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Vier Impulse : Eine Location, vier Manager, Ihre Zeit effektiv genutzt Speaker: Maxime Botti

Q3 2018

RAM Active Investments

The Background

2 RAM Active Investments | For Professional Investors Only

Company profile


Key Facts:

Founding

- Established in 2007 by Thomas de Saint-Seine, Maxime Botti and Emmanuel Hauptmann

Ownership

- Majority owned by MedioBanca since 2018

Staff

- RAM currently employs 40 people

AUM

- AUM as at end of December 2017 stood at USD 5.0bn

Governance

- Regulated by FINMA, CSSF and the SEC

Luxembourg

Zurich

Geneva (Headquarters)

-

1'000

2'000

3'000

4'000

5'000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

The Growth of RAM’s Business (U.S. $mn)

Source: RAM Active Investments . As at 29th December 2017

3 RAM Active Investments SA | For Professional Investors Only

Who we are


Company

We are an active specialist and alternative asset manager with the mission to deliver high risk-adjusted returns, diversification benefits, and liquid

products and solutions to our investors.

Belief

A disciplined and active management style can deliver compelling value to investors. Rigorous in-house research strengthens objectivity of the alpha

sourcing. We believe inefficiencies will continue to persist in global markets, while the means of extracting alpha will continue to vary by approach. As

investors, we strive to extend the possibilities in both the systematic and discretionary disciplines.

Business Lines

Over the years, we have developed two distinct businesses, managing systematic long-only and liquid alternative equity strategies and discretionary

fixed income strategies.

Our History

2005 2004 2014 2013 2001 2016 2017 2008 2007 2009 2011

Thomas de

Saint-Seine

started asset

management

business in REYL

Maxime Botti

joined to

develop REYL’s

AM business

Implemented

Systematic

methodology

within the

European and

North American

Equities Equities

Foundation of

RAM Active

Investments

Emmanuel

Hauptmann

joined

Launch of RAM

Long/Short

European

Equities and

RAM and

Long/Short

Emerging

Markets

Equities Funds

Regulated by

the Swiss

Financial

Market

Supervisory

Authority

Opened

Luxembourg

office, regulated

by the CSSF

Launch of the

RAM Emerging

Markets CORE

Equities fund for

a large-cap

universe

Established

RAM (Lux)

Tactical Funds

Range

Launch of the

RAM Emerging

Markets

Equities Fund

Launched

RAM Global

Shareholder

Yield Equities

Fund

Launch of a

Macro/CTA

strategy

Launched third

long/short beta

neutral RAM

Long/Short

Global Equities

Fund in UCITS

format

Launch of the RAM

Global Multi-Asset

Fund in UCITS

format

2018: MedioBanca *and RAM enter into a long-term strategic partnership

*MEDIOBANCA S.P.A – HEADQUARTERS Piazzetta Enrico Cuccia, 1 20121 Milan, Italy


Environmental, social and corporate governance

Corporate Responsibility

At RAM AI, we believe that corporate responsibility should permeate our business, from investment management to business administration.

Reducing the firm’s environmental footprint through a Corporate Green Policy

Environmental, Social and Corporate Governance issues are accounted for in investment decisions

Signatory of the UN Principles for Responsible Investment and dedicated to acting in the best, long-term interests of our clients

Learning, development and talent management to improve the expertise and capabilities of our employees


Promoting sustainable finance

“The Principles for Responsible Investment”

Incorporate ESG

(Environmental, Social and

Governance) issues into investment analysis and

decision-making processes

Incorporate ESG issues into our ownership

policies and practices

Promote acceptance and implementation of the principles

within the investment

industry

Work together to enhance our effectiveness in implementing

these principles

Report on activities and

progress towards implementing

these principles

Disclose ESG issues by the

entities in which we invest

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Committed to RAM’s long-term success

Equity Investment Team- Fund Managers

Thomas, Maxime and Emmanuel created and developed the investment philosophy and

processes which underpin RAM’s Systematic Equity Fund Range.

Thomas de Saint-Seine, CEO &Senior Equity Fund Manager

Thomas de Saint-Seine is the CEO, a Senior Equity Fund Manager and a Founding Partner of RAM Active Investments SA, which specialises in

managing the investment funds grouped under the RAM Systematic Funds and RAM Tactical Funds brands. He initiated and played a determining role in

the research that underpins the management of the RAM Systematic Equity Funds.

Thomas has 20 years of experience in fund management. From 1996 to 2001, he worked as an equity and bond Fund Manager at Crédit Agricole

Indosuez. In 2001, he joined the Reyl Group to fund and develop the fund management activity which has become totally independent since 2007 and is

known as RAM Active Investments. Thomas is a graduate of the University of Paris X (Econometrics, 1994) and the Master in Management of NEOMA

Business School (Finance, 1996).

Maxime Botti, Senior Equity Fund Manager

Maxime Botti is a Senior Equity Fund Manager and a Founding Partner of RAM Active Investments SA, which specialises in managing the investment

funds grouped under the RAM Systematic Funds and RAM Tactical Funds brands. He initiated and played a determining role in the research that

underpins the management of the RAM Systematic Equity Funds.

Before joining RAM in 2004, Maxime worked as a hedge fund manager at Equinoxe Partners and risk-arbitrage analyst at Barep Asset Management, a

subsidiary of Société Générale. Maxime is a graduate of the NEOMA Business School (Master in Management, Finance, 2002).

Emmanuel Hauptmann, Senior Equity Fund Manager

Emmanuel Hauptmann is a Senior Equity Fund Manager and a Founding Partner of RAM Active Investments SA, which specialises in managing the

investment funds grouped under the RAM Systematic Funds and RAM Tactical Funds brands. He played a determining role in the research that

underpins the management of the RAM Systematic Equity Funds.

He started his career in London as European Equity Derivatives quant strategist in Morgan Stanley’s Quantitative and Derivative Strategies team in 2002.

He was then Senior Quantitative Analyst as Director within Citigroup’s Alternative Execution team in London. He joined RAM Active Investments in 2007.

Emmanuel is a graduate of the Ecole Centrale Paris (MSc, Financial Engineering, 2002), the London School of Economics (MSc, Finance and

Economics, 2002) and the University of Paris I (BSc, Economics, 2001).


A Reinforced Team

Quantitative Trading and Research

Philippe Huber, Senior Quantitative Analyst

Philippe Huber works together with the portfolio managers on the development of systematic investment strategies.

Philippe started his career in 2006 as a quantitative analyst in Union Bancaire Privée in Geneva. In 2007, he launched a systematic U.S. equity

hedge fund as the partner of Company Cinetics SA; in 2009 he joined Galena Asset Management as a quantitative analyst, becoming a derivatives

oil trader. Philippe Huber joined RAM Active Investments in June 2016.

Philippe is an award-winning PhD in Econometrics and Statistics (University of Geneva, 2004), a graduate of the EPFL (MSc, Physics, 1998) and a

graduate of the University of Geneva (MSc, Econometrics and Statistics). He has a number of publications under his name in some of the best

academic journals in Statistics.

Nicolas Jamet, Senior Quantitative Analyst

Nicolas Jamet works closely with the Portfolio Managers to develop systematic investment strategies. The models are based on a broad range of

information including; company fundamentals, analyst estimates and market data.

Nicolas started his career at Société Générale Hong Kong in 2006, where he joined the equity proprietary trading desk to work on systematic

fundamental investment strategies, covering Asian markets. In 2011, he moved to Macquarie Group where he ran their global fundamental

quantitative book. In 2012, he co-founded Fundamental Dynamics, a hedge fund that was managing long/short global equity strategies for an

institutional mandate. He joined RAM in September 2016.

Nicolas graduated in 2005 as a Business Engineer in ICHEC, Brussels. In 2015, he became a CFA Charterholder.

Thierry Dessingy, Head of Quantitative Trading

Working closely with the portfolio managers, Thierry Dessingy operates the trading platform for the equity funds managed by RAM Active

Investments. He manages the implementation, maintenance and development of the platform.

A software engineer by training, Thierry began his professional career in 2000 at Annuncio Software, in the United States. He then returned to

Geneva to work at Geneprot as a bioinformatician until 2003. After receiving his MBA, he chose to dedicate himself to finance. In 2005, he joined

Avendis Group where he co-managed a SIV fund (structured investment vehicle) with assets of USD 2 billion. He joined RAM Active Investments in

2008. Thierry holds a Master in Communication Systems from EPFL (Ecole Polytechnique Fédérale de Lausanne, 2000) and an MBA from the

Université de Lausanne (HEC, 2004).

Valentin Betrix, Senior Quantitative Analyst, Trader Valentin Betrix works as a quantitative analyst and trader in the RAM Systematic Equity Funds Management team. He participates in dealing in

global markets and developing the trading platform, with a strong focus on trading analytics and execution enhancement. His research covers

optimizing rebalancing methodology and developing systematic investment strategies.

Valentin Betrix started his career as a quantitative analyst at BPCE Group, then as a corporate finance analyst at BNP Paribas in London, in 2006.

In 2007, he joined Alpstar Capital as a cross-asset quantitative analyst and trader. Valentin Betrix joined RAM Active Investments in August 2013.

Valentin Betrix graduated in Engineering from Ecole des Mines de Saint-Etienne and then qualified as an Actuary from ISFA in Lyon.

