Sunday, January 26, 2020

Artificial Intelligence And Finance: New Frontiers

Artificial Intelligence (AI) is re-shaping the progress of many sectors today; and is perhaps the most important ‘general purpose’ technology of our times. The effects of AI will be continue to expand manifold in the coming decade as the sectors of manufacturing, media and entertainment, retail (especially e-commerce), advertising, finance, healthcare, insurance, education etc- all of which are being impacted by this technology; the usage of which is spreading gradually from the developed nations of the West to India.

One sector that has been majorly impacted is Finance. Let us consider the phenomenon of algorithmic trading for a start- this type of trading uses software and computers to run complex mathematical formulas combined with mathematical models and human oversight for trading in securities, to make decisions to buy or sell financial securities on an exchange.

Algorithmic traders often make use of high-frequency trading technology, which can enable a firm to make tens of thousands of trades per second. No human being can replicate this speed; and hence software is often replacing human desk traders.

Conventional (manual) trading models only utilize historical data, are often static, require human intervention, and don’t perform as well when the market changes. Consequently, funds are increasingly migrating towards true artificial intelligence models that can not only analyse large volumes of data, but also continue to improve themselves.

Most AI trading software today can absorb enormous volumes of data to learn about the world and make predictions about the financial market - stocks, bonds, commodities and other financial instruments. To understand global trends, software can consume everything from books, tweets, news reports, financial data, earnings numbers, and international monetary policy to Saturday Night Live sketches. The AI can keep watching this information all the time, never tiring, always learning and perfecting its predictions.

Let us consider the case of perhaps the most well-known of all investment banks, Goldman Sachs. In 2014, Goldman Sachs reportedly invested in and began installing an AI-driven trading platform called Kensho. The usage of this gradually increased- as exemplified by this remarkable statistic: In 2000, Goldman Sach’s U.S. cash equities trading desk in its New York headquarters employed 600 traders buying and selling stock. Today, it has reportedly just two equity traders, with machines doing the rest.

This has essentially been replicated at a macro scale. After a gradual start, by 2010, upwards of 60 percent of all trades were executed by computers, with the figure over 70 percent more recently. In India as well, the percentage of trades executed by computers has crossed the 40 percent mark (As an aside, readers may be interested to read Michael Lewis’ book ‘Flash Boys’ that brought high-frequency, algorithmic trading to the general public’s attention, which spoke about the lives of Wall Street traders and entrepreneurs who helped build the companies that came to define the structure of electronic trading in America. An interesting tenet of his book was that Wall Street firms were engaged in a race to build ever faster computers, which could communicate with exchanges ever more quickly, to gain advantage on competitors – solely through speed, thus completely overpowering those who used more traditional methods to trade on the exchange).

Now a days, even DIY (or do-it-yourself) algorithmic trading has become common- a hedge fund called Quantopian, for instance, crowd source algorithms from amateur programmers who compete to win commissions for writing the most profitable code.

What is also noteworthy is the potential of these algorithms to get better and better; for most softwares today rely on machine learning- programs can improve themselves through an iterative process called deep learning.

Why is algorithmic trading popular? Broadly, it provides the following benefits:
  • Trades can be executed at the best possible prices.
  • Trade order placement is instant and accurate
  • Trades are timed correctly and instantly to avoid significant price changes.
  • Reduced transaction costs.
  • Simultaneous automated checks on multiple market conditions.
  • Reduced risk of manual errors when placing trades.
  • Algo-trading can be backtested using available historical and real-time datato see if it is a viable trading strategy.
  • Reduced possibility of mistakes by human traders based on emotional and psychological factors.
There are many other benefits of AI based products- some especially relevant for developing nations such as India. In our country, for example, aspects such as the pricing of financial products such as insurance policies, the decision to extend credit facilities (including credit cards) suffer in the absence of information about end users due to the absence of credit records and user profiles. As AI and digital technologies become more widespread, some of these issues could be resolved, at least partially.

