Online Trading | |
Online Trading | |
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Wednesday, September 02, 2020 / 11:50 AM / By Proshare Research / Header Image Credit: EcoGraphics
Executive Summary
"Throughout my financial career, I have continually witnessed examples of other people that I have known being ruined by a failure to respect risk. If you don't take a hard look at risk, it will take you."- Larry Hite
The
new evolution of trading in financial markets rests on digital platforms that
enable clients and traders to develop relationships that save time, improve
quality and hedge risks. Fintech institutions in Nigeria and collaborating
stockbroking companies have noted that working through new products and sharper
service delivery channels would enable greater market intimacy and provide a
friendlier environment for a new generation of investors. Generation Z and Y,
the new investment kids on the bloc, represent a demography that will
increasingly dominate both the equities and fixed income market as they
gradually improve their financial savvy and deepen their understanding of how
local and international capital markets work.
The
ecosystem will see greater intervention by fintech companies who will likely
provide mobile applications that will enhance trading opportunities but at the
same time provide options for the aggressive risk-taking younger generation to
hedge their bets and reduce their susceptibility to 'animal spirits".
The new fintech platforms that allow trading in a wide variety of asset classes
must equally have a risk-protection mechanism that ensures that younger
investors can buy financial assets but with a clear understanding of the
downsides making them equipped with the knowledge of how to use loss-breakers
to stabilize the overall value of their portfolios.
Financial
markets can be brutal and tormenting leaving the unblooded with deep scars, but
with CMOs using artificial intelligence (AI) to profile investors the 'hot' passions of youth can be tamed and allowed to mature into seasoned
decision-making.
The
rise of AI would enable a smoother market transaction process with traders
gaining deeper insights into the requirements of their clients and the asset
combinations and risk/return expectations that fit into the preferences of
investors. So far technology is still fairly rudimentary as digital sandboxes
are still undergoing development and testing. More sandboxes need to be
deployed to provide a richer ecosystem of alternative solutions from which the
best would be chosen.
To
be sure, local Nigerian financial markets are steadily rising to match global
standards. Fintech companies are putting pressure on the brick-and-mortar
paradigms of classic trading platforms and raising the performance bar for
younger investors insisting on a different consumer journey from their
forbears. Indeed the new user of financial products is fixated with speed,
governance, responsiveness and accuracy. Capital Market Operators (CMOs) that
cannot fit into the revised framework of client expectations have one choice,
to fold up. The evolving capital market environment is gruellingly competitive
and crushingly innovative, the time for genteel paper-pushing has ended and
operating firms that do not rethink, reimagine and restrategize their
businesses could kiss such businesses farewell as digital innovation becomes an
ever more powerful force for change.
In
the online digital trading report for 2020, analysis shows that CMOs have become
more aware of the pressures to build robust online platforms that communicate
interactively with customers. The outbreak of the coronavirus pandemic in late
2019 has made the case for remote business interface compelling. The report
notes that the fixed income securities market is the largest and possibly the
most attractive segment of financial trades. With the government increasing
activity in the treasury bill and bonds market to cope with the challenges of
widening budget gaps, the market for public treasury instruments has grown
phenomenally over the last decade 2010-2020. While the Nigerian Stock Exchange
(NSE) market capitalization rose from N11.48trn in 2014 to N12.96trn in 2019,
reflecting a six-year growth rate of +12.89%,
the bond market saw growth from N104trn in 2014 to N232.68trn in 2019, showing
a much faster-paced six-year growth rate of +123.73%.
The Digital Deal: Asset Class Spread
Despite
the faster growth in the fixed income market and the relatively larger size of
government treasury trades, the digital market still favours equities. The
report discovered that 72.90% of online trades are equity transactions, 14.18%
mutual funds transactions(mainly equity), fixed income 5.29%, forex 2.19%,
commodities 0.90% and others 3.35%. Investors appear be feel easier handling
traditional equity businesses online than any other asset class. The limited
nature of online trades means that the online market of asset trading in
Nigeria is thin and narrow, thereby representing an opportunity.
If
traders educate their clients and show them how to make decent returns on
trading different asset classes, the volume of traded online business would
increase exponentially and investor portfolio diversification would improve
risk/return ratios. The online financial asset trading business appears
constrained by a lack of strategic effort at getting investors to migrate to
digital mobile trading platforms. The problem appears to be a lack of
CMO-friendliness with digital technology and constraining 'muscle memory' that
compel CMOs to revert to the comfortable and familiar. Fintech companies are,
however, shaking things up.