8 RAM Active Investments | For Professional Investors Only

Industry recognition

Award-Winning Specialist Fund Manager

RAM L/S European Equities Fund RAM Emerging Markets Equities Fund

RAM L/S Emerging Markets Equities Fund RAM European Equities Fund


Instit share class net of fee Summary Investment Performance-

Selected Strategies (Data as of August 2018) 2018 3 Yr Ann. 5 Yr. Ann. Perf. Ann.

Since Launch

Vol. Ann.

Since Launch Inception Date

Systematic

Long Only

RAM Emerging Markets Equities ($)

MSCI Emerging Markets TRN ($)

-7.28%

-7.19%

8.54%

11.27%

4.50%

5.01%

8.86%

4.97%

15.6%

17.2% 31 Jul 2009

RAM European Equities (€)

MSCI Europe TRN (€)

2.08%

0.31%

8.14%

4.49%

11.96%

7.63%

11.11%

6.13%

14.3%

13.8%

30 Sep 2004

RAM North American Equities ($)

MSCI North America TRN ($)

4.37%

9.04%

13.86%

14.29%

11.94%

13.07%

9.1%

8.6%

15.2%

13.9%

30 Apr 2005

Global Shareholder Yield Equities ($)

MSCI World High Dividend Yield TRN ($)

0.39%

0.29%

10.90%

9.50%

6.79%

4.76%

10.4%

10.8%

2 May 2014

Long / Short

RAM Long/Short European Equities (€) -1.53% 3.67% 6.87% 6.80% 6.1% 31 March 2009

RAM Long/Short Emerging Markets Eq. ($) -0.73% 0.19% 1.70% 2.63% 3.8% 15 Dec 2011

RAM Long/Short Global Equities ($) -2.63% 1.08% 3.6% 16 Dec 2016

Tactical

RAM Convertible Europe (€)

Exane Convertible Europe TR (€)

-2.89%

0.93%

1.07%

2.41%

2.00%

3.03%

5.6%

6.1%

25 Jun 2014

RAM Global Bond Total Return B ($) -0.32% 2.59% 2.79% 4.36% 2.3% 31 Mar 2009

RAM Asia Bond Total Return PI ($)

JP Morgan Asia Credit TR ($)

-2.52%

-1.29%

4.17%

3.77%

4.44%

4.99%

4.29%

4.67%

2.8%

3.0%

14 Jun 2013

Past performance is not a guide to current or future results. The performance data do not take into account fees and expenses charged on issuance and redemption of the shares nor any taxes that may be levied. Changes in exchange rates may cause the NAV per share in the investor's base currency to go up or down

(1) Performance data shown is for institutional share classes net of management and performance fees (2) Source: RAM Active Investments

RAM Long/Short Equities Approaches

The Opportunity & Historic Performance


High alpha generation

Offering Long/Short Equity Funds

RAM Emerging Markets Equities Fund RAM UCITS Long/Short Emerging Markets

Equities Fund

July 2009

RAM European Equities Fund RAM Long/Short European Equities

Strategy

September 2004 March 2009

December 2011

Funds vs MSCI Europe TRN€ 5 Years

Alpha Beta Sharpe Ratio

RAM European Equities Fund 5.24% 0.74 0.95

RAM Long/Short European Equities Strategy 6.50% 0.08 0.97

Funds vs MSCI EM TRN$ 5 Years

Alpha Beta Sharpe Ratio

RAM Emerging Markets Equities Fund 0.21% 0.80 0.30

RAM Long/Short Emerging Markets Equities Fund 1.04% 0.01 0.27

Note: RAM European Equities Fund performance net of fee (Class I-EUR , 1.0% of MF+15% of PF) / RAM Emerging Markets Equities Fund performance net of fee (Class Ip—USD , 1.0% of

MF + 15% of PF) / RAM Long/Short European Equities Strategy performance net of fee (RAM L/S European Equities Fund Class-I from December 2011 (1.5% of MF + 20% of PF) / RAM

Long/Short Emerging Markets Equities Fund Class I-USD (performance net of 1.5% of MF + 20% of PF)

Source: RAM Active Investments, MSCI indices as of 31.08.2018

Past performance is not a guide to future performance

L/S FUND CHARACTERISTICS & OBJECTIVES

Average annual returns around 6-8%

Volatility budget of 4-6%

L/S FUND CHARACTERISTICS & OBJECTIVES

Average annual returns above 8%

Volatility budget of 6-10%

Launch of the RAM Long/Short Global Equities Fund in December 2016

L/S FUND CHARACTERISTICS & OBJECTIVES • Average annual returns above 8%

• Volatility budget of 6-8%


Our beliefs

RAM Long/Short Strategies

PHILOSOPHY:

• Capture persistent inefficiencies across European, Emerging and Global Equity Markets

• Invest using fundamentally-driven stock picking strategies, applied systematically

• A disciplined long-short investment approach aimed at generating alpha on the both long and short side, neutralized

with a book of indices

• A fixed allocation of Value, Momentum and Defensive strategies designed to avoid market timing and risk/style arbitrage

• A proprietary alpha engine based on uncorrelated alpha sources in terms of style and market capitalization segments

• Benefits from the potential of an all-cap approach with strong focus on market impact and liquidity risk

• Since 2005, we have built a quantitative investment methodology applied to the RAM European Equities Fund, capable

of delivering consistent alpha in the medium and long term.

• Since 2009 we have applied this methodology to capture opportunities both on the long and the short side, hedging our

market exposure.

• In 2011 we decided to adapt our Long/Short European Equities investment strategy into a transparent and liquid UCITS

structure under the new name of the RAM Long/Short European Equities Fund.

• In 2016 we leveraged this investment philosophy to create our Long/Short Global Equities strategy. The strategy follows

the same investment philosophy, applied to global developed equities.

FOUNDATION OF OUR PHILOSOPHY


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Performance

RAM Long/Short European Equities

The RAM Long/Short European Equities strategy has a diversified long exposure, hedged with a basket of indices and

short stocks.

Net Performance

Strategy inception:

03.2009

AUM

EUR 1046Mn

Note: Whether real or simulated, past

performance is not necessarily a reliable

guide to future performance

Note: RAM Long/Short European Equities Strategy shows performance net of fee of the RAM L/S European Equities Fund Class-I from December 2011 (1.5% of management

fee+20% of performance fee) and of the RAM Absolute Return Fund prior to December 2011. The RAM Absolute Return Fund followed the same exact investment strategy within a

Cayman vehicle (1.75% of Management fee+20% of performance fee) before it was converted to a UCITS.



Return figures since Inception (monthly data)

2018

YTD 2017 2016 2015 2014 2013 2012 2011 2010

Annualised

Return

Annualized

Volatility

RAM Long/Short European Equities Strat. 1.53% 8.76% -4.00% 14.48% 7.92% 13.26% 5.37% -0.81% 16.56% 8.37% 6.29%

Last 3 Years Statistics (weekly data)

Alpha Beta Sharpe

Ratio

Max

Drawdown

Return, %

Max Drawdown

Period

RAM Long/Short European Equities Strat. 4.03% 0.00% 0.53 -10.9 21.12.15-

22.04.16


in USD, 11.2011 - 08.2018

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Performance

RAM Long/Short Emerging Markets Equities

The RAM Long/Short Emerging Markets Equities strategy has a diversified long exposure, hedged with a basket of indices

and short stocks.

Net Performance

▬ LONG/SHORT EMERGING MARKETS EQUITIES FUND (CLASS I-USD, NET OF FEE)

Strategy inception:

12.2011

AUM

USD 131Mn

Note: Whether real or simulated, past

performance is not necessarily a reliable

guide to future performance

Note: RAM Long/Short Emerging Markets Equities Fund Class I-USD (performance net of 1.5% of MF + 20% of PF)



2018 YTD 2017 2016 2015 2014 2013 Annualised

Return

RAM Long/Short Emerging Markets Equities Fund I$ -0.73% 4.29% -3.68% 2.24% 3.02% 6.66% 2.63%

(weekly data since fund launch) Annualized

Volatility Alpha Beta

Sharpe

Ratio

Max Drawdown

Return, %

RAM Long/Short Emerging Markets Equities Fund I$ 3.8% 1.91% 0.01% 0.52 -4.97%


Since December 2016

Realised Track Record

Performance Statistics vs Peers since incpetion, monthly data in USD

in USD, 12.2016 - 08.2018

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5th to 25th Percentile 25th to Median Median to 75th Percentile 75th to 95th Percentile

RAM Long/Short Global Equities (Class PI) HFRX EH: Equity Market Neutral Index

RAM Long/Short Equities Approach

Investment Process & Portfolio Construction


Extracting information from data sources

to capture inefficiences

Agnostic Capturing of Inefficiences

Capture

Information

Analyse

Analysing the inefficiencies

which can be captured

according to our three styles

Feedback Loop Essential part of our process;

feedback and analysis of live

strategy performance

Income

Quality

Growth

Momentum

Low Risk

Positioning

Liquidity

Value

Sentiment

Gain insight Strategy = Factor

Combination

Alpha-Capture Factor Standalone factors capturing alpha from the

inefficiencies

Strategies

3 2

1

A. Pure Profile strategies

B. Best-of-Breed strategies


Consistent alpha generation in all markets

Repeatable Outperformance

• At RAM we have built a systematic engine which sits at the very heart of our investment philosophy, taking an optimal blend of Value,

GARP/Momentum and Defensive sub-strategies

• A proprietary market impact model including volatility and liquidity metrics

• We apply our systematic approach to equity investing; not seeking to time the market, in a highly-disciplined approach across regions

Expansion

Slowdown

Contraction

Recovery

GARP/ Momentum

Typical best performing

strategy

In an environment of rising

volatility, our DEFENSIVE

strategy helps stabilize

portfolio returns

Naturally, following the initial

phase of the downturn, the

VALUE, then GARP sub-

strategies identify larger

stocks, turning increasingly

defensive

In the second phase, the

MOMENTUM sub-strategy

takes over, catching new

positive market trends

The first phase of the

recovery would see a

strong contribution of the

VALUE sub-strategy -

benefiting from a return to

quality and small/mid cap

effect


A blend of styles

The Strategies – Long Book

• A systematic bottom-up stock picking strategy

• Extensive research in the emerging and European markets space has led us to identify large

market inefficiencies that we aim to capture through three distinct strategies:

Value names with strong free cash

flow generation, superior

profitability relative to peers and a

high quality balance sheet.

