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October 2017

Independent Research in Asia 2.0

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Independent Research in Asia 2.0

by Douglas Kim

Published on Smartkarma as an independent insight on the 25th October 2017
Read more of Douglas’ work by clicking here!


This is a follow-up report of Mark Artherton‘s note The Future of Investment Research. The implementation of MiFID II is less than three months away and there are great changes that will occur in the investment research arena. In this note, I try to provide the major advantages and disadvantages of independent research in Asia as well as important changes that may impact this sector in the coming years. Clearly, technology will play a key role in these changes ahead and the companies that are well prepared for the technological innovations in the independent research are well positioned to benefit ahead.

It doesn’t matter if a cat is black or white, so long as it catches mice. (Source: Deng Xiaoping)

The quote above is one of Deng Xiaoping’s most memorable quotes and I believe it is very relevant to the changes ahead for both the sell-side and buy-side in terms of producing and consuming research. The buy-side wants research that will effectively enable them to make the proper investment decisions. For them, it really does not matter if the research comes from top-tier I-banks, smaller brokers, or independent research firms. As long as the research and ideas help these investment firms to make the correct buy or sell calls and help them to achieve extra alpha, that’s really what they are most interested in.

Alternative Data – Technology Driven Research

For example, there is a new field of technology-driven investment research that many asset management companies and hedge funds are increasingly relying upon, which is called “Alternative Data.” This is basically what the name suggests, which is using alternative data sources (as opposed to traditional data sources) and apply analytics to achieve extra alpha in the portfolio performance.

According to the Tabb Group, the alternative data market was about US$200 million in 2016 and is expected to become about US$400 million in 2020. According to the, the number of “pure-play” alternative data providers globally rose from about 60 in 2010 to more than 130 as of September 2017.

Some of the leaders in the alternative data sector include companies such as Yipitdata, Foursquare, and 7 Park Data. Top-tier brokers such as Morgan Stanley (Alphawise) and UBS (Evidence Lab) also provide various data analytics services.

The alternative data sector is often broken down into the following main areas:

  • Web data
  • Credit card/debit card information
  • Email receipt
  • Web traffic
  • Geo-location/satellite
  • Sentiment

Main areas of alternative data: (Source:

How Does Alternative Data Work?

The following are examples of how alternative data works. These examples are taken from public sources mostly from the United States.

  • Foursquare – In 2016, Foursquare accurately predicted that Chipotle’s quarterly sales would drop about 30% versus actual sales decline of 29.7%. Foursquare is a local search and discovery service mobile app. The company uses its smartphone driven database and lots of foot traffic of its users to provide alternative data insights on retailers, real estate, and other consumer sectors.
  • Dataminr – This company uses Twitter and other social media sources to provide investors early indications on certain event outcomes. For example, tweets coming from Japan provided early clues to a recent North Korean missile launch over Japan. Dataminr also claims to have detected the vote outcome of Brexit and communicated to its clients prior to the results becoming public.
  • RS Metrics – Using satellite images, get access to the improved information about traffic flow at JCPenny malls and investors could trade on this name prior to the quarterly earnings announcement.
  • Quandl – Gather access to building permits throughout the US and the data is analyzed so that the user can view the changing levels of construction activities in different parts of the US and derive how certain construction companies are doing.
  • M Science – The company uses data mostly derived from credit card transaction data, tracking various metrics such as average transaction values, unique shoppers, and gross subscriber additions for various companies and industries.

Implications for Asian Alternative Data Providers

The examples above were mostly from the US market. However, as the market gets bigger, customers will increasingly seek alternative data in non-US markets such as Asia and Europe. On the Smartkarma platform, there are insight providers such as Ben Li (JD Finance Quantamental Research) and Ryan Shea (Amareos) that provide “alternative data” related research. My understanding of how JD Finance Quantamental Research works is that it utilizes the web data and other Big Data sources to refine and analyze information that is useful for many clients while Amareos provides extensive data analytics using various sentiment indicators. Please contact Ben Li and Ryan Shea for further details.

