The Hutch Report

The Fear of Choosing

By | Economics, Marketing, Psychology

I moved to Europe years ago from Canada and although I made the move to embrace the change and experience another way of life, the first thing I noticed was the stores closed at 6pm. There was no 24 hour convenience that would provide me some peace of mind should I run out of milk at 8pm. I also noticed that restaurants closed at 2h30 pm, once the lunch crowd was served. If I happened to get hungry at that time I was out of luck, the kitchen staff had all left.

The supermarkets, at the time, were far from the super that I knew.  Although they had all the necessities, they didn’t have all the necessities in different sizes, colours, shapes and flavors. Something that I was accustomed to.

Regardless, over time I found myself adapting to the rhythm of this world and stopped trying to fight it. I couldn’t find my beloved peanut butter so I did without and eventually found other products that were just as good and fun to experience. I discovered the joy of having fresh bread everyday, as was the custom, rather than having that loaf of Wonder Bread that would last two weeks before mold started to set in.

On a visit back to Canada I had the chance to show my new Swiss in-laws the city that I grew up in, along with many of the aspects of North American living that they only knew from movies.

In order to accommodate them I wanted to make sure that they had everything they needed to make their stay comfortable. This included their much desired morning coffee. We had instant coffee at the time and they preferred fresh brewed so no problem, I said, “Let’s go over to the supermarket and I will show you an incredible assortment of coffee to choose from.”

We arrived at the supermarket and made our way over to the coffee isle. In front of us were rows of shelves of every kind of coffee you could imagine. I said to my mother-in-law proudly “look, we are here, you can find any kind of coffee you want.” There was deep roasted, light roasted, medium roasted, french roast, instant, ground, finely ground, whole bean, and decaf. There was Mexican coffee, Ethiopian, Colombian, and Ecuadorian. Then there were the different brands. There was Folgers, Maxwell House, Juan Valdez, Nabob, Nescafé, Tully’s, Tim Horton, Van Houtte and others.

I turned to my mother-in-law and asked, “So, what kind of coffee do you want?” In a state of anguish, she replied, “I just want coffee, just regular coffee, Espresso, Espresso.” So we found the regular espresso in the regular packaging and the regular size and left the store. I then found myself actually disappointed by her reaction. I thought it would be one of amazement, such as, “wow, I can find every kind of coffee I can imagine here.” Instead, what I found was that this myriad of choice that she was presented with, in fact, complicated things for her.

I spent years in University studying all aspects of Marketing and it never occurred to me that more choice could be a problem for somebody, until I saw my mother-in-law’s reaction. In addition, it forced me to reflect on my years in Europe doing without all that choice and I actually found daily life to be easier. I gained an appreciation for basic things that we often take for granted. So, I looked a bit deeper into this choice dilemma to see why it would cause such psychological reactions in us.

We can, in fact, go back to the 14th century, where we find an analysis of the condition with the illustration of Buridan’s ass. There’s an ass (donkey) and it’s very hungry and thirsty. But because someone is very cruel, the ass has been placed at equal distances between a pail of water and a stack of hay. The donkey would try to relieve its desire for food or drink, with the choice between those depending on which is closer. But since they’re equally spaced, the donkey is paralyzed. So it stands there, and sits, and ultimately dies.

In her book “The Art of Choosing,” Professor Sheena Iyengar, S.T. Lee Professor of Business in the Management Division at Columbia Business School researched this phenomenon. A grocery store presented customers with two different sampling stations: one with 24 flavours of jam and the other with only six options. The results of the study revealed that the availability of six options resulted in 30% of consumers purchasing at least one jar of jam, while the sampling station with 24 flavors had a conversion rate of only 3%. While the larger selection attracted more onlookers, the smaller selection actually generated more sales.

When we are presented with many options, we usually fear making the wrong decision. This can be translated mathematically. When there are only two options, we have a 50% chance of choosing the right one. But when there are five options, our chances suddenly decrease to 20%. Matters become even more complicated when there are twenty options or more. Human cognitive ability cannot efficiently compare more than five options, so most of us will start looking at the first few options and then stop.

According to classical studies the consumer goes through 5 stages in the decision making process:

Image result for 5 steps decision making process

The problems begin in the Search for information and Evaluation of alternatives stage. Most consumers do not feel particularly confident, which has the potential to trigger strong emotions like frustration, confusion or annoyance. Frustrated shoppers who are unable to choose will most likely postpone their purchase, whereas confused shoppers may rush themselves only to get over with it quickly, and choose something they will regret later. Annoyed shoppers are quick to leave the store and head straight to a competitor, swearing to never ever return.

