Heavy Tail Investing Strategy with QPT | QPX
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What’s Wrong with MPT?
Since 1952, Modern Portfolio Theory (MPT) has been used to analyze returns and assess risk in financial markets. Because of limited computer capabilities at the time, MPT was designed using a normal distribution model. While it works well in normal markets, MPT doesn’t account for less frequent but significant market moves and fails to measure risk very well.
Measuring Risk More Precisely Is a Way to Build Better Portfolios
AdvisorShares has two ETFs utilizing an investment strategy based on Q Methodology™ that seeks to measure the risk outliers that MPT ignores:  
QPT   AdvisorShares Q Portfolio Blended Allocation ETF
  Q Methodology in Action
When using normal distribution models, if a sample is far from the average, the results can be unrealistic and highly skewed.
 EVENT – Market Volatility | Feb. 6, 2018 | DJIA fell and retraced 7.5% over three days
Modern Portfolio Theory: Once every 4,409 years
Q Methodology: Once every 15 months
Given the extreme volatility in 2008 and 2020, MPT’s calculation sure doesn’t feel right.
 EVENT – Covid-19 Crisis | March 2020 | The S&P 500 Index fell over 30% in just 22 days
Modern Portfolio Theory: Once every 33,956,653 years
Q Methodology: Once every 37 years
If MPT was a good measure of risk, then we would not have to worry about another COVID-type selloff for another 34 million years.
Learn how QPT and QPX account for important market outliers with ThinkBetter's heavy tail investment analysis
(click and scroll down) 
Ron Piccinni, Ph.D.
Founder and President
Portfolio Manager of QPT and QPX
Q Methodology is a modern quantitative approach from ThinkBetter that assesses risk/reward and optimizes investment portfolios. The methodology is based on heavy-tail distribution mathematical analysis and focuses on estimating the downside of a portfolio (expected drawdown) under extreme but plausible stress (tail risk).
Using high performance computing power, Q Methodology generates tens of thousands of portfolio simulations to identify the asset allocation offering the greatest return for a given level of risk. Simply put, we believe Q Methodology is better math for better investment management.
Tail risk is the possibility of an investment’s return moving significantly beyond expectations (i.e., more than three standard deviations from its mean).
Expected drawdown is the maximum peak to trough capital loss over a full market cycle (as measured from January 2006 to March 2020).
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Before investing you should carefully consider the Fund’s investment objectives, risks, charges and expenses. This and other information is in the prospectus, a copy of which may be obtained by visiting the Fund’s website at www.AdvisorShares.com. Please read the prospectus carefully before you invest. Foreside Fund Services, LLC, distributor.
nvesting involves risk including possible loss of principal. There is no guarantee the Advisors investment strategy will be successful. When models and data prove to be incorrect or incomplete, any decisions made in reliance thereon expose the Fund to potential risks. In addition, the use of predictive models has inherent risk. Because predictive models are usually constructed based on historical data supplied by third parties, the success of relying on such models may depend heavily on the accuracy and reliability of the supplied historical data. The Fund’s particular allocations may have a significant effect on the Fund’s performance. Fixed income investments are subject to interest rate risk; their value will normally decline as interest rates rise. Fixed income investments are also subject to credit risk, the risk that the issuer of a bond will fail to pay interest and principal in a timely manner, or that negative perceptions of the issuer’s ability to make such payments will cause the price of that bond to decline. For a list of the asset class specific risks please see the prospectus.
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