📄 Extracted Text (1,115 words)
Alex Gerasev
Bounded Tradable Processe
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Confidentiality
■ Information in this presentation is strictly
private & confidential
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Background
■ Strategy live at Buttonwood Group Trading (BGT)
07/2011-1o/2012 (16 months); back-tested from
01/2006 with similar performance results
■ Founder of Quanterra Advisors LLC and developer of
quantitative trading strategies since 06/2010
■ Project Manager/ Subject Matter Expert, Global
Banking & Markets at RBS and ABN AMRO 2001-2010
■ M.Sc. in Financial Mathematics, University of Chicago
■ B.Sc. in Physics & IT, Novosibirsk State University
■ Research atVEPP-4 electron-positron collider of
Novosibirsk Institute of Nuclear Physics (11 GeV
energy range)
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Track Record
Buttonwood Group Trading, 07/2011 — 10/2012
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Live Track Record Ptc
Date range 07/2011 —10/2012 (16 months)
Reserved capital 3.5m
Average utilized capital (AUC) 1.4m
Available leverage 15X
Reinvestment of gains into the strategy No
Asset classes Equities (85%); futures (15%)
Total net PnL o.97m (67.5% return on AUC)
Positive months 13 (81%)
Negative months 3 (19%)
Best month O. 27M
Worst month - 0.07M
Sharpe ratio 2.67
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Live Track Record - BGT
Monthly Net PnL
300,000.00
250,000.00
200,000.00
150,000.00
100,000.00
50,000.00
•
0.00
2011-07 zon-o8 2011-09 2011-10 2011-11 2011-12 2012-01 2012-02 2012 -04 2012-06 2012-07 2012-08 2012-09 2012-10
-50,000.00
-100,000.00
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Live Track Record BG
Cumulative Net Return on AUC
80.00%
70.00%
6o.00%
50.0o%
40.00%
30.00%
20.00%
io.00%
o.00%
2011.07 2011.08 2011.09 2011.10 2011.11 2011.12 2012.01 2012-02 2012.03 2012.04 2012.05 2012.06 2012-07 2012.08 2012.09 2012.10
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Live Track Record — BG7
Comments:
• Reinvestment of strategy gains back into the
strategy would have resulted in significant
performance improvement due to compounding
(total return on AUC 89.9% vs. 67.5%)
• Strategy performance was negatively impacted
on at least 3 occasions by emergency re-allocation
of capital to other traders
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Back -Testing Track Record
01/2006 - 12/2012 (84 months)
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Back-Testing Track Record
Date range 01/2006 - 12/2012 (84 months)
Reserved capital i.om
Average utilized capital (AUC) o.62m
Available leverage isx
Reinvestment of gains into the strategy No
Asset classes Same as live trading
Annualized net PnL 0.57m (57.8%)
Positive months 70 (83%)
Negative months 14 (17%)
Best month 0.42M
Worst month -0.17M
Sharpe ratio 3.12
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Back-Testing Track Record
Observations:
■ Slightly better performance vs. live performance
during 07/2011 —10/2012 period (no capital re-
allocation issues as mentioned above)
• Slightly better overall performance (higher
average volatility)
• Market volatility results in better performance;
best years for the strategy were 2008 and 2009
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Strategy Description
Bounded Tradable Processes
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Strategy Description: Bounded
Tradable Processes
"Process" can be
single financial instrument (stock, future, option, FX, etc.)
two-legged spread S = X— aY, where X and Yare financial
instruments (stocks, futures, options, FX, etc.)
three-legged spread S = X— aY— bZ, where X, Y, Z are
financial instruments
complex combination spreads e.g. S = aX/Y, S=aX —bY/gZ,
etc.
"Tradable" means that all components of S can be
traded at any time in required quantities (given
liquidity constraints and other technicalities)
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Arbitrage Bounds
Tradable Process that has lower, upper, or both lower
and upper arbitrage bounds can be unwound at a pre-
determined price
Various "mechanics" enforcing bounds
Asset swap ("fungibility"): X may be swapped for Y at
holder's discretion — ensures that X> Y; if X < Y, buy bunch
of X, swap for Y and sell Yfor higher price and riskless
profit ("pure" arbitrage)
Multi-step asset swap: similar to above, but involving
multiple steps to unwind complex spread at pre-
determined price
"Hard" bounds — guaranteed to be able to unwind the
process at a known price
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Non-Arbitrage Bounds
Process should not go beyond certain values due to
fundamentals; however there is no way to unwind if it
does
Example: "asset quality"
Equity with voting rights vs. equity without voting rights
Higher-grade commodity vs. lower-grade commodity
Senior vs. subordinated debt
Once the process moves beyond the bound and
information spreads through the market, the relationship
would typically get restored as participants buy superior
asset for less, or holders of inferior asset replace it with
superior asset while booking a profit
More dangerous than arbitrage bounds — reflect in
position sizing (e.g. io% of arbitrage-bounded trade)
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Example: Arbitrage Bounded
Process ("hard" bound at zero)
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Example: Non-Arbitrage Bounded
Process ("soft" bound at zero)
25
20
15
10
5
0
S
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Approach to Trading
■ The closer the process gets to its bound, the
bigger the position with i00% of target
position size right at the bound
■ As the process moves away from the bound,
reduce position size
■ As the process oscillates we generate PnL
buy buying lower and selling higher
■ The schedule of process values and
corresponding position sizes is known as
loading curve
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Loading Curve Example
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Profitability Analysis
Volatility is good!
Great opportunities when position can be
entered or increased close to the bound and
unwound as the process moves away
Worst-case scenario: process approaching its
bound with very low volatility and staying at
the bound for prolonged period of time
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Other PnL Contributors
■ Market making
■ Intraday fluctuations
■ Capturing market impact
■ Mean-reversion
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Loading Curve Optimization
■ Goal: create a loading curve shape that would
• maximize PnL
• minimize drawdowns
• minimize PnL volatility
• maximize Sharpe ratio
• other considerations
■ Highly computationally-intensive
optimization techniques based on historical
data
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Competitive Advantage
Space not nearly as crowded as pure
arbitrage trades
Requires significant R&D efforts that further
reduce competition
Unique and highly computationally intensive
process of model calibration and
optimization
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Capacity and Scalability
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Existing Product Groups
14 product groups (tradable processes) are
fully set up and are available for trading
Estimated capacity without adverse impact
on performance: up to io —15m
Further scalability with some performance
impact: up to 20-25m
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Adding New Product Groups
New product groups (tradable processes)
may be added
Approximately 2 months of R&D per product
group
Many interesting opportunities in
international markets
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Expanding Across Asset Classes
■ Same quantitative research methods may be
applied to other asset classes and across asset
classes
■ Virtually unlimited scalability
■ Some ideas:
• Commodity calendar spreads or spread options +
physical storage
• Inter-commodity spreads + physical asset (refinery,
power plant)
• Convertible debt
• Debt + CDS
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Summary
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Summary
Time-tested strategy with excellent
performance characteristics
Market-neutral with no correlation with the S&P
500
Highly scalable
Diversified portfolio of trades already live
Robust quant research framework
Large search universe for adding new product
groups
Further scalability by expanding across asset
classes
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ℹ️ Document Details
SHA-256
259400f7ea820e1cb6a1eb2355bd67707ff90bf823cea4ef46fba984ef7375ba
Bates Number
EFTA02725017
Dataset
DataSet-11
Document Type
document
Pages
29
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