In his book, “The Paradox of Choice” (HarperCollins, 2003), author and psychology professor at Swarthmore College, Barry Schwartz said, “Consumers have always had choices, but today options have exploded beyond all reason.” “It’s the ethos of American society; the idea that freedom is good, more is better, and you enhance those ideas by offering choice. Logically, you can’t hurt anyone by adding options. It makes no one worse off, and some better. That’s the theory, but in practicality it’s not true.”

Schwartz argues that even if we do make a choice, “We end up less satisfied with the result of the choice than we would be if we had fewer options to choose from”. Increased choice, can make us miserable because of regret, self-blame and opportunity costs. Worse, increased choice has created a new problem: the escalation in expectations. Greater expectations will drive companies to increase the number of choices they offer, which will in turn make it harder for the consumer to make a choice. A vicious cycle.

What consumers have been confronted with is “Choice Overload”, a term that was first introduced by Alvin Toffler in his 1970 book, Future Shock. Toffler noted that as the choice turns to over-choice, “freedom of more choices” ironically becomes the opposite—the “unfreedom.” This choice overload has become even more evident in the new economy with the likes of super online stores such as Amazon and Alibaba.

In the end, according to Professor Sheena Iyengar, when faced with a complex multitude of options, consumers tend to disregard sound reasoning and pick a product based on what’s easiest to evaluate, not what’s most important. She says that, “We stick to the familiar or go by price because we don’t want to deal with so many choices and scrutinize label claims or nutrition information.”

Between 1975 and 2008, the number of products in the average supermarket swelled from an average of 8,948 to almost 47,000, according to the trade group, Food Marketing Institute. The business point of view, most new items are generated because manufacturers are under pressure to increase growth, even if those items are an extension of an existing product as opposed to something innovative. Yet, in spite of this point of view companies usually see just 20 percent of products accounting for 80 percent of total sales.

Tesco chief executive Dave Lewis, in 2015, decided to scrap 30,000 of the 90,000 products from Tesco’s shelves. This was, in part, a response to the growing market shares of Aldi and Lidl, which only offer between 2,000 and 3,000 lines. This has enabled Aldi and Lidl to be more competitive on price which has in turn helped them to gain market share.

Although we have highlighted supermarkets, choice overload is apparent across many industries and if more companies don’t take the same actions as Tesco then the onus is ultimately upon the consumer to deal with the myriad of choices before them. But how?

There is an overwhelming amount of studies on what makes consumers decide, how to force consumers into decisions, how to manipulate a consumers buying process and on and on. What is less available is information related to helping consumers fend off this barrage of marketing and choice overload, which would make sense since companies are making money from consumers and not vice versa, but there are solutions.

In a 2003 JPSP paper (Vol. 85, No. 1), it was reported that the bigger the assortment, the harder it is for people to choose, “except” under one condition: when they enter with an articulated preference. Nobel Laureate Herb Simon, PhD, first referred to this as a “satisficing” option: the first decent choice that fits their preference as opposed to exhaustively scanning all options until finding the perfect, or “maximising” one.

Essentially, the best thing that a consumer can do is to know as close as possible what he wants to purchase before he goes searching for it, no matter what the product is. Simplify it as much as you can. In addition, it may be wise to lower one’s standards when making a buying decision.

“Any customer can have a car painted any colour that he wants so long as it is black.” — Henry Ford

The next time you purchase coffee, define as close as possible what you want before you even think about choices or enter a store. Next, lower your standards and accept the fact that it may not rank as the best coffee in the world, then you reduce the chance of regretting your choice.

Do this and you will feel better about your decision and at which time you will have made the ultimate choice you can make!

The Hutch Report

2017 Wealth Management Review

By | Economics

At the beginning of 2017, The Hutch Report completed a “Smart Money” analysis to highlight how the smart money was looking at the markets for 2017 and beyond. It was meant to provide a high level overview based on an aggregated synthesis of the macro views of the world’s Top 50 largest wealth management institutions.

Now we are looking back on all the forecasts made by these “Smart Money” managers and institutions to see how accurate they were in predicting the future or if they were just exhibiting an “Illusion of Understanding.”

