Founded in December 2007, quant Global Research (qGR) is the thriving heart and inquisitive mind that energizes and guides the quant framework. qGR is driven by a simple idea: to extract predictive clues on market trends, it is critical to look beyond the obvious. Multiple data points outside the popular domain must be collected and synthesized into investment decisions using alternate analytical methodologies, as only differentiated research can lead to meaningful insights. A truism for all markets is that when everyone has found the key, the lock has already changed. So explore the unexplored. While following convention and staying with the herd may feel comfortable, markets do not follow what is written in textbooks or preached by perceived influencers.

A decade ago, market research was primarily focused on a company's financial statements, industry analysis, and, to some extent, macroeconomic studies. qGR began with a different idea about research with a focus on financial markets and the real economy as interlinked feedback mechanisms, along with a large emphasis on the role of investors' dynamic behaviour. As markets evolve and the velocity of information transmission accelerates, the ability to harness high-frequency data opens up opportunities far beyond simple exposure recalibration. The development of the MARCOV investment framework is driven by this recognition that decoding rapid shifts in liquidity, sentiment, and cross-asset correlations transforms micro-level signals into macro portfolio insights. This allows MARCOV to capture the structural impact of fast-moving flows and bridge short-term market microstructure with long-term capital allocation decisions.

The 'Multi-Dimensional' aspects come in because, in addition to conventional qualitative analysis, qGR is extensively focused on quantitative measures, 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 the various markets that form the 'financial economy'. Formal economics' understanding of the real economy is largely theoretical and grounded in assumption-based models. qGR focuses on empirical market analysis, discovering a multitude of interlinked, overlapping but independently-driven cycles based on extensive historical data, going back centuries in some cases. Apart from cycles, pioneering research on global liquidity through alternative data sources enables quantification and tracking of the flow of money and its consequences across markets and asset classes.

Going further, qGR Objectivity Analytics identifies the risk posturing of market and economic participants. The collective appetite of businesses and investors helps categorize the economic and market environment into zones of risk-loving, neutral, and risk-averse. 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' (AAA) execution methodology for money management. The various models, indicators, and cycles are continuously 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 that we believe is the source of outperformance. There is no search for a Holy Grail; it is about applying simple and time-tested market principles through a multi-dimensional lens.

– 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 that 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 approaches 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 with a vision of the future that was substantially different than the prevailing wisdom of 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. Mistakes have helped us refine our tools and framework. At the same time, the diversity of research that we have covered has seen immense growth.

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 phenomena. Fully aware that it may not materialise completely, however, they 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 Specialised Investment Fund (qsif).

We believe it is the right time to test our philosophy, put on the glasses of our MARCOV 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 proprietary investment frameworks are our primary tools for making optimal investment decisions. Significant market meltdowns usually happen because of 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 of data, computing power, and quantitative methodologies. However, research has continued to focus on 'real economy' factors.

The coverage and attention the financial economy gets are minimal. Even more surprisingly, despite all the asset classes being interlinked, 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 commodities is considerably larger than the real economy, by a factor of approximately 7 times or more. Due to this gross imbalance in scale between the financial and the real economies, we believe it is the financial economy that primarily 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 second and third-order derivatives based on them.

Redefining the research perspective

Most market intermediaries continue to focus on the real economy over and above the much more significant financial economy. 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 larger than the real economy, and consequently, the former drives the fundamentals of the latter. Research on the real economy, no matter how thorough, leads the majority of advisors and money managers to miss out on crucial predictive information by ignoring the financial economy. qGR seeks to harness this opportunity through its multidimensional research perspective.

quantamine is a fully integrated, in-house intelligence and execution architecture engineered for latency-sensitive multi-asset strategies. Designed as the central nervous system of the firm’s investment operations, it unifies risk, compliance, investments, and operations into a frictionless, coordinated workflow. It ingests heterogeneous, high-dimensional datasets on macroeconomy, microstructure, sentiment, liquidity, and volatility into a single actionable layer. Its architecture utilizes advanced pattern recognition models to detect regime shifts, liquidity stress points, and microstructure anomalies, dynamically recalibrating risk exposure in real-time.

Born in 1995 as Stockmagic on a personal computer at the Founder’s residence, the platform grew into a large-scale effort employing 75 engineers at its peak. Its evolution has been forged in crises: Risk Appetite Analytics emerged after the 2000 dot-com collapse to gauge shifts in investor tolerance, Liquidity Analytics developed during the 2008 financial crisis to track hidden fragilities in funding markets, and Money Flow Analytics was synthesized as their culmination to map cross-asset capital movements. Post the 2020 COVID-19 crash, Perception Analytics reoriented from static earnings forecasts to modelling valuation multiples, while Volatility Analytics expanded across asset classes to anticipate regime breaks and bolster proactive risk management.

These pillars now form a tightly interlinked, adaptive framework that allows quantamine to anticipate market change with precision instead of simply reacting to it. Alongside, the platform delivers custom dashboards and performance analytics at any level of granularity. Extensive logging, maker-checker controls, and breach tracking ensure an auditable environment that balances agility and governance.

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.