The growth of alternative data is likely to be explosive in Asia, mainly because this industry is starting from a low base and also there appears to be a great demand for technology-driven research that could be more effectual than the traditional way of conducting “channel checks.” 

For example, one of the traditional ways of conducting channel checks of a retail store is to check them out in person to get a “better feel” for the traffic flow and also chat with the salespeople to listen to what are some of the best selling items recently. However, if the smartphone users and their foot traffic patterns can be tracked at various retail shops and if there are enough users and data sets to reduce the potential outlier effect (such as the Foursquare’s analysis of Chipotle’s quarterly sales using the foot traffic of its users mentioned above), from a fund managers’ perspective, the latter information would be much more worthwhile having.

The competition for alternative data research in Asia will become more intense in the years to come. The natural path of competition will likely be the major players that have already established a strong presence in the US mentioned above will try to expand their services to cover more Asian companies. Plus, the large I-Banks such as Morgan Stanley and UBS as well as other large information providers such as Bloomberg and Thompson Reuters will likely bolster their alternative data analytics services. The numerous insight providers at Smartkarma that already provide alternative data services will also benefit from the greater customer demand and for those companies that do not provide alternative data services, they will likely be forced by the market to consider providing them as well.

In addition to these alternative data providers, there is a growing niche for industry expertise by sector management veterans. The most prominent firm in this sector globally is the well-known Gerson Lehrman. On the Smartkarma platform, there are industry veterans such as Howard J Klein who provide unique sector insights of the global gaming industry. Howard’s proprietary gaming metrics are different from the standard sell-side data points but are based on industry views of management evaluation, discussions with gaming industry contacts, and data points such as average bets per table over time, total ratio of gaming positions to the marketplace, etc.

Independent Research Pros and Cons

1. Non-Biased, “Out-of-the-Box” Investment Call on a Company/Sector

Without a question, technology will play a much bigger role in all areas of research in the coming years. The alternative data research that we summarized above is just a tip-of-the-iceberg. In the midst of these changes, there are some significant changes that are likely to occur as a result of the implementation of MiFID II. One of the major ones is that the buy-side will be scrutinizing carefully exactly how and what they spend on written research and interactions with analysts/companies. In a recent article on Bloomberg, it showed how the fund managers viewed one-to-one meetings and corporate access as two of the most highly valued services provided by the sell-side (see below).

Given the fact that setting up company meetings and corporate access are so critical, it is very difficult to have non-biased views of a company. For example, there are more than 20 local sell-side firms that cover widely followed stocks such as Samsung Electronics Co Ltd (005930 KS) and NCsoft Corp (036570 KS). All of the local sell-side analysts have BUY ratings on these names. If analysts put a HOLD or SELL report on these names, they could kiss goodbye any chances of a non-deal investor roadshow with these companies and they may even have difficulties setting up a company visit as well.

In the table below, we have tabulated the investment recommendations of the top 20 stocks listed on the KOSPI exchange by the local sell-side firms. Typically, there are 20+ sell-side local firms in Korea that cover these stocks. Of these 20 stocks, there are a total of 357 investment recommendations by the local sell-side firms. BUY recommendations represent an overwhelming 86% of the total, HOLD represent 13.2%, and SELL/Others are a tiny 0.8%. In fact, there is only one SELL rating out of 357 total ratings by the local brokers in Korea for the top 20 stocks on KOSPI! This is a clear-cut indication of a CLEAR BIAS towards having a BUY rating on the well-followed stocks in Korea.

When the stock market (such as KOSPI) is going up as it has been in the past year, having such a positive bias may be ok but we have seen numerous times in the past two decades how the market could turn down violently in a short period of time. From the perspective of fund managers, having such an overwhelming positive bias by the sell-side community is not really helpful. However, the incentive system (especially the significant demand to provide one-to-one company meetings and corporate access have a clear impact on the sell-side analysts’ having a positive bias in their written research of the companies under their coverage.

