MB Fund Podcast: Death of financial media with Patrick Poke

In today’s webinar, hear from MB Fund’s Head of Investment Damien Klassen, Tim Fuller and special guest Patrick Poke of Livewire Markets as they cover “The Death of Traditional Financial Media.”

On the agenda this week is falling broker and industry research, what to make of writer biases and motives, growing interest in International equities among investors, the media silence of Superannuation fund managers, and much more.

This week we’ve included timestamps of topics in the YouTube and podcast descriptions for your convenience

Take us on your daily commute! Podcasts now available on iTunes and all major Android Podcast Platforms for Nucleus Insights.

Subscribe on Android
Subscribe on itunes
Subscribe on Spotify
Subscribe on Google Podcasts


Tim Fuller is Head of Operations at the Macrobusiness Fund, which is powered by Nucleus Wealth.

The information on this blog contains general information and does not take into account your personal objectives, financial situation or needs. Past performance is not an indication of future performance. Tim Fuller is an authorised representative of Nucleus Wealth Management, a Corporate Authorised Representative of Nucleus Advice Pty Ltd – AFSL 515796.

Tim Fuller


  1. Thanks for an interesting and thought provoking discussion. I was listening in and the below is pretty much my stream of conscious consideration of the content…….

    For me, as an ex-business journo, all business/economic/financial writing is ultimately about models and the data they are based on.

    Models about the global economy (eg. the production and consumer rise of China, the post 2008 staving off of financial system thrombosis, tax cuts in the US, the advents of negative yields, financialisation of industry sectors etc)

    Models about domestic economies Incorporating bits of the above – or assumptions – and tailoring to a locale (debt and/or house prices in Australia, and the impact of tax cuts, Brexit and its implications for the UK economy, Trump’s trade war and its scope for bringing investment/jobs back to the US for the US economy, etc)

    Models about economic sectors and industry sectors in parts of the local or global economy Incorporating bits of the above – or assumptions – and tailoring to a locale and industry (or industries) (eg the rise of consumers in China, the rise of aged care in Australia the US Europe, telecoms in Africa, consumer demand in Russia or India, the advent of solar power, the rise of online shopping and its impact on bricks and mortar retail and supply chains etc)

    Models about economic actors (companies) and their activities in parts of the local or global economy Incorporating bits of the above – or assumptions – and tailoring to specific economic entities, be they local or global (eg, Coca Cola, Amazon, Nestle, China Industrial Bank, Deutsche Bank, Unilever, Japan Tobacco, Ridley Corporation, Cherkizovo etc etc etc)

    Models about projects and proposals being considered by economic actors Incorporating bits of the above – or assumptions – and tailoring to a project or investment decision (eg. BHP or RIO to build new mines to support China demand, Amazon to roll out supply drones, Gazprom to build a pipeline to supply China, retailers to build new shops/malls, Company XYZ to move or establish production of ABC widgets in any given location)

    Models about the ownership/operation/life cycle/use of existing production, movement, or retail assets Incorporating bits of the above – or assumptions – and tailoring to specific sites in specific locales (eg. Restaurants, cinemas, petrol station chains, grain handling facilities, car fleet purchases, company M launches takeover bid for Company P)

    Almost all serious discussion of the above involves data. How much capital, how much demand, Net Present Value, Forecast return on Investment, Net Interest, Margins, what population growth, what wage growth, what inflation, how have these values changed over time, why and how are they forecast to change, what are the implications of these changes for the models, how do existing models get adapted to accommodate change, and what are the costs of that adaptation? And on and on.

    Anyone talking/writing about business, finance, or the economy without anchoring it to a model and fueling that model with relatively verifiable data is essentially either off on an ideological/book talking/ vested interest supporting (or opposing) rant, or is talking out of their backside.

    Beyond that there is the phenomena of (as examples can sadly be found within Australia’s media world) journalists who don’t actually know what they are talking about – and have all too often simply been told by an editor ‘we want a piece about – insert subject here – and you need to come up with one. Two or Three vox pops, a comment from an economist or two, and an industry insider or player of some sort, and you are there. You’ve got 6 hours.’

    The Media

    But it isn’t all just the ‘media’s’ fault. Where, a generation ago, they were often highly profitable and could invest in a story, the advent of online news aggregation and Google and Facebook means that all too often they just want someone to land on a site (and hopefully pay attention to an advert once there). Their scope to deploy journalists to source information and talk with people and get often conflicting opinions about what information actually means has been largely compromised.

    All too often today the question facing the media management is ‘What is the potential return on investment (of giving our journalists the time to go into a set of data or an announcement or an event) for our highly leveraged cash strapped media entity?’ and from there it becomes ‘can we get a better return on our investment, or even the same return on investment with less risk, if we deploy our assets another way?’ (eg just get a cadet or incompetent to cut and paste press release quotes with some meaningless sentences in between, and slap a headline over it which attracts a few clicks – and doing that can often be as profitable as a meaningful story which has involved a lot of effort).

