JPMorgan Analysis: JPMorgan Invents Trading Robot For The Best Dealing Performance

The article was written by Dmitry Podretskiy, a Financial Analyst at I Know First.

JPMorgan Analysis: Robot Trading

Summary:

  • Robots save time and increase efficiency
  • Investments to AI and robotics
  • JPMorgan AI algorithm
  • I Know First implementation of AI technology

JPMorgan analysis

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Robo-traders

JPMorgan is going to use a first-of-its-kind real-time robot to complete trades over its global equities. This change comes as a result of a test of a new artificial intelligence (AI) program at European bank’s division that showed to be more efficient than traditional trading methods.

Daniel Ciment, JPMorgan’s head of global equities electronic trading, stated after testing in their European division, that the algorithm (LOXM as known internally) could be launched in Asia and US by the end of the year.JPMorgan analysis

It uses cases from hundreds of millions of previous trades, even simulated ones, to deal with possible problems. Such as how to optimally offload big equity stakes without moving market prices. The algorithm achieves max speed for client orders and the best trading price. Additionally, the AI algorithm shows much better trading results. The robotic program can reach pricing that is much better than its benchmark.

Investment banks are trying to use AI for to cut costs and reduce routine work. For example, UBS’s recent introduction of AI saved up to 45 minutes of human work per task. Deloitte helped UBS to develop the system. Clients send emails with specific directions on how they want to spread money between different funds. AI then processes these and does the transfers. Now managers can concentrate their time on dealing with client requests.

AI systems also help UBS clients to trade volatility by using algorithms to find new trading strategies and to execute orders on behalf of customers. The program studies through the vast amount of trading history data and develops its work style regarding market patterns. UBS has been offering this “adaptive strategy” to clients for two months already and has received positive feedback.

Robots Rising

According to Morgan Stanley research, robots could have $6.5 trillion under management by 2025, from about $100 billion in 2016. The bank has been piloting the program with 500 financial advisers since July and expects to roll it out to all of them by year-end. Advisers will send employees multiple-choice recommendations based on things like market changes and events in a client’s life.

JPMorgan analysis

For the previous several years, investment into AI and robotics has risen fast. According to CB Insights, the investments in robotics sector globally almost doubled from $273 million in 2014 to $587 million in 2015. The investment growth in 2015 was 115%, as compared to 55% in 2014.

JPMorgan analysis(Source: CB Insights)

LOXM

JPMorgan considers themselves as the first on Wall Street to use algorithmic technology to execute trades. They believe it would potentially take rivals a lot of time and significant investments to introduce the same type of trading robot. Such AI technologies could become the main side of the marketing proposal to clients.

The program was developed with “Deep Reinforcement Learning” (DRL) methods. The algorithm can learn from a vast amount of historical trading data. DRL can also help with automatic hedging and market making.

LOXM can analyse clients’ behavior and desires. Due to this, AI can teach the machine how to consider customers habits and reactions while trading.

The program is restricted to its trading actions and has no decision-making capabilities. JPMorgan didn’t have any risk management issues with this technology. The algorithm works within parallel to general trading risk framework, which is overseen by bank’s control groups and by regulators. The LOXM’s sole role is to decide how things are bought and sold.

I Know First’s Implementation of Artificial Intelligence Technology

I Know First is among 5 start-ups, who showcased their solutions in Payments, Finance Management, Security and other specialties according to Israel Economic Mission in the USA.

Through its self-learning ability and flexible multi-layered neural networks structure, the algorithm can learn from, adapt to and evoslve together with continuouly changing markets. It offers an independent, objective and unique perspective on the financial markets and doesn’t rely on any human derived assumptions or traditional theories and models that often do not hold (anymore).

The results of intense learning and prediction cycles are aggregated into two indicators per time frame: signal and predictability. While predictability indicator helps to identify and focus on the most predictable assets, the signal is used to define and rank the trades and is related to the magnitude of expected return.

I Know First predicts a growing universe of over 3,000 securities for the short, medium and long term horizons daily by applying Artificial Intelligence and Machine Learning techniques to search for patterns and relationships in large sets of historical stock market data.

The applications of the algorithmic AI-based forecasts are multi-fold.

JPMorgan analysis

The scalability of the algorithmic predictive system allows I Know First to offer custom forecasting solutions to hedge funds and other financial institutions, so they can identify the best opportunities as discovered by the self-learning algorithm within the investment universe of their interest. Further, the solution can be used as a decision support system in the form of an algorithmic screen integrated into client’s investment process to confirm or reject investment ideas before the execution.

Moreover, I Know First develops and back-tests systematic trading strategies which are used in partnerships with hedge funds and other asset managing entities. These strategies are rules-based and utilize algorithmic forecasting indicators mentioned above to rank and select the trades as well as the time the execution. The type of strategies varies, including mean-reversion logic and more trend focused approaches, all generating high positive alpha while keeping beta in the  0.3-0.8 range, yielding overall high risk-adjusted returns. The strategies can be used in partnership with I Know First to launch hedge funds, mutual funds or other investment vehicles.

JPMorgan analysis


JPMorgan analysis