• Successes. – Developed and implemented first deep-learning applications providing a massive improvement in analytical power by leveraging previous years hardware purchases – Acceleration in pipeline of third party cutting edge quantitative research to implement – Impressive performance from improved security selection criteria – Further improved the fundamental and technical criteria for security selection – Corrected and refined machine learning methods in asset allocation – Further improved econometric criteria in asset allocation – Developed new software to access better data sources – Now accepting client defined portfolio universes (asset allocation, ESG, religious etc.) – First venture capital investment • Fails. – Single digit net return for year (annualised double digit return over three years) – Poor asset allocation due to not applying correct procedures for machine learning – Natural language processing sentiment analysis not developed further
Between Wednesday 28th August and Wednesday 11th September (the last 10 bars in the charts below) the S&P 500 Index had a mild recovery to near record highs on light volume.
However over the same period the DJ US Thematic Market Neutral Momentum index fell steeply, in it’s most violent move ever.
Whilst the DJ US Thematic Market Neutral Value index recovered strongly.
Further during the period we incurred several security specific news items that were detrimental to our positions.
Securities in our AI selected global equity strategy have a minimum holding period of three months and profitable positions suffered from this rapid reversal. The AI does however assesses both momentum and value and will adapt (over time) to changes in thematic rotation whilst not suffering behavioural issues of short term misfortunes.
Broker statements are always available for inspection.
Bitcoin has a market capitalisation of
approximately US $200bn with 24 hour trading 7 days a week, making it
the perfect TRADING instrument.
At present the value of mining a
bitcoin, is sustained by the price of bitcoin, which is sustained by
net new money into the market, which is sustained by……(insert
your own ideas).
When all 21m bitcoins have been mined
or by 2140, miners who verify transactions will no longer be rewarded
for mining but only by the transaction fee they can charge.
However the cost in electricity to do
one transaction in bitcoin is the same as approximately 400,000 Visa
For bitcoin use as a transaction medium
to be valid when the last coin is mined requires huge productivity
falls from Visa to equate the two systems.
Or the protocols of bitcoin can be
changed by 95% support from the last 2,016 miners, to lower the cost
of validation. Either by increasing the amount of bitcoins, i.e. a
reduction in the value of a bitcoin or, they could change the method
for validation (the highly praised algorithm).
Further approximately 80% of mining
pools are in China, making bitcoin protocol susceptible to that
countries political system.
Whilst we have been a huge successful
INVESTOR in the Chinese economy it has been with companies that ADR
list, therefore providing transparent and recognised reporting.
Unfortunately for us, bitcoin remains an instrument too far.
First Published In FOTT Family Office Magazine Beijing – June 2019
The Turing machine that broke the enigma code during WWII was the birth of Artificial Intelligence (AI). However since then, the adoption of AI has mainly been confined to the manufacturing, transportation and distribution sectors; with the rise of robots that build Japanese cars and stack Amazon warehouses. But now AI is moving leaps and bounds into the service sector including: game playing, self driving vehicles, facial recognition, customer service chat bots, language translation and even medical surgery.
AI consists of two strains: machine
learning and deep learning. Deep learning seeks a statistical
inference from a small part of the data and then apply all that it
has “learnt” upto that stage to the next small part until all
parts have been examined, similar to the way a human will adapt from
experience. Machine learning seeks to extract a statistical inference
intermediately from the whole data. Your preference would depend on
whether you believe the way humans learn is superior, although there
are statistical methods of measurements that provide a guide as to
which gives the best results based on the PREVIOUS data. The
resources to develop both deep and machine learning are: free, open
source and available on-line to all who wish to utilise.
The benefit of AI is that it can
provide: repeatable results, irrespective of the behavioural bias of
humans and with unimaginable productivity. Repeatable results allow
an amount of certainty as to performance in the future. A lack of
behavioural bias provides results without human failings such as:
hangovers, partner disputes, career pressure, saving face and
emotional attachment to incorrect decisions. However where AI comes
into its own is handling exponential growing amounts of data and
choices, that our 10,000 year old brain design is not equipped for.
An early adopter of AI in investment
management was the Medallion Fund of Renaissance Technologies with
spectacular results for over 30 years. However the majority of
adoption has been on the sell side with automated customer service
departments and robo-advisors that provide asset allocation
portfolios to retail markets. The downside of the recent adoption
being, data scientists and computer programmers extract the most
perfect result from the available data without any understanding as
to whether the input data is correct or relevant to the result
(“garbage in garbage out”) or, if the model has any intellectual
rigour. Leading to failure once the program goes “live”.
Market participants can either accept
or reject the relevance of AI on the investment industry, I can only
give you our story……
Way back in autumn 2016 as CIO of a
Swiss based multi-family office it was out of scientific curiosity
that I attended a seminar on AI coding (computer programming). It was
given by a former CERN employee, who discussed how they discovered
“The God Particle” or “Higgs-Boson”, the smallest sub-atomic
particle for which I still have a still have an early edition of the
same named book. However as someone steeped in investment education
and not quantum physics it appeared easier to utilised these
techniques in my chosen professional field, any by the end of that
year we were ready to go live.
