At Picton Mahoney Asset
Management, two independent research teams generate long and short stock recommendations for Portfolio Managers David Picton and Jeff Bradacs. In this article, Rob Poole (Head of Fundamental Equity Research), Dashmeet Singh (Portfolio Manager and Director, Quantitative Research & Risk) and Bradacs explain how this process leads to high-conviction portfolios.
JEFF BRADACS PORTFOLIO MANAGER, CANADIAN EQUITIES, PICTON MAHONEY ASSET MANAGEMENT
ROB POOLE HEAD OF FUNDAMENTAL EQUITY RESEARCH, PICTON MAHONEY ASSET MANAGEMENT
DASHMEET SINGH PORTFOLIO MANAGER AND DIRECTOR, QUANTITATIVE RESEARCH & RISK, PICTON MAHONEY ASSET MANAGEMENT
WHAT DISTINGUISHES PICTON MAHONEY’S INVESTMENT PROCESS?
BRADACS: We have a mission to help investors achieve their financial goals with greater certainty. On the equity team, we do things differently from other asset managers—and we believe differentiation has been key to driving value-add for our investors. First, we don’t fall into the typical style boxes of value and growth. Our style, specific to our firm, looks for companies exhibiting fundamental change; and then we long companies with positive change and short companies with negative change. Second, when it comes to stock selection, we look at companies through independent fundamental and quantitative lenses because we see strength in incorporating two different signals into our decision-making.
HOW DO THE TWO RESEARCH TEAMS IDENTIFY COMPANIES WITH FUNDAMENTAL CHANGE?
POOLE: Our fundamental analysis team has 13 sector analysts and associates. They’re largely based in Toronto, but our tech analyst and health-care analyst are in New York because those sectors are much larger in the U.S. market. Our coverage is broad and deep. Our analysts are true experts and thought leaders in their sectors, too. They spend their days monitoring macro, industry and company-specific data, meeting with management teams, industry bodies, regulators, as well as attending conferences. That said, when positive or negative change happens, they pick up on it quickly and flow that through into their coverage universe.
SINGH: We have a team of seven working on quantitative research and risk, with very strong academic and professional backgrounds—including experience in artificial intelligence and machine learning. We parse data from structured sources (like traditional financial statements) and from unstructured sources (like earnings call transcripts and regulatory filings). We then apply traditional linear regression and advanced machine-learning techniques to build models that help us understand which company attributes might outperform and drive positive change.
HOW DO FUNDAMENTAL ANALYSIS AND QUANTITATIVE RESEARCH COMPLEMENT EACH OTHER?
POOLE: The fundamental and quantitative teams are run independently, but both focus on identifying early signs of positive or negative change. Our fundamental analysis captures signs of change before macro or industry events flow through the fundamentals. We spend a lot of time sizing the sustainability of that change, the upside or downside potential from that change and how we envision that flowing through financial statements and forecasts in the future. Then, as the change becomes more evident and starts to reinforce itself, we watch how it flows through the financials and how our projections differ from consensus on the street. Our ability to be open to how that marginal piece of data could impact a sector or company, and to examine the potential change paths, is a very important aspect of our team’s contribution.
SINGH: Our systematic process also aims to capture change on the margin as quickly as possible. We work to find change in an unbiased, unemotional, disciplined way— independent of fundamental views. At the same time, the information we generate can be enhanced by fundamental analysis—for example, during one-off events like regime changes where fundamentals are quicker to adapt.
DOES ONE APPROACH CARRY MORE WEIGHT IN CERTAIN SITUATIONS?
BRADACS: Fundamental analysis and quantitative research are both key parts of our process, but there are times when we lean into the strengths of one more than the other. The fundamental side provides deep, forward-looking insights into the company where change is happening and is very powerful at turning points. The quantitative side covers a broad universe of companies in an unbiased way and is very powerful during periods of stability and trending markets, as well as when buying, selling or shorting stocks.
HOW HAVE YOUR TEAMS’ METHODS EVOLVED OVER TIME?
POOLE: We now have access to alternative data and service providers that enable us to better synthesize and aggregate large sources of data. Historically, a lot of buy-side shops predominantly focused only on financial statements in their equity research. Now, we’re involved with expert networks, which provide deep industry knowledge. Also, we have much more access to real-time and high-frequency data—for example, credit card spend data. That’s a huge advantage when you’re monitoring for change at the margin.
SINGH: On the quantitative side, we have two areas of focus: the data and the modelling technique applied to that data. Data has evolved drastically; and we can now combine the breadth of the traditional data set with the depth and speed of unstructured data. Modelling has also evolved to incorporate new data—from earnings transcripts to 10-K and insider filings. For example, we pay close attention to changes in the risk section of the 10-Ks because that section doesn’t change much under normal circumstances. We also watch for insider transactions that may influence a stock’s returns. As our teams’ technical capabilities deepen, we’re able to build even stronger and more effective models.
BRADACS: One way our portfolio management process has evolved is that we’re incorporating ESG considerations. We believe companies exhibiting positive change in ESG factors will likely see more investment dollars and, conversely, companies with negative change will likely see investment dollars flow away. We’ve integrated ESG into both our fundamental and quantitative research engines, from a risk and opportunity perspective. We’re continuously evolving our approach to risk management to help minimize any unintended risk in our portfolios, too.
HOW DOES HAVING INPUTS FROM TWO INDEPENDENT EQUITY RESEARCH TEAMS HELP PICTON MAHONEY BUILD HIGH-CONVICTION PORTFOLIOS?
BRADACS: At a high level, we want to build a diversified portfolio that maximizes our clients’ exposure to fundamental change characteristics within our risk budget. We start by building the portfolio with the names identified by the fundamental and quantitative teams. Then we build conviction weights—the largest positions—where both signals agree. We see significant power when two groups look for fundamental change but come at it from different perspectives. Finally, we use risk management and optimization tools as a guide for positioning weights to build a diversified portfolio within the established risk constraints.