Playing medium-term convergence

of each selected name to its

sector’s valuation.

Companies with a low risk profile

and high dividend and earnings

yield, with a bias to large-cap non-

cyclical stocks.

Low-volatility income selection

stabilizing the returns of the long

book.

High growth companies with

sustained earnings and price

momentum with a value bias.

Playing the continuation of

their divergence on the upside

from the universe.

Growth at Reasonable

Price / Momentum

Defensive /

Low-Vol Value


Why Now?

Deep Learning Evolution

Hardware:

▲ processing power – ▼cost with new technology like GPU, TPU, TPU2

Software:

Largest tech companies (Google, Amazon, Facebook) contribute to open-source

deep learning libraries giving us access to the highest evolutive, robust

Machine Learning software

Data:

▲ number of Data brings need efficient way of combining factors across

different strategies

How the new strategy integration improves the risk return profile of the fund?

Alphawith ML integratiion> Alphawithout

Riskwith ML integratiion ≤ Riskwithout

Increase Diversification

Decrease turnover

Reduce trading costs


Best Standards Selection

Deep Learning

Helps to capture stocks that may not be

a pure Value, low-risk, Growth

Momentum profile, but are highly alpha

generative being great by all standards

Deep Learning


Sub-strategies implemented

A blend of styles

The Strategies – Short Book

The short book consists of a short indices basket to neutralize the portfolio’s beta, as well as short stock

positions to enhance the overall alpha.

Short

Momentum

Short

Value

Short

Quality

Single Names Strategies

Index

Basket

Shorting major country &

regional indices to neutralize

Beta exposure

Short exposure in

Indices

Short Value Cash Flow (used in EU, EM, Global)

Short Value Cycle (used in EM, Global)

Short DASP (used in EU, EM, Global)

Short EPS Negative

Convexity (used in Global)

Short Overstated

(used in EM, Global)

Short Overinvestment (used in EU)

Names with negative fundamentals

and price trends

Levered companies destroying a

high level of operating cash-flows,

relative to their sectors

Companies having low quality

of earnings or book


To identify and capture inefficiencies

Focus on research

All our research have been inspired on a number of academic papers having identified persistent market inefficiencies:

Liquidity

R. Almgren, C.Thum, E. Hauptmann, and H. Li, 2005, Direct Estimation of Equity Market

Impact

Written in collaboration with Emmanuel Hauptmann, Fund Manager of

the RAM Systematic Equity Fund Range, this paper is illustrative of

our ongoing work to control costs and reduce the liquidity risk of our

holdings.

Value

E. F. Fama, K. R. French, 2011, Size, Value, and Momentum in International Stock Returns

Foundation paper on the Value and Momentum inefficiency blends,

concept we apply at RAM across a number of our systematic

investment philosophies.

J. Boudoukh, R. Michaely, M. Richardson, M. R. Roberts, 2003, On The Importance of

Measuring Payout Yield: Implications for Empirical Asset Pricing

Strong evidence of the Shareholder Yield inefficiency captured

through our global Shareholder Yield approach, differentiating from

traditional income funds.

Momentum

N. Jegadeesh, J. Kim, S. D. Krische, C. M. C. Lee, 2002, Analyzing the analysts: When do

recommendations add value?

A pivotal research that analyze sell-side analysts recommendations

and how the change in the consensus is a robust return predictor,

inspiration for some of our Analyst sentiment momentum factors.

Quality

D. Hirshleifer, K. Hou, S. Hong Teoh , 2010, The Accrual Anomaly: Risk Or Mispricing?

The paper illustrates the Accruals anomaly which we exploit in some of

our Short selection strategies.

M. D. Beneish, D. C. Nichols, 2007, The Predictable Cost of Earnings Manipulation

This paper on US Earnings overstatement inspired the RAM

Systematic Equity team research in Emerging Markets leading to the

development of a Short Overstated Earnings philosophy.

Low-Risk

Frazzini, L. Heje Pedersen, 2011, Betting against Beta

Low-volatility and low-beta stocks tend to have significantly higher risk-

adjusted returns than predicted by efficient markets’ hypothesis, which

we capture in a number of our Defensive strategies.


An ethical approach to investing with RAM

Incorporation of ESG Issues

As an UNPRI Signatory, RAM defined an SRI policy for responsible investment setting out the investment beliefs, the guidelines, and the

approach for us to consider and incorporate corporate governance, environmental, and social factors into our investment process and

strategies.

Analyse & Incorporate Exclude

Screening criteria are applied through a

systematic monitoring of companies to identify

holdings for further assessment, engagement,

and/or exclusion, focusing mainly on the

following:

• Illegal or controversial weapons

• Suspected of accounting fraud

• Disregard international norms for labor rights

• Violate human rights

• Environmental damage

• Exposed to sanctions; OFAC list

Analyze and incorporate ESG Data and Metrics:

• Introduction of an ESG specific strategy,

called the RAM Responsible Income

Equities Fund.

• Strong Governance integration aiming at

identifying quality names looking at sound

accounting and board practices.

• RAM analyzes climate data to filter out

stocks with excessive carbon footprint from

some its EM fund investment universe.

• Alignment of interest between sustainability

of the company and the sustainability of its

shareholders

Engage

Engage collaboratively with companies and

exercise active shareholder stewardship:

• RAM directly engages and participates in in

collaborative engagement with companies.

• RAM applies a voting policy to the full range

of its Funds to which RAM acts as

investment manager or delegated

investment manager.

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Making it work together

Investment Process

Objective: Construct a well

diversified portfolio with stocks

that create sustained value and

growth at reasonable price

Exposure: static

Optimisation: optimal

allocation of strategy or stock

weights given their alpha,

liquidity and risk characteristics

Objective: select stocks that

destroy cash flow using high

leverage or have negative

fundamental trends

Exposure: static

Optimisation: through

historical research

Objective: select a basked of

liquid index futures. Avoid

short squeezes

Exposure: variable,

depending on beta

Optimisation: optimal

allocation of futures positions

to hedge the portfolio risk

Maximum Risk Adjusted Return

Historical Beta : -0.2 to 0.2

Value

Index

Basket

Short

Value

LONG

Growth/Momentum

SHORTS

Short

Quality

Optimiser

Low-Vol

Short

Momentum


The building blocks of our philosophy

Investment Process

Our entire equity fund range is built on a systematic investment process that seeks to perform throughout different market

cycles with, at its core, an Alpha Engine.

Value Added

~ 6’000 stocks reduced to

~ 1’500 stocks

Proprietary Alpha Model Impact Model Portfolio

We screen a large

universe of more than

6’000 stocks in developed

Europe and above 30’000

in emerging markets and

over 50’000 in the

developed world

Data is screened so that

only stocks with set

liquidity profiles and

capitalizations are

selected.

The universe is reduced

to 3’500 stocks in EM and

to 1’500 in developed

Europe, and 6’000 in the

dev. world.

Screening

0

Alpha Engines

Through the underlying strategies, our model is well balanced between

fundamental and behavioral approaches with minimal

correlation.

Impact model including

volatility and liquidity

metrics (measured over

the last few weeks of

trading) helps scale

down positions with

eventual liquidity

impact, fully integrated

in portfolio construction

A highly-diversified

portfolio across country,

sector and market caps,

rebalanced on an optimal

basis to maximize

expected alpha

c. 600 stocks (L/S Europe)

c. 600 stocks (L/S

Emerging)

c. 800 stocks (L/S Global)

Final Portfolio

We collect our information from a number of data sources to

construct a wide area of fundamental & technical factors, which form the building blocks

for our strategies.

Volatility & Liquidity

Data Treatment

Information Sources

Other Data Sources

Analyst Estimates

Management Transactions

Stock Loan Data

ESG Data

Financial Statements

Market Data

Value

Index

Basket

Short

Value

LONG

Growth/

Momentum

SHORTS

Short

Quality

Optimiser

Low-Vol

Short

Momentum


The rebalancing methodology

Liquidity Risk and Market Impact

• Rebalance on an optimal basis to maximize expected alpha

• Minimize market impact due to our high turnover

RAM has developed a technique to gradually allow the integration of new information within our overall portfolio and

reduce the market impact during the rebalancing phase.

