Faber Ivy Amplified Leaderboard: Can It Beat SPY? | 47.9% CAGR, -49.6% MDD
A 47.9 percent annualized return is the kind of number that immediately grabs attention, but it should not be separated from the 49.6 percent worst drop that came with it. Faber Ivy Amplified Leaderboard takes the basic logic of the Ivy Portfolio—own assets showing positive momentum while respecting a long-term trend filter—and applies it to a much more aggressive universe dominated by leveraged growth ETFs. The result is a systematic strategy with unusually high simulated upside, but also losses large enough to cut a portfolio roughly in half before recovery. Its 0.97 risk-adjusted score shows that the return was earned with substantial volatility rather than through a smooth compounding path. The important question, therefore, is not simply whether the historical return was impressive, but whether the rules, concentration, leverage, and losing periods make the strategy realistically tradable for a given investor.
📈 Yearly return (CAGR): 47.9%
📉 Worst drop (max drawdown): -49.6%
⚡ Sharpe Ratio: 0.97
💰 Total Return: 4792.1%
🎯 Universe: TQQQ, UPRO, SOXL, FNGU, BULZ, TECL, TNA, SPXL (growth) + TLT, GLD, BIL (defensive) + SPY (regime benchmark)
The Trade-Off: Exceptional Return, Very High Risk
The headline backtest produced a 47.9 percent annualized return and a 4,792.1 percent total return, but the portfolio also suffered a 49.6 percent maximum decline from a previous peak. That combination places the strategy firmly in the very-high-risk category, because a loss approaching half the portfolio can overwhelm investors who size the position as if it were an ordinary diversified portfolio. A risk-adjusted score of 0.97 indicates that the strategy was rewarded for the risk it took, but it does not mean the path was comfortable or predictable. Leveraged equity funds can rise rapidly during persistent bull markets, yet they can also lose value at extraordinary speed when trends reverse. The trend and momentum rules are designed to reduce exposure when conditions deteriorate, but monthly decision points cannot eliminate losses that occur between signals. The practical trade-off is therefore straightforward: the strategy seeks unusually strong compounding by accepting unusually severe portfolio swings.
What You Would Actually Trade
The growth side of the universe consists of TQQQ, UPRO, SOXL, FNGU, BULZ, TECL, TNA, and SPXL, all of which provide amplified exposure to aggressive equity themes or indexes. The defensive candidates are TLT, GLD, and BIL, representing long-duration Treasury bonds, gold, and short-term Treasury bills, while SPY serves as the broad-market regime benchmark. The portfolio is reviewed monthly, with the rebalance occurring on the first trading session of a new calendar month. In plain language, the system asks which eligible assets are behaving strongly enough to deserve capital and whether the broader market environment supports taking aggressive equity risk. When growth assets fail the required momentum or trend conditions, defensive holdings provide places for capital to move rather than forcing the strategy to remain fully invested in leveraged equities. This structure is systematic, meaning the allocation is supposed to follow predefined signals instead of discretionary predictions about the next market move.
How the Ivy Logic Works
The original Ivy Portfolio framework is built around two related ideas: favor assets with positive momentum and avoid assets that fall below a long-term trend threshold. Absolute momentum asks whether an asset has actually been rising over the chosen lookback period rather than merely performing better than another weak asset. A trend filter adds a second test by requiring price behavior to remain consistent with a longer-term uptrend before capital is committed. These rules matter because a ranking system by itself can still select the least-bad asset in a falling market. By combining momentum with a trend requirement, the strategy attempts to participate in persistent advances while stepping away from assets whose price structure has materially weakened. The approach does not predict tops or bottoms; it reacts after price behavior has already changed, which means every protective signal necessarily contains some delay.
My Adaptation: Amplifying the Leaderboard
The key adaptation is applying the Ivy-style momentum and trend discipline to a leaderboard dominated by leveraged growth vehicles rather than the more conventional asset classes usually associated with the original Ivy framework. That change greatly increases the potential reward when strong equity trends persist, because funds such as TQQQ, SOXL, and UPRO magnify daily movements in their underlying markets. It also increases path dependency, meaning the sequence of daily gains and losses can materially affect long-run results even if an underlying index eventually returns to the same level. The defensive sleeve of TLT, GLD, and BIL is therefore especially important because it gives the system alternatives when leveraged growth exposure no longer qualifies. SPY functions as a regime benchmark so that the strategy can distinguish a broadly supportive equity environment from one in which aggressive exposure may be less appropriate. This adaptation is what creates the possibility of extraordinary historical compounding, but it is also the main reason the strategy cannot be evaluated like a standard unleveraged allocation.
