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Antifragile Dynamic Portfolios of ETF’s

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There is Alpha in Protecting the Downside

Long Term Returns of DataCore Indices Are Much More Robust
than Typical Market Indices

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Medium Term Returns of DataCore Indices Are Still Surprisingly Stable

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Even Short Term Returns of DataCore Indices Tend to be Positive

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AIDA's Alpha is high...

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... And Max DrawDown Risk is Significantly Lower 

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Performance Analysis

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DF1

What are DataSave™ and DataGrow™ Indices?

DataSave™: relatively safe, short term

  • Description: an equity-boosted alternative to a Money Market account

  • Investment horizon: short to medium term

  • Maximum Drawdown: less than 4% in back-testing over 20 years

  • Rebalances: monthly

  • Composition: 40 best performing ETFs are selected based on proprietary risk-reward profile.

  • Constituent Weights: risk-based. A limit on total equity ETF risk. A floor for cash-like ETFs’ risk.

DataGrow™: safer than the market, long term

  • Description: A safer alternative to a long-term investment in broad equities market (e.g., such as S&P 500)

  • Investment horizon: medium to long term

  • Maximum Drawdown: comparable to broad market in normal times; a fraction of the market in severe crisis

  • Rebalances: monthly

  • Composition: borrows constituents from DataSave but reweighs them

  • Constituent weights: more weight is allocated to equity constituents. May result in zero weights for cash-like ETFs.

DataSave™ and DataGrow™ Indices reflect two particular passive investment portfolio construction strategies powered by proprietary Dominant Factor™ Index methodology. For each strategy, the objective is to produce, within its class and investment horizon, competitive returns and to provide superior downside risk protection when markets are in distress.

DataSave™ and DataGrow™ are built out of the the same universe of pre-selected liquid US Exchange-traded ETFs.

Introducing

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AIDA stands for AI-Driven Antifragile strategy: it has all the smart gamma properties of DataSave and DataGrow but also exhibits strong alpha

AIDA: safer than the market, long term + alpha

  • Description: A safer alternative to a long-term investment in broad equities market and many hedge funds

  • Investment horizon: long term 

  • Maximum Drawdown: comparable to broad market in normal times; significantly lower tha market in severe crisis, and recovering faster 

  • Rebalances: monthly

  • Composition: borrows constituents from DataSave™ and DataGrow™ but reweighs them

  • Constituent weights: more weight is allocated to equity constituents. May result in zero weights for cash-like ETFs.

AIDA vs. DataGrow™: more risk, with significant alpha

  • While DataGrow’s selection favors funds with a low SVaR (Stress Value-at-Risk, i.e. the worst risk stemming from one of the "dominant factors"), even if the performance is not so great, AIDA selection is principally based on the LTA (the Long-term Alpha (LTA) is the average long-term performance of the fund, as extrapolated over 20+ years history, using the various "dominant factors")

  • The consequence of this selection is that AIDA favors funds that offer good alpha expectations

DF2

What are Dominant Factor™ Indices?

DataCore utilizes its next generation Dominant Factor™ methodology to automate construction of investible asset portfolios that afford competitive returns with lower downside risk in difficult markets.

Dominant Factor™ Indices are quantitative dynamic portfolios of ETFs selected for their Antifragility.

  • Dominant Factor™ Indices characteristics:

  • Constituents are picked out of pre-selected universe of liquid exchange-traded ETFs

  • Altogether approx. 360 ETFs, all traded on US exchanges in USD:

    • 23 of them are short duration fixed income (cash equiv.) 

    • All others trade equities worldwide

    • 20+ of them are either leveraged or shorting the market

  • Monthly index constituent updates. The pre-selected universe itself is updated annually

  • Each potential constituent risk-reward profile is analyzed based on Dominant Factor™ proprietary methodology

  • Index constituent selection and its weight determination are data-driven and automated

  • No leverage is used, the sum of all weights is 100%, all weights are nonnegative

  • Superior long-term risk-adjusted performance with lower downside risk

  • Resulting index is not only smart beta, but is smart gamma as well: it avoids bad convexity

DataCore utilizes its next generation Dominant Factor™ methodology to automate construction of  investible asset portfolios that afford competitive returns with lower downside risk in difficult markets.

Dominant Factor™ Indices are quantitative dynamic portfolios of ETFs selected for their Antifragility.

Dominant Factor™ Methodology

Dominant Factor™ methodology screens each candidate asset against a set of about 500 DataCore proprietary factors that are based on market observables (these risk factors have been carefully pre-selected, using Artificial Intelligence techniques). It tests for statistically significant non-linear models linking asset total returns and those of the factors within the fitting window (typically, the last 3 years) and retains for the asset  only those asset-specific factors that show significant explanatory power. It then constructs asset-specific risk-reward profile that incorporates asset’s projected losses in the event of severe crises based on established links and observed long-term behavior of the proprietary factors retained for the asset. Asset selection decision is then based on its risk-reward profile and risk tolerance parameters set for a particular index.

As a result, a sector (industry or geographic) is considered attractive when capital starts flowing into the sector, producing a rally in its components. But, unlike common methods (such as Black-Litterman), which tend to be fooled by speculative bubbles and suffer when these burst out, DataCore portfolios flee away from a sector when the rally becomes nervous, announcing instability and a potential severe downturn. In a way, by its nonlinear approach, the Dominant Factor methodology detects the behavioral effects of traders’ sentiment on prices and is able to interpret them, so as to avoid catastrophes. Instead of following the crowd, the system reads its sentiment from its impact on price behavior and acts accordingly. This results in a portfolio that is cautious during the rallies that are fragile, and thus cuts down losses by a significant amount in the downturns. Clearly, the Beta adjusts appropriately according to the market conditions, which is for us the very meaning of "Smart Beta" and "Smart Gamma".

List of Asset Managers Tracking DataCore Indices

Managed by Vantage Consulting Group since November 2017.

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