolio Selection: Our algorithm scores and ranks the universe of investable stocks on a composite metric quantifying price volatility and fundamental quality factors and allocates to the stocks in the top-decile.

  2. Consistently profitable "low surprise" companies: The combination of low price-volatility and fundamental factors unearths companies with steady underlying performance with potential for steady future earnings growth making Resilient suitable for significant long-term allocation

  3. Large cap core with addition of mid and small caps: Consists of strong core of large cap stocks with prudent mix of mid and small caps when appropriate to offer potential for strong long-term performance

Learn More and Invest in Capitalmind Resilient

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