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Publication Date: 28 June 2018.

Issues With Investment Research

Research from existing banks, brokers, research houses, rating agencies, press commentators, newspapers, blogs, etc. and financial reporting from the companies themselves is now extremely voluminous and all needs to be absorbed and distilled before investors can form their own, composite view of opportunities and decide which ones are relevant

We see the following pain points

  • Equity research suffers from the myriad of different theories on beta, alpha, CAPM, options theory (Black Scholes), discounted cashflow, passive vs active vs ‘smart’ approaches, long/short, hedge fund, long-only, value vs momentum vs technical (chartist), and other approaches to stock selection and the equity market in general. The sheer range of theories presents a major cognitive overload challenge.
  • Credit rating agencies are paid by the bond issuers but theoretically represent the bond buyers.
  • Commodities research is tough because those markets are significantly more volatile than, e.g. listed equities or bonds. The question is more one of weight within the investor’s portfolio and setting limits on how much downside risk can be afforded, on a weight averaged portfolio view?
  • Currency research is a function of pairs, e.g. USD:JPY. Investors’ time horizons are often uncertain. Executing at a target price can be difficult because of the speed at which the FX markets move intra-day.
  • Real estate research is always and everywhere bullish. Even the mounting anecdotal evidence that internet shopping is affecting retail malls and high street shops is still mostly ‘disregarded’ by property industry insiders.
  • Fund management research focuses on performance track record over varying time horizons and relative to this or that benchmark, but indicates little in terms of learning from mistakes.

Our View

It is Cardynal’s firm belief that we are now, finally, at the crossroads in terms of the potential for better research.

Progress in Artificial Intelligence, Machine Learning, natural language algorithms, and related improvements from the tech space that do not come with all the baggage of the financial market industry from the last 100 years or so, are putting app-based research and investor learning potential within reach.

While gathering your thoughts on investment opportunities, knowing when to shut out the white noise and when to actively search for conflicting signals or alternative points of view, is important.

Investors need good heuristics (rules of thumb) for investing, access to global financial data in an easily synthesised, app-based format, and an open, inquisitive mind!

The Competition

In professional or Olympic sport, players and coaches routinely undertake video and statistical analysis of the competition before a match. Few investors take much, or any, time to consider who they are up against when it comes to price movements, in each asset class, trusting perhaps indirectly that regulators will catch any untoward or insider trading.


Price formation is driven by specific players in each asset class

  • Equities: large institutional investors, high frequency or high speed traders, computer automated trades, hedge funds, short sellers, dark pools
  • Bonds: institutional investors, central banks, sovereign wealth funds, short sellers, hedge funds
  • Currencies: investment banks, hedge funds
  • Commodities: commodity producers, trading houses, hedge funds, investment banks
  • Real Estate: investors can add value provided they have the means to continue capital expenditure to upkeep the property and make it attractive to tenants. The competition takes the form of elevated entry prices (i.e. extremely poor rental yields), substitution risk from online shopping in the case of retail property, and planning constraints.

Apart from the risk of poor performance at the asset level (e.g. profit warning from the individual company), the competing investor universe collectively determine asset prices and investors have to play in that crowded field.

Additionally there are regulatory or geopolitical event risks (eg US-China trade war) that can cause promising returns to go up in smoke at a moment’s notice.

Our View

When considering investments, due diligence must extend beyond the target asset’s own financial and strategic performance, to the track record, approach and firepower of the existing investors including short sellers.


The global opportunity set is defined by all listed and unlisted asset classes: equities, bonds, currencies, commodities, real estate, funds/ETFs/unit trusts/collective investment units, alternative assets.


Financial repression and national boundaries to investing (free movement of capital) are rife, limiting choice for non-HNW investors. At the same time, there is now so much information and data out there that it is difficult to know where to begin.

Having an ‘unbounded’ opportunity set may make it harder for investors to handle the cognitive load

Our View

Democratisation of investing requires much better translation and filtering capabilities, and a need to overcome home market bias (to the extent the latter is due to the complexity of investing cross-border).

An app-based method of accessing and filtering listed and unlisted opportunities globally is now coming into the realms of the feasible thanks to advances in computing power, some 11 years after Apple released the first smart phone.