AI allows for new ways of pricing financial products accurately to be brought into play. A piece of software called Lenddo, for example, can reportedly look at a potential applicants’ entire digital footprint to determine their creditworthiness. The company claims that it can look at hundreds of factors including social media account use, internet browsing, geolocation data, and other smartphone information.

Their machine learning algorithm turns all this data into a credit score, which banks and other lenders can use towards provision of a credit score; and avoiding the issue of ‘adverse selection’. The technology can therefore help extend credit and insurance to those who were hitherto left out of formal channels.

There are also indirect benefits of a more widespread usage of AI. One of these comes from what has been called ‘robo-journalism’. This technology allows for entire news stories can be written by machines, which can supplement editors and reporters and produce simple factual reports, increase the speed with which they are published, and cover topics currently below the capacity of journalism.

This is especially true when the story deals primarily with facts and data - as do many financial quarterly earnings reports. Associated Press extensively uses AI to churn out financial news related coverage and states that this technology has allowed it to expand its coverage of companies listed on the exchange from just 400 per quarter earlier to 4,000 today.

Greater usage of this technology could help the Indian financial sector, especially the stock exchanges. The Bombay Stock Exchange in India holds the record for the largest number of listed entities in the world however the number of stocks actively traded is low. Should media coverage be expanded to a greater number of entities, it would greatly increase the options to retail investors by broadening the coverage of companies, as people would have information on more stocks and thus feel comfortable to trade in them.

It is clear therefore, that AI and machine learning systems, while not always needing to replace people, can often complement human activities, which can make the work of humans ever more valuable. For example, using ‘robo journalism’ can free up the time of editors to write more pieces dealing with analysis, opinion and stories of human interest and emotion, while leaving the fact-based work to robots.

Monday, January 20, 2020

Power of Thoughts

As trainers, coaches, catalysts and change agents, we find ourselves motivating our participants on this powerful quote quite often:

"Sow a thought and you reap an action,

 Sow an action and you reap a habit,

 Sow a habit and you reap a character,

 Sow a character and you reap a destiny."

As we pause, reflect and truly comprehend this causal relationship, the profundity of this quote truly sinks in.

That thought is a powerful seed that germinates into one's attitude, choice of words and action is itself a powerful thought! Let me elaborate…

How many times are we prepared to dig deep in the iceberg beyond the visible tip of an individual's observed behaviour, habits and accompanying results? Amidst the frenetic pace of today's existence, there is an inordinate focus on dissecting one's behaviour - what wrong did he do? what did he say? what is the pattern of results? You get the drift....

As trainers, we strive to accomplish change of behaviour of the participants. We find ourselves investing huge energy in not only training (hopefully, with engaging activities in the classroom or otherwise!) but also motivating them to surpass benchmarks and at times, do what perhaps, nobody has achieved. Motivational speakers seem to flirt with this tip of the iceberg in ample measure and leave their audience spell bound, seemingly ready for some dramatic action. Alas, this excitement is short lived with no tangible action or a behaviour change seeing the light of the day - in the long term. Memories of a 'feel good' experience are carried forward by the participants as a saving grace.

Let us shift our attention to the 90% of the iceberg that is hidden. Therein lies the proverbial mass that comprises thoughts and feelings, beliefs and values and even underlying needs of the individual. How can we understand these? The challenge lies in the complexity of this mass with a multiplier effect due to variations on account of different individuals. One of the ways is to trigger their thought processes by asking questions that encourage learners to dig deep within and look for affinity and congruence to their feelings, set of values they hold dear, their belief system, and the needs they feel will be met.

Therefore, some essential questions to consider can be:
  • what would you gain in this learning engagement?
  • how will you overcome the odds to keep yourself motivated during the training?
  • how would the learning help you back on the job?
  • what changes can you visualize for the better?
  • how does it relate to what is dear to you?
  • how do you see yourself progressing hereafter?
  • what will you lose if you were to miss out on this experience? Etc.
 Time and effort need to be invested in these questions by the trainer both at the pre-training stage and prior to the start of actual training session as a minimum. These should be reiterated later during the training sessions and also at the conclusion to trigger the chain of thoughts of the participants. What would appeal to an individual is after all difficult to predict.