COVID-19
may have wobbled CMO perceptions and their operating preferences as remote
interaction increasingly becomes the new normal, with clients
increasingly expressing a preference for transaction journeys that reduce a
human interface. Gen-Zers in particular would want the customer experience to
be plugged into a mobile digital journey similar to their daily consumer retail
transactions. To improve digital online trading, CMOs will need to rethink
their service-delivery buckets and drive more business to digital platforms.
Eyeballing The Survey
On
reviewing the outcome of the 2020 survey that received 785 responses, the top
five fastest online platforms were:
These
platforms, according to the survey, provide investors with the fastest trading
journeys but most of the experience relates to equity trades. What informs the
choice of online trading platforms? The survey result suggests that users of
online platforms made choices based on the following considerations:
The
consumer experience journey has shown that financial sector clients continue to
discriminate amongst online service providers for the following key reasons:
S0
where do online clients desire to see improvement in service delivery
experience? The research survey suggests that the most significant areas of
online service improvement required by clients are in the following areas:
The
survey covers other areas of importance to retail and wholesale customers,
building a body of information of strategic importance to CMOs who would need
to Rethink, Reimagine and Restructure platform operations in a way that feeds
into a product and process value chain that fully recognizes the needs and
wants of younger demography of investors.
The Wrap Up
Most
of the CMOs surveyed would need to ramp up digital service quality if they are
to improve their digital conversion rates. The report shows that digital
conversion rates are still relatively low for most capital market operators.
Transitioning clients from brick-and-mortar trades to digital transactions have
been a hard long walk because most CMOs are yet to figure out the dynamics and
functional architecture of a truly virtual trading structure. CMOs appear
locked in tradition and find it difficult to connect with emerging realities
despite the powerful statement on a new remote work culture dictated by
external business shocks such as COVID-19.
The
report wraps up with the admonition that to meet client's demand along a rising
expectations curve of wants and needs they must plug into a product and process
culture driven by big data, artificial intelligence (AI), and a visceral
understanding of generation Y and Z, anything short of this could mean the
difference between corporate survival and the other side of business daylight.
Trading Technology and
The New Digital Customer Experience: The J-Curve
Trading
asset classes on formal Exchanges are no longer matters of physical space but
that of digital cyberspace. Investors in equity and bond trades now conduct
their affairs on computer devices loaded with software that drives bid and
offer transactions.
The
consequence of a formal format shift for the trading of traditional asset
classes has been the creation of new consumer expectations and the adoption of
revised methods of the interface between floor traders, analysts and
investors. Technology is the new lifeblood of asset trading and so, beyond
fundamental and technical analysis of equities and bonds, the trading platforms
used to execute investor mandates have become critical as time has become a
crucial variable in investor action.
With
the timeliness of transactions becoming just as important as the particular
assets traded, trading houses have had to improve the quality of their
platforms in terms of data processing, research, customer interaction and
generational segmentation. This has created a sort of J-Curve pattern where
service delivery quality at the point of transition or upscaling of digital
trading transactions shows early signs of difficulties with service quality
which dip briefly at the point of the first-stage implementation and then
improve exponentially. The 2020 online ranking digital trade report suggests
that trading houses are still located somewhere at the lower end of the rising
J-curve (see illustration 1 below).
Illustration 1 Climbing The Digital Trading Curve
Indeed,
stockbrokers have improved their adoption of digital trading platforms across
stockbroking houses, however, the customer service journey remains relatively
poor. The speed of transactions and response to customer enquiries have not
improved significantly since the last report in 2019.
Stockbrokers
may have possibly failed in providing clients with the transactional experience
they expect in terms of allowing customers to have regular daily digital
interaction with the market through detailed research produced in a format that
is quick and easy to interpret and represents actionable data. Nigeria's
capital market operators (CMOs) also appear to be lax to the quality of their trade
advisory services. The lack of engaging and interactive advisory activities as
experienced by investors abroad prevents local CMOs from creating broad digital
interaction with clients. Analysts note that the domestic trend appears to be
for stockbroking firms to project their in-house research on their custom-built
websites, this limits the number of eyeballs that see the research and
recommendations and hurts the opportunities that exist to widen their client
base.