Long Portfolio

Short Portfolio

Index Basket

Rebalancing Phases

Sub-portfolio #1 Sub-portfolio #2 Sub-portfolio #3 Sub-portfolio #4

Period 1 Period 2 Period 3 Period 4 …

Long Portfolio Long Portfolio Long Portfolio

Short Portfolio Short Portfolio Short Portfolio

Index Basket Index Basket Index Basket


Limits and constraints

Portfolio Construction

Strategy Characteristics RAM Long/Short European

Equities Fund

RAM Long/Short Emerging

Markets Equities Fund

RAM Long/Short Global

Equities Fund

Target Return Above 8% annualised across a market

cycle

Above 6% annualised across a market

cycle

Above 8% annualised across a market

cycle

Target Volatility 6-10% 4-6% 6-10%

Max Net L/S country exposure: 25% 25% 25%

Max Net L/S sector exposure: 25% 25% 25%

Max Net L/S single stock weight: 3% 2.5% 2.5%

Regional Coverage Developed Europe Global emerging markets and satellites Developed Global Equities

Investment Instruments Common equity, CFDs, Futures Common equity, CFDs, Futures Common equity, CFDs, Futures

Liquidity +$150mn market cap

daily liquidity thresholds

+$150mn market cap


+$500mn market cap


# of holdings Typically above 600 stocks Typically above 600 stocks Typically above 800 stocks

Principal Risk Limits

A strict VAR limit set at 15% (20 days-

99% confidence level)

Maximum leverage via derivative

instruments: 170%

Stress Tests limits- Max Loss Level (1

Day, 1 Week, 1 Month)

UCITS Regulatory Risk Limits

(counterparty, concentration, coverage

risk)




instruments: 100%





risk)




instruments: 200%





risk)


An integrated component of the investment process

Risk Controls & Liquidity Monitoring

Investment Team RAM Risk

Management Custodian

Banque de Luxembourg

RAM Risk

Management

Pre –trade and Trade Post Trade

Internal Limits

• Allocation Limits

• Proprietary Market Impact

Model

• Liquidity

• Best execution

• Broker Selection relying on

in-house pre and post

trade analytics

UCITS Pretrade check

• Counterparty Risk

• Investment guidelines

control

UCITS Guidelines



control

RAM Middle Office

NAV Reconciliation UCITS Post Trade Check



control

• Market Risk (VaR), etc

• Daily report to the ManCo

Broker Committee Asset Management & Market Risk

Committee

Compliance & Operational Risk

Committee

Analysis of Broker execution and follow up

of best execution policy

Assessment of market risk and funds’

positioning

Assessment and follow-up of key risk

indicators such as operational, compliance,

counterparty risks

Fund Administrator European Fund Administration

NAV Calculation

• Risk review and on-going strategy reviews are at the heart of risk management models

• Daily oversight of market and liquidity risk by the Risk Management team

• Highly conservative approach to cash management and counterparty risk

• UCITs limits are fully implemented into the investment process, with complete risk management oversight

Investment Team

Best Execution

• Post trade analysis

• Slippage Anaylsis


Liquidity curve

Liquidity Risk and Market Impact

Source: RAM Active Investments, Holdings as of 29.06.2018

• RAM has developed a proprietary market impact model including volatility and liquidity metrics

• Off-benchmark positions present a different liquidity profile to peers

• Subsequently careful monitoring and management of liquidity risk is key

Number of Days to Liquidate the Portfolio

Based on 20% ADV (Average Daily Volume) - 20 days

RAM Long/Short Emerging Markets Equities RAM Long/Short Global Equities RAM Long/Short European Equities

68% of the portfolio can be liquidated

within 1 day, 88% within 3 days.

99%

1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Day 1 Day 2

100%

0% 0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Day 1 Day 2

68%

13% 7% 5% 4% 2%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Day 1 Day 2 Day 3 Day 4 Day 5 Day 6

To update with Latesst figures


Long, short portfolios

Historic Exposures

RAM Long/Short Emerging Markets Equities Fund 12.2011-06.2018

The Fund’s leverage is at a level far below restrictions

imposed by UCITS Guidelines, with less risk than its

competitors

RAM Long/Short European Equities Strategy 06.2009-06.2018

Levera

ge,

%

Levera

ge,

%

-100

-60

-20

20

60

100

140

Long Book Short Stocks Book Short Indices Net Exposure

-100

-60

-20

20

60

100

140

-100

-60

-20

20

60

100

140

RAM Long/Short Global Equities Fund 12.2016-06.2018

Annex

Long/Short European Equities Fund


vs our peers

Comparative Performance

Last 5 Years Cumulative Performance

Inception of the UCITS fund in December 2011,

previously managed within a Cayman vehicle (cf. Note)

Note: RAM Long/Short European Equities Strategy shows performance net of fee of the RAM L/S European Equities Fund Class-I from December 2011 (1.5% of management fee+20% of

performance fee) and of the RAM Absolute Return Fund prior to December 2011. The RAM Absolute Return Fund followed the same exact investment strategy within a Cayman vehicle

(1.75% of Management fee+20% of performance fee) before it was converted to a UCITS.

Past performance is not a guide to future performance / Source: RAM Active Investments, MSCI indices as of 29.06.2018

An annualized return of 6.75% with a volatility of 6.43%, over the last 5 years Our RAM Long/Short European Equities approach exhibits very low correlation to the European equity market (0.1 over 60 months) and persistent alpha generation over the mid term


-50

-40

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

-100 -80 -60 -40 -20 0 20 40 60 80 100 120 140

Morningstar Alt- Market Neutral Equity UCITS Funds Peers' Group

RAM Long/Short European Equities Strategy Net of Fee

MPT Statistics

in LOC, 01.04.09 to 29.06.18 on common weekly dates

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

Up

Mkt C

ap

ture

Ra

tio

, %

-100 -80 -60 -40 -20 0 20 40 60 80 100 120 140

Down Mkt Capture Ratio, %

Mstar Alt - Market Neutral - Equity Funds Peers Group dyn,Mstar Long-Short Europe Equity Funds Peers Group dyn

MSCI Europe Total Return Net EUR

In correction phases

Controlling its Downside Risk

Up/Down Market Capture Ratio since inception RAM Long/Short European Equities Strategy

A negative down market capture

ratio of -33% means that when

the market is down by 1% the

Fund is up by 33bps, while the

RAM Long/Short European

Equities maintains a neutral

Beta.


Up M

kt

Captu

re R

atio,

%

Our beta-neutral approach

provides a complementarity

return profile relative to our

peers.





MPT Statistics

in LOC, 01.04.09 to 28.02.18 on common weekly dates

-50

-40

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

Up M

kt C

aptu

re R

atio, %

-100 -80 -60 -40 -20 0 20 40 60 80 100 120 140


Mstar Long-Short Europe Equity UCITS Funds Peers' Group

MSCI Europe Total Return Net EUR


36-Month Rolling Beta vs MSCI Europe TRN€

in EUR, 03.2012 - 06.2018

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Be

ta

03.2012 12.2012 06.2013 12.2013 06.2014 12.2014 06.2015 12.2015 06.2016 12.2016 06.2017 12.2017 06.2018



Beta36-Month Rolling Alpha vs MSCI Europe TRN€

in EUR, 03.2012 - 06.2018

(Morningstar Long/Short Europe Equity+ Market Neutral Equity Funds, 316 oldest EUR share class)

-15

-10

-5

0

5

10

15

Alp

ha

, %

An

.

03.2012 12.2012 06.2013 12.2013 06.2014 12.2014 06.2015 12.2015 06.2016 12.2016 06.2017 12.2017 06.2018



Alpha

A persistent alpha

A Neutral Beta





Alp

ha


156 Week Rolling Alpha

in EUR, 29.06.2012 - 29.06.2018

-10

-5

0

5

10

15

Alp

ha

, %

29.06.2012 03.01.2014 02.01.2015 31.12.2015 30.12.2016 29.06.2018

156 Week Rolling Beta

in EUR, 29.06.2012 - 29.06.2018

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Be

ta

29.06.2012 03.01.2014 02.01.2015 31.12.2015 30.12.2016 29.06.2018

RAM Long/Short European Equities (Gross of MF & PF) RAM L/S EE- Long Side

RAM L/S EE- Short Single Names RAM L/S EE- Short Indices

Maximize alpha

Neutralize Beta

Note: RAM Long/Short European Equities Strategy performance gross of fee (RAM L/S European Equities Fund from December 2011 (gross of management and

performance fee, before performance of the RAM Absolute Return Fund gross of fees, Short & Long Book returns are estimates.


