“Chance is a word void of sense; nothing can exist without a cause.”
“Chance is a word void of sense; nothing can exist without a cause.”
Both the machine and the human are indispensable to the success of our company.
“True wisdom comes to each of us when we realize how little we understand about life, ourselves, and the world around us.”
We begin with information and attention to details. Information is a door to discovery; attention to details is its key. Master Information and Understand Details are the two major tasks at the first stage. Through data acquisition, raw data is transformed into an information network by connecting disjointed sources of data into a cohesive information repository, one that is ready for query and inference. Knowing more constitutes the first step toward the goal of consistent outperformance. Although knowing more does not guarantee an outperformance, without it a firm is bound to lose.
At Qtron, we always hunt for new information. With modern technology infrastructure, we aim to obtain more information in-house over competitors. Our scientific backgrounds teach us to appreciate details; we love diving deep and finding meaning.
“Models are worthless, but modelling is everything.”
Creative research transforms information into actionable investment insights. Our approach to research encompasses three steps: 1) it starts with a creative conjecture, 2) then, follows a thoughtful, thorough, and exhaustive empirical research, and 3) ends with practical considerations. Creative research enables firms to identify more investment opportunities. For example, our Fundamental Boosting approach instills fundamental insights into quantitative models and corrects misspecifications of traditional one-size-fits-all models; our Smart Beta Squared strategy considers changes in factors rather than levels and arbitrages smart beta techniques that are growing in popularity despite being ‘known to all’.
We find research in the investment industry is often old-school; we put forward creativity and innovation.
Most quants use each predictor to forecast every security. The assumption is that all companies face the same challenges and have identical value enhancing drivers. This is unrealistic.
At Qtron, we value the intuition necessary to design models. For predictive factors, we look for boosting variables in order to narrow zones of their effectiveness; for different stocks, we build tailored models reflecting their unique economic challenges. Essentially, we replace the old-school linear models with intuitive and effective piecewise linear models.
Most quants employ a sequential portfolio construction. First, they develop a stock picking model and submit it through a widely-used risk model. Then they submerge the fusion to a transaction estimate model and, finally, wrap the divergent hybrid around a benchmark. Most good investment ideas have likely been lost somewhere on this tortuous path. Mechanics dictates the portfolio. Error multiplication destroys back-tested results.
At Qtron, we design the process to be parallel. We use multiple horizon models, control risk, and estimate liquidity at the same time. We amplify signals and models that are expected to deliver more while we play down others. We seek to control critical risks and monitor others.
In the old-school approach, quants sift through past data to find a winning strategy that worked in the past. Most fail to recognize that other competitors are doing exactly the same thing. Moreover, the old-school approach treats quantitative investing as a hard science, like physics, and fails to follow the reflexivity in markets.
At Qtron, we strive to work in the present by augmenting our information set to stay aware of current market intelligence. In addition, we explore reflexivity by examining the impact of both positive and negative feedback loops.
“In order to act wisely it is not enough to be wise.”
– Fyodor Dostoyevsky
Smart execution is intended to turn investment insights that are on paper into clients’ excess returns; it transforms alpha signals into trades. Common practices focus on transaction cost modeling, broker, and trading algorithm selection. Although most quantitative shops devote significant resources in these areas, many fail to address what we consider the fundamental question in execution — being timely! As a result, they trade portfolios periodically to capture only the latest changes in return forecasts. This way of trading is neither timely nor efficient. Each trade incurs transactions — liquidity costs money.
At Qtron, with timely execution, we believe more returns can be harvested to enrich our clients’ portfolios. In contrast to the old-school approach that forecasts excess returns for a fixed horizon, we attempt to explicitly forecast when a payoff occurs. We do this by incorporating horizon and calendar seasonality as well as event-driven analysis.
““If you realize that all things change there is nothing you will try to hold on to.”
We believe quantitative portfolio managers are primarily investors who build and, consequently, know their model from the inside out. To generate outperformance, they need to recognize their models’ strengths and more importantly, their failings. They also must know everything there is to be known in addition to the model. Their job is to take the good risk — what a model understands and captures, and forgo the bad risk — a model’s blind spots. In many ways, portfolio managers are the risk allocators sitting between quant models and clients’ portfolios. They add value by identifying models’ blind spots and mitigating undesirable model risks.
At Qtron, we let the model do what it does best: process massive amount of information efficiently, and let portfolio managers do what they do best: adapt to a changing environment.
To attain your target of outperformance, we strive to become intelligent not merely today, but to respond to our ever-changing world tomorrow. Our models and approaches adapt promptly and we inform you about our research. We constantly listen, create, and consult to meet your needs.Read More
“Opportunities? I make them.”
– Napoleon Bonaparte
We believe most signals and techniques in the quantitative arena are old-school and crowded. The combination of similar techniques, identical data sets, and crowded trading may create predictable patterns! Managers tend to use the same benchmarks and rebalancing rules, the same liquidity provisions and techniques to address risk. Since they worry about the same events, they react in similar ways and at the same time. Yet how can you beat the market if your behavior is the same as the majority of market participants?
Technology disrupts one industry after another; innovation cycles become shorter and faster. New types of risk emerge from unprecedented central bank experiments. Investors are faced with a glut of information and its asymmetric nature, rampant predatory trading, and volatile markets.
At Qtron, our goal is to accept the flux of events, to find investment opportunities in changes.
A small leak can sink a great ship. To cut costs and improve corporate efficiencies, we embrace modern technology. With our low corporate overhead, lean technology infrastructure, and productivity-enhancing business apps, we strive to pass savings to your organization.
“Everything should be as simple as possible, but not simpler.”
– Albert Einstein
We do not own computer servers, disk arrays, network routers, or firewalls. We do not and will not have an army of system engineers, programmers, or administrators to support our hardware and software infrastructure. Instead, our computing environment resides in the cloud. With cloud computing, we enjoy unlimited computing resources on demand and are able to outsource supporting activities.
At Qtron, we focus our energy on core investment competencies.
“Knowledge is learning something every day. Wisdom is letting go of something every day.”
Building in-house proprietary software is a thing of the past; our view is that open source architecture is the best path forward. We find high quality open source packages — from a linear algebra library, to database software, to machine learning, etc. We replace monolithic software design with micro-services architecture. Instead of vertical integration and control, we choose horizontal collaboration and flexibility. Open source architecture not only lowers software development costs, it also shortens the time-to-market.
At Qtron, we believe we can rival any large financial firms at a fraction of their costs.
“If you turn with your face to the sun, shadows will fall behind.”
We subscribe to the notion, “If you can’t measure it, you can’t improve it.” To measure, we first collect relevant data and then examine it with an appropriate metric. This is the essence of how big data drives improvements in efficiency. We employ many business apps, like Applicant Tracking System (ATS) or Customer Relationship Management (CRM), to save costs, improve productivity, and increase customer satisfaction.
At Qtron, we are avid participants in the open source community and productivity enhancing solutions.