In the midst of this dilemma, how do sell-side analysts try to provide a “more negative, differentiated” view of a company without putting a HOLD or a SELL rating? Having worked on the sell-side for many years, there are several “arsenals” that the sell-side analysts have at their disposal where they could maintain a BUY rating but have a more negative view than the consensus which are as follows:

  • Lower earnings estimates and target prices – When a well-followed sell-side analyst slashes earnings and price targets of a large-cap company in Korea (especially when this is the FIRST earnings/price target reduction) among the sell-side community, it sometimes pays to take heed.
  • Set target prices that are at the low end of the consensus target price ranges
  • “Trading Buy” – This is a weak form of Buy (in between Buy and Hold).

All the methods mentioned above are ways that the sell-side analysts could partially differentiate their research without provoking a severe backlash from the company they cover by putting a SELL report on a company.

Clearly, the Buy-Side is not happy with existing sell-side coverage. They want change. That’s why companies such as Smartkarma have been able to develop a real business capitalizing on the existing shortfalls of the marketplace. The European regulators also understand the frustrations of the Buy-side and have taken the lead in trying to implement MiFID II. As such, we believe that one of the major advantages of independent research firms will be their ability to provide real value-added research in making “out-of-the-box,” non-consensus calls on stock investments. 

Investment Recommendations of the Top 20 Stocks on KOSPI Among Local Sell-Side Firms
Company# of Sell-Side Firms BUY*HOLDSELLOthers*
Samsung Electronics2323000
SK Hynix2319400
Hyundai Motor2320300
Samsung C&T1110100
LG Chem2119110
Samsung Life Insurance1614200
Samsung Biologics109100
KB Financial Group1111000
Shinhan Financial Group1110100
Hyundai Mobis2119101
SK Telecom1513200
SK Holdings1212000
SK Innovation2020000
LG H&H2315701
Amore Pacific2151600
LG Electronics1816200
Source: Naver Finance, WiseFN
Note: Trading Buy is included in Buy; Others – Excluded from coverage

Fund managers’ changing behaviour with respect to taking meetings
 – We have been hearing from industry contacts that there will likely be a changing behaviour of how fund managers take meetings. For example, while fund managers are likely to continue to take meetings with top companies in Korea, they will be more hesitant on taking meetings with sell-side analysts, especially if they are relatively junior or are not one of the top-ranked analysts. In the past, the equity salespeople played a key role in“schmoozing” their clients to take meetings with junior research analysts. Now, because of the need to put a firm “dollar value” on the time spent with the analyst, the fund managers will reduce the number of meetings taken with the sell-side analysts.

How the Buy-Side Uses the Sell-Side: The Bread and Butter – With the oncoming MiFID II, there are a lot of concerns about the extent to which the overall research pie will shrink, despite the growth of independent research. One of the “bread-and-butter” ways that the buy-side uses the sell-side is as follows:

  • The buy-side fund manager is interested in a particular stock (let’s say POSCO).
  • The buy-side analyst/fund manager asks for models of POSCO from sell-side analysts. Typically, the fund manager asks models from 3-5 sell-side firms.
  • The buy-side analyst/fund manager goes through the model in detail and sees where the consensus numbers are.
  • If the buy-side analyst/fund manager has a strong conviction in POSCO and believes that the sell side is “too low” or “too high” in their estimates of sales, profits, and cash flow, then the buy-side analyst/fund manager will pull the trigger and buy or sell POSCO.

There will always be a need for sell-side equity analysts since they provide financial projections from which the buy-side could gauge the consensus and interesting ideas that the fund managers could use to make investment decisions. Despite this need, because of the shrinking research budget, the mid-to-low tiered brokers with lack of any differentiation in their research are ripe for consolidation or exit from the research business.

2. Payment for Independent Research

The payments for independent research are mainly broken down into fixed monthly fees or a certain amount per report. Companies such as Smartkarma charges a fixed monthly fees to its clients whereas other independent research outlets charge its clients on a per report basis. It would appear that the monthly fixed payment scheme is winning among the different types of independent research payments.

A major reason for this is that a big part of independent research is all about providing great ideas. And that great idea could be presented in a short one page or it may need to involve 20+ pages of explanations. Every research is different in terms of its contents and length. Plus, research analysts may provide great investment ideas one day but fail to deliver great ideas on their next reports. As such, it is very difficult to price a research on a per a research basis (exception could be customized, in-depth research for a specific client).