Very few managers can generate

alpha on the short side, sellers

face important issues such as the

ability to borrow, execution impact,

capacity limitations, etc

Our short book has been

constructed to:

• Generate strong alpha within its

book of short stocks (45% of the

short side)

• Control risk with its basket of

index futures (i.e. limiting risk in

case of deleveraging) and

maintain a neutral Beta

156-week Rolling Alpha vs MSCI Europe TR€

156-week Rolling Beta vs MSCI Europe TR€


50

100

150

200

250

300

350

400

Gro

wth

of

10

0 E

UR

31.07.2009 31.12.2010 30.12.2011 28.12.2012 03.01.2014 02.01.2015 31.12.2015 30.12.2016 29.06.2018

RAM L/S EE- Long Side RAM L/S EE- Short Single Names

RAM L/S EE- Short Indices MSCI Europe TRN€

Calendar Year Book Performance

in EUR, 31.12.2010 - 22.06.2018

-30

-20

-10

0

10

20

30

40

To

tal R

etu

rn, %

31.12.2010 30.12.2011 28.12.2012 27.12.2013 24.12.2014 31.12.2015 30.12.2016 29.12.2017 22.06.2018

Performance contribution

Short, Futures, Long Book

Note: RAM Long/Short European Equities Strategy performance gross of fee (RAM L/S European Equities Fund from December 2011 (gross of management and

performance fee, before performance of the RAM Absolute Return Fund gross of fees, Short & Long Book returns are estimates.



In 2011, during the

European sovereign debt

crisis, our short book

proved resilient for the

Fund, while providing

strong returns during the

subsequent rebound

(2012-2013).

Cumulative Performance

(Book Long, Short Single Names, Short Indices)


Fiscal Annual Performance

in EUR, 12.2010 - 12.2017

-25

-20

-15

-10

-5

0

5

10

15

20

25

Exc

ess

Retu

rn,

%

12.2010 12.2011 12.2012 12.2013 12.2014 12.2015 12.2016 12.2017

EE-Defensive EE-Momentum EE-Value

RAM L/S EE- Short Single Names

Model strategies

Benefit from the Alternate Source of Returns

In 2011, the

short

strategies

performed

strongly

Market rebound

following

expansionist

monetary

policy, excellent

contribution

from the mid-

cap segment

within a Value

allocation

In 2014 long

and short

strategies

were positive

contributors

RAM European Equities Model Strategies (Long & Short) vs MSCI Europe TRN€

Gross Excess Return

Note: Whether real

or simulated, past

performance is not

necessarily a

reliable guide to

future performance

In 2013

momentum

allocation

caught up with

the value

strategies

Shorts

Note: Figures shown above are for illustration purpose only. On the long-side sub-strategy performance is calculated based on simulated model portfolios rebalanced monthly on RAM equity

investment screenings and may not represent the exact contribution of strategies in real portfolio. Strategy performance is adjusted considering their long-term theoretical fixed allocation in the

fund. For the short book, performance is estimates. Performance is gross of management and performance fee. Client’s return will be reduced by such fees in case of investment in such

strategies.

Source: RAM as of 29.12.2017, Bloomberg Port



Sector breakdown

Active Positioning

RAM LONG/SHORT EUROPEAN EQUITIES FUND

SECTOR ALLOCATION

Net exposure

Source: RAM Active Investments as of 29.06.2018

-20

-10

0

10

20

30

40

50

Real estate

Industrials

Consumer Staples

Consumer Discretionary

Healthcare

Information Technology

Telecommunication Services

Utilities

Financials

Energy

Materials

Annex

Long/Short Emerging Markets Equities Fund


156 Week Rolling Alpha

12.12.2014 - 29.06.2018

-4

-2

0

2

4

6

8

10

12

14

Alp

ha

, %

12.12.2014 02.07.2015 31.12.2015 01.07.2016 30.12.2016 30.06.2017 29.12.2017 29.06.2018

156 Week Rolling Beta

12.12.2014 - 29.06.2018

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

Be

ta

12.12.2014 02.07.2015 31.12.2015 01.07.2016 30.12.2016 30.06.2017 29.12.2017 29.06.2018

RAM Long/Short Emerging Markets Equities (Gross of MF & PF) RAM L/S EM- Long Side

RAM L/S EM- Short Single Names RAM L/S EM- Short Indices

Maximize alpha

Neutralize Beta

Note: RAM Long/Short Emerging Markets Equities Strategy performance gross of fee , Short & Long Book returns are estimates


Very few managers can generate alpha on the short side, sellers

face important issues such as ability to borrow, execution impact,

capacity limitations, etc

Our short book has been constructed to:

• Generate strong alpha within its book

of short stocks (35% of the short side)

• Control risk with its basket of index

(i.e.. limiting risk in case of

deleveraging) and maintain a neutral

Beta


Cumulative Book Performance

16.12.2011 - 29.06.2018

60

80

100

120

140

160

180

200

220

240

Gro

wth

of

$100

16.12.2011 28.12.2012 03.01.2014 02.01.2015 31.12.2015 30.12.2016 29.06.2018

RAM Long/Short Emerging Markets Equities (Gross of MF & PF) RAM L/S EM- Long Side


MSCI Emerging Markets TRN$

Caldendar Year Book Performance

28.12.2012 - 29.06.2018

-30

-20

-10

0

10

20

30

40

Tota

l R

etu

rn,

%

28.12.2012 27.12.2013 24.12.2014 31.12.2015 30.12.2016 29.12.2017 29.06.2018

Performance Contribution

16.12.2011 - 29.06.2018RAM Long/Short Emerging Markets Equities (Gross of MF & PF) RAM L/S EM- Long Side


MSCI Emerging Markets TRN$

Performance contribution


Note: RAM Long/Short Emerging Markets Equities Strategy performance gross of fee , Short & Long Book returns are estimates




Fiscal Annual Performance

31.12.2012 - 29.12.2017

-20

-15

-10

-5

0

5

10

15

20

Exce

ss R

etu

rn,

%

31.12.2012 31.12.2013 31.12.2014 31.12.2015 30.12.2016 29.12.2017

Long - Defensive Long - Value Long - GARP RAM L/S EME- Short Single Names

Model strategies

Benefit from the Alternate Source of Returns

Emerging Market Equities - RAM Model Strategies (Long & Short) vs MSCI EM

Gross Excess Return

Note: Whether real or

simulated, past

performance is not

necessarily a reliable

guide to future

performance

Shorts

Note: Figures showed above are for illustration purpose only. On the long-side sub-strategy performances are calculated based on simulated model portfolios rebalanced monthly on RAM

equity investment screenings and may not represent the exact contribution of strategies in real portfolio. Strategies performances are here adjusted considering their long-term theoretical fixed

allocation in the fund. For the short book performance are estimates. Performance are gross of management and performance fee. Client’s return will be reduced by such fees in case of

investment in such strategies

Source: RAM as of 29.12.2017, Bloomberg Port

Implementation of the

short Overstated

Earnings strategy in Q3

2013

Implementation of the

short Value Cash Flow

strategy in Q3 2014


Geographical breakdown

Active Positioning

COUNTRY ALLOCATION

Net exposure


-30

-20

-10

0

10

20

30

40

50 Chile

Peru

India

Turkey

China + Hong Kong

Thailand

Malaysia

South Africa

Taiwan

Singapore

Mexico

Russia

New Zealand

Poland

Philippines

Australia

Indonesia

Israel

Czech Republic

United Arab Emirates

Greece

Colombia

Brazil

South Korea


-20

-10

0

10

20

30

40

50

Real Estate

Utilities


Materials


Industrials

Health Care

Financials

Energy

Consumer Staples


Sector breakdown

Active Positioning


SECTOR ALLOCATION

Net exposure

Annex

Long/Short Global Equities Fund


Important Information

Long/Short Global Equities

These presentation materials (collectively, this "Presentation") have been provided in order to provide a high-level overview of RAM Active

Investments SA (the "Investment Manager"), certain of its operational and advisory programs and processes, and certain of its key personnel.

This Presentation is provided for information purposes only and does not constitute an offer to sell or a solicitation to buy any securities in any

mutual fund (the “Fund”) that offers the Long/Short Global Equities investment strategy (the “Strategy”), and may not be relied upon in connection

with any offer or sale of securities. Any such offer or solicitation may only be made pursuant to a Prospectus (or similar document) and the

organizational documents for such Fund (e.g. limited partnership agreements, articles of association, etc.), which will be provided only to

qualified/institutional offerees and which should be carefully reviewed prior to investing.

An investment in the Strategy is speculative and entails substantial risks, including the fact that such an investment would be illiquid and be subject

to significant restrictions on transferability. No market is expected to develop for interests in the Fund.

Financial instruments and investment opportunities discussed or referenced herein may not be suitable for all investors, and potential investors

must make an independent assessment of the appropriateness of any transaction in light of their own objectives and circumstances, including the

possible risk and benefits of entering into such a transaction.

A number of indices are referenced herein. Each index is presented because RAM feels that it serves as a useful point of comparison with aspects of

the Fund's portfolio management and composition. The Fund's portfolio will not replicate any of these indices and no guarantee is given that

performance will match any of the indices; it is not possible to invest in any index.


Important Information

Long/Short Global Equities

There are significant differences between the Strategy's investments and the indices references below (the "Indices"). For instance, the Strategy

may use short sales and leverage and may invest in securities that have a greater degree of risk and volatility, as well as less liquidity, than those

securities contained in the Indices. Moreover, the Indices may not reflect the reinvestment of income or dividends and may not be subject to any of

the management fees or expenses that the Fund must pay. It should not be assumed that the Fund will invest in any specific securities that comprise

the Indices, nor should it be understood to mean that there is a correlation between the Fund's returns and the Indices' performance. The Indices are

included for informational purposes only.