Taking Action
To
improve interactiveness between CMOs and their clients CMOs will need to show
greater presence in the digital media space, they would need to get their
research posted on leading business and finance websites and engage in online
media conversations around the different financial markets. The supply of
qualitative market information in the popular business media would build
investor confidence, help in ensuring knowledge-based trade action and provide
opportunities for CMOs to market their bespoke niche products and services. The
balance would be to assess the cost of potential media partnerships with the
expected revenues that would emerge from more intensive client relationships
and stronger brand positioning.
Upping The Strategic Push
Going
forward, CMOs will need to break into new strategic pathways where they can
adopt product/service differentiation as a basis for a competitive tussle for
market share. Speed, for example, at this stage goes beyond being a feature to
being a value promise. The commitment to speed evolves into a conscious
discovery of ways of providing excellence within the shortest practical period.
Besides speed, CMOs would review cost-to-market issues. The lower the cost of
delivering service the better the ability of the CMO to squeeze profit margins
per trade, one clear way of reducing cost over the medium to long-term would be
the adoption of big data and artificial intelligence (AI) skills to farm
information and package it within a framework that gives both asset managers
and investors strategic data in usable small-sized buckets.
The
last arm of the CMOs digital competitive strategy would be to create
service/product niches that provide non-contested (blue ocean) market
opportunities. For example, repackaging the daily stock market report in a way
that removes inactive stocks and concentrates on active stocks with specific
threshold market capitalizations and shares price movements on a moving-average
basis for the last 30 days. In other words, the strategic imperatives for CMOs
would be; differentiation, cost and niche (see
illustration 2 below).
Illustration 2 Digital Competitive Strategy, From Old Models To New Objectives
Of Waterfalls and Monkeys
Two
models can be used to further the digital plans of CMOs; one model is the waterfall
model which allows the implementation to take place in one full sweep, with
execution taking place on all fronts simultaneously.
In
other words, all goals are addressed at the same time or something akin to a 'full-court press' in basketball. The alternative model is called the agile
model which allows CMOs to take a step at a time, using each step as a
learning ladder to be lined up against the next phase of digital
implementation. This approach, bearing the agility of a monkey, reduces risk
and allows for incremental reviews but may be slower than its waterfall
counterpart and lead to several realignments based on changing situations (see illustration 3 below).
Illustration 3 Adopting Different Digital Strategies could Involve Tough Choices
CMOs
will have to decide which approach works for them, but whichever is chosen must
be done with the ultimate intention of significantly improving their client's
service/product delivery experience. The struggle for the digital market of the
future will go beyond just understanding J-curves and classic models of
competition to understanding the idiosyncrasies of the emerging generation of
traders and designing services to meet the new expectations.
Online Trading: A Peep Into Tomorrow
Online trading is gradually making a shift in global importance. The
need for AI in online trading in Nigeria has become more of a pillar than a
building block. Artificial intelligence help brokers in getting larger trade
transactions done, ensure that the stock market works efficiently with lower
volatility for a period. AI presents grand opportunities for millennials and
perhaps generation Y and Z that can get a quick run on its intricacies.
A wide variety of online trading platforms around the world are taking
advantage of AI. Companies such as Greenkey technologies in Chicago
adopted AIfor trading uses, speech recognition, and natural language
processing technology to save traders time searching through conversions,
financial data, and notes. Artificial intelligence is also maximized by Auquan
company in U.K. Auquan's data science competition platform democratizes trading
by allowing data scientists from all backgrounds to produce algorithmic trading
strategies that help solve investment challenges. Also, Kavout's "K-score" is a
product of its Kai intelligence platform that processes massive diverse sets of
data and runs a variety of predictive models to come up with a stock-ranking
rating (see Illustration 4 below).
Illustration 4 AI and The Future: Surfing The Rise
Based on the current state of artificial intelligence applications in stock brokerage by use-cases from companies operating in the space, artificial intelligence applications in stockbroking can be classified into three major segments:
In trade executions using artificial intelligence, the trade execution
algorithms are programmed. When a trader executes a buy request, stock
exchanges need to match these buy orders or bids, with sell orders to execute
securities trades. Artificial intelligence uses statistical techniques to break
up trades into smaller orders to minimize the impact on the stock prices after
the trade is executed.