    The variables in this day and age about the profitability of any given piece will not necessarily reflect its importance in the greater scheme of things (let alone its ability to provide some sort of investment insight) but how it plays against the feelings/thoughts/prejudices of a reader or viewer (who may only give the headline a scan to work out whether the article comes within the ambit of things they would actually like to know about (or think they would like to know about)), any competing news information easily accessible (be it about business or not – football, Kim Kardashian’s backside, global warming, the intense loathability of politicians).

    It is also worth noting that contemporary media managements will rarely invest in people/journalists to become subject specialists, or become knowledgeable enough to become ‘investigators’ but more often focus on their stable of journalists having cross subject skills (economics/politics/law/banking/finance/criminal issues), and cross medium skills (eg video/audio/print), and opt to buy in either an in house subject specialist – someone who has enough credibility to come out with opinions, in the past established by years of on the ground sniffing around subject matter (and often set free from any need to back their opinions with much data on that basis) or buy in opinion pieces (from Bloomberg’s stable, from Reuters stable, from the Times or NY Times or WaPo, or Project-Syndicate).

    Australia’s media – strapped for cash, and credibility

    From there let’s move to contemporary Australian Mainstream media. And although Australia is an extreme case there are facets of this in most of the developed world’s media spaces.

    Australia’s contemporary Mainstream Media world consists of 3 commercial broadcast networks which don’t do news (let alone business news) in any meaningful sense, a couple of radio networks (the same) and two print stables which haven’t made a profit in a generation – and are largely run as exhortation amplification tools for Uncle Rupert (News Ltd) or objet d’moment to cling to (Ninefax). Then there is the ABC (which sometimes comes out of the basement where it is kept bound and gagged for fear of offending political interests – which are never offended more than by comment or data reflecting on economic/tax/budget policy) or the SBS (which specializes in being fairly innocuous).

    In Australia’s case the media largely no longer has the funding to source much data (and equally importantly to verify data), it often has little scope for seriously analysing data, or for comparing different data sets to derive a meaning from them, or for analysing how changes to data or to a range of data sets may implicate themselves in terms of a model or models. All too often it is reliant on information provided by a company, and needs to accept and report that at face value without any question, and without any acknowledgement of whatever assumptions underlay it.

    There is a poignant reticence of Australian fund managers (notably super funds) to have themselves in the media. Surely some of this reflects just how utterly discredited Australia’s mainstream media actually is. Australian fund managers will be all too aware of that – how many of them will be invested in contemporary Australian media? More ominously for the mainstream media, particularly in Australia, there are an awfully large number of other imperatives which can shape how much coverage of financial issues. Does a masthead want to devote effort to how and why industry superannuation funds continually outperform their retail counterparts, when the largest single advertisers with the mastheads are the banks who own the retail funds? Individual journalists may well get the story which editorial considerations would rather they didn’t.

    The notable exception is arguably Bloomberg. But even here it is worth noting that Bloomberg keeps its best data for its paying clients, and that Australia is fairly small fry in the Bloomberg world, and that much of Australia’s value for Bloomberg is in simply providing another venue for comment to originate from.

    That leaves a vast swathe of quite detailed consideration of Australia’s business and economic or finance world in the hands of bloggers, and subject specialists who have gone outside mainstream media to have the scope to examine and report on their particular field of interest. Some of the analysis to be found in blogs and small specialist internet publications is superb. But those interested in the research need to know of the publications and blogs, and have the time to wade through them. Then, for the most part, those blogs and smaller publications are all too often run, not as ongoing commercial entities, but as loss leaders for the proprietors and their personal interests or obsessions – often based in disgust with the lack of awareness of an issue or issues in the mainstream media, meaning the blog is an individual’s sense of public service.

    Investment research

    That brings us to Investment research by investment banks, funds managers, fixed income and equity advice advisors/brokers/credit analysts. This too is all about the same models. The generally quite overtly stated purpose of this research is to promote the idea of investing in an economy/sector/corporate vehicle/project as being feasible, desirable, interesting opportunity. It is almost always pitched at specialists (those with the knowledge and the money, or those with the money employing specialists to do the hard yards for them). Generally it is far more likely to be ostensibly data driven (those with the money to invest tend to be far more concerned with hard data and an economic/financial narrative than witty writing styles, extreme opinions or political allegiances) and is written deliberately for a far more discerning clientele who are far more likely to read through an article and reflect upon the information contained in it than your average news reader.

    The research made available to subscribers/investors/sometimes the general public is about how the investment models of the bank/fund/portfolio are set up, and the conceptual underpinnings of these, why investment decision A makes for a potentially good investment decision and therefor better sense than investment decision B. It generally stems from the investment themes identified by a strategist or chief strategist (which are in themselves invariably intensively explored and often have loads of data). This type of research is generally heavily data backed – reflecting the fact that investment management is essentially about constructing investment models from all available data, and powering those models with the most up to date and best quality of data. Anyone knowing anything about funds management/investment banking/credit analyses knows that the sexy part of the job for generally highly intelligent people is about constructing the investment models, and the profoundly tedious part of their job is about the sourcing, extracting and verifying of the data which drives the models. After that it’s generally all about selling the models and dressing to meet and greet potential investors.