Sometimes, people refer to pricing research similar to how Apple makes money from users that download music on iTunes. We would argue otherwise, mainly because music is not about ideas. When you download a song on iTunes, you pretty much know what you are getting. This is not the case with research. Smartkarma has been trying to create a “ranking system” for a research (such as how many times it has been viewed by clients, how many times it has received “insight liked”, etc. We believe that this is a step in the right direction, although the overall payment system for independent research will continue to evolve with improving technology and changing customers’ demands.

In a recent Bloomberg article, it mentioned how Morgan Stanley plans to charge US$2,500 an hour for private meetings with its equity analysts for bespoke research projects. This appears to be the top-end pricing for a one-on-one meeting with a sell-side analyst. We wonder how many firms are willing to spend this amount of money for a one-hour session with the sell-side equity analyst. Fewer than 300? or 100?

One of the challenges of the payment system for independent research post-MiFID II is the difficulties in scaling up the business. Currently, the securities firms such as Goldman Sachs get paid by asset managers based on a variable rate basis, mostly determined by how much the asset managers trade with Goldman Sachs. However, some of the independent research providers charge their fees based fixed rate basis. So one of the main issues is that regardless of the size of the asset manager (whether it manages US$10 billion or US$100 million), the independent research provider whose payment system is based on fixed rate basis will typically charge the same monthly rate for both clients.

Sector/Company Coverage

One of the major issues of the independent research firms is the sector and company coverage. In the traditional sell-side coverage, the formula is pretty simple. The senior analyst at a sell-side firm typically has 12-18 companies under coverage, with focus on specific sectors such as banking, technology, or telecom/Internet. The focus on a specific sector is both positive and negative. For example, in Korea, the senior tech analysts with extensive experience in covering Samsung Electronics are the most highly sought after right now. They are typically paid more than double the average sell-side analysts.

When a certain sector is in a surging mode (such as the Korean shipbuilding sector from 2005 to 2007), there is a great demand for shipbuilding analysts. However, when the shipbuilding sector crashed from 2008 to 2010, the shipbuilding analysts also fell out of favour. Therefore, a key question that the independent research analysts and companies need to address is to have a specific plan of what sector and companies to cover and ask themselves whether the research adds additional value to the clients compared to the research that is already available in the market.

Opportunities for IPOs, M&As, and Merger Arb Related Research in Asia – In Asia, the research related to IPOs, M&As, and merger arb related opportunities have been lacking and this is one of the areas that Smartkarma has rightly identified and has been able to exploit. For example, there are numerous interesting IPOs coming out of Korea, China, and Southeast Asia. In the past, the bankers that were arranging the IPO deals were mostly responsible for the research of these IPO related companies in Asia. There was a clear need for more independent research of these Asian IPO companies and Smartkarma has been able to provide research of many of these Asian IPOs.

Opportunities for Companies Sponsored Research in Asia – Unlike in North America where companies sponsored research is well accepted, this is not the case in Asia. There are numerous independent equity research firms in North America that generate revenue from companies (typically small-mid cap) sponsored research. These companies want a greater research of their companies in order to generate higher investors interest in the stock. Typically, these companies pay US$25k to US$30k+ on 20 plus pages of initiation of company report plus quarterly updates that are distributed to major institutional investors as well as major global information platforms such as Bloomberg.

Although it would be nice to have Asian companies pay for research on initiation of company reports, this is not common practice in Asia right now. There are a lot of stumbling blocks to this in Asia. A key reason for this is because the owners and professional managers that are running the companies in North America have high incentives to raise the stock prices of their companies since many of them have stock options or equity in the company. On the other hand, the professional managers running companies in Asia typically do not have stock options or significant equity in their companies. Overall, we think that the company sponsored research will likely move at a snail-like pace in Asia in the coming years.


The onset of MiFID II will bring about enormous changes to the independent research globally. There will finally be a price attached to research and that is both good and bad for the industry participants. The changes should have a positive impact on independent research providers that are able to bring real value in terms of non-consensus ideas that impact share prices and provide extra alpha to their clients. But there are credible concerns that the overall research budget will shrink.

