Hadrien Darmon
Equity Portfolio
Quantitative strategies Market neutral
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.
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
‒
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.
3
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
4
• 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
Risk
management
Portfolio
construction
Experienced
PM
•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
PnL per Pockets
|
Low to High
|
Mid
|
High to Low
|
versus Market
|
correlation
|
correlation
|
correlation
|
transition
|
|||
Relative Value
|
++
|
++
|
+/-
|
Opportunities
|
++
|
+/-
|
+++
|
6
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
1. Daily news scoring models on European
Single stocks within SXXP Index members
2. 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)
3. Multi technical factors model on European
and US Single stocks rebalanced weekly
4. Mean reversion and technical models on
blue chip European single stocks rebalanced weekly
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.
-
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.
Date
|
Return on
|
AUM
|
Equity capital
|
AUM
|
|||
2009 ING
|
18,2%
|
AUM = $30M
|
$30M x $30M
|
2010 ING
|
16,6%
|
AUM = $30M
|
$30M x $30M
|
2011 Visium AM
|
18,8%
|
AUM = $25M
|
$25M x $25M
|
2012 Visium AM
|
15,6%
|
AUM = $25M
|
$25M x $25M
|
2013 Visium AM
|
8.7%
|
AUM = $100M
|
$50M x $50M
|
2014 Visium AM
|
7.4%
|
AUM = $200M
|
$100M x $100M
|
2015 Visium AM
|
5%
|
AUM = $200M
|
$100M x $100M
|
10
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
11
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 :
➢100% ownership on our IP
|
12
|
|
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 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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