Initially we had a macro model for the
US economy that provided basic asset allocation. Our model accessed
the limitless information provided by Federal Reserve Banks and the
rest of the internet. The trick was knowing which information was
relevant to use. In the last thirty years we already had two “new
paradigms” called by the economic community. And as someone who
skipped his undergraduate econometric exam due to never getting
beyond being asked for a password on the university computer, this
could have been a show stopper. However in 2008 our office had
already delivered a 23% investment return against the 45% fall in the
S&P 500, that was the result of: experience in several previous
economic cycles, admitting and learning from mistakes, strong
outperformance of managing a multi sector portfolio for a big four UK
bank, and actually attending and getting some decent grades in
international, monetary and fiscal economic undergraduate exams.
Our US economic model actually gives us
an eighteen month forward forecast, which allows us adjust the
portfolios in a timely manner, and back in early 2017 we were still
very bullish. Due to our very strong stock picking abilities (long
and short) the next stage was to utilise the AI to assist in this
task. We took the universe of stocks with a US, ADR, Canadian or UK
listing and a market capitalisation of over $1billion, that is over
6000 stocks. Again the challenge was to choose the relevant input
data, be it: fundamental, technical, industry, company or independent
news, as well as the multiple other sources, for example,
outperformance against Google “usual customer attendance” matrix.
Our limiting factor was the intel i5 core processor that our AI was
using (we wish to avoid the cloud due to security issues), which
again meant that we could only choose a few most relevant inputs.
This resulted in the very strong appearance of Chinese stocks, some
of which produced returns of nearly 200% over the year. It was an
obvious step to develop an AI macro model of the Chinese economy,
which by coincidence was the second largest. However during 2017 our
US economic model started to flash recession meaning we would soon
need to move to fixed income and so also developed an AI model for
the US 10 treasury.
Despite our massive risk adjusted
performance of 2017, in 2018 we had a little underperformance as we
transitioned to the cautious portfolio, caused mainly by the poor
performance of our individual stock positions. We reprogrammed our
stock picking AI to allow it to make better decisions given the stage
in the economic cycle and this year it is producing absolute returns
on a monthly basis whilst being net short the market. Our biggest
problem is what to do with all our cash, especially given our AI US
10 treasury view is not positive (in contrast to our traditional
methods), so we are investing in 3 month corporate bonds.
After the initial success we had an
obvious capital requirement to invest in internal hardware,
purchasing the top of the range “gaming” computers with the best
CPU and GPU. In AI the CPU is used for the machine learning software
and the GPU is used for the deep learning software. We have further
developed, “natural language processing” AI to provide sentiment
analysis on news flow especially transcripts, reading and deciphering
in a matter of seconds as opposed to the hours a human would take.
So what is my job as the CIO of an AI
driven MFO? It is both master and servant; as servant it is to
ensure that the data the AI receives is not garbage and, as master it
is to reprogram the AI to take account of changing computing,
economic and investment circumstances. Can the AI do these spare
roles? As servant certainly, for us it’s a matter of cost
effectiveness, will the time taken writing and testing the code be
recouped by using the code, at this moment we are happy just to run
our human eye over the data to ensure accuracy and suitability. Can
the AI learn from its own mistakes and take over the master role? The
beauty of deep learning is that it is unsupervised (it can choose its
own inputs) take for example the champion Go program developed by
Deep Mind (also UCL alumni) after given the rules it taught itself
strategy or, Google language translation that no longer needs a
Rosetta Stone, it can understand just by word structure.
Unfortunately we don’t have the resources to develop these high level
creative solutions, whilst undoubtedly some of the larger houses do,
their decision makers are steeped the fear of losing their jobs and,
their indecisiveness provides us with an alpha to harvest.
So what have I done, I’ve cloned myself
as a senior level analyst to live forever but instead of eating my
lunch it is eating the lunch of the 2000 other analysts I would have
had to employ to get the same level of productivity.
Whilst it will be very difficult for AI
to capture the creativity of genius (“thinking outside the box”)
it can certainly do the hard-work.
Suffice to say there is very little
genius in the top professions: law, medicine, engineering,
architecture, hairdressing etc. so the service sector is not immune
In fact, where the is enough data on
any successful person decision making in an professional industry, AI
can isolate the factors that made them successful, and then apply
these factors to opportunities for eternity.