Central Banks and Monetary Policy

Federal Open Market Committee (FED) 

The consensus (40%) of wealth management firms predicted two hikes in 2017 of 25 bps each hike which would bring the Fed Funds target rate to 1.25%. Roughly 8% predicted three rate hikes. No precise forecasts were provided as to how much or when but of the wealth management institution outlooks reviewed, they all indicated an expectation that Central Bank monetary stimulus policies (eg. quantitative easing) would start to weaken.

On December 12-13 the Fed raised rates for a third time. Only 8% of our wealth management professionals got it right.

The FOMC did announce a tapering plan at the September 2017 meeting and have started in October by letting $10B in bonds mature each month and will slowly increase that number to $50B. As a reminder, in 2008 the FED balance sheet was $800B. It is now at about $4.50T as a result of QE.

European Central Bank (ECB) 

Taper would commence second half of 2017. One dissenter stated the ECB would be unable to discontinue QE.

The ECB did not make any rate changes for overnight credit in 2017 and that rate remains at 0.00%. They did not commence tapering in 2017. However, they did signal in October of this year that they would start tapering in 2018 by cutting in half the monthly purchases from the current rate of €60B to €30B.

The People’s Bank of China (PBOC)

The PBOC will continue to stimulate demand through adjustments of the reserve requirement ratio (the amount of money that the banks must hold as reserves).

In September of 2017 the POBC announced that in 2018 the reserve requirement ratio would be lowered for certain banks from 200 bps to 150 bps. In return for the reduction the banks must meet certain requirements for lending to small business, agricultural sectors, entrepreneurship and education.

Changing of the Guard

The next two years, 2018 and 2019, we will see some changes to the heads of some of the world’s most influential central banks.

Most people are by now well aware that in February 2018, Yellen’s term as Chair of the FOMC expires and Trump has nominated Fed Governor Jerome Powell as the next Fed chair. The post of the Fed chair is subject to Senate confirmation. The Senate Banking Committee has approved Jerome Powell which clears the way for the Senate confirmation vote.

At the Bank of Japan the current Governor is Haruhiko Kuroda and his term will be expiring in April 2018. Current headlines indicate that there is a strong likelihood that his term will be renewed as the Japanese government has expressed satisfaction with the BOJ’s policies under Kuroda.

In 2019, the terms for Mark Carney at Bank of England (BOE) and for Mario Draghi at the European Central Bank (ECB) will expire. Due to the bylaws of the ECB which state that the term of the ECB presidency is for an eight-year non-renewable term the ECB has to find a new president and it cannot be Draghi. It remains to be seen what will happen with the BOE Governorship as Carney has been seen as a strong leader.

Governments and Fiscal Policy

The EU

The consensus for 2017 was that the EU would experience a modest recovery but mitigated by concern, seen to be short term, on political risks due to rising anti-EU and populist sentiment but that this would be limited and most likely would not extend past the UK.

The EU economy so far has actually exceeded forecasts with real GDP growth expected to be 2.2% for the year compared with earlier forecasts of 1.7%.

Everyone was waiting with baited breath to see if populism and a BREXIT, separatist, type mindset would spread via the 2017 elections in 2017 in Europe – specifically in the Netherlands, the France and Germany. However, that did not come to pass and more centrist candidates won those elections. However, this did not mean that the populist and separatist parties went away. Even though Merkel won in Germany for a fourth term, the far-right, anti-immigration party in Germany, the AFD, won seats in the Bundestag with an historic breakthrough for the party and it is the first time in 60 years that an explicitly nationalist party sits in the Bundestag.

Meanwhile in Spain, there was a big push for Catalonia to separate from Spain. While the independence movement was effectively stifled the issue is far from being resolved as manifested by pro-independence parties renewing their majority in the Catalan parliament in the regional elections just held at the end of the year on December 21.


The consensus for 2017 was that the deflationary policies of the incoming administration with Republican majority in both houses of congress, will be positive in the short term for US equities (promises of tax cuts, repatriation of foreign US earnings and higher public spending plus a pledge to invest over $1 T in US infrastructure) Caution for the longer term with potentially greater inflationary pressure and the impact of populist and protectionist ideals.