Technological innovation will play a key role amidst all these changes in research distribution. Smartkarma has understood the importance of technology from the inception of the company and has tried to develop its business with the emphasis on using technology to develop a superior platform for independent research. Our studies of the independent research have also revealed that the technology-driven “alternative data” research & analytics are likely to be one of the fastest growing services in the years ahead.


Independent Research in Asia 2.0

by Douglas Kim

Published on Smartkarma as an independent insight on the 25th October 2017
Read more of Douglas’ work by clicking here!



The Future of Research

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The Future of Research

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 19th October 2017
Read more of Mark’s work by clicking here!


I recently attended the opening event for the Smartkarma UK office in Soho, London.  The event was well attended and there was plenty of lively debate around the impact of technology on investment research.

The first panel discussion focused on the subscription economy.  The discussion on this panel moved onto the similarities (or lack of) between investment research and other things that are now moving to be sold under a subscription model.  The moderator likened car sharing to investment research.  Ownership of cars will be a thing of the past and there will be a car waiting at the end of the road for the time you wish to use it.  The implication of such a model is that instead of a portfolio management firm ‘owning’ investment bank waterfront coverage at a very high price, that research would be better served by a more focused subscription model where the users of research only used the research that they required at the time they required it.  No need for that expensive SUV to be sat on the driveway or in the garage when the slack can be used by others whilst reducing your costs.

It was a well-received analogy, despite the differences between information and physical goods.  The analogy triggered some interesting discussion amongst the panel and I would encourage readers to view the panel discussion when it is posted on the Smartkarma website.  The downside of such a move for the producers of research is that the size of the pie is that much smaller.  Some panelists felt that the amount spent on investment research could halve.   It was stated that most the impact should be felt by the investment banks rather than independent research providers and there would be a huge market share gain from independent research.  Independent Research would be in a stronger position to utilise the rise of new models to meet the subscription requirements of the consumers of research.

I would like to move this analogy further along and to sketch out the way I believe that the investment research ecosystem should evolve.   This is an opinion piece and the existence of extreme legacy issues and path dependency make it likely that my vision of the future will not necessarily be the one that comes to pass and I will discuss those issues at the end of the piece.

How do you define investment research?

Investment Research can be broken down into three parts.  The first part is obtaining knowledge or information.  Specifically, knowledge that is available to all, not inside information.  This knowledge can be disseminated widely using new technologies and is accessible to all at all times.  This gives pure knowledge little intrinsic value beyond its initial cost of production.  This is one of reasons why Wikipedia is free.

The second part is the filtering of that knowledge.  The first stage of filtering is removing ‘fake’ knowledge.  Fake news is a hot topic at the moment and likely to continue to be so.  In an unfiltered, unedited internet base world the ability for anyone to pass anything off as knowledge increases dramatically.  Google’s search algorithms attempt to provide some comfort for the user, by (and I am massively oversimplifying here) using other sites link to a particular source as a way to measure its veracity and validity.

The second stage of filtering is reducing the knowledge down to that which is the most pertinent to an individual’s investment process and decision-making needs.   Filtering the relevant from the irrelevant in a way that fits a decision-making process.  In a world where all (non-inside) knowledge is potentially available to all this filtering system is exceptionally important.  This filtering has tremendous value.

The final part is the synthesis of this filtered and relevant knowledge.  The synthesis has two major applications for fundamental portfolio managers.  The first is its application to buying a stock in the portfolio or selling a stock from the portfolio.  The second application of the synthesis is for portfolio construction, how to arrange the individual building blocks of a given portfolio.  Synthesis, when combined with a circumstance based approach, has tremendous value.

Traditional investment researchers carry out all three of these functions in ways that vary in their effectiveness and use, but each will have their own specific method of filtering and synthesis which may or may not need an individual client’s needs.

To summarise, investment research is the following:

  • Obtaining knowledge;
  • Filtering this knowledge for quality and relevance;
  • Synthesising the filtered knowledge to impact buying and selling instruments and the portfolio construction of those instruments.

