Looking to the Future of Investing

Quantamental - Best from both for investors

?Investment firms typically rely on two main forms of analysis – quantitative and fundamental. The former involves using statistical methods and big data to assess the probability of price movements, while fundamental analysis involves studying factors such as emerging trends or financial statements to assess the potential for growth.

?The issue is that both approaches have significant limitations when performed in isolation. Quantitative analysis takes data at face value and can assume that the markets are rational, while fundamental analysis can take too narrow a view and is often subject to behavioural biases.

As a result, traders are increasingly mixing both types to form a ‘quantamental’ assessment.

?What we Understand by the Definition of ‘Quantamental’ Investing

Professor Aswath Damodaran in famous annual lecture series on Valuations introduces the course by asking his students “Is Investing an ‘Art’ or ‘Science’?” He further goes on to elaborate by calling Investing what truly it is - a ‘Craft’ that is ‘Investing’ is combination of art and science.

?If definitions are drilled down Science is defined as ‘the intellectual and practical activity encompassing the systematic study of the structure and behaviour of the physical and natural world through observation and experiment.’ – the key words here being ‘systematic’ and ‘through observation and experiment’. In the modern day of information where we are drowning in the ever-expanding ocean of data, the only way we can harness its true power and have anything ‘systematic’ is via machines. Using this power of computing to make sense of market trends is what the modern day sense of the word ‘Quant’. This domain involves using statistical methods and big data to study historical trends as well as assess the probability of price movements in the future.

Similarly definition of art reads ‘the expression or application of human creative skill and imagination’ – in the world of finance, nothing comes closer to it than fundamental research. As in a painting or a sculpture - there is no right or wrong to a valuation exercise. It’s a mix of assumptions in cash flows, growth and risk, macro trends, sector trends, moats and industry growth projections.

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If we think of ‘Quants’ as being the ‘Science’ and analysing based on “Fundamentals” as the ‘art’ of investing, a combination of the two is what we would refer to as ‘Quantamental’ – this harnesses the beauty of machines and combines it with an analysts reading of the market to generate alpha for portfolios.

Why Quantamental – Strengths?

Key benefits of using ‘Quantamental’ investing can be split into various buckets:

§?Limitations of Both when carried out in Isolation:

Both Quants and Fundamental analysis have their limitations when performed in isolation. Quantitative analysis takes data at face value and can assume that the markets are rational, while fundamental analysis can take too narrow a view and is often subject to behavioural biases of the analyst.

?§?Size of Data:

The Applied Material annual report has an interesting chart on “Data Generation by Category” which mentions that the year 2018 was the time we had the ‘Machine > Human’ Crossover, that is, data generated by machines for the first time became higher than data generated by humans. With the advent of AI/ML and newer technologies (advances in material sciences allowing more chips to be compressed in a device), Internet of Things, the gap between data generated by machines vs human is expected to increase (exponentially). The only way to analyse this mass of data is via machines themselves.

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§?Diversity of Data Sets:

The deluge of data over the past decade also includes an important flavour – the diversity of data. Quantitative analysis could include anything from price/volume action or financial statements data on a stock (technical/fundamental) to the number of clicks in a link in a webpage to the Twitter/Google trends for a company – with this information analysed and compared to historical data in seconds.

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§?Economics of Analysis:

An assessment of this magnitude on such large and diverse datasets isn’t economical – and might not even be possible – with traditional methods, and these can help to identify surprising trends.

§?Analyse Fundamental Factors which can’t be reduced to Numbers:

Analysis of behavioural elements – be it trading segment sentiments (retail being an important element now), CEO’s tone of voice on an earnings call all need quants to be analysed

§?The Element of Time:

The timing element in investing and especially trading has never been more critical – the quantitative world enable updates on analytical elements in real time which can’t be imagined using traditional modes of analysis.

?§?Never Take Your Models to be the Truth:

Whilst the above points all signify the criticality of quants and models, the human element and fundamental analysis is a critical component in investing too. The criticality can especially be understood with examples in history – LTCM’s absolute trust in their models finally leading to their bankruptcy having lost all their capital in 1998 despite initial impressive gains (Scholes and Merton, Nobel Laureates in their board) vs Renaissance Tech’s and Jim Simons decision to override their model’s in the GFC where they decided to go against their models which were having a strong buying bias. Sometimes, human judgment is needed when the investing landscape changes drastically due to unusual circumstances not captured by a model. It is also then doubly important to know the limits of a model, as well as the assumptions that went into it.

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IWM Quantamental Investing Framework:

In IWM, the ‘Quantamental’ domain has been a key focus area with the objective to achieve systematic selection framework for stocks / ETFs / Indices. From a systematic selection perspective, we as human beings have a limited capacity and might end up ignoring attractive stocks etc., especially when selection is to be made form a basket of 2,000+ underlings. However a Quantamental approach, that utilizes computing power to run a rules-based framework around various data domains, can highlight attractive opportunities, which might be ignored by a human being looking at a large universe of stocks.??

One of our most used models, which we have built using the Bloomberg Quant (BQNT) platform has been the ‘Fortuna’ and ‘Plutus’ frameworks. These can be used across indices/sectors/ETFs or even individual stocks and utilise the power of quantitative analysis from a ‘fundamental’ and ‘technical’ lens respectively. These frameworks can be used independently or in conjunction with each other and can be applied to a large Universe of stocks/ETFs/Indices .