Steven J Cohen CFA is the principal and CIO of a Zurich based multi-family office. He gained his BSc Econ from UCL, spent several years in Chartered Accountancy and had established a retail clothing firm in central London. He was in-house counsel to the wealthiest family in the UK and managed a multi billion dollar portfolio for a big 4 UK bank. After a very successful 2007 & 2008 he established his family office and today develops artificial intelligence generated investment strategies for an increasing Asian client base.
he sensitive, was he hell? Did he ride to the rescue…..more times
than you’ve had hot dinners. And boy could he walk, talk & shoot
straight. If he starred in a modern political feature his usual
“can-do”character may have got into the following minor scraps and
righting of wrongs.
Simplifying and reducing tax rates, encouraging: investment at home, employment and, rewards for success in business and career.
Reminiscent of Reaganomics unmet spending, but this time from Debt
levels not seen since the end of WWII. With demand from global pension
plans to meet cash requirements of the expanding number of retirees,
allowing easy adoption of increased issuance, until expanding US growth
rates permits increased tax recovery and Debt pay-down.
Infrastructure & Urban Regeneration:
Not talking bridges to nowhere as in the Japanese example, for
fertility rates in the US are still reasonable and the legal immigration
policy liberal. But improving productivity and bringing previously
criminal elements into legal activities boosting growth and tax
Relaxation of the burden on small business to enter markets and
complete against global market leaders, bringing back the local feel.
And a return of Caveat Emptor improving the self-reliance and
diminishing the hollering in recent generations.
Realigned Foreign Policy:
Requiring Allied nations to meet defence spending requirements that
may reduce the need for US foreign bases that have prevented any recent
major European wars. Not undermining solid allies with a shared cultural
outlook, together with a healthy scepticism of vocal cultural
opponents, thereby providing certainty of deterrent. Even the Duke would
never call US citizens of Mexican heritage, rapist, murderers and drug
dealers and would have found it inconceivable to want to eliminate the
Chicano vote. Unless the comments were referring to ILLEGAL immigrants
whilst still assuming some of them are good people. Profiling of LEGAL
entrants who’s cultures are sympathetic to extremist/criminal
Renegotiated Trade Agreements:
Whilst most country trading surpluses are caused by large savings and
productivity gains they are also usually accompanied by a certain
amount of xenophobia. Restriction of free trade can be inflationary but
may also bring in the huge amount of people not counted as looking for
work and an incentive to invest in robotics.
And the fantastic cinematography that usually accompanies Duke’s
features? This is being provided by the beautiful and breathtaking
capital markets reaction of higher expected growth and a decent yield on
fixed income savings of the more conservative.
But what of the plot, of course that would depend on the director of the feature?
Directed by Michael Moore we’ll just get a remake of the Alamo, when
the Central Bank returns to its misguided ways of belated and
exaggerated action to stifle this hero’s efforts.
But with Quentin Tarantino we’ll get his reboot of the Searchers with
the search, discovery but this time, successful reuniting of America
with it’s Greatness.
finally really did it…You Maniacs! You blew it up! Ah, damn You! God
damn you all to hell!” Cry the Bremain supporters, EU politicians and FX
and equity capital markets.
The departing and presumptive British PMs suggests a period of calm
negotiations before any change occurs. EU politicians and administrators
continue their disregard for democracy and demand immediate panic,
liberal elite demand disenfranchisement of over half the British public,
and investors, employers and capital markets bemoan uncertainty.
The benefits of free trade remain: purchasing of goods from the
cheapest source allowing allocation of remaining resources to the most
relative productive activity.
In the coming re-negotiations Britain approach from a position of
strength, it accepts net services and goods from the EU and the rest of
the world, any threat to allowing British goods and services into Europe
(as long as they meet EU regulatory standards) could be met with even
harsher reprisal. Of course as the UK is smaller than the EU the
relative effect would hurt the UK more. But both Switzerland &
Norway with massive net exports have access to the EU free market for
which they pay, on this basis the UK could maintain access and receive a
Under free movement of labour Britain again receives net migration
from the EU. Britain could limit EU immigration, on a one-to-one basis,
to the highest quality and demanded resources without jeopardising
British nationals working or living in their homes in the EU.
Britain is also a net contributor to the subsidies and grants of the
EU, for that benefit it is allowed access to the decision and law making
processes that is shared with 27 other nations. Whilst the direction of
political EU and UK may now differ, the UK would be free to adopt any
of the best in-class practises from the EU without having to contribute
to the EU treasury.
For trade with the rest of the world any existing EU agreements with
the rest of the world could also be adopted by the UK and the non-EU
blocks until if necessary renegotiation take place.
A call for calm rational negotiations by British leaders and the head
of the other successful economy in the EU (and provider of the British
royal family, maintained after the Magna Carta, reinstalled after the
English Civil War as a constitutional monarchy and, possible model for
UK’s continued membership of the EU) would lead to a beneficial outcome
for both sides (and a similar non event to the Y2K). The rash hysterical
shrill for punitive action from the world liberal elite provides the
reasoning for British exit, but also evokes uncertainty for the UK, EU
and rest of the world.