The Investment Research car

Let’s now return to the analogy of the shared car.  Investment research is so much more than sharing a ready-made car.  Ideally, investment research is having a bespoke vehicle built to your current specification at that moment in time to achieve the complete goals of a particular journey.  From choosing the type of fuel, the individual parts in the engine, the seating layout, the technology available within the vehicle, the type of terrain the vehicle will have to traverse, and the final destination.  All of this needs to be carried out in a way that understands the portfolio manager’s immediate needs without the portfolio manager necessarily having to be explicit about those needs.

Imagine a scenario where a portfolio manager has at his fingertips all of the information that is relevant and synthesised to meet her individual decision-making process allowing her to make an effective decision as to Sell something from the portfolio, buy something for the portfolio, alter the portfolio construction or just to leave everything alone at the correct point in time.  This information is supplied in a way that it can be digested rapidly.  Quantitative and algorithmic funds are already in this scenario because numbers are easy (easier) to put into such a system.  If we accept the premise that active human-led portfolio management can add value then a system as described above would add tremendous value (though some of this value is likely to be short-term and ephemeral – as you might pay hundreds of ponds to eat in a high-end restaurant).  The system as described does appear to be some form of unattainable nirvana given the path dependency built into the system.

However, it is my belief that the technology tools are there to achieve this aim.  From data collection all the way up to the basic level of Artificial Intelligence that has been achieved(human replicating AI is a lot further out than the futurologists would have us believe in my opinion).  Human input is required at all levels and it is this human technology interaction that is very important.  What is missing is the correct application of these tools – Smartkarma is a step in the right direction.

Is history holding us back?

Historical activities and path dependency often slow the evolution of systems.  The vast bulk of investment research has barely changed in it format over the past 50/60 years – since Ben Graham’s seminal book ‘Security Analysis’ and the creation of the Investment Research Report as the demand from institutional investors built in the 1950s.  There have been many tweaks and improvements in education and even quality, but the production model has not changed too much.  Delivery was impacted by email, the internet, and smartphones.  Though most delivery models are just online libraries.  Consumption itself has also altered little over time.

The historical model has not lent itself well to collaboration.  At best the lead analyst had a team of ‘grunts’ to do the legwork, but true collaboration across disciplines was very hard to find.

What is required is a 360-degree restructuring of the whole active management industry and the way research is produced, distributed and consumed.  Cherry picking models and technology from other industries is key to this.  Collaboration is also very important in this approach, getting the best to work together to give an outcome that is greater than the sum of the parts.  The success of such an approach would become clear very quickly so a shift from early adopters to the mainstream could be very rapid for the company that delivers such a system.

Creative Destruction

MIFID II has provided a catalyst for buy-side firms to think about their consumption of investment research and it has also forced all the providers of investment research to evaluate their distribution models.  The sell-side (investment banks) remain formidable opponents for independent research.  Prior to MIFID II, inbuilt biases in the system favoured investment bank (IB) research.  Some independent research providers (IRPs) were able to build businesses but true scale was rarely reached.  Some IBs may exit research but most will alter their delivery of research to benefit from the changing marketplace.  The bulge bracket investment banks have a lot of advantages on their side – deep pockets, extensive client relationships, and technology expertise to name but a few.

Does the buy-side need research that is produced outside of its own walls?  Large buy side houses may not need it at all in the future. With more effective internal communication, the larger houses will be pressured to use the resources and the knowledge within their own walls. If the payments for research out of p&l migrates globally then justifying external research becomes harder and harder, especially when process fit is considered.  The day cannot be too far away when a large buy-side house cuts off all external research. The trend of M&A to create larger and larger fund houses accelerates this possibility.  A key advantage that larger houses have is the relationships with the companies. An investor relations professional can only deal with a limited number of market touch points. Large shareholders will flex their muscles and retain access.  This approach of self-sufficiency does make seem to make some sense for the larger fund houses.   There is a global trend to bring more capabilities in house for the larger companies.  Especially for those institutions that deal in information.

