In our Chart for the Curious about Apple Computer, we document the challenges faced by investors who follow forecasters. For those seeking compelling evidence based on robust quantitative methods, please see our White Paper The Persistence of Profits. That piece builds on work done by a legendary professor of behavioral finance Joseph Lakonishok – a founder of LSV – one of the world’s great asset managers.
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What is Quantamental Investing?
Quant investing management typically employs large portfolios of stocks rebalanced at predetermined intervals. These approaches attempt to exploit alpha from various factors or perceived information advantages gained from alternative data. In contrast, fundamental investors seek to ascertain the quality of a firm based on its current and future cash flows and numerous other qualitative factors.
The term “quantamental” is really just an ugly merger of the words “quantitative” and “fundamental.” Quantamental just means that someone is using quantitative outputs while also pursuing the more traditional fundamental investment process frequently associated with people like Peter Lynch. We will talk more about both in a moment but want to make sure we give the fundamental side of the term its due. In our post on speculative trading we transcribed dialogue from a presentation given by Peter Lynch that hammered home, with a good deal of humor, the tremendous value in understanding what you are investing in.
Quantamental investing merges the use of systematic stock picking from quantitative tools with the oversight and diligence of fundamental investors. As the asset management industry has embraced this approach, quantamental investing has become an omnibus term that defines a wide range of often disparate methods. At one extreme are programmers using big data and machine learning to try and parse alpha from high-speed trading. At the other extreme, traditional fundamental researchers use simple factor-based tools to help ensure they are hewing to their mandates which might hold their positions for over a decade.
Quantitative methods typically benefit from removing of human beings’ unfortunate tendency to be their own worst enemies when it comes to investing. Fundamental methods benefit from human beings’ ability to recognize everything from environmental factors, like a global pandemic, to granular items in footnotes that data cannot capture. By avoiding bias and incorporating rigorous firm-level information, quantamental investors seek to exploit returns that are available from both factors (quantitative) and stock selection (fundamental).
Summarily, combining quantitative and fundamental analysis, a “quant amental” approach, allows users to get the best out of both the fundamental research and quantitative investment processes.
Quantamental Investing Strategies: The KCR Approach
If you look at the biographies of the Research Team’s co-founders, you will see they both spent their entire careers using a “quantamental strategy.” For them, this is a skill set they have been refining and working on for 50 combined years. Our team views the quantitative side as integral to the fundamental research process which, then surfaces improvements in the quantitative models we use.
KCR’s portfolio managers and researchers know no other method to successfully create systematic alpha.
Steeped in behavioral finance, our ranking tools seek to exploit the tremendous pricing errors that emerge due to the inevitable herding, fear, and greed that characterize markets. The financial data used to build our models was hand cleaned at the company’s founding in 2010. This arduous process continues to this day and is why KCR’s models are used by some of the top institutional investors and asset allocation firms in the world.
Spanning over a decade, our published research has used our quantamental approach to successfully identify and exploit bubbles in everything from dividend stocks to pockets of speculative excess akin to that seen in 1999. Similarly, our work has identified areas where undue pessimism has gripped the market and allowed us to buy blue-chip companies trading at significant discounts to intrinsic value.
An Example of a KCR Model: Our S&P 500 Large Cap Model
The chart below shows how KCR classifies our bullish, neutral, and bearish zones.
- When a stock ranks in the top 100 ranked stocks, the model highlights the stocks Kailash Concepts believes, represent mispriced quality
- When the stock is in the middle of the model, between rank 200 – 400, that means the model effectively has no view
- When the stock falls into the bottom 100 stocks, the model is warning us that the firm is either grossly overvalued, has balance sheet problems, accounting irregularities, or some combination of those issues
Please contact us if you would like a trial of any or all of our various tools.
Remember steer clear of bear trading.