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What is the FSI Sector Allocation?
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Quite simply, the goal of the FSI Sector Allocation is to outperform the overall S&P 500 as whole without increasing risk. The main user for this allocation is someone who likely would own the index as a whole or is benchmarked to the index.
Our FSI allocation is determined by using a disciplined process approach that is run by our Head of Portfolio Strategy and Asset Allocation, Brian Rauscher. So, it is making active bets to increase one’s return and alpha, and beat the S&P 500 benchmark.
If one has a more aggressive investment style and is willing take on more risk in an attempt to attain more investment return, then they can take even bigger weighting deviations either by shifting their ETF allocations or by supplementing their portfolios by adding exposure to single stock names in sectors that are favorable. In the near future, we will be introducing a single stock product called Brian's Dunks that will provide names that our research finds favorable. At the moment, a disproportionate number of stocks are within Financials, Industrials, Materials, Energy and Tech sectors.
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Why does Brian's FSI Sector Allocation differ from Tom Lee's strategy?
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We provide a wide variety of viewpoints on the markets, with services in Macro strategy, Policy, Technical Analysis as several of our offerings. As part of this, some strategies may view sectors as favorable whereas other strategies may view the sector in a different light. The top three sectors described in Tom’s 2022 Outlook reflects his Macro viewpoints on the markets. The ETF strategy is headed by Brian Rauscher our Global Portfolio Strategist.
For more information on Tom’s 2022 Outlook, please wath the recording of Tom Lee's webinar.
To learn about our portfolio recommendations going into 2022 watch the recording of Brian Rauscher’s 2022 Portfolio Outlook.
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Why does Brian Rauscher allocate less to energy and cyclicals than Tom Lee does?
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It is important to note that our FSI Sector Allocation is in relation to what the respective sector weights are within the overall S&P 500 as shown below.
A couple of key points:
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Our weight for Energy is now at 3.3%, which is 57% higher than its current benchmark weight, which is also up from a zero weight in September when we launched FSI Sector Allocation
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Tech’s weight is now 25.5%, which is 23% above its benchmark weight, which is down from our 37% recommended weight from our September update.
In the benchmark world, these are pretty dramatic shifts in positioning and clearly are consistent with both the commentaries from Tom Lee and Brian Rauscher, who has upgraded Energy three time since September.
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Where can I learn about the track record of Brian Rauscher's strategy?
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You can view the recent performance of the FSI Sector Allocation strategy on the Performance tab.
This is a strategy of variant forms that Brian Rauscher has been providing to his institutional clients for over 20 years now, but it was never been formalized like this until recently. During those years, a winning strategy was cristallized by Brian that promotes the wellbeing of portfolios of all sizes yielding outperformance for hundreds of clients in several different countries.
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When do you update your comments regarding specific sectors?
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The rule for whether or not a sector gets a comment for the monthly outlook is as follows:
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Any sector changes get a comment
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Sectors with HIGH favorability get a comment: Negative (dark red) and Positive (dark green)
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LOW favorability (light red and green) sectors do not unless there was a change.
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What is a "HALO" model?
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The proprietary Fundstrat Portfolio Strategy Halo Model is a multi-factor model that attempts to predict the forward 1 – 6 month relative performance of a group. The goal is to help both strategic accounts better time their implementation strategies that would be consistent with our more strategic conclusions derived by our sector/sub-industry 8-panels as well as our stock specific Estimate Revisions Model (ERM), and to generate tactical ideas for aggressive trading accounts.
The model has both momentum and contrarian characteristics. When the blue line, which is the model, is trending, our proprietary tool is in a momentum phase, and our research shows a high probability that relative performance will mirror the slope of the line. Importantly, because the model is built to oscillate, an extreme reading that inflects strongly suggests that a reversal in the most recent performance trend is likely to occur.