There are some shortcomings to this model.  Would a large house pay for a shipping analyst, for example?  Someone whose knowledge is only relevant in short bursts every few years. This is also a problem for the independent research analyst who covers this sector.  Large houses could avoid this sector completely.  Small sectors, such as shipping, can be (more or less safely) ignored – in markets like Korea where they can move the index dial maybe this is not the case.  A further option is to hire or develop specialists with complementary skills in these markets so they remain relevant through the cycle.  The correct use of technology will enable individuals to cover more and more in the future, in my opinion.

For medium and small size fund houses the issue revolves around access to expertise (in this case I am not explicitly talking about expert networks as inside information issues cause problems for many).  Medium and small houses need access to external research. Prior to MIFID II this would almost force smaller houses to trade more to generate commission dollars to get research access.  We are all aware of the premium tiers of service at IBs and the amounts to get such service.  In effect, the buy side shared the sell side’s product.  Thousands upon thousands of buy-side firms sharing tens, maybe a hundred, sell-side firms resources.  Large houses generated the most commission, but medium and small houses got access to this research, which was, in effect, paid for by the larger houses.

As suppliers of investment research, there are many, many high-quality individuals looking at the same things.  Some will have greater knowledge and understanding in some areas and some will have a better reading of the market for making buy calls and some will have a better reading to make sell calls.  Some are better at making such calls in absolute terms and some are better making them relative to a country benchmark and yet others are better making them against regional or global benchmarks.  Some will fit better with one client’s style whilst others will fit better with other styles.

Oddly enough, even though they may appear to be more challenged now, the mid and small sized investment houses could be forced into the correct solution.  By providing a ‘virtual’ research department that alters its composition in line with the buy-side institutions needs, a solution can be found that shares resources effectively without diluting their value.  A research report that can be read by anyone is viewed as having limited value.  A bespoke, collaborative piece generated by AI and HI (Human Intelligence) has much more value.

Independent research needs to decide if they are media like – low fee high readership – like a high-end FT, or if they are bespoke consultancy providers.  There is space for both models in the marketplace.  There are also risks in both models, with the overhead for the media model being huge, for example.  Bespoke consultancy is exceptionally difficult to scale, but advances in technology are bringing scalable bespoke solutions much closer.

Does it make sense for multiple people to read the latest monetary report from the Korean Central bank? Or does it make sense for one individual to do so and summarise in a specific database friendly way?  Does it make sense for multiple people to listen to the earnings call of company A or read the presentation of company B or read the IPO prospectus of company C (to be fair I am pretty sure that most people don’t have the time to read these)?  Or does it make the most sense for one person to do this and summarise for a database?  There is so much duplication and inefficiency in investment research.

An additional factor to consider in such a model is the benefit it could have to consumers of wealth management products.  Roboadvisors are both adding new clients but also eating into the lower end of the wealth management client base.   This is not the place to discuss the pros and cons of roboadvisors, but the relationship model offered to more wealthy clients would be pressured by the changes we are seeing in research delivery.  The simple delivery of other’s views will not survive this revolution in the delivery of investment thought.  There will always be a place for individuals to ‘sell’ the initial benefits of a given system of research, but the management of that relationship will become less lucrative.

One thing is very clear, the future of investment research will be very different to its past.


Being the iTunes of investment research is not enough in an industry undergoing such significant change, not when it is clear that the more effective business models such as Spotify and others are eating at the iTunes model.  Differentiated models that treat information as ingredients that are supplied effectively to the synthesisers is a possible way forward.

Differentiated models are needed that treat information as Lego building blocks to be put together in a variety of different ways, collaboratively, to achieve different ends.  The days of the long form report written by an individual which is then stocked in a library, put on a website, emailed (or added to iTunes) are limited.  The way research is produced, delivered, and consumed will be drastically different from the model we see today.  Technology will provide each individual at each point of time, a differentiated and unique build of relevant, high-quality information in a structure which allows a decision maker to rapidly make investment decisions.


The Future of Research

by Mark Artherton – Founder & CEO of LR Investment Services

Posted on Smartkarma as an independent insight on 19th October 2017
Read more of Mark’s work by clicking here!