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. The qGR Multi-Dimensional research approach is significantly differentiated: our indicators represent unbiased, actionable analyses, a cognitive tool for quantifying fundamental expectations, tradable sentiments, and behavioural attitudes. They are unique in their ability to condense multidimensional research into unidimensional singularities. Further, qGR utilizes its unique skills in aggregating market inputs for all asset classes, dividing smart money/ dumb money, subtracting cross-market overlap and finally multiplying with the long-term macro landscape. The hidden force behind market dynamics is best understood by quantifying as many aspects of the global economy as possible.

Analysis adds up

With an exhaustive data-driven investment paradigm, our tools and methodologies allow us to see beyond the vision of standard fundamental and other analyses. A testament to this ability to see beyond the obvious is our track record over the years. This is why 'Measurable is Reliable' remains one of the key guiding investment principles in all our decision-making.

Especially in the world of investments, numbers are, well, mere numbers. However, analysed numbers talk, analysed numbers can truly reveal the whole story – that is why measurable is reliable. When it comes to investment advice, guesswork never works. What matters is pure, sharp, accurate analysis – everything that has been measured properly can be relied on.

We have always invested in systems, digital, and IT infrastructure. What exactly does technology have to do with investment? Everything, according to us, as it helps measure, assess, quantify, analyse – truly making reliable, everything that is measurable

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 have been surprised at the discovery of what could be the next big event to hit markets and the world economy – not wars, some over-leveraged sector bursting, or an overzealous government going bankrupt, although all of them will also take place. However, they may all be overshadowed as the magnitude of ramifications brought about by nature will be 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 tornadoes and cyclones, solar storms, geomagnetic shifts – our study into these phenomena over a really long time frame has thrown up some interesting implications for the next few decades. It is also why we feel the time is right to study these phenomena and discover their impacts 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. For example, a large body of psychological research shows that geomagnetic storms have a profound effect on people’s moods, which in turn affect 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 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 a higher probability, its impact on energy prices is again relevant. There are many such relationships we have found, and we certainly aim to keep discovering more.

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

The pursuit of risk management in today's markets demands more than selective intuition or episodic conviction. It calls for a process that is both structured and adaptive, one that can absorb complexity without being paralysed by it. Systematic Active Investing is that process — an investment style that combines the structural discipline of passive investing with the adaptability and insight of discretionary active management.

At its core, it is a structured, rules-based decision architecture that is both conviction-driven and risk-aware. It leverages machine intelligence, advanced analytics, and human insight to identify opportunities across asset classes, construct resilient portfolios, and manage risks with precision. This style thrives on data density and analytical depth, continuously interrogating high-frequency signals, structural dislocations, and behavioural anomalies across markets.

At quant, Systematic Active Investing forms the strategic backbone of qsif, enabling dynamic positioning across long–short portfolios with the objective of delivering steady performance through market cycles. All investment decisions originate from measurable signals — derived from price behaviour, market microstructure and macro cycles with real-time data integration, and multi-factor modelling. Unlike conventional active investing, which often depends on episodic human judgment or passive investing, which forgoes responsiveness, this style operates within a disciplined, repeatable and adaptive framework.

In essence, Systematic Active Investing is the operating system that powers our long-short conviction: a high-integrity, low-latency, multi-layered architecture that seeks to deliver asymmetric returns with institutional robustness.

Financial markets are no longer a simple reflection of real economic output. They have evolved into hyper connected, multi-layered systems where liquidity, sentiment, and cross-asset correlations create complex and often nonlinear dynamics. The periodic dislocations witnessed in recent decades — whether triggered by central bank pivots, sovereign defaults, pandemics, or technological shocks — illustrate that the health of the system is as much a function of liquidity flow as of underlying productivity.

Our investment framework MARCOV addresses this by integrating high-frequency indicators through our High Frequency Analytics (HFA).

At its foundation lies a recognition that markets are not continuous streams but layered tapestries of liquidity and intent. HFA reads this fabric at its highest resolution, drawing upon trade-level data, depth dynamics, liquidity gradients, sentiment drifts, and volatility clusters to reveal the subtle inflexion points that precede regime change. Its architecture is designed for seamless throughput and immediate response, yet its purpose is enduring: to enhance strategic posture without distorting structural intent. Through advanced state-mapping, HFA quantifies order flow toxicity, tracks liquidity fractures, and anticipates adverse selection long before it manifests in conventional frames. It aligns execution with natural liquidity rhythms, using decay curves and transaction cost intelligence to minimise footprint without compromising conviction. Volatility clustering models further refine exposure bands, ensuring that agility does not come at the cost of stability, and that drawdown containment coexists with convex upside capture.

Within the MARCOV framework for qsif, HFA acts as the timing oracle—the real-time intelligence layer that synchronises predictive signals with market reality. It is the bridge between the model and the moment, allowing strategies to flex without losing coherence, and portfolios to move with precision rather than haste. HFA is a living system of observation and adaptation, enabling decisive action under uncertainty while maintaining fidelity to long-term design. By doing so, it allows for the identification of inflexion points not visible through traditional quarterly or annual datasets, and for a continuous recalibration of portfolio exposures across equity, debt, derivatives, and alternate assets.