Additional information on each index follows:

• The MSCI Europe Total Return Net Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity

market performance of the developed markets in Europe. The MSCI Europe Index consists of the following 16 developed market country indices:

Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, and

the United Kingdom

• The MSCI Emerging Markets Total Return Net Index is a free float-adjusted market capitalization-weighted index of the performance of the global

emerging markets reflects. It approximates the minimum possible dividend reinvestment. The dividend is reinvested after deduction of withholding

tax, applying the rate to non-resident individuals who do not benefit from double taxation treaties. MSCI uses withholding tax rates applicable to

Luxembourg holding companies, as Luxembourg applies the highest rates.

• The MSCI World Total Return Net Index measures the performance of large and mid cap stocks across 23 developed markets countries covering

approximately 85% of the free float-adjusted market capitalization of each country. The index is constructed to provide a comprehensive and

unbiased barometer and is completely reconstituted annually to ensure all countries and their stocks are included on merit, and thus do not distort

the performance and characteristics of the opportunity set.

• The MSCI ACWI Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity market performance of

developed and emerging markets. The MSCI ACWI consists of 44 country indices comprising 23 developed and 21 emerging market country indices.

The developed market country indices included are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland,

Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the United Kingdom and the United States.

The emerging market country indices included are: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Korea,

Malaysia, Mexico, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey.


Dislcaimer: Theoretical Performances

Important Note

THE THEORETICAL MODELS PRESENTED HEREIN ARE BASED ON A NUMBER OF HYPOTHETICAL ASSUMPTIONS, INCLUDING THE

PERFORMANCE OF STOCKS WITH MARKET CAPITALIZATION ABOVE U.S.$500Mn AND A DEFINED LIQUIDUTY THRESHOLD BASED ON

A 10-DAY AVERAGE DAILY VOLUME. THEY ARE PRESENTED ONLY FOR THE LIMITED PURPOSE OF PROVIDING SAMPLE

ILLUSTRATIONS. CHANGES IN THESE ASSUMPTIONS MAY HAVE A MATERIAL IMPACT ON THE BACKTESTED RETURNS PRESENTED.

CERTAIN ASSUMPTIONS HAVE BEEN MADE FOR MODELING PURPOSES AND ARE UNLIKELY TO BE REALIZED. NO

REPRESENTATIONS AND WARRANTIES ARE MADE AS TO THE REASONABLENESS OF THE ASSUMPTIONS. THE THEORETICAL

MODELS ARE NOT REFLECTIVE OF AN ACTUAL STRATEGY OFFERED TO INVESTORS AND ARE NOT INTENDED TO REPRESENT

WHAT THE STRATEGY WOULD HAVE EARNED OVER THE SAME PERIOD HAD THE STRATEGY BEEN IN OPERATION. THE ACTUAL

RETURNS OF ANY STRATEGY ARE LIKELY TO HAVE NO CORRELATION WITH THE THEORETICAL MODELS PRESENTED HEREIN.

The Manager calculated the theoretical performance of the Long/Short Global Equities Backtest using the following methodology:

Backtest Peformance:

Performance results created by applying an investment strategy or methodology to historical data from December 2005 to June 2016. Backtested

performance attempts to indicate how a product constructed with the benefit of hindsight would have performed during a certain period in the past if

the product had been in existence during such time.

The Manager calculated the hypothetical performance data of the Long/Short Global Equities Backtest using the following methodology:

The model backtest has been extracted for the long side using separate stock selection engines able to analyze and select stocks among a

universe of over 6’000 names globally. Each strategy has unique characteristics which it uses to identify and capture pre-defined inefficiencies

using Factset Fundamentals database. On the long side we consider different strategies with a fixed allocation summing up to 100% of the

exposure, and on the short side, a combination of short strategies representing -60% of the exposure and an short allocation to the MSCI World

TRN$ Index which is adjusted to neutralize the portfolio’s beta. A filter has been applied by excluding the following subsets:

1- Small Caps <$500 Mn and unassigned stocks

2- a defined liquidity threshold based on a 10-day Average Daily Volume

Performance presented includes management fees of (1.5%), performance fees of (15%), administrative fees and custodian fees. Transactions

costs, tax and slippage have been estimated based on the level reached by the RAM (Lux) Systematic Funds- Long/Short European Equities in

2015 and according to the investment manager’s experience.


Dislcaimer on Theoretical performance

Important Note

Theoretical Models including Backtesting

The Theoretical Models provided herein may materially differ from what the Strategy's actual performance would have been. This is

due to a number of factors, including the inherent limitations that would have existed if the Investment Manager had managed the

Strategy. Such limitations may include, but are not limited to, the inaccuracy of data available for the research process, the fact that

the signals which drive the models can lose efficiency when applied in live markets, the inability to account for how RAM personnel

would have actually traded on a real time basis in a live market. Alternative assumptions which may be relied on in the future could

produce significantly different results. The hypothetical results do not represent actual trading and may not reflect the impact that

material economic and market conditions could have on the Investment Manager's decision making had this been an actual

investment portfolio. Further, backtesting allows the security selection methodology to be adjusted until past returns are maximized.

The model returns provided herein assume the reinvestment of all hypothetical dividends and income. In addition, the actual returns

of the Fund will differ from model returns as the actual returns will be subject to different advisory fees or allocations,

administration fees and estimated organizational expenses, additional transaction costs, ongoing expenses and other

expenses. These eventual additional fees and expenses, compounded over a period of years, would result in lower performance

results. No cash balance or cash flow is included in the calculation.


Cumulative Performance

in USD, 12.2005 - 06.2016

100

125

150

175

200

225

250

275

300

325

Gro

wth

of $100

12.2005 12.2006 12.2007 12.2008 12.2009 12.2010 12.2011 12.2012 12.2013 12.2014 06.2016

Long/Short Global Equities Backtested

Theoretical Performance

The Long/Short Global Equities Strategy will aim to have a diversified long exposure, hedged with a basket of

indices and short stocks.

Backtest Performance (gross of management and performance fee, net of implementation costs)

▬ LONG/SHORT GLOBAL EQUITIES BACKTEST

Backtest:

Last 10 Years Returns 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006

Annualised

Return

Long/Short Global Equities Backtest 0.03% 12.70% 13.53% 22.34% 5.76% 14.91% 7.07% -4.86% 14.18% 20.80% 18.74% 11.63%

Capture Ratio Max Drawdown

Backtest:

Last 10 Years Stats

An. Volatility Alpha Beta Sharpe

Ratio Up Mkt

Down

Mkt Return Period Duration

Recovery

Period

Long/Short Global Equities Backtest 7.27 10.60 -0.10 1.40 20.50 -23.97 -13.21

01.2009-

04.2009 4 18 months

Performance and risk data are based on simulation

See important disclaimer on slide 10-11. The results do not represent actual results.

Actual results may significantly differ from the theoretical returns being presented. The performance information is simulated net of fees and expenses, including a

management fee of 1.5% and a relative performance fee of 15%.

Source: RAM Active Investments, MSCI indices as of 06.2016


Neutralise Beta & Maximize alpha

Theoretical Performance

Our short book aims at:

• generate strong alpha within its

book of short stocks (60% of

the short side)

• Mitigate risk with its basket of

index (i.e.. limiting risk in case

of deleveraging) and maintain

a neutral Beta

36 Month Rolling Alpha

in USD, 12.2008 - 06.2016

-10

-5

0

5

10

15

20

Alp

ha, %

12.2008 06.2009 12.2009 06.2010 12.2010 06.2011 12.2011 06.2012 12.2012 06.2013 12.2013 06.2014 12.2014 06.2015 12.2015 06.2016

36 Month Rolling Beta

in USD, 12.2008 - 06.2016

-2

-1

0

1

2

Beta

12.2008 06.2009 12.2009 06.2010 12.2010 06.2011 12.2011 06.2012 12.2012 06.2013 12.2013 06.2014 12.2014 06.2015 12.2015 06.2016

Long Book Short Book Single Names Short Futures RAM LS Global Backtest Net I





Actual results may significantly differ from

the theoretical data of the backtest

presented herein

Short Indices


Calendar Year Book Performance

in USD, 12.2006 - 06.2016

-60

-40

-20

0

20

40

60

80

Tot

al R

etur

n, %

12.2006 12.2007 12.2008 12.2009 12.2010 12.2011 12.2012 12.2013 12.2014 12.2015 06.2016

Cumulative Book Performance

in USD, 12.2005 - 06.2016

0

50

100

150

200

250

300

350

Gro

wth

of $

100

12.2005 12.2006 12.2007 12.2008 12.2009 12.2010 12.2011 12.2012 12.2013 12.2014 06.2016

Long Book Short Book Single Names

Short Futures RAM LS Global Backtest Net I

MSCI AC World Index ND USD

Performance contribution – Backtested






Actual results may significantly differ from

the theoretical data of the backtest

presented herein

Short Indices


Limits and constraints

Portfolio Construction

Strategy Characteristics RAM Long/Short Global Equities Fund

Expected Return Above 8% annualised across a market cycle

Expected Volatility 6-10%

Max Net L/S country exposure: 25%

Max Net L/S sector exposure: 25%

Max Net L/S single stock weight: 2.5%

Regional Coverage Developed Global Equities

Investment Instruments Common equity, CFDs, Futures

Liquidity +$500mn market cap


# of holdings Typically above 800 stocks

Principal Risk Limits

A strict VAR limit set at 15% (20 days- 99% confidence level)

Maximum leverage via derivative instruments: 200%

Stress Tests limits- Max Loss Level (1 Day, 1 Week, 1 Month)

UCITS Regulatory Risk Limits (counterparty, concentration, coverage risk)


Stress Test

Backtested Portfolio

-1'200

-1'000

-800

-600

-400

-200

0

200

Asian Crisis (1997) Gulf War (1990)Mexican Crisis

(1995)Russian

Devaluation (1998) Sept 11th Gulf War 2 Bond Sell-Off

RAM Global Long/Short Equities Backtest MSCI World Index

RAM Long/Short Global Equities Strategy under diverse scenarios (RiskMetrics 5D models in USD)

NAV Changes in BPS

As of October 2016

The strategy emphasis on

risk control helps the fund to

cross different stressed

scenarios


Actual results may significantly differ from the theoretical returns being presented. The performance information is simulated based on model portfolio extracted from

the backtest as of 31.10.2016.