Understanding Fortuna Quadrant Approach

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???????Fortuna Quadrant framework is a systematic approach to stock / ETF / sector (or “underlying”) selection, allowing investors to exploit market mispricing and make an informed entry and exit decision. Like “Circle of Life”, quadrant approach depicts “Stock cycle phases” as stocks move in a circular fashion from Q2 to Q1 to Q4 to Q3 and back to Q2.

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??????What do quadrants depict??Each quadrant is a combination of trading multiple (premium or discount to historic valuation multiple of choice) and earnings (in this sample case it is revenue) upgrade or downgrade for the underlying.

???????Q1: Trading at premium to 2yr. historic avg. EV / Rev + Rev. upgrade in last 3m.

??????Q2: Trading at discount to 2yr. historic avg. EV / Rev + Rev. upgrade in last 3 m.

??????Q3: Trading at discount to 2yr. historic avg. EV / Rev + Rev. downgrade in last 3m.

??????Q4: Trading at premium to 2yr. historic avg. EV / Rev + Rev. downgrade in last 3m.

???????Quadrants as Traffic Lights: An underlying in Q2 should be a favored BUY by investors as earnings upgrade has started while multiple expansion still remains on card. As the underlying moves into Q1, investors should enjoy the expansion in trading multiple but should lookout for any signs of earnings downgrade and become a SELLER as underlying is about to move to Q4. And as the underlying gradually moves from Q4 to Q3, investors should be on the lookout for earnings upgrade to become a BUYER.

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??????What else to look for / limitations of the Framework:?After selection of underlying using quadrant framework, a fundamental analysis of the underlying is recommended. This is to avoid – a)?BUYING deep discount stocks which are in Q2 due to some fundamental issues with the underlying and b) early SELLING of the underlying in Q1 and missing additional upside. Further, a technical analysis is suggested to better time the trade.

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Sample Interface of Fortuna

?S&P Sector Indices “Circle of Life” –?Fortuna depicting the “Stock cycle phases” – How S&P sector Indices have moved in a circular fashion from Q2 to Q1 to Q4 to Q3 and back to Q2.?

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Understanding Plutus Quadrant Approach

?“No person can play the market all the time and win. There are times when you should be completely out of the market, for emotional as well as economic reasons.” - Jesse Lauriston Livermore

?“Patterns of price movement are not random. However, they’re close enough to random so that getting some excess, some edge out of it, is not easy and not so obvious-thank God. God probably doesn’t care. Thank whoever.” – Jim Simons

?As the legendary tape reader Jesse Livermore and the famous quant Jim Simons highlight the importance of analyzing price movements – We developed our ‘Plutus’ framework to do just that aka suggest if one should look at buying a particular stock/ETF/Indices for the next 30 days or avoid buying it.???

?We implemented VPCI (Volume Price Confirmation Indicator or Trend) developed by Technician Buff Dormeier along with Volume trend analysis for systematic generation of technical BUY, HOLD and SELL recommendation (one month – 30D analysis). The indicator is similar to our Fortuna framework but generates technical quadrants.

?Variables – a) VPCI is the sign of the difference between Volume Weighted Moving Average (VWMA) and Simple Moving Average (SMA) i.e. if VWMA > SMA, VPCI is +1 or else -1 and, b) Volume Trend = If Volume is higher than simple moving average it is +1 or else -1

???????Q1: Volume Trend is -1 & VPCI is +1

??????Q2: Volume Trend is +1 & VPCI is +1

??????Q3: Volume Trend is -1 & VPCI is -1

??????Q4: Volume Trend is +1 & VPCI is -1

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Just ike Fortuna, Plutus Quadrants have similar actionable - Quadrants as Traffic Lights

An underlying in Q2 should be a favoured BUY by investors as trend is up and volume is rising. As the underlying moves into Q1, investors should technically hold the stock as trend is up but remember that now volume is falling. The investor should lookout for any signs of technical breakdown and become a SELLER as underlying is about to move to Q4 (trend is down + volume is rising). And as the underlying gradually moves from Q4 to Q3 (trend is down + volume is falling), the stock enters sideways movement (consolidation) and investor should wait for Technical to move to Q2.?

?Sample Interface of Plutus

Below is the back-testing data which we are not sure if it will be eligible to but in the Nomura Connects website. Please let us know if we should include these.

?Backtesting of “Fortuna” -?S&P sector indices as set with monthly rebalancing - Significant outperformance by Quadrant 2 vs. SPX

?Backtesting of “Plutus” -?S&P sector indices as set with monthly rebalancing - Significant outperformance by Quadrant 2 vs. SPX

Looking to the Future

?If investment firms looked at themselves like they do their investments, they would spend less time touting past successes and more time explaining how they are evolving to win tomorrow. With this as context, fundamental investors integrating aspects of what quantitative investors do well – and vice versa – is not something to be debated, but something that should be actively explored. After all, it stands to reason that other firms are doing some things better than you. Learning what that is – and how it can be re-purposed for your own needs – is a big part of how any company stays ahead of the competition, investment firms included.

?The logic of quantamental investing is simple. Well-trained human analysts can understand how the future may look different than the past - think of changing industry structures, emerging technologies, shifting company positions or new industry regulations. In these situations, machines focused on historical data are at a disadvantage.

?On the other hand, well-developed computer models are unmatched in automating tasks, analyzing how the past may predict the future and identifying anomalies (i.e., automation, prediction, detection). No human can match an algorithm’s ability to vet millions of data points in such a manner. Uniquely integrating both presents a logical opportunity.

?Success will require more than hiring some people and telling everyone to get to work, however. To be successful, each firm faces a similar but distinct challenge: discover how to best integrate these methods given their unique objectives, skills and experience.

?The firms that figure that out are likely to outperform.