Many investors are searching for the “ideal” funds. These must not only fit specific investor requirements they also have to provide: Significant AuM (> 100 Mio.), high liquidity, best-in-class performance - ideally outperforming the market, low costs, experienced investment managers and last-but-not-least long and successful track records of minimum 3-5 years. This approach of searching for the “holy grail” has been the standard paradigm for decades…and still is! Unfortunately, the reality shows that most investment managers are not capable to outperform the market over a longer period, as a recent study from S&P Dow Jones Indices confirms*. We suggest to consider a new investment paradigm, and show how this can work in practice…

1. “Invest in Technology and not in Mileage!”
Why investors should review traditional investment paradigms…
Zurich, August 2019

2. Disclaimer
This document is copyrighted, and its content may not be reproduced without the permission of the authors.
This material has been prepared solely for informational purposes only and it is not intended to be and should
not be considered as an offer, or a solicitation of an offer, or an invitation or a personal recommendation to buy
or sell any stocks and bonds, or any other fund, security, or financial instrument, or to participate in any
investment strategy, directly or indirectly. It is intended for use in research only by those recipients to whom it
was made available by the authors of the document.
All information for an investment strategy prior to its launch date is back-tested, based on the methodology that
was in effect on the launch date. Back-tested performance, which is hypothetical and not actual performance, is
subject to inherent limitations because it reflects application of a methodology and selection of constituents in
hindsight. No theoretical approach can take into account all of the factors in the markets in general and the
impact of decisions that might have been made during the actual operation of an investment strategy. Actual
returns may differ from, and be lower than, back-tested returns.
© OpenMetrics Solutions LLC, Zurich (2019) 2

3. “We cannot solve our problems with the same thinking we
used when we created them.”
Albert Einstein
3

4. Introduction
• Many investors are searching for the “ideal” funds. These must not only fit specific investor
requirements they also have to provide: Significant AuM (> 100 Mio.), high liquidity, best-in-class
performance - ideally outperforming the market, low costs, experienced investment managers and last-
but-not-least long and successful track records of minimum 3-5 years.
• This approach of searching for the “holy grail” has been the standard paradigm for decades…and still is!
• Unfortunately, the reality shows that most investment managers are not capable to outperform the
market over a longer period, as a recent study from S&P Dow Jones Indices confirms*.
• We suggest to consider a new investment paradigm, and show how this can work in practice…
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 4
* https://www.cnbc.com/2019/03/15/active-fund-managers-trail-the-sp-500-for-the-ninth-year-in-a-row-in-triumph-for-indexing.html

5. A New Paradigm
The combination of cost-efficient index exposure with advanced risk management
overlays.
This protects against severe losses during negative index phases and tracks the positive
index phases as accurate as possible.
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 5

6. Prerequisites
1. Solid Mathematical Models: We know, that seems to be a bold claim. However, don’t have to refer to
our own experience. Just read “The Money Formula” from Paul Wilmott and David Orrel. An excellent
book, which outlines in a very entertaining way that many investment solutions in the market are built
on flawed models.
2. Correct Simulations: Unfortunately, we can observe that many backtests are not done correctly, which
leads to phenomenal results in the simulation but collapsing in real trading. Therefore, it is of utmost
importance to have a solid backtesting framework, which generates realistic results, which hold the
test of reality.
3. Benchmarking: As stated in the introduction, many active investment solutions do not beat the
market…so focus on cost efficient and liquid index products.
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 6

7. Solid Mathematical Models
© OpenMetrics Solutions LLC, Zurich (2019) 7
T. Setz, STABLE PORTFOLIO DESIGN USING BAYESIAN CHANGE POINT
MODELS AND GEOMETRIC SHAPE FACTORS, Dissertation ETH Zurich No.:
24754, (2018).
https://doi.org/10.3929/ethz-b-000244960
• Full Transparency; Published 2018 at ETH Zurich:
• OpenMetrics technology is based on latest research developed throughout almost a
decade at ETH Zurich.
• All presented models and applications are based on this research and thus fully
transparent to the users.
In contrast to other common approaches, the BCP (Bayesian Change Point) model can
be used without any adaptations (methodology or parameters) on all stochastic data.