My belief is that these questions check on and build the willingness of the learner towards the learning journey that lies ahead. This mental priming is essential and should not be missed or neglected. As the learners find their own answers, clarity of thought emerges clearing the cobwebs in the learners' minds. The learners then, are prepared to acquire new knowledge and skills and are ready to even slog it out. This is evidenced through the change in their body language, vocabulary and of course, 'willing' action - all to the delight of the trainer. The learner is now ready to take the plunge - with both his heart and mind in complete sync - into the realms of learning and emerge strongly influenced and motivated to ‘change’.

We get credible evidence of this in sports and military training. In both, the trainer and the coach highlight the importance of winning the mind game to outwit the opponent or the enemy. The presumption is that winning thoughts clearly precede and determine the action on the ground. At the thinking and willingness level, enough lessons and time is invested so that the learner focuses on the action (to be performed and perfected) with an uncluttered mind. An adversary who hasn't prepared at commensurate levels of priming and preparing the 'thoughts' is clearly at a disadvantage!

Be a willing and ‘thinking’ learner yourself and create tribes of learners who are harnessed on the power of clear thoughts!!

Source - Rajneesh Mathur

Thursday, January 16, 2020

Learning is Not a Spectator Sport

Learning something new is always exciting! More so, if the motivation to learn comes from within. For example, an impatient teenager who wishes to learn driving a car or a bike before he moves out of his teens. He impresses his friends and family alike with his confident grip on the wheel and (near) deft handling of pedals and gear shifts. Has there been early signs of a behaviour change? Your guess is as good as mine!

Training someone on a competence hitherto unknown is one of the ways to learn and effect a change of behaviour. In this effort, besides the learner herself, at least two more entities are involved. A trainer or a teacher, for sure. Often, the role of the third entity is missed out by both the other two. I am talking of the learner's sponsor or stakeholder if you will, who stands to benefit from the learner's learning. In my example, the learner's girlfriend or even his parents who will be better off than before with a new competence firming up - sooner than later.

Let us examine the three entities one by one .

First, a successful teacher or a trainer is one who leads by example and demonstrates what ought to be learnt. Preparing for the lessons, tailoring his efforts to the needs of the learner in terms of instructional methodology are the hallmarks of a great instructor. Lack of initiative, effort or application of knowledge on his part will differentiate between chalk and cheese. With each participant or a set of learners, the teacher's own learning gets reaffirmed and strengthened.

Second, the learner herself has to be most willing and motivated to see a bright light at the end of the 'learning' tunnel. The trainer steps in here to engage the learner in activities that help learn seamlessly. Dirtying one's hands in the learning arena is not left to the whims of inertia or self doubt. Hands on practice that helps solve problems or life tasks such as negotiating a deal or handling an irate client are the essentials. The confidence thus gained adds to the learner's conviction that gradually builds up. This is a critical juncture when the learner steps into the 'real' world and is keen to put to test what she has learnt. A world that is dynamic and throws challenges at you each moment.

Allow me to introduce the learner's sponsor at this stage. As an extremely important cog in the learner's learning wheel, he cannot afford to remain a spectator while the 'new' learner tests out what works and what doesn't. Vitamin EA - as in, Encouragement and Appreciation - in ample measures can do wonders. A helping hand (in form of wise counsel, a practical demonstration etc.) to kill the demon of hesitant starts and a public approbation of the learner is all what is needed to cement the learning of the latter. Sadly, in reality, more often than not, the learner is often left to her devices with no assurance of the stakeholder's help and support. As if to say that the latter chooses to remain a wilful spectator and be witness to an avoidable failure. What a pity!!

What are the roles that you are playing at your workplace? What are you doing to ensure your own or your team member's learning is not illusory? What must be done to build that sweet spot at the intersection of ample confidence and unshakeable conviction?

A resounding applause on a newly learned competence is a defining moment for the learner. This requires humongous effort and an indomitable will - both individually and they say, it takes two to tango and a pair of hands to applaud!

Source: "Rajneesh Mathur"

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