Market Cap – Global Long/Short Backtest

Backtest- Portfolio Allocation

0%

20%

40%

60%

80%

100%

Long Book

Short Book

Net Exposure

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

Large Cap Mid Cap Small Cap

0%

50%

100%


Actual results may significantly differ from the theoretical information being presented.

Source: RAM Active Investments as of 06.2016


Country breakdown – Long & Short Book

Backtest - Portfolio Allocation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100% United States

United Kingdom

Switzerland

Sweden

Spain

South Korea

Singapore

Portugal

Peru

Norway

New Zealand

Netherlands

Luxembourg

Japan

Italy

Israel

Ireland

Greece

Germany

France

Finland

Denmark

China

Canada

Belgium

Austria

Australia

Long Book Short Book

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%





Net Country Exposure – Global L/S Approach


-30

-20

-10

0

10

20

30

40

50

60 United States

United Kingdom

Switzerland

Sweden

Spain

South Korea

Singapore

Portugal

Peru

Norway

New Zealand

Netherlands

Luxembourg

Japan

Italy

Israel

Ireland

Greece

Germany

France

Finland

Denmark

China

Canada

Belgium

Austria

Australia





Sector breakdown – Global L/S Approach


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100% Others

Utilities


Real Estate

Materials


Industrials

Health Care

Financials

Energy

Consumer Staples


Long Book Short Book

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%





Net Sector Exposure – Global L/S Approach

Backtest - Portfolio Allocation

-40

-30

-20

-10

0

10

20

30

40

50

60Others

Utilities


Real Estate

Materials


Industrials

Health Care

Financials

Energy

Consumer Staples






60 Month Rolling Performance

in USD, 04.2014 - 06.2016

0

2

4

6

8

10

12

14

16

Tota

l A

nnualized R

etu

rn, %

04.2014 06.2014 09.2014 12.2014 03.2015 06.2015 09.2015 12.2015 03.2016 06.2016

60 Month Rolling Risk

in USD, 04.2014 - 06.2016

0

1

2

3

4

5

6

7

8

Tota

l A

nnualized S

tdD

ev, %

04.2014 06.2014 09.2014 12.2014 03.2015 06.2015 09.2015 12.2015 03.2016 06.2016

Allocacation (equally w eighted) RAM LS EE Fund Class I EUR Net of fee+ RAM L/S Global Eq. Backtest Net of fee RAM LS Global Backtest Net of fee

RAM LS EE Fund Class I EUR Net of fee

Europe and Global Equity Markets

Comparing RAM Long/Short Approaches

See important disclaimer on slide 10-11. The results do not represent actual results. Actual results may significantly differ from the theoretical returns being

presented.

RAM Long/Short European Equities Strategy shows performance net of fee of the RAM L/S European Equities Fund Class-I from December 2011 (1.5% of

management fee+20% of performance fee) and of the RAM Absolute Return Fund prior to December 2011. The RAM Absolute Return Fund followed the same exact

investment strategy within a Cayman vehicle (1.75% of Management fee+20% of performance fee) before it was converted to a UCITS.

Source: Source: RAM Active Investments as of 06.2016.

RAM Long/Short Global Equities Backtest has a

higher volatility, but subsequently higher returns

The performance of the RAM Long/Short Global Equities Backtest is net of 1.5% management fee

and 15% of performance fee (net of implementation cost). The allocation shown here RAM L/S

EE+RAM L/S Global Eq is a simulated equally-weighted portfolio combining the RAM Long/Short

Global Equities Backtest net of fee and the actual performance from April 2009 to June 2016 of the

RAM LS EE Fund Strategy net of fee.


European and Global Equity Markets

Combining RAM Long/Short Approaches

Based on a backtest, RAM

Long/Short Global Equities Backtest

and RAM Long/Short European

Equities Backtest are lowly

correlated. Hence a simulated

equally weighted portfolio combining

both strategies could improve the

risk/return profile of an investment.

Annualised Return vs Sharpe Ratio

05.2009 - 06.2016

-2

0

2

4

6

8

10

12

14

16

Tota

l A

nnualized R

etu

rn, %

0.0 0.5 1.0 1.5 2.0 2.5

Sharpe Ratio

Allocacation (equally w eighted) RAM LS EE Fund Class I EUR Net of fee+ RAM L/S Global Eq. Backtest Net of fee

RAM LS Global Backtest Net of fee

RAM LS EE Fund Class I EUR Net of fee

MSCI Europe TRN€

MSCI AC World Index ND USD

Correlation

(from

12.2011)

Equally

Weighted

Allocation

RAM LS Global

Backtest

Net of fee

RAM LS EE Fund

Class I EUR

Net of fee

MSCI

Europe

TRN€

MSCI AC

World Index

ND USD

Equally Weighted

Allocation1.00 0.82 0.84 -0.05 -0.11

RAM LS Global

Backtest Net of fee0.82 1.00 0.39 -0.12 -0.12

RAM LS EE Fund Class

I EUR Net of fee0.84 0.39 1.00 0.04 -0.07

MSCI Europe

TRN€-0.05 -0.12 0.04 1.00 0.82

MSCI AC World

Index ND USD-0.11 -0.12 -0.07 0.82 1.00

The performance of the RAM Long/Short Global Equities backtest is net of 1.5%

management fee and 15% of performance fee (net of implementation cost). The allocation

RAM L/S EE+RAM L/S Global Eq. is a simulated equally weighted portfolio combining the

RAM Long/Short Global Equities Backtest net of fee and the actual performance from April

2009 to June 2016 of the RAM LS EE Fund Strategy net of fee.

See important disclaimer on slide 10-11. The results do not represent actual results. Actual results may significantly differ from the theoretical returns being

presented.

RAM Long/Short European Equities Strategy shows performance net of fee of the RAM L/S European Equities Fund Class-I from December 2011 (1.5% of

management fee+20% of performance fee) and of the RAM Absolute Return Fund prior to December 2011. The RAM Absolute Return Fund followed the same exact

investment strategy within a Cayman vehicle (1.75% of Management fee+20% of performance fee) before it was converted to a UCITS.

Source: Source: RAM Active Investments as of 06.2016.


RAM (Lux) Long/Short Emerging Markets Equities

Fund Terms and Service Providers

INVESTMENT CLASSES & TERMS:

Classes Class B Class I Class I

Retail/Instit Retail (oldest share class) Instit Instit

Currency USD USD USD

Management Fee 2.0 % 1.5 % 1.2 %

Performance fee 20% without hurdle 20% without hurdle 15% with hurdle

High Water Mark Yes Yes Yes

Bloomberg RLSEMEB LX RLSEMEI LX

ISIN LU0705072188 LU0705072691 LU1149832922

Minimum Subscription N/A USD 1 Mn USD 20 Mn

Fund Terms

Fund Name RAM (LUX) SYSTEMATIC FUNDS

Domicile Luxembourg

Compartment Long Short Emerging Markets Equities

Distribution SGP, AUT, CHE, FRA, ITA, BEL, DEU, NLD, GBR, ESP, NOR, SWE, FIN, DNK

Manager RAM Active Investments S.A.