Artificial Intelligence and natural language generation algorithms are reaching early stages of maturity and can now be used as helpful complements to traditional investment selection processes.

Technically speaking - our approach to investing

Experienced Venture Capital, Private Equity and Angel Investors who are looking for truly outsized returns over a 5-10 yr horizon, will spend about 40% of their working year meeting possible targets. This can mean 700 to 1000+ screening interviews per year. Private investors just don’t have that sort of time available.


There is little agreement, even among seasoned professionals, as to how best to select, manage and exit positions. Imagine if airline pilots had a similarly wide range of opinions on how to take off, approach and land! Investors differ wildly on valuations, Key Performance Indicators, indexing vs active, portfolio theories, how much cash to set aside for new opportunities, use of leverage, holding periods (day traders vs 30-yrs) and when to exit, among a host of other things.

Our View

Investors should first screen ‘numerically’.

  • Do build a decent understanding of the asset or company’s position and performance potential.
  • Don’t invest because of e.g. familiarity with the brand, unless the other factors stack up.
  • Manage existing holdings according to the same criteria used for asset selection.
  • Use natural language algorithm driven data analysis to look back and learn from investment mistakes, so that performance and investment skill improve over time.


Ultra long-term goals are difficult to work towards in the here and now.

Cardynal’s approach is to understand the long-term and make use of compounding effects. However, we are also mindful of the need to steer around the next corner and tackle the biggest risks first.

Long range planning requires drilling down to the key fixed cost inputs (e.g. school fees, mortgages, car leases, median monthly food costs, etc.) while recognising that the variable costs (lifestyle items) are prone to skew. Ensuring that planning outputs are actually usable / useful / accurate requires any projections to be kept to 5-10 years forward, otherwise there cannot be much confidence in their reliability. There is not much sense in having vague 30 year plans that have huge buffers of conservatism built into them: the cost of keeping powder dry for the buffer may be entirely unreasonable compared to a decent opportunity nearby.

Similarly, when it comes to deciding how and when to exit an asset, if an opportunity to crystallise already decent returns arises, it can be better to act now rather than being too late or worse, underestimating the ‘risk’ in “risk weighted return” and using nest-egg money in an attempt to hold out that little bit longer, only because it was originally part of a nebulous “30-year plan”

We debate these issues hard and openly, and encourage action once the key risks have been articulated and sufficiently mitigated.

We intend to create an end to end platform that genuinely democratises global investing and makes it accessible to anyone.


Financial market professionals have, over the last century or so, self-organised into very costly legacy infrastructures for screening and managing investments:

  • Investment banks, brokers, clearing houses, stock exchanges
  • Private equity, hedge funds, venture capital, institutional investors
  • Rating agencies, lawyers, accountants, commercial and retail banks, insurers, asset managers, family offices

Private investors struggle with an excess of choice, complexity, costs. They may not have sufficient investment experience, even if they have accumulated huge expertise in their own profession or business, to be able to confidently branch out into global opportunities.

Our View

Confidence and global market access can now be realistically combined in an app format. It is reasonable to think that professional investment skills can be put in the hands of ordinary investors without requiring them to spend 20 years working in an investment firm

Our Business Philosophy Has Six Main Tenets

  1. Screen markets using natural language algorithms to sift through bulk data sets, with filters the investor specifies themself
  2. Do not limit the investible universe to geographies or situations that are familiar
  3. Trade infrequently and decisively
  4. Build very wide antennae, to help make good decisions early by learning from unfamiliar domains - get involved in a broad set of discussions with other investors
  5. Maximise adaptability even where that’s uncomfortable
  6. Be aware of loss aversion and take the emotion out of it: don’t shop for food on an empty stomach!

Welcome to Cardynal!

We are a fintech startup building the next generation of investment technology

Three pain points Investors are frustrated with today
  • Front end on-boarding and compliance: There is a profound need to streamline current cross-border Know-Your-Customer hurdles
  • Opportunities: it’s tough to buy/sell across multiple asset classes, particularly outside your home jurisdiction
  • Keeping track: With multiple service providers, investment managers, banks etc., investors struggle to get decent aggregate transaction reporting and news. So far, Artificial Intelligence and Machine Learning haven’t improved the situation much - why not?