During the course of the year and up until December, the Trump administration had not succeeded in passing any legislation. This caused some doubt during the year whether the administration would be able to succeed with the measures they had promised. The Trump administration finally did succeed in passing a much contested tax reform bill which was approved by the senate in December and then passed into law and signed by Trump on December 22. Much debate is still raging on whether the new tax bill, which among other sweeping changes cuts corporate taxes from 35% to 20%,  will be effective in repatriating corporate money back into the US and whether this will translate to investment by those corporations into the US economy.

With regards to other campaign promises, notably the border wall, while many prototypes have been proposed there is still no clarity on how the wall will be paid for or what the next steps really are. Meanwhile the $1 Trillion in infrastructure spending does not have any more clarity either. In October of the year, Trump pivoted from a stance pushing for private investment and is now looking towards the treasury which would possibly imply further borrowing and using proceeds from taxes on gas.

Emerging Markets

Despite concern on a potentially rising USD along with interest rates which would negatively impact  emerging markets, especially countries with a majority of their exports to the US like like Brazil and Mexico, the wealth managers were still predicting higher GDP growth in BRIC countries in 2017.

The final GDP rates are not yet available for 2017 however so far it can be said that: Brazil has exhibited modest GDP growth so far this year and slightly surpassed initial forecasts, while   Mexico, which started off the year well in the first half of the year has not faired so well in the second half of the year due to disruptions from two earthquakes, subdued consumer spending and inflation. NAFTA negotiations are still continuing with the US and are expected to continue in 2018.


The majority of wealth managers estimated that Trump policies would help drive up the USD and provide a tailwind to Japanese fiscal policy would also weaken the Yen which in turn would strengthen the Japanese economy in 2017.

Despite a stronger Yen against the USD, Japan saw stellar export performance, supporting manufacturing activity, as highlighted by December’s PMI figure, which hit a nearly four-year high. Investment also benefited from resilient global growth, with business confidence in Q4 climbing to an over one-decade high. So the Japanese economy strengthened but not for the reason’s outlined by the wealth institutions.

Inflation Outlook

The view was that Inflation would increase slightly in developed markets and despite the big question mark whether the central banks would be able to keep inflation in check following the massive reflationary measures they have taken the consensus seemed to be that inflation would be kept in check.

Higher inflation was forecasted in Asia due to less Asian central bank intervention.

For the developed markets, the wealth institutions basically got this one correct in their outlooks for 2017. The inflation rate in both the US and Europe increased the most in the first half of the year and is still trending slightly higher than it was at the beginning of the year. Concerning inflation in Asia, directionally the wealth management outlook for 2017 was correct. Whether or not the reasoning was correct is another story. The theory was that inflation would be higher due to less central bank intervention than in developed markets. This is a subject worthy of debate and whether or not less intervention is even true. For example, the Chinese central bank, the People’s Bank of Chine (PBOC), is suspected to have intervened several times in 2017 in order to keep the yuan propped up.


The historical experiment of quantitative easing in the US, Europe and Japan has seen unprecedented buying of bonds, driving yields down to historic lows. However, with the European Central Bank (ECB) and Bank of Japan (BOJ) running out of bonds to buy and facing the unintended adverse consequences of negative rates (for banks and insurers), 2017 was seen to be the final year for quantitative easing and negative rates. It was believed that political resistance to fiscal expansion would weaken, particularly in Japan. Therefore, the consensus was that there would be nowhere for yields to go but up.

The yields on the US 10yr began the year at 2.45%, however, despite 3 rate increases from the Fed, the 10yr yield spent most of the year lower, closing at 2.405%, going against the consensus view of higher yields.

The Eurozone 10yr government benchmark yield began the year at 0.86%. It spent most of the year above this rate and closed the year at 1.05%. German 10yr yield began at 0.189% and finished at 0.427%. When referring to the Euro Zone the consensus got it right.

Japan continues to confuse many. In July, The Bank of Japan offered to buy an unlimited amount of JGBs, as it sought to put a lid on domestic interest rates pushed higher by the broad sell-off in developed market bonds. JGB 10yr yield began the year at 0.046% and finished at 0.048%, essentially staying flat.


In regards to public equity, a large majority, nearly 85%, of those with a positive outlook on equities were positive on headroom in the US equity market.  Following the US equities market there was no other region or country for which the reports reviewed indicated a majority positive outlook in general for equities, however, close to 50% were favorable on Japan, followed in this order, by Europe, Emerging Markets and then Asia.

