Hadrien Darmon

Equity Portfolio

Quantitative strategies Market neutral

1 Investment overview

1.1 Investment strategy:

– Equity Market neutral (+/- 10% net Delta-Beta)

– Systematic and quantitative (proprietary models)

– Low (daily rebalancing) to mid frequency (10 days average holding position)

– Average Return 10 to 15% – SR = 2.5 to 3 – portfolio running lived for the last 6 years on the buy side.

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1.2 Investment approach:

– Quantitative and disciplined investment process

– Qualitative investment methodology and Systematic risk management

1.3 Investment universe:

– Underlying : stocks and indices

– Product : cash and index futures (90% of the portfolio), only listed and highly liquid products

– Region: Europe (85%) and US markets (15%)

– Liquidity : Highly liquid underlying (Portfolio liquidity ratio: less than half a day) – Portfolio highly scalable 2

1.4 Investment Process :

‒ My portfolio is built around uncorrelated systematic strategies classified in 2 pockets :

Relative value (85% of the portfolio)
Opportunities (15% of the portfolio)
‒ The portfolio is market neutral : very little net delta-beta (though less 10% on the whole portfolio).

‒ The process is quantitative and systematic : each of the strategies is quantitative driven, following its own signals and indicators. Between them, there is little to no correlation.



‒ Risk management is at the core of my portfolio management, following a disciplined risk management per position and for the entire portfolio. A risk reduction process (position sizing down) is triggered in case of drawdowns.

‒ A relevant ratio VaR utilization per profit target is maintained in order to optimize our risk utilization. We are running 70% of our VaR limit on average to have a risk buffer in distressed markets to capture the best opportunities.

‒ Risk parameters used on the portfolio are a VaR (99%, 1Y historical) capped at 1,5% of the NAV, stress test (-5%, -10% Spx) and 10% net Delta-beta limit of the NAV.



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2 Universe

The portfolio is solely focused on:

➢ Equities

➢Exclusively Single stocks, ETF and indices

➢ Universe : Europe and US

➢80% Europe /20% US repartition

➢Strategies run on a geographical area / index basis

➢ Highly Liquid Stocks and futures ➢Stoxx 600 – SXXP in Europe

➢SPX, Russel 2000 and Nasdaq in the US ➢Top European futures

➢Top US futures

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3 Alpha Combination

• My Alpha stems from focusing on the final product, ie the portfolio

I have built a multistrategy quant portfolio, adopting the multi manager/ funds approach

4 Portfolio Construction

•the alpha generation comes from combining :

•Portfolio construction : Focusing on a portfolio not just combining a mix of profitable strategies

•Strategies selection : 2 pockets a strong core long/short quant pocket and a smart opportunistic one

•Strong individual strategies are selected with the best risk adjusted returns for the portfolio

•the focus is therefore on volatility and drawn-down of the portfolio

•Focusing on cross-strategies correlation, notably during their respective draw-down and high volatility periods

•Backtesting them on a 15 years horizon basis and have run them live for more than 7 years on the buy-side

5 Strategies Selection

5.1 Relative value : Quantitative long / short equity (80% of the portfolio)

Composition : Some example of the independent and uncorrelated sleeves rebalanced daily to bi monthly

Daily news scoring models on European Single stocks within SXXP Index members
Multi fundamental factors model on European and US Single stocks rebalanced weekly
Basket of 100 equally weighted single names long versus basket of 100 equally weighted short (Cash)

Multi technical factors model on European and US Single stocks rebalanced weekly
Mean reversion and technical models on blue chip European single stocks rebalanced weekly
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5.2 Opportunities (20% of the portfolio)

Methodology :

This pocket is driven by quantitative triggers and is not always fully invested. The approach is based on



quantitative indictors while seeking asymmetric risk/reward opportunities. 2 sub-strategies are in this

pocket. For each position a take profit / stop loss trigger is defined at inception as well as a time buffer.

Composition :

– Market pattern : Spot versus Volatility (smart delta)

SPX Futures against VIX futures (delta-beta neutral) takes advantage of the asymmetric pattern spot/volatility in certain environment. The investment decision is driven by a quantitative model.

– Mean reverting Spread : VIX Futures spreads and V2X (only 2nd or 3rd maturity)

Smart alpha generation by exploiting the mean-reverting property of those spreads thanks to a multi-variables proprietary model.



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5.3 The Portfolio : advantage of 2 pockets combined

– Both pockets complement one another allowing us to deliver a positive steady PnL profile exhibiting low volatility.

– Most importantly, in distressed markets, it allows to take advantage of the best mispricing and opportunities.

– With the current environment, the end of synchronized QE among central banks, we should keep seeing higher volatility and spike of correlation which is very favourable to our portfolio.

6 Performance

7 Risk Model

Risk management and discipline are key to the investment process. It translates at different levels:

➢ Money Management Rules

➢ Clear hard limits on both portfolio and strategies levels

➢ Exposure constraints









Delta / Beta < +-10% NAV

Factor constraints (Momentum, value, growth, low beta…)

Country/ Sectors FX exposure

➢ Liquidity





100% NAV that can be liquidated in 1 day Taking into account volume per stock selection

➢ Scenario

➢ Market/ factor shocks and stress test scenario on the portfolio

➢ Historical VaR and Monte carlo VaR

8 Data / IT / Execution / IP/ Reporting

We have integrated the different stages to our plug and play process and have limited external requirements




➢In terms of data :

➢Requirement : Bloomberg and Thomson Reuters (Data Scope…)

➢Always working with other data vendors (might later in the future be added if alpha discovery)

➢In terms of IT :

➢Developped in Visual Basic / R since inception and progessively moving to Python ➢Highly adaptive internal system to be plug and play -> quick set up

➢In terms of Execution :

➢DMA of Bloomberg’s : EMSX (flexible)

➢No need of special connectivity (low latency, high speed)

➢In terms of Reporting :

➢Reconciliation Front office management system with PB account

➢In terms of IP :



9 Team

Key facts :

➢ more than 12 years of experience running money, half of it on the buy-side

➢ 7 years running the portfolio on the buy side

Profiles :

Hadrien Darmon, Portfolio manager – Quantitative Equity L/S

Hadrien has 12 years experience in equity trading with a focus on quantitative strategies. He started his career in 2005 working for the proprietary exotic desk at Societe Generale. Then he moved in 2009 to the proprietary trading desk of ING prior to joining Visium Asset Management.

Hadrien has a quantitative background, he holds a master degree of applied mathematics to finance from Ecole Centrale Paris, a top tier French engineering school, as well as a master of banking and finance at University Pantheon-Assas Paris II.

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