What Actually Happened in the Backtest
Over the tested history, the strategy compounded at 47.9 percent per year and generated a cumulative return of 4,792.1 percent. It recorded 10 positive calendar years and 1 negative year, which sounds remarkably consistent until the 49.6 percent worst decline is considered alongside those annual statistics. Calendar-year results can hide severe losses that begin and recover within the same year, so the number of winning years should never be treated as a substitute for examining the full equity curve. The 0.97 risk-adjusted score suggests the return was strong relative to volatility, but it still reflects a portfolio exposed to abrupt leveraged-market moves. A maximum decline of nearly 50 percent means an investor could have watched approximately half of the strategy's peak value disappear before a recovery was completed. These results are historical simulations rather than forecasts, and they describe what the rules would have done under the test assumptions rather than what they are guaranteed to do next.
The Catch: The Path Matters More Than the Average
The largest danger in reading a backtest like this is focusing on the 47.9 percent annualized return while mentally assuming that return arrived in something close to a straight line. It did not: a strategy can produce an excellent long-term average while still experiencing violent interim declines, extended recoveries, and periods when its signals react too slowly. Leveraged ETFs can compound favorably in persistent trends but can suffer from volatility drag when markets repeatedly reverse direction, making choppy environments particularly difficult. Monthly rebalancing also creates timing risk because the system may remain exposed until the next scheduled signal even after market conditions begin deteriorating. The correct way to judge the strategy is to examine the equity curve, the magnitude of the worst decline, and the time required to recover previous highs together. If a 49.6 percent temporary loss would cause an investor to abandon the system, then the historical return is largely irrelevant because the strategy would probably be abandoned before its long-run statistics could be realized.
Who This Strategy Fits
Faber Ivy Amplified Leaderboard is best viewed as a very-high-risk systematic strategy for investors who understand leveraged products and can tolerate large swings without overriding the rules emotionally. The 49.6 percent historical maximum decline should be treated as evidence of the scale of loss that has already occurred in simulation, not as a guaranteed upper limit on future losses. Position sizing is therefore critical: an investor who cannot tolerate a roughly 50 percent decline in the strategy itself would need to allocate only a fraction of total capital to it. The approach may appeal to people who prefer objective monthly rules over discretionary market forecasts and who are willing to exchange smoother returns for greater upside potential. It is much less suitable for capital needed on a fixed date, investors with low loss tolerance, or anyone likely to abandon the strategy after a sharp leveraged selloff. The backtest is useful as research evidence, but it should be compared with simpler alternatives because higher historical returns do not automatically produce better real-world outcomes.
Frequently Asked Questions
What is the Faber Ivy Amplified Leaderboard strategy?
It is an aggressive variation of the Ivy Portfolio concept that uses absolute momentum and a trend filter to decide when leveraged growth ETFs deserve exposure, while defensive assets provide alternatives when conditions weaken. The portfolio is evaluated monthly and includes leveraged equity funds, Treasury bonds, gold, Treasury bills, and SPY as a market-regime benchmark.
How risky is this strategy?
It is very high risk: the backtest experienced a 49.6 percent maximum decline despite producing a 47.9 percent annualized return. Because the universe contains leveraged ETFs, losses can develop quickly and future declines could be larger than the historical backtest shows.
Can the strategy be traded today?
The instruments in the stated universe are tradable market products, so the rules can in principle be followed today if the required funds remain available and liquid. However, the historical results do not guarantee similar future performance, and an investor would still need to calculate the current monthly momentum, trend, and regime signals before knowing what the strategy would hold now.
What data and assumptions does the backtest rely on?
The reported simulation assumes the stated universe, monthly rebalancing on the first trading session of each new calendar month, and the strategy's momentum, trend-filter, and regime rules applied consistently through the test period. Results can change materially depending on price data, signal definitions, start date, trading costs, fund availability, execution assumptions, and how periods before a leveraged ETF existed are handled, so those details should be verified before treating the statistics as reproducible.
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⚠️ Not financial advice. This is for educational purposes only. Always do your own research before investing.
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