The cap-weighted S&P 500 gained 19.42% on the year, whereas the average stock in the index was up less than that at just over 18%. Regardless, 85% of the smart money managers were correct in forecasting higher equities for 2017.

Close behind, the Japanese Nikkei gained 19.10%, where only close to 50% envisioned such a strong performance.

The Euro Stoxx 600 index closed up roughly 7%.


There was a clear and overwhelming agreement that the new Trump administration policies would be bullish for the US dollar. In addition to the US government policies, it was also believed that the Federal Reserve would begin to increase interest rates, which would in turn also be bullish for the US dollar.  Where there was lack of vision was to how high the US dollar would rise, but it was expected to rise throughout the year of 2017.

The view regarding the Chinese Yuan (also recognized as the Renminbi) was that it would remain weak against the USD for some time. However, the majority was expecting the Yen to depreciate further against the US dollar into late 2017.

There were a number of elections coming up in Europe and that was expected to increase risk and put downward pressure on the Euro. The expectation was that it would reach parity with the US dollar.

Not everything worked out as neatly as planned by our smart money managers. 2017 was a nasty combination of buy-the-rumor-sell-the-news for the Greenback. Action on Fed tightening and fiscal reform, more weight on disappointing data versus upbeat results, and the “Trump effect” left the US dollar sliding for most of the year.

The 2016 close for the EURUSD cross was 1.0517, however the close of 1.2004 destroyed the dreams of all those banking on parity.

The USDCNY cross began the year at 6.96 and ended at 6.50. The US dollar’s unforeseen slide  helped to bump up the Yuan against the USD going against the view of a weaker Chinese Yuan for the year.

Last but not least, the US dollar lost 3.69% to the Japanese Yen, going against the majority view that the Yen would continue to depreciate against the US dollar in 2017


80% of the researched wealth institutions believed that the commodity cycle had based and was set to recover, however, the market structure remained a challenge and fundamentals across many raw materials continued to point to concerns of an oversupply. For this reason, there was not an overly bullish view on commodities but a wait and see neutral one.

Concerning Oil, we found a range of forecasts from $45 to $65 a barrel with no clear majority on any one price point. Oil started the year at $52.46, fell to as much as $42 and rebounded to end the year at roughly $60 a barrel.

There was no clear agreement when it came to Gold, however, as the majority linked the performance of gold to the USD, and that same majority expected the USD to rise (indicating Gold would fall, or stay range bound at best) were all off the mark. Gold ended up roughly 13% beginning the year at $1,150oz and ending the year at roughly $1,306oz.

New Alternative Investments

What a difference a year makes! Bitcoin was a curiosity at most at the beginning of the year, however its stubbornness to sell off for any extended period, while it continued its meteoric rise, forced wealth managers to take notice.

It began the year at roughly $984 and continued to rise to $19,211 before rounding out the year at $12,610, beating any other asset class (although the debate is still raging about whether or not Bitcoin is an asset or other). Regardless, Bitcoin is now something to be reckoned with and will not be taken so frivolously as it was in the beginning of the year.

Along with the rise of Bitcoin came a host of other Alt coins and ICOs (initial coin offerings), however, as far as professional money managers are concerned, Bitcoin is the main act for the moment until proven otherwise.

We also mentioned Bitgold in our report which was the idea of a cryptocurrency backed by the equivalent amount of gold. It was believed that this would stabilize the volatility seen in pure cryptocurrencies and provide them with an air of respectability. However, it is still too early to know if this will take hold and for the moment this concept is not really of interest to the professional investment manager.

Our special report on Gold Backed Cryptocurrencies supported this lack of interest as we researched all the principle players in the area, large and small and found them largely lacking in many areas.

In Conclusion

2017 was not an easy year for our wealth management institutions in many respects. There were no great winners or losers.

Will 2018 prove to be any easier? We don’t know, but if the smart money is having such a difficult time making sense of all these moving pieces you can bet that the dumb money is at a complete disadvantage (unless they bought and held Bitcoin, which currently would make them look like the smart money….for the moment).

A principle lesson to be learned is that all these forecasts that appear in these glossy yearly outlook reports, quarterly reports, weekly reports and minute by minute reports that continue throughout the year on your local financial media networks, by all these institutions that manage the largest fortunes are just that, forecasts.

Everybody speaks in their best interests which makes following these prognostications and forecasts all the much more difficult and more often than not puts you, as an investor, at a disadvantage because you are more likely than not to be buying from those who are selling (which happen to be the same people which have advised you to buy). Therefore, don’t listen to the smart money, follow the smart money.