    The Media and the Investment Research

    The crossover between media and investment research reflects the fact that journalists will often come across investment research (which is often circulated for precisely this reason) and identify that the research they are looking at is chock full of useful bits of data, often a chart or two (or ten), and invariably includes some great comment – which journalists can often just copy and paste, and position according to their (or their editorial) narrative needs. This is good for investment houses/banks/analysts as it gets them into the media (when they often have some form of pecuniary interest in being a presence in the media), and good for the ‘journalists’ as it gets them out of doing a lot of the writing and analysis. One of the downside risks of the contemporary age is that sometimes data makes its way into a piece of research, which has been picked up by some plausibly credible source (lets say FT as an example – referring in an article to the Egyptian Economy Minister saying it will export XXX tonnes of cotton this year) which may well have been sourced by whatever journo from a data supplier or aggregator (possibly based somewhere like India) which has taken up the piece of data from an article translated into English, from an original article written in another language where a translator has made a mistake. Depending on who picks up the information and where, it can be all over the public domain, though incorrect, and widely believed, and commented upon before any sort of factuality gets a look in. That sort of stuff can happen.

    So the story of contemporary business journalism and investment research is the story of Data – Data which can be accessed and assembled into some sort of narrative, which makes sense to someone somewhere. It doesn’t need to make all that much sense as far as readers of contemporary mainstream media are concerned (often only compelling enough to make them buy what they already believe), but needs to be plausibly compelling enough to prompt a buy or sell thought for investment research. Data which mainstream media rarely looks to explore, and more often treats with a cargo cult mentality, and which can be attributed to someone else if there is anything subsequently found to be wrong with the data (UBS research says, The Commonwealth bank says, Exxon Mobile says, BHP says etc), needs to be handled far more carefully with investment research if only because someone may have skin in the game (and dollars) off the back of that research and someone with money may sue if it were to be complete bullshido (notwithstanding all the riders and caveats and legalese your average piece of investment research has all over it).

    The data

    But this takes us along to the researched ‘data’ itself.

    Something really good investment research does is take a look at the data, and often compares it longitudinally (same company or institution over a number of years) or across like companies in the one sector in one year. Anyone knowing anything about how the corporate management mindset works, and how investor relations themes, branding issues, disclosure requirements under law, corporate borrowing or equity raising considerations (etc) can influence how information is presented to the public. Any number in an audited financial report can mean something ever so slightly different from one year to another, and big important numbers can often be gilded. A change in forecast here or there can change valuations in the here and now, bringing forward or deferring all sorts of outlays or revenues, and all sorts of weird and wonderful contingency or project spends can be salted away into things referred to in Annexe F (or A B or C) to the Annuals or Quarterlies, Returns on Investment or Asset, or even yields, let alone dividends, can all be quite ‘flexible’ from year to year, management regime to management regime, or reporting jurisdiction to reporting jurisdiction. Of course that is all before contemplation of whether a company financial report is produced under IFRS or US GAAP.

    Then of course there are state actors feeding data into the public domain, which companies regularly incorporate into their assumptions about the markets in which they operate. You don’t need to examine China’s credit growth or GDP stats to find dubious looking official statistics. Do Australian unemployment or immigration stats mean the same thing in 2019 that they did in 1989 or 1999 or 2009? Do US Budget Office forecasts? Or German Industrial Production stats? Do household incomes imply the same marginal propensity to spend, or do fuel or energy prices imply a similar demand variation to those they did in the past?

    The answers to these questions, and countless others just like them at company or even individual level, are where real analysis, and real analysts come in. They explore real differentiation in the models they construct from the analysis they undertake, based on data with enough integrity to enable comparison. They identify value propositions, which aren’t crowded with other investors to the point where valuations are stretched beyond credulity, or return for the effort.

    So where does this take us as the future unfolds?

    The obvious first point is enabling some form of data integrity. Enabling comparison between numbers reported under US GAAP and IFRS for starters, enabling the construction (or reconstruction) of the underlying accounting structures of firms, nations, societies, and projects. This starts to get us down the road of making an analysts job easier (or less time consuming – if they don’t need to sift through pages of annual reports and then copy and paste relevant numbers from them into a spreadsheet forming the basis of their models).

    This will almost certainly come from the investment research end of the world, as the finance journalism end of the world has been withering on the vine for most of a generation now. Those journalists remaining will presumably continue to pick up morsels of data making their way into the public domain from the data sets of analysts. But from here it is all about the data and the models, as the narratives of the mainstream financial media haven’t been taken up for a long time. And the first narratives taken up will be those taken up by investors off the back of analyst research.