8. Correct Simulations
© OpenMetrics Solutions LLC, Zurich (2019) 8
1. Exposition
• Regions, Sectors, etc.
2. Strategic Weighting
• Based on Benchmark or internal targets
3. Constraints
• Strategic bandwidths or other
requirements
4. Risk-Averseness
• Maximal market exposure. If required with
leverage
5. Hedging Method
• Pure hedge, money market or other
alternative universe
6. Frequency
• Monthly, weekly or daily
1. Rating and ranking of assets
2. Strategic weights
3. Hedging overlay
4. Inclusion of additional
requirements
1. Own order execution
• Via report or web interface (Saas)
2. External order execution
• For smaller mandates < 20 Mio AMC
(Actively ManagedCertificate)
• For larger mandates > 20 Mio UCITS
fund with specialized partner
Both solutions provide:
• Listed ISIN & full transparency
• Daily prices/ liquidity
• Open for other investors
Definition Calculation Implementation

9. Benchmarking
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 9

10. USE CASES
• MSCI AC World Index
• Swiss Performance Index
• Bond Index Portfolio
• GSCI Commodity Index
10

11. Simulation Results
• All simulation results have been generated based on the OpenMetrics framework and avoid the typical
pitfalls when performing back-tests. The results are based on many years of practical experience in
applying the underlying technology to investable products.
• All returns are gross returns, as implementation and operating costs depend on AuM, selected
instruments and investment vehicle. From our experience, these costs are typically in the range of 0.5-
2.0%.
All simulation results are intended to demonstrate the application of published mathematical risk
management models and do not represent any type of investment advice. Please read the disclaimer at
the beginning of the presentation!
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 11

12. © OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 12
Simulation Results for
MSCIAC World Index
Regions
Dynamic Hedge
(green line)
StrategicWeights:
as benchmark
Other Restrictions
none
Risk-Averseness
market exposure between
0% and 100%
Hedging-Method
money market
Frequency
weekly

13. © OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 13
Simulation Results for
Swiss Performance
Index
Sectors
Dynamic Hedge
(green line)
StrategicWeights:
equally weighted
Other Restrictions
none
Risk-Averseness
market exposure between
0% and 100%
Hedging-Method
zero cash
Frequency
weekly

14. © OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 14
Simulation Results for
Bond Index Portfolio
Dynamic Hedge
(green line)
StrategicWeights:
equally weighted
Other Restrictions
none
Risk-Averseness
market exposure between
0% and 100%
Hedging-Method
money market
Frequency
weekly

15. © OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 15
Simulation Results of
GSCICommodity
Index
Sectors
Dynamic Hedge
(green line)
StrategicWeights:
equally weighted
Other Restrictions
none
Risk-Averseness
market exposure between
0% and 100%
Hedging-Method
money market
Frequency
weekly

16. Conclusion
• In terms of expectation management, we must stress the fact that active management is not necessarily
about trying to generate higher returns than the benchmark, as in order to achieve an outperformance
the investment manager typically must assume higher risks.
• Instead, active management from a risk-controlled perspective has the objective to reduce volatility,
minimize losses and capture as much upside as possible during positive trends. Given the stochastic
nature of financial markets, this comes at the expense of generating lower returns than the benchmark –
except a market crisis occurs.
• In contrast to simplistic approaches (e.g. passive hedge) or more complex approaches (e.g. volatility) the
Bayesian Change Point model provides higher returns and better risk protection with comparable
operational costs.
© OpenMetrics Solutions LLC, Zurich (2019) - CONFIDENTIAL 16

17. Contact
OpenMetrics Solutions LLC
Dufoursstrasse 47
CH-8008 Zurich
+41 44 552 4909
contact@openmetrics.ch
www.openmetrics.ch
OpenMetrics Solutions LLC is an approved ETH Zurich Spin-off
OpenMetrics© is a registered trademark at IPI (Swiss Federal Institute of Intellectual Property), Berne
© OpenMetrics Solutions LLC, Zurich (2019) 17
swiss made software is the nationally and
internationally recognized symbol for
Swiss quality in software development.