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In this month’s Portfolio Compass, we revive the debate among academics and practitioners as to whether cash flows or earnings offer more useful information to equity investors. Empirically, we find that cash flow based factors excel on valuation and profitability dimensions, while earnings-based signals are better at measuring growth and analyst sentiment in most regions of the world (e.g., US, Europe, AxJ, and Japan).
This is Part II of our Global Energy Investing series. Last week, we introduced our global energy industry rotation and stock selection models (see Active Global Energy Stock Investing Guide). In this note, we focus on predicting crude oil price, using both traditional and alternative data.
On March 22, the 10Y US Treasury yield fell below the 3M bill, marking the first yield curve inversion since the 2008-2009 financial crisis, on the back of disappointing global economic data. The inverted yield curve further caused a widespread market selloff, as fears of a near-term recession intensified. Although a negative yield spread has successfully predicted every single recession since 1970s, it is far from certain that a recession is inevitable.
Our Malessa (Machine Adaptive Learning Energy Stock Selection Alpha) model has delivered superior Sharpe ratios of 2.4x and 3.1x, in the US and international energy sectors, respectively, since 1994. The dashboard provides access to the latest scores and ranking that update every day.
On March 22, we held our first NLP (Natural Language Processing) and Machine Learning Investment Conference in New York City. Almost 150 buy-side investment managers and researchers from around the world attended the event.
The S&P 500 keeps charging ahead since December 2018 lows, reaching a five-month high lately. At the same time, the Russell 2000 index has lagged behind. In particular, we observed a dramatic relative underperformance of small-cap on March 6 – a relatively rare two sigma event.
In this month’s Portfolio Compass, we add three measures of earnings quality to our factor library: earnings smoothness, earnings variability, and cash flow variability. All factors show decent predictive power, especially in AxJ, the UK, and Canada, with
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