Fund Administrator European Fund Administration (EFA)

Custodian Banque de Luxembourg

Auditor Ernst & Young

Dealing Weekly

Redemption Fee None

Retail and Institutional share classes are also available in EUR, GBP, CHF and SEK


RAM (Lux) Long/Short European Equities



Classes Class B Class I Class I


Currency EUR EUR EUR


Performance fee 20% without hurdle 20% without hurdle 15% without hurdle


Bloomberg REYLSEB LX REYLSEI LX RELSIPF LX

ISIN LU0705071453 LU0705071701 LU1149832682

Minimum Subscription N/A EUR 1 Mn EUR 20 Mn

Fund Terms


Domicile Luxembourg

Compartment Long Short European Equities

Distribution SGP, AUT, CHE, FRA, ITA, BEL, DEU, NLD, GBR, ESP, NOR, SWE, FIN, DNK





Dealing Weekly

Redemption Fee None

Retail and Institutional share classes are also available in USD, GBP, CHF and SEK


RAM (Lux) Long/Short Global Equities



Classes Class B Class I Class PI


Currency USD USD USD


Performance fee 20% without hurdle 15% without hurdle 15% without hurdle


Bloomberg RMLSGLB LX REYLSEI LX RMLSIPF LX

ISIN LU1520758985 LU1520762235 LU1520759363

Minimum Subscription N/A USD 1 Mn USD 20 Mn

Fund Terms


Domicile Luxembourg

Compartment Long Short Global Equities

Distribution AUT, CHE, FRA, ITA, BEL, DEU, NLD, GBR, NOR, SWE, FIN





Dealing Daily

Redemption Fee None

Retail and Institutional share classes are also available in EUR, GBP, CHF and SEK


Structure


Z Pierre-Olivier Pourcelot

Roberto Zito

Thomas de Saint-Seine

CEO

Maxime Botti

Emmanuel Hauptmann

Executive Committee

Equity

Fund Managers

T. De Saint-Seine

M. Botti

E. Hauptmann

Systematic

Execution

T. Dessingy

V. Betrix

Quantitative Analyst

N. Jamet

P. Huber

Investment

Management

Head T. de Saint-Seine

Fixed Income

Fund Managers

C. Daras

G. Pradere

O. Mulin

C. Perrette

Product Specialist

H. Aslan

Legal &

Compliance

Risk Management

Head L. Lienard

Head S. Pilozzi

CSR

M. Saunders

SRI & CSR

Business Process

Management

Communications

& Events.

Head B. Li

Head A. Petit

Head S. Saccone

Communications

M. Sandell

Events

L. Marqués

Sales & Client

Services

Head P.O. Pourcelot

Sales

Sales Executives

P.O. Pourcelot

G. Glotin

E. Biella

J. Chevalier

B. Li

Assistant

Milena Follini

Client Services

Head C. Joye

S. Payne

Y. Wittrock

C. Tremege

A. Bataille

C. Castillo

F. Rossi

Operations &

Finance

Middle Office

C. Cardoso (Head)

C. Boulanger

R. Darbas

Y. Bernachot

Head R. Zito

Finance

A. Vaudan

GIPS Compliance

A. Petit

Laurent Lienard

Philippe Wagener Yves Wagner

Executive Committee

Operations

Operations &

Services Manager

N. Kraemer

Senior

Regulatory

Officer

I. Pacho Tejero

Legal &

Compliance

Sales & Client

Services

D. Endres

G. Glotin *

E. Biella *

J. Chevalier *

C. Tremege*

RAM Active Investments SA

(Geneva)

RAM Active Investments SA

(Luxembourg)

*part time between Geneva and Luxembourg


Contacts


[email protected]

GENEVA

62, rue du Rhône

1204 Geneva

SWITZERLAND

Tel: +41 22 816 8730

Fax: +41 22 816 8701

ZÜRICH

Talstrasse 65

8001 Zurich

SWITZERLAND

Tel: +41 58 717 9797

Fax: +41 58 717 9311

LUXEMBOURG

51, avenue John F. Kennedy,

L-1855

LUXEMBOURG

Tel: +352 285 614 22

Fax:+352 285 614 44

mailto:[email protected]




Disclaimer

This document has been drawn up for information purposes only. It is neither an offer nor an invitation to buy or sell the investment products

mentioned herein and may not be interpreted as an investment advisory service. It is not intended to be distributed, published or used in a jurisdiction

where such distribution, publication or use is forbidden, and is not intended for any person or entity to whom or to which it would be illegal to address

such a document. In particular, the investment products are not offered for sale in the United States or its territories and possessions, nor to any US

person (citizens or residents of the United States of America). The opinions expressed herein do not take into account each customer’s individual

situation, objectives or needs. Customers should form their own opinion about any security or financial instrument mentioned in this document. Prior

to any transaction, customers should check whether it is suited to their personal situation, and analyse the specific risks incurred, especially financial,

legal and tax risks, and consult professional advisers if necessary.

The information and analyses contained in this document are based on sources deemed to be reliable. However, RAM Active Investments S.A. cannot

guarantee that said information and analyses are up-to-date, accurate or exhaustive, and accepts no liability for any loss or damage that may result

from their use. All information and assessments are subject to change without notice. Subscriptions will be accepted only if they are made on the basis

of the most recent prospectus and the latest annual or half-year reports for the financial product. The value of units and income thereon may rise or

fall and is in no way guaranteed. The price of the financial products mentioned in this document may fluctuate and drop both suddenly and sharply, and

it is even possible that all money invested may be lost. If requested, RAM Active Investments S.A. will provide customers with more detailed

information on the risks attached to specific investments. Exchange rate variations may also cause the value of an investment to rise or fall. Whether

real or simulated, past performance is not a reliable guide to future results. The prospectus, KIID, constitutive documents and financial reports are

available free of charge from the SICAV’s head office , its representative and distributor in Switzerland, RAM Active Investments SA, and the

distributor in Luxembourg, RAM Active Investments SA. This document is confidential and addressed solely to its intended recipient; its reproduction

and distribution are prohibited. RAM Active Investments SA is authorised and regulated in Switzerland by the Swiss Financial Market Supervisory

Authority (FINMA). Issued in Switzerland by RAM Active Investments S.A. which is authorised and regulated in Switzerland by the Swiss Financial

Market Supervisory Authority (FINMA). Issued in the European Union and the EEA by the Management Company RAM Active Investments

(Luxembourg) S.A., 51 av. John F. Kennedy L-1855 Luxembourg, Grand Duchy of Luxembourg.

No part of this document may be copied, stored electronically or transferred in any way, whether manually or electronically, without the prior

agreement of RAM Active Investments S.A.


Monthly historical net returns

Appendix I

January February March April May June July August September October November December Year

2017 1.04% 0.38% 0.47% 2.86% 0.34% 0.81% 1.30% 2.05% -1.07% 1.19% -0.65% -0.24% 8.76%

2016 -1.11% -2.74% -1.71% -3.65% 2.63% 3.48% 3.20% -3.3% 1.88% -0.21% -1.00% -1.18% -4.00%

2015 5.18% 0.64% 1.53% -2.93% 2.15% -0.85% 2.84% 0.19% 1.48% -0.59% 2.20% 2.00% 14.48%

2014 2.28% 1.22% -0.24% -3.52% 0.51% 2.87% 0.49% -0.06% 0.93% 1.31% -0.12% 2.15% 7.92%

2013 -0.64% 3.93% 1.92% 2.11% -0.40% 1.27% 1.47% -3.44% 1.24% 2.65% 1.57% 1.04% 13.26%

2012 -1.77% 0.20% 2.63% 2.11% 0.86% -1.32% 0.98% -1.49% 0.86% 1.91% 0.29% 0.10% 5.37%

2011 -3.54% -0.21% 1.09% 1.82% 0.89% 0.11% 1.37% -2.13% -0.21% -0.67% 0.70% -0.23% -0.81%

2010 3.96% 0.26% 1.33% 1.61% -0.5% 1.93% -0.34% 1.92% 2.42% 0.38% 1.28% 1.24% 16.56%

2009 0.21% 1.67% -1.34% -0.33% 1.17% 2.40% 2.26% -0.30% -0.23%

Note: RAM Long/Short European Equities Strategy shows performance net of fee of the RAM L/S European Equities Fund Class-I from December 2011 (1.5% of management

fee+20% of performance fee) and of the RAM Absolute Return Fund prior to December 2011. The RAM Absolute Return Fund followed the same exact investment strategy within a

Cayman vehicle (1.75% of Management fee+20% of performance fee) before it was converted to a UCITS.



RAM Long/Short European Equities Strategy - Net Monthly Performance



Appendix II


2017 0.68% 1.24% -0.02% -0.34% -0.29% 1.32% 0.90% 0.70% -0.65% -0.94% 0.25% 1.45% 4.29%

2016 -0.48% -0.40% 0.46% -1.31% 1.13% 0.75% 0.52% 0.03% -0.67% -1.00% -3.03% 0.31% -3.68%

2015 0.85% 0.01% 1.63% -0.43% 0.92% -0.20% 0.37% -1.75% 0.12% -0.80% 0.72% 0.84% 2.24%

2014 -1.03% 0.50% -0.20% -0.17% 0.84% 0.11% -0.13% 0.41% 0.59% 0.28% 1.36% 0.45% 3.02%

2013 0.67% 1.42% 2.03% 1.65% -1.10% 0.04% -0.35% -1.46% 1.59% 0.64% 0.68% 0.73% 6.66%

2012 0.36% 0.97% 0.81% -0.06% -0.79% 1.28% 1.55% 0.09% -0.16% 0.24% 0.61% 1.08% 6.12%

RAM Long/Short Emerging Markets Equities Strategy - Net Monthly Performance

Note: RAM Long/Short Emerging Markets Equities Fund Class I-USD (performance net of 1.5% of MF + 20% of PF)





Appendix III


2017 0.51% 0.47% 0.58% 0.21% 1.90% -0.04% 0.99% 1.71% -1.54% 0.94% -0.18% -0.71% 4.88%

2016 -0.22%

RAM Long/Short Global Equities Strategy - Net Monthly Performance

Note: RAM Long/Short Global Equities Fund Class PI-USD (performance net of 1.0% of MF + 15% of PF)



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