Possibilities in Futures Trading - Quantitative Analysis without Historical Pricing [Webinar] - 22 Apr. 2021 Description: Is it possible to build a profitable trading model, using no historical data, no fundamental data, no stop loss and no target price? This presentation aims at introducing a potentially new way of approaching market analysis which is currently only applied by futures trading professionals. Quantitative Analysis is traditionally based on historical data, which can be analyzed visually in a chart or mathematically using time series analysis. There is however no reason for this to be a limitation. Using the information found in the term structure of futures markets we can extend our quant toolkit and broaden our scope. The key point of this presentation will be to investigate if there is a predictive value in this term structure information and if we can trade based on nothing but this curve. --------------------------------------------------------------------- SESSION OUTLINE - Key Question: Can we construct a profitable quantitative trading model without the use of historical time series, fundamental data or macro data? - Futures mechanics explained - What makes them unique - Term structure explained - Issues and Opportunities - Measuring term structure - Identifying Interesting Situations - Trading term structure - Constructing and Testing Rules - Q&A --------------------------------------------------------------------- ABOUT THE SPEAKER Andreas Clenow (Chief Investment Officer, Acies Asset Management Group, Switzerland) Andreas Clenow is the Chief Investment Officer of Acies Asset Management group, based in Zurich, Switzerland. Having started out as an IT entrepreneur in the 1990s, he joined Reuters Consulting in 2000 as head of their Nordic financial consultancy. At the time he left Reuters he was heading up their global financial modelling team out of Geneva, Switzerland. After this, he went on to found and manage multiple hedge funds as well as to author three international best selling books. As CIO of Acies group he now oversees the investment and allocation of a nine-figure (USD) asset base across all major asset classes and investment products. --------------------------------------------------------------------- Important Links Find more info on - https://quantra.quantinsti.com/ Follow us on LinkedIn: https://www.linkedin.com/company/goquantra Like us on Facebook: https://www.facebook.com/goquantra/ Follow us on Twitter: https://twitter.com/GoQuantra Follow us on Instagram:https://instagram.com/goquantra

1. Futures Trading: Quantitative
Analysis without Historical
Pricing

2. About QuantInsti
Team
We are a group of traders, coders, analysts who love to teach and share their experience. QuantInsti was started by
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To bridge the gap between theory and practice in Algorithmic Trading.
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All retail investors use Quant & Algorithmic trading by upskilling themselves and by simplifying technology.

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4. CIO and partner of ACIES Asset Management,
overseeing all investment strategies over a nine
figure asset base. Author of Futures Trading:
Concepts & Strategies on Quantra and
international best seller Following the Trend
(Wiley 2013), Stocks on the Move (2015) and
Trading Evolved (2019).
Speakers Profile
Ishan Shah leads the content & research team at
Quantra by QuantInsti. Prior to that, he worked
with Barclays in the Global Markets team & with
Bank of America Merrill Lynch. He has a rich
experience in financial markets spanning across
various asset classes in different roles.
Ishan Shah
Quant Researcher at QuantInsti
Andreas Clenow
Chief Investment Officer, ACIES Asset
Management AG

5. Trading the Curve
Quant Trading without Time Series
Andreas F. Clenow

6. Extending the Quant Toolkit
Can we Build a Quantitative Trading
Model without Fundamental or Time
Series Data?
“I need to think about the future and consider my options.” – Nick Leeson
6
Strictly Confidential – Not for distribution or duplication. Not an offer to invest. Risk of loss exist.
www.clenow-research.com

7. Presentation Outline
“I need to think about the future and consider my options.” – Nick Leeson
7
Strictly Confidential – Not for distribution or duplication. Not an offer to invest. Risk of loss exist.
Futures
Mechanics
Introducing
Term
Structure
Term
Structure
Problems
Term
Structure
Opportunities
Measuring
Term
Structure
Trading Term
Structure
www.clenow-research.com

8. Only way to Gain, is at someone else’s Expense
“Money itself is not made or lost, simply transferred” – Gordon Gekko
8
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PvP
Zero Sum
Game
Someone’s
Long,
Someone’s
Short
Settled
Every Day
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9. Futures Chain
Introducing Term Structure
9
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10. Futures Chain
Introducing Term Structure
10
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www.clenow-research.com

11. Multiple Contracts Traded at the Same Time
Different delivery month, different price
11
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www.clenow-research.com

12. Implications of Multiple Contracts
Issues with Limited Life Span
12
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No Long
Term
Data
Rolling
Required
Contract
Selection
Futures
≠
Underlying
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13. The Underlying and the Futures are not the Same
Futures are not Spot
13
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Most underlying
are not tradable.
Underlying and
Tradable price
can differ
substantially
Analysis of
Underlying often
Nonsensical.
Analyze what
you Trade!
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14. Analyze what you Trade
The Underlying is Rarely Tradable
14
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15. Trade what you Analyze
The difference can be significant
15
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16. Term Structure
Contango and Backwardation
16
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17. What Term Structure Implies
Directional Bias of Term Structure
17
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18. Quantifying Term Structure
Crunching the Numbers
18
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Solution: Implied Yield
Need to
Quantify
Need to
Compare
Visual
won’t
Help
Dollar
Value
won’t
help
Percent
won’t
help.
www.clenow-research.com