Also, AI can be used for the identification of arbitrage. This is a case
where investment managers can potentially take advantage of differing prices
for the same assets in different markets. It can search for such arbitrage
opportunities and list them out to the investor in their dashboard (see Illustration 5 below).
Illustration 5 AI King of The Arbitrage
Game
The second segment in which AI can be applied is discretionary trading.
Artificial intelligence can prompt traders and stockbrokers with trading
strategies for individual stocks e.g. AI can recommend the best stocks to trade
based on the highest probability of returns the next day. This will be a
certain win-win for CMOs that build business models on the customer's
transaction journey (see
Illustration 6 below).
Illustration 6 When AI Takes Discretion
The
third segment in which AI can be applied is advisory services. Artificial
intelligence can analyze financial data such as SEC filings, technical
indicators, price patterns, and sentiment analysis based on news, blogs,
analyst, reports and social media feeds relevant to a particular broker's
marker interest. CMOs need to lock this part of their activities down to
guarantee superior client services (see
Illustration 7 below).
Illustration 7 AI and The Beauty of Analysis
When Online Platforms Give a Boost, a Pat and a Kick
The world is becoming increasingly digitized, automated, and advanced in
technology adoption. There is a gradual shift towards the application of AI in
massive online transactions. Some online trading platforms around the globe
have adopted this methodology, hence the call for Nigerian online trading
platforms to tilt towards this direction. The speed at which such technological
advancement is adopted by an online trading platform will determine its
competitive level and its survival in the nearest future.
An online trading platform quick to adopt this technology would record
an increase in its user's satisfaction, an increase in the level of
sophistication of its platform, an increase in the number of users, and also a
significant rise in its brokerage revenue. A modest approach to the adoption
would mean that the online trading platform would record a fair increase in
user's satisfaction, continue operation in the short run to medium period, its
level of sophistication would be intermediate, there would be the need for room
for growth and improvement and a modest rise in brokerage revenues.
The two undesirable actions for any online trading platform would be to
be slow in the adoption of AI and not adopting AI at all. Online trading
platforms slow to adopt artificial intelligence in the nearest future would
record a significant decline in the number of users, low level of
user-satisfaction, low level of sophistication, and significant decline in
brokerage revenue. While an online trading platform that fails to adopt
artificial intelligence would lose a majority of its users, significant decline
in brokerage revenue, a decline in user's satisfaction as they are likely to
migrate to more sophisticated online platforms and would be forced to upgrade
its services a sophistication to ensure its survival (see Illustration 8 below).
Illustration 8 The Online
Digital Trade, Boost, Pat and Kick
Artificial Intelligence and the Nigerian Stock Market, Navigating A
Black Box
Integrating and adopting artificial intelligence on online trading
platforms present numerous benefits, opportunities as well as risks and
challenges. Artificial intelligence suggests that the number of humans
involved in trading and investment decisions decreases and this may affect
markets and price actions.
Analysts have said that application of AI to asset trading could create
efficiency with lower market volatility. Stocktraders, in turn, have argued
that greater efficiency could come from a reduction in subjective market
decisions based on human sentiment, thereby, cutting down on what investors call, 'white noise'. Furthermore, AI also reduces trading cost, it provides dynamic
automated modelling and rapidly and efficiently collects and analyzes far more
information than considered previously possible.
Despite the benefits of AI, there are still challenges associated with
integrating it as a tool to facilitate online trading. Unsupervised,
self-taught AI presents the challenge that its decision-making and financial
trading processes take place in a 'black box' and they may be incomprehensible
to both users and regulators. Also, implementing AI is not easy as it is
expensive, requires sophisticated expertise. Furthermore, some of the
commercial benefits of AI are constrained by the current regulatory framework
governing financial markets, there is the potential threat of a compliance arms
race as individuals and organizations try to game the system.
There are also risks associated with AI in online trading. AI programs
used in trading and investing rely on third-party data sources that are
susceptible to manipulation. Also, models used in financial markets stress
testing may provide misleading results if they are given insufficient training.
Furthermore, if many traders use similar AI strategies, they may pose a risk to
market stability as different actors unwittingly act in concert (see Illustration 9 below).
Illustration 9 Inside A Black AI Box
Do
feel free to share your opinions/observations and feedback with us vide research@proshareng.com.
Thank you.
For:
Proshare Editorial Board
Teslim Shitta-Bey
Saheed Kiaribe
Managing
Editor
Director, Research
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