Aventine Asset Management Inc.

Strategy Overview

The performance information relating to this Strategy represents back-tested results as of October 31, 2017.

The Aventine Global Tactical ETF Strategy follows a systematic investment approach based on proprietary machine learning algorithms which independently process and analyze large amounts of security-related information to produce an optimized investment portfolio based on the MSCI All Countries World ex-US Index (“ACWX”) constituents.  The computational nature of the Strategy is intended to eliminate the behavioural biases of discretionary investors as well as overcome other flaws in qualitative analysis generally.

The primary goal of this strategy is to outperform the ACWX on a total return basis with a similar or better volatility profile.

Investment Objectives

  • Outperform the ACWX Index on a total return basis.
  • Provide a superior Sharpe Ratio vs. the ACWX
  • Deliver moderate volatility.


The Aventine Global Tactical ETF Strategy is an algorithmic investment strategy that utilizes statistics and machine learning principles to identify short to intermediate term trading opportunities. It will hold a very focused portfolio of global ETFs that may not meet general guidelines for diversification and may experience higher than average turnover.  The Strategy is intended to comprise a modest weight in a well balanced portfolio, or be used in higher concentrations by sophisticated investors seeking more aggressive outperformance of global equities.

Investment Process

Portfolio Design

The Strategy follows a systematic investment approach that machine learning algorithms to independently process and analyze large amounts of security-related information to produce an optimized investment portfolio.  An explanation of the model’s design principles:

  • Focus on security selection within a closed investment universe (the ACWX).
  • Use machine learning to evaluate companies across a set of common factors.
  • Identify and evaluate factors with predictive performance ability relative to the investment universe.
  • Maintain a flexible analytical structure, incorporate new data or sources as their suitability is proven out.

Capital Allocation and Security Selection

The model is optimized to new data at the open on the first trading of each week, meaning that the portfolio is fully evaluated and re-balanced on a weekly basis.

  • Securities are held for a minimum of one week.
  • A Security may be held if it continues to be recommended by the model in consecutive weeks.
  • The portfolio is optimized to invest in between 4 and 8 securities.
  • The portfolio is always fully invested (the portfolio will have no cash component).

Risk Management

The investment strategy focuses on outperforming a benchmark. To achieve this, it attempts to outperform the average returns of an investment universe that represents an index, i.e. the 43 country ETFs that comprise the ACWX . The investment universe is restricted to the country ETFs in this benchmark as it may be reconstituted from time to time and subject to specific liquidity constraints.

The investment philosophy is simple, and the strategy’s risk profile is anticipated to be similar to that of an index fund. However, risk management is restricted by this; the strategy offers no special protection against large market drawdowns, though it is designed to outperform them (i.e. draw down less) by rapidly optimizing into the most defensively tilted securities of the universe.

The Strategy does not currently utilize any of the following investment techniques in the portfolio, however the strategy is continually being improved and any or all of the following may be used at some point in the future if it increases the Strategy’s ability to achieve its objectives:

  • Leverage or margin.
  • Derivative securities of any form.
  • Equity market hedges.
  • Foreign exchange hedges.
  • Security stop loss orders.

Strategy Performance

The Aventine Global Tactical ETF Wealth Strategy is managed by Andrew Shortreid and James Telfser with technology consultancy AH Frankl and Sons Inc. providing services in respect of machine learning and other advanced mathematical and computational disciplines involving big data analysis. Since inception the Strategy has consistently outperformed both its active and passive comparables while realizing low correlation and beta relative to its global equity benchmark, the MSCI All Countries World ex-US Index.   The Global Tactical Strategy targets annualized returns of 10% per year or better with no peak-to-trough losses greater than 15%.

The presented information primarily represent back-tested results as of October 31, 2017.

Growth of $1,000,000

Graph showing monetary figures

Performance Highlights

  • Annualized ROI of 11.0% Since Inception
  • Annualized Alpha of 6.8% vs. Benchmark
  • Annualized Volatility: 14.6%
  • Sharpe Ratio: 0.75
  • Beta versus Benchmark: 0.59
  • Worst peak to trough loss of -11.1%