Is the Middle East ready for robo-traders?

Updated 31 October 2018
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Is the Middle East ready for robo-traders?

Antonio Simeone, co-founder of Euklid, which manages savings and investments through thousands of algorithms, tells Arab News how his company is developing code that aims to understand not only the vagaries of the market but also the psychology of the trader.
Can you describe the likely application of your idea? That is to say, are you offering the technology to existing fund managers or other investment companies, or do you plan to perform that role yourself — deploying capital for clients in investments picked by algorithms?
We have already established a fund in Luxembourg and recently started raising funds from both qualified and institutional investors. The AUM (assets under management) in our fund are then invested utilizing our artificial intelligence (AI). Our AI studies the psychology of traders and recognizes the fingerprints that they leave behind, besides also being able to identify patterns and micro-patterns which can’t be perceived by the human eye. Due to our entrepreneurial spirit, we chose to set up our own structure and manage money directly instead of licensing our technology.
Part of a fund manager’s job is to predict investments that will perform well in the future, not just collate those which have done well in the past. While algorithms can help with the latter, are they as effective in looking ahead?
By using our algorithms, we aim to understand the traders’ psychology regarding a specific stock.
Our experience has shown us that each trader leaves some kind of traces and that these signs are written in the historical series.
We aren’t managers but scientists. What we do is completely guided by artificial intelligence, thus removing human discretion in the investment process.
Particularly, our AI is capable of recognizing stock fingerprints that traders leave behind and, by analyzing these and a number of other variables, predicting the changes in value of each stock in our portfolio.
We have developed around 45 algorithms that have been customized for every single asset that we trade.
Our portfolio is made of 184 equities among the most liquid on the markets, 70 percent being US equities. The algorithms are based on biocomputing, a science linked to maths, physics and biology. In order to keep the learning process efficient, an optimization process is ensured by swarm intelligence, neural networks and genetic algorithms.
We could say that we create the basic foundation and then it is up to AI to create other structures autonomously and independently.
Let me simplify this concept for you: It is as if we had thousands of traders at our disposal, who are, however, virtual. The strongest or the best are those that stay alive, and those who are not simply die.
Do you have targets in terms of projected assets under management?
Our fund launched in mid-August and therefore we don’t have a vast AUM at the moment. However, many qualified and institutional investors who have been following us for a long time are really interested in our activity and we have received many soft and hard commitments.
Our objective is … to reach the maximum amount (around $13 billion) manageable with our algorithms in three to five years. This limit is due to the fact that the algorithms trade exclusively blue chips and highly liquid stocks. However, the AI is created to
understand and predict the market’s psychology, and it would start to have issues when the AI itself starts influencing markets.
How far away are we from the point at which algorithms replace fund managers in the same way that other functions in different sectors have been made redundant by technology?
This is the reason why we do not have any management fees. We are a team made up of just a few people but our technology acts like thousands of “virtual” traders who work 24/7 for us. They are able to observe an asset from many different points of view. We are the first fund to use both AI and blockchain. But, honestly, the financial industry is rapidly evolving and getting more and more software-based; Thus this scenario is not that far from the current practice as we may wrongly think.
How can algorithms make sense of the extremely volatile and illiquid markets such as in the Arabian Gulf, where there is little raw data to process?
I happen to think about the cryptocurrency world. When we first started our algotrading activity on bitcoin, we had little and unreliable data. Only three years of historical series. Despite this, our algorithms were able to understand the trades’ psychology in a very accurate manner. But that was a very volatile and predictable scenario, and I don’t think we could achieve similar results with other assets.
The traders’ psychology was redundant and very simple; even the alleged manipulations were easily predictable. But, right after the bubble burst — or maybe right after the features were issued — the market sentiment really changed. Algorithms keep learning but this world seems less attractive and it is impossible for our algorithms to operate with more than $50 million because of the limited market capitalization.
As far as the Arab market is concerned, we are still studying it but we have many problems in searching and computing data.


Tesla plans 7% staff cut as CEO Elon Musk says company must ‘work harder’

Updated 38 min 26 sec ago
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Tesla plans 7% staff cut as CEO Elon Musk says company must ‘work harder’

  • Tesla delivered over 245,000 electric cars and SUVs last year, nearly as many as all previous years combined
  • But its 2018 production fell far short of a goal set nearly three years ago of manufacturing 500,000 vehicles for the year

Saying the road ahead was “very difficult,” Tesla’s CEO Elon Musk said Friday that the company would be cutting its staff by about 7 percent.
The electric car and solar panel maker notified its employees about the staff cuts and other plans in an email posted on Tesla Inc.’s website.
Musk said Tesla hopes to post a “tiny profit” in the current quarter but a 30 percent expansion in its workforce last year was more than it can support.
Tesla’s shares tumbled earlier this month after it cut vehicle prices by $2,000 and announced fourth-quarter sales figures that fell short of Wall Street estimates.
“Our products are too expensive for most people,” Musk said in the memo to Tesla staff, saying the company has to “work harder.”
“Tesla has only been producing cars for about a decade and we’re up against massive, entrenched competitors,” he said.
Musk said in a tweet in October that Tesla, based on Palo Alto, California, had 45,000 employees. A 7 percent cut would involve laying off about 3,150 people.
“We unfortunately have no choice but to reduce full-time employee headcount by approximately 7 percent ... and retain only the most critical temps and contractors,” he said.
The company says it delivered over 245,000 electric cars and SUVs last year, nearly as many as all previous years combined. But its 2018 production fell far short of a goal set nearly three years ago of manufacturing 500,000 vehicles for the year. That goal was announced in May of 2016 based on advance orders for its mid-range Model 3, which Musk said sells for $44,000.
Musk said Tesla plans to ramp up production of the Model 3, “as we need to reach more customers who can afford our vehicles.”
“Attempting to build affordable clean energy products at scale necessarily requires extreme effort and relentless creativity,” he said in the memo, “but succeeding in our mission is essential to ensure that the future is good, so we must do everything we can to advance the cause.”
Tesla broke ground earlier this month for a factory in Shanghai, its first outside the US. Musk said it plans to begin production there of the Model 3 and a planned crossover by the year’s end.
Tesla and other global automakers including General Motors Co., Volkswagen and Nissan Motor Corp. are pouring billions of dollars into manufacturing electric vehicles in China.