mer€¦ · mer disclaimer algodynamix ltd. (the company) is a limited company registered in...
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Dis
cla
ime
rDisclaimer
AlgoDynamix Ltd. (the Company) is a limited company registered in England andWales, with registration number 08853134 and with a registered address at 23Skyline Village, Limeharbour, Canary Wharf, London E14 9TS, United Kingdom
The Company is not a Registered Investment Advisor, Broker/Dealer, FinancialAnalyst, Financial Bank, Securities Broker or Financial Planner. The Information inthis document is provided for information purposes only. The Information is notintended to be and does not constitute financial advice or any other advice, isgeneral in nature and not specific to you. Before using the Company’sinformation to make an investment decision, you should seek the advice of aqualified and registered securities professional and undertake your own duediligence. None of the information in this document intended as investmentadvice, as an offer or solicitation of an offer to buy or sell, or as arecommendation, endorsement, or sponsorship of any security, company, orfund. The Company is not responsible for any investment decision made by you.You are responsible for your own investment research and investment decisions.The Company will not be responsible for updating any information containedwithin these document and opinions and information contained herein aresubject to change without notice.
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▪ Company started in 2013, incorporated in January 2014
▪ Our technology is based on many years of research at Cambridge University
▪ We have offices in London (HQ), Cambridge (Technology) and Frankfurt (support)
▪ Investment banking and asset management clients all over he world
▪ Financially backed by institutional investors including Amadeus Capital Partners
Coverage:
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Lo
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Dr
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Multi asset portfolio manager:
• Discretionary equites
• Systematic equities with AlgoDynamix
• Corporate & Government debt
• Illiquids (start-ups)
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An
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Historical data, research notes etc…B
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Ou
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• The AlgoDynamix risk analytics engine is based on sophisticated ‘deep data’
agent-based algorithms scanning - in real-time - multiple quantitative
primary data sources (order books).
▪ These algorithms analyse the dynamic behaviour of market participants, i.e.
buyers and sellers, through our unsupervised machine learning technology
which clusters them based on common feature sets.
▪ Noise classification, cluster identification and behavioural finance theory are
part of our unique core capabilities.
▪ Market anomalies occur when large clusters of buyers or sellers are
identified, note that in the following slides everything still ‘looks normal’ but
the deep data insights reveal a very different picture.
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Underlying technology (behavioural)
→‘Cluster the limit order book’
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AlgoDynamix analytics engine▪ Software identified
´clusters` of user-behaviour
▪ Within each cluster, users have comparable feature sets
▪ Cluster identification amongst noisy buyers and sellers is part of our unique core capabilities
SellerBuyer Cluster
No
rma
l d
ay
Time16 Jun 18 Jun 20 Jun 21 Jun
170
160
150
180
14 Jun
USD
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AlgoDynamix analytics engine▪ Software identified
´clusters` of user-behaviour
▪ Within each cluster, users have comparable feature sets
▪ Cluster identification amongst noisy buyers and sellers is part of our unique core capabilities
SellerBuyer Cluster
Up
Fla
g
Time
170
160
150
180Up Flag: market going up
Price S&P 500 USD
16 Jun 18 Jun 20 Jun 21 Jun14 Jun
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AlgoDynamix analytics engine▪ Software identified
´clusters` of user-behaviour
▪ Within each cluster, users have comparable feature sets
▪ Cluster identification amongst noisy buyers and sellers is part of our unique core capabilities
SellerBuyer Cluster
En
d p
oin
t
Time16 Jun 18 Jun 22 Jun 24 Jun14 Jun
170
160
150
180Price S&P 500 USD
Up Flag: market going up +3% End Flag: no more market information
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Pro
du
ct
de
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→ Up Flags, Down Flags, End Flags across most financial instruments and asset classes, see also next slides.
→ Client specific trading strategies are developed on the back of these directional insights.
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Ex
am
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s:
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isa
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Re
su
lts,
pra
cti
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l tr
ad
ing
0
50
100
150
200
250
02/01/2014 28/05/2014 17/10/2014 13/03/2015 05/08/2015 28/12/2015 20/05/2016 12/10/2016 08/03/2017 31/07/2017 20/12/2017 16/05/2018 08/10/2018
RN-1 versus S&P 5005 Year performance
Results (live): RN-1 S&P 5002018 Returns +6.01% -4.38%Volatility ~17% ~17%
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Investment Banking
• Structured products• Market insights• Trade execution flow• Market making
Asset Management, typically +3 to 5%/year
• Hedging• Alpha capture• Factor model selection• Sector rotation
Corporate treasury departments, +5%/year
• FX exposure• Fixed Income• Working Capital optimisation
-
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
180.00
200.00
2 January 201224 May 201211 October 20127 March 201329 July 201317 December 201313 May 201430 September 201423 February 201515 July 20152 December 201527 April 201615 September 20166 February 201730 June 2017
Hedged versus unhedged EURO STOXX 50 U
se
ca
se
s:
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Th
an
k y
ou
! g
o a
nd
try
it
ou
t
• Workshop with registration of selected users
• Selection of financial instruments*
*We do not require any internal or proprietary data sets
• 8 weeks access to risk analytics software
• Ongoing support
AlgoDynamix Proof of Concept