A decade ago, market research was focused primarily on the financial statements of a company, industry analysis and macro-economic studies to some extent. qGR began with a different idea about research with a focus on financial markets and the real economy as interlinked with feedback mechanisms, and a large emphasis on the role of investors’ dynamic behavior. This idea evolved into a multi-dimensional research perspective which is now formulated in our VLRT framework.

The ‘multi-dimensional’ aspects comes in because in addition to conventional qualitative analysis, qGR is extensively focused on quantitative measures and indicators of market patterns and various cash and derivatives market attributes. These diverse variables provide a picture of the inner workings and changing structure of various markets which form the ‘financial economy’. For the real economy, while formal economics is largely theoretical with assumptions-based models, qGR focuses on empirical market analysis, discovering a multitude of interlinked, overlapping though independently-driven cycles based on extensive historical data, going back centuries in some cases. Apart from cycles, pioneering research on global liquidity through alternate data sources enables quantification and tracking of the flow of money and its consequences across markets and asset classes.

Going further, qGR behavioral analytics identifies the risk posturing of market and economic participants. The collective appetite of businesses and investors helps categorize the economic and market environment in zones of risk loving, neutral and risk aversion. Sentiment clues are also computed through proprietary risk indicators that enable us to quantify varying levels of fear and greed. Granular analysis specific to sectors or individual companies is also performed by identifying bouts of euphoria and panic.

Along with research, qGR provides a unique ‘Adaptive Asset Allocation’ execution methodology for money management. The various models, indicators and cycles are continuously being observed as they change with the market environment. Investment calls are triggered by certain observations in any one of the components, following which the call evolves based on further evidence from other relevant components. This endows our money management with an adaptive ability which we believe is the source of outperformance. There is no search for a Holy Grail, it is about applying simple and time-tested market logic through a multi-dimensional lens.

“quant’s indicators are unique in their ability to condense multi-dimensional research into a one-dimensional single number. Our typical day starts with quant Risk Index, one metric that encapsulates risk across markets and across assets. The challenge has been of marrying momentum with qualitative research, and assimilating various macroeconomic variables and time series data with cross-sectional data. It has worked well for us and we hope to continue our best efforts in that direction.”

– Sandeep Tandon

As Niels Bohr famously remarked, ‘it is very hard to make predictions, especially about the future”. Any market participant, whether a value investor or a day trader, would more or less agree with this statement. They would also agree that the task becomes exponentially more difficult with cross-asset, cross-market forecasts. As we go further out into the future, the cumulative amount of relationships and independent attributes that need to be analysed and predicted almost approach infinity.

Yet, an honest attempt must be made and the analysis that we present to you here is the result of just such an attempt. A decade ago, we started out with a vision of the future that was substantially different than the prevailing perspective at that time. It gives us great pleasure to note that the past decade has seen the materialization of a substantial part of that thought process. To be honest, several mistakes have also been made but they are cherished by us even more as they helped us refine our tools and framework. At the same time, the diversity of research that we have covered has seen immense growth.

Going further, qGR behavioral analytics identifies the risk posturing of market and economic participants. The collective appetite of businesses and investors helps categorize the economic and market environment in zones of risk loving, neutral and risk aversion. Sentiment clues are also computed through proprietary risk indicators that enable us to quantify varying levels of fear and greed. Granular analysis specific to sectors or individual companies is also performed by identifying bouts of euphoria and panic.

Now, at a crucial moment in history, we have formed another vision of the future after meticulously connecting the dots across a broad spectrum of phenomenon. We present here glimpses of that picture while being fully aware that it may not materialise completely. However, the glimpses we present here can serve as a rough map to navigate the uncertain future. The coming decades will be chaotic and overturn most of the commonly held beliefs and systems that we are accustomed to. Being prepared is the least we can do.

Words without action mean much less, of course, which is why we have embarked on a new journey with the launch of our money management business (quant Mutual Fund).

We believe it is the right time to test our philosophy, put on the glasses of our VLRT framework and implement the ‘Adaptive Asset Allocation’ methodology.

In a dynamic world, it is not just a choice but a necessity to adopt a multi-dimensional view.

We believe that alternate perspectives such as behavioral finance, volatility analytics and earth changes along with liquidity analytics are going to become more and more important.

The world is becoming non-linear and parabolic and to stay relevant, money managers must think with an unconstrained mind, actively update their methods and earnestly search for absolute returns, considering all markets and asset classes.

For identifying cross-asset, cross market inflexion points, qGR’s VLRT framework is our primary tool for making the right decision. Significant market meltdowns usually happen because of a failure by participants to quickly process complex information. In such an environment, a more holistic analysis of data helps deploy capital rationally in any asset class. The investment research process has evolved dramatically – from the time Wall Street first started putting together teams of analysts in the 1950s for institutions – with an explosion in data, computing power and quantitative methodologies. However, research has continued to focus on ‘real economy’ factors.