The Hutch Report

The Illusion of Understanding

By | Economics, Psychology

How is it that no matter how much any financial market goes up or down during the day, somebody has an answer as to why? Financial markets are made up of millions of participants making large numbers of investment decisions at any one time. In addition, we now have a large number of computers that have been programmed to trade at incredibly high speeds, even up to the milisecond, and they are making millions of these trades a day. Yet somehow financial media commentators and self proclaimed experts are able to define what it all means, all within the constraints of a 3 minute clip. There are 3 possible explanations why.

I read once where a CNBC regular guest financial commentator disclosed that any guest invited onto the show was not allowed to say “they didn’t know” as an answer to why something was occuring. It was explained that these people were portrayed as experts, and experts were not allowed to not know a fact. If they presented themselves in such a way, they would not be invited back. Since being on television can be great exposure for the individual or the company they work for, they would simply do what was asked of them. You may also have noticed that during times of advancing markets, the financial media programs tend to have a long list of guests that are bullish the markets. In times of declining markets, the long list of guests will be bearish the markets. This will help to reinforce the proper bias regarding explanations for the current state of the market.

The second possible explanation is that the comments reflect the personal motives of these guests. Many of the guests are fund managers or traders and have ulterior motives as to why they see the markets in a certain way. If they, or their employers, happen to manage a large portfolio and are fully invested, it is probably not in their best interest to tell the concerned public that the current markets are unstable and not the smartest place to invest their money. Therefore, they will provide views that support their current positions regardless of whether or not their views explain the questions asked. Since the financial media will present bullish guests during advancing markets it is rare that you will find many with contrarian views and if there are they are most likely supporting their own interests also.

There is also a third possible explanation. There is the possiblity that these experts are victims of “the illusion of understanding,” or known in psychology as the illusion of explanatory depth (IOED).  The illusion of understanding is where people feel they understand the world with far greater detail, coherence, and depth than they really do. They only realise the illusory nature of this belief when they attempt to explain a fact. Opinionated guests on financial media are normally allotted no more than 3 minutes to give their views. For this reason there is hardly enough time to delve into the subject matter in any great detail to where the viewer may become aware that these guests are not able to fully explain themselves. Therefore, they give the illusion of understanding but it is far from clear if they actually do understand the issues they are discussing.

A fact, event or situation that is observed to exist is also known as phenomena. According to R. A. Wilson and F. C. Keil., in their paper, The Shadows and Shallows of Explanation, 1998, we all encounter a vast number of phenomena on a daily basis but only possess a superficial level of understanding of most of these phenomena . In addition to a limited understanding of many everyday domains, people lack an understanding of their own understanding and tend to believe that they are much more skilled in a variety of domains than they actually are (Dunning, Johnson, Ehrlinger, & Kruger, 2003).

Stav Atir and David Dunning of Cornell University, along with Emily Rosenzweig of Tulane University designed a series of experiments testing people’s self-perceived knowledge, comparing it to their actual expertise. The researchers tested 100 individuals, who perceived themselves to be experts in personal finance. They were asked to rate their knowledge of particular financial terms which included three made-up terms (pre-rated stocks, fixed-rate deduction, and annualised credit). They found that 93 per cent of participants claimed knowledge of at least one of those three terms. Stav Atir explained, “The more people believed they knew about finances in general, the more likely they were to over claim knowledge of the fictitious financial terms.” It appears that self-perceived expertise causes people to think they know more than they really do.

These findings are of course not limited to the field of finance alone. They are present in all areas. For example, people may know that a door lock works by inserting a key and turning it, which causes the lock to unlock. This understanding may lead people to believe that they know how a lock works, even though they lack an understanding of the detailed internal mechanisms of the lock. The same can be said regarding everybody’s favorite gadget, the smartphone. The fact that people can download applications, modify the smartphone settings to change the background or a ringtone may give many the impression that they understand how the smartphone works, yet their true understanding of these incredible little computational devices are incredibly shallow.