19. Implied Yield Example
Crunching the Numbers
19
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Delivery Price Days Pct Annualized Open Interest
201805 91.4 0 - - 187,349
201807 92.1 67 -0.8% -4.0% 105,794
201809 96.4 127 -5.5% -14.7% 84,044
201812 97.2 190 -6.3% -11.7% 31,451
201903 99.1 281 -8.4% -10.7% 11,574
201905 99.5 371 -8.9% -8.6% 8,424
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20. Calculating Implied Yield
The Obligatory Formula
20
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𝑃1 = 𝑃𝑟𝑖𝑐𝑒 𝑜𝑓 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐 𝐶𝑜𝑛𝑡𝑟𝑎𝑐𝑡
𝑃0 = 𝐹𝑟𝑜𝑛𝑡 𝑜𝑟 𝑆𝑝𝑜𝑡 𝑃𝑟𝑖𝑐𝑒
𝐷1 = 𝐶𝑜𝑛𝑡𝑟𝑎𝑐𝑡 𝐷𝑎𝑦𝑠 𝑡𝑜 𝐸𝑥𝑝𝑖𝑟𝑦
𝐶𝑜𝑛𝑡𝑟𝑎𝑐𝑡 𝐼𝑚𝑝𝑙𝑖𝑒𝑑 𝑌𝑖𝑒𝑙𝑑 =
𝑃0
𝑃1
365
𝐷1
− 1
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21. Constructing a Term Structure Model
Rubber, meet Road
21
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• Implied Yield holds predictive directional
value.
Hypothesis
• Try variations of using IY for portfolio
construction.
• Looking for indication of predictive value –
Not for Amazing Super Magical Returns
Model.
Test
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22. Balanced Fixed Distance
Rubber, meet Road
22
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Always 5 long and 5 short.
Always same distance out.
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23. Term Structure Ranking Table
Rubber, meet Road
23
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Backwardation
Contango
Front 12M Out Implied Yield
LGC17 LCG18 15.9%
RBG17 RBG18 2.8%
SBH17 SBH18 2.8%
NGG17 NGG18 1.9%
CTH17 CTH18 1.3%
_SF17 _SF18 1.0%
HGH17 HGH18 -0.8%
GCG17 GCG18 -1.5%
HOG17 HOG18 -4.3%
CLG17 CLG18 -5.0%
KCH17 CKH18 -8.5%
_CH17 _CH18 -9.7%
_WH17 _WH18 -14.4%
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24. Measuring Full Year Carry
12 Months Fixed – 5x2 long short
24
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Annualized
Return
10.8%
Max
Drawdown
-34.4%
Annualized
Volatility
20.0%
Sharpe Ratio 0.61
www.clenow-research.com

25. What about Nine Months?
9 Months Fixed – 5x2 long short
25
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Annualized
Return
15.3%
Max
Drawdown
-21.1%
Annualized
Volatility
22.5%
Sharpe Ratio 0.85
www.clenow-research.com

26. Lowering to Half Year
6 Months Fixed – 5x2 long short
26
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Annualized
Return
21.1%
Max
Drawdown
-29.0%
Annualized
Volatility
22.5%
Sharpe Ratio 0.96
www.clenow-research.com

27. Casting a Wider Net
Rubber, meet Road
27
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No Stops.
No Targets.
No Indicators.
No History.
www.clenow-research.com

28. Contract Selection
Rubber, meet Road
28
Strictly Confidential – Not for distribution or duplication. Not an offer to invest. Risk of loss exist.
Ticker Expiry Price Implied Yield
LCG0 28 February 2020 119.73
LCG1 26 February 2021 120.00 -0.23%
LCJ0 30 April 2020 118.25 7.57%
LCJ1 30 April 2021 121.28 -1.09%
LCM0 30 June 2020 110.28 27.63%
LCM1 30 June 2021 114.50 3.39%
LCQ0 31 August 2020 109.40 19.47%
LCV0 30 October 2020 113.28 8.60%
LCZ0 31 December 2020 117.53 2.23%
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29. Initial Model
Requiring 15% minimum contango or backwardation
29
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Annualized
Return
30.1%
Max
Drawdown
-35.9%
Annualized
Volatility
31.9%
Sharpe Ratio 0.98
www.clenow-research.com

30. Lowering Backwardation Requirement
Min 15% Contango, 0% Backwardation
30
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Annualized
Return
19.2%
Max
Drawdown
-25.2%
Annualized
Volatility
15.7%
Sharpe Ratio 1.20
www.clenow-research.com

31. Pointing in the Right Direction
Simple Model Variations
31
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32. Not your Average Trading Model
Different Approach
32
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No Stop No Target No Time
Series
No Indicators No
Fundamentals
www.clenow-research.com

33. Key Learning
What to Take Away
33
Strictly Confidential – Not for distribution or duplication. Not an offer to invest. Risk of loss exist.
Expand your
Toolkit
Look Beyond
the Classics
Alternative
Analytics
Look to
Uncorrelated
Returns
Think
Outside the
Box
www.clenow-research.com

34. Implied Yield as a Directional Indicator
Quo Vadis?
34
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Directional
Force
One of
Multiple
Forces
Headwind /
Tailwind
Potential
Indicator
Implied Yield
to Measure
Force
www.clenow-research.com

35. 35
Go Replicate the Research
Strictly Confidential – Not for distribution or duplication. Not an offer to invest. Risk of loss exist. 35
Where to go from here
www.Clenow-Research.com
Verify what you’re told.
Model ideas and test
them.
Pick a solid backtesting
environment.
Get proper data.
Don’t take my word for it.

36. Q&A Session

37. Webinar Recording

38. Thank you!