The coverage and attention that financial economy gets is minimal. Even more surprisingly, despite all the asset classes being inter-linked, most market intermediaries follow a silo approach to analysis. This is where qGR aims to harness alpha through its multi-dimensional research approach. We believe the financial (leveraged) economy, comprising global equity, currency, fixed income and commodity is considerably larger than the real economy, by a factor of approximately 10 times or more.

Due to this gross imbalance in scale between the financial and the real economies, we believe it is the financial economy primarily which drives the real economy, and not the other way round. Therefore, qGR methodologies focus on the constituents of the financial economy, namely, the various asset classes which are traded globally — equities, currencies, commodities, fixed income, and, most importantly, the 2nd and 3rd order derivatives based on them.

Redefining the research perspective

Like Penny-farthing bicycles of yesteryears, most market intermediaries continue to focus on the real economy (small wheel) over and above the much larger financial economy (big wheel). On the contrary, qGR follows a more holistic approach by focusing on the financial as well as the real economy. The financial economy is several times the size of the real economy, and consequently, the former drives the fundamentals of the latter. Research on the real economy, no matter how thorough, while ignoring the financial economy leads the majority of advisors and money managers to miss out on crucial predictive information. qGR seeks to harness this opportunity through its multi-dimensional research perspective.

Market moves are highly dependent on the aptitude and appetite of market participants. To address this, we at qGR track several proprietary indicators which measure market sentiments from different perspectives. Extreme euphoria or fear can be gauged by many of these indicators, helping us to deduce how players are positioned and how they react to a particular situation. Once we understand investor behavior through these indicators, we can identify times when players are being irrational or making illogical decisions or showing signs of exuberance/paranoia.

qGR predictive analytics indicators are identifiers of inflexion points and opportunities in the complex investing environment. They provide clarity during difficult times when there are many questions that entail event and polity risk.

Redefining the research perspective

‘Measurable is Reliable’ – is a fundamental qGR mantra.

Our research enables us to capture market behavior in terms of quantifiable variables through our proprietary indicators.

These extensively back-tested indicators – which in combination help us to capture market trends – are the soul of our market calls and are backed by years of extensive technology-driven research.

First name hungry, last name always

Summarily, quant’s investment philosophy and tools aid in rational decision making, particularly in these tumultuous times, when it has become critical to look beyond the obvious to extract proactive clues on market trends. quant’s multi-faceted research approach is significantly differentiated: our indicators represent unbiased actionable analyses, a cognitive tool for quantifying fundamental expectations, tradable sentiments and behavioral attitudes. They are unique in their ability to condense multi-dimensional research into one-dimensional singularities. Further, qGR utilizes its unique skills in aggregating market inputs for all asset classes, dividing smart money/ dumb money and subtracting cross-market overlap and finally multiplying with the long-term macro landscape.

The hidden force behind market dynamics lies in quant and we are quant!

Analysis adds up

With an exhaustive data-driven investment paradigm, we are confident that our methodology allows us to see beyond the vision of standard fundamental and technical analysis. A testament to this ability to see beyond what is obvious is our prescient track record over the years.

The belief of ‘looking beyond the obvious’ which we started with a decade ago, continues to burn bright and light up the path ahead – no branch of knowledge rooted in logic and reason should be ignored as all pieces eventually fit together to form a clear picture. In this endeavor, we ourselves have been surprised at the discovery of what could be the next big event to hit markets and the world economy – not wars, or some over-leveraged sector bursting, or an overzealous government going bankrupt, although all of them are also going to take place. However, they may all be overshadowed as the magnitude of ramifications brought about by nature is far greater.

Our research enables us to capture market behavior in terms of quantifiable variables through our proprietary indicators.

Earthquakes, floods, unexpectedly cold and wet climate, increasingly volatile weather, higher frequency appearance of tornados and cyclones, solar storms, geomagnetic shifts – our study into these phenomenon on a really long time frame has thrown up some interesting implications for the next few decades. It is also why we feel it is the right time to study these phenomenon and discover their possible impact on markets.

Everything in nature is connected and the law of cause and effect is supreme. This is clear from everyone’s own experiences and a basic understanding of the physical sciences. To understand this connection, one example is that a large body of psychological research has shown that geomagnetic storms have a profound effect on people’s moods, which affects human behavior, judgments and decisions about risk. One of the key causes of geomagnetic storms is activity on the surface of the sun, which in turn is a complex result of the ever-changing gravitational pulls on the Sun’s surface of both near and far cosmic bodies. This connection makes studying the Sun’s behavior a potential source of predictive clues on socio-economics.

We believe financial analysis need not be limited to just human-driven entities but should cover everything that can possibly affect markets. If an increased likelihood of extreme weather events in a region has implications for certain crops, it’s a relevant factor for predicting prices. Similarly, if a period of extreme weather has higher probability, its impact on energy prices is again relevant. There are many more such relationships which we have already found and certainly more we aim to discover going ahead.

Just as a decade of research into quantitative, qualitative and behavioral aspects of markets led us to develop the VLRT framework, qGR believes ‘Earth Analytics’ may also emerge as a valuable dimension of research during the next few decades.