Charlie Munger, the billionaire business partner of Warren Buffett explained it brilliantly at the USC Law School Commencement speech in 2007:

“I frequently tell the apocryphal story about how Max Planck, after he won the Nobel Prize, went around Germany giving the same standard lecture on the new quantum mechanics. Over time, his chauffeur memorized the lecture and said, “Would you mind, Professor Planck, because it’s so boring to stay in our routine, if I gave the lecture in Munich and you just sat in front wearing my chauffeur’s hat?” Planck said, “Why not?” And the chauffeur got up and gave this long lecture on quantum mechanics. After which a physics professor stood up and asked a perfectly ghastly question. The speaker said, “Well I’m surprised that in an advanced city like Munich I get such an elementary question. I’m going to ask my chauffeur to reply.”

Munger told this story in order to highlight the difference between real knowledge (as was the case with Max Planck) and fake knowledge, or the illusion of understanding (as was the case with the chauffeur).

Max Planck

So how are we able to even identify the difference between having real knowledge and our illusion of having real knowledge? How are we able to identify our own limitations or illusions of understanding? A solution was provided by and practised by the great physicist Richard Feynman.

Feynman believed that understanding something is not just about working through advanced mathematics. One must also have a notion that is intuitive enough to explain to an audience that cannot follow the detailed derivation. In other words if you can’t explain it in simple terms then you don’t know it well enough.

Explanations can be useful in helping people to evaluate their own comprehension. When people attempt to generate an explanation for a phenomenon, they not only learn what they know but also become aware of “gaps” in their understanding: those parts of the explanation that are difficult or impossible to generate (Keil, Rozenblit, & Mills, 2004). That is, people are often unaware of what they do not know until they try to explain it.

The Feynman technique of learning was laid out clearly in James Gleick’s 1993 biography, “Genius: The Life and Science of Richard Feynman.”

  1. Pick a topic you want to understand and start studying it. Write down everything you know about the topic on a notebook page, and add to that page every time you learn something new about it.
  2. Pretend to teach your topic to a classroom. Make sure you’re able to explain the topic in simple terms.
  3. Go back to the books when you get stuck. The gaps in your knowledge should be obvious. Revisit problem areas until you can explain the topic fully.
  4. Simplify and use analogies. Repeat the process while simplifying your language and connecting facts with analogies to help strengthen your understanding.

When referring back to the financial media we can now ask ourselves, “how much information that we are provided is actually real knowledge?” The answer, particularly in the case of journalism, is not always so evident as there are many participants with real knowledge, yet they are often concealed by a large number of so called “chauffeurs.”

The founders of RealVision Television recognised this. They realised limitations of a three minute soundbite on the current financial media programs and the tendency for many guests to present the illusion of understanding. So they launched a platform where the guests are given as long as an hour to discuss various financial subjects in detail. Many of their guests use the freedom of the platform to admit they do not always know why certain things are as they are. They do this because they are asked to explain their views and provide educated insights, which often have limitations. This is refreshing because we are not confronted with the illusion of understanding but the quest for understanding and in turn we are presented with a wealth of real knowledge.

Only by forcing yourself to explain does it become apparent how little you understand. Practicing explanations is the best way to fill your information gaps and also the key to form the kinds of memory you need to perform later and avoid presenting the illusion of understanding.

The Hutch Report

The Illusive Stock Market Crash

By | Economics

On October 19, 1987, 30 years ago, the stock market dropped 22.6%, with volume at 604 million shares doubling that of the previous record. So, how illusive are these crashes and how often do they happen? The panic of 1901, the panic of 1907, the depression of 1920-21, the crash of 1929, the Brazilian market crash of 1971, the crash of 1973-74, 1998 LTCM debacle, 2000 dotcom bust, 2007-08…..and on and on. I have only mentioned a few yet in spite of what history tells us, less and less people today think that it is possible for the stock markets to crash again. Why would we think this? Margin debt is at all time highs, consumer confidence numbers seem to be quite bullish in spite of what the retail sector tells us.

So are things really different this time? Will markets never go down again? In order to understand this we can look at what has changed since the last downturn in the market. 1) The Central Banks have created over $4 trillion of liquidity (more if you add up all the central bank interventions), so investors have come to believe that no matter what happens the central banks will be there to pick up the pieces and just print more money. The word for this is moral hazard. If you invest in something and believe that if you lose, somebody will support you financially, are you going to take less risk or more risk? The answer is you are going to take more risk. You would be stupid not to, seeing that you can’t lose no matter what you do. 2) High Frequency Traders (HFT) have increased in size and number. They now make up the largest portion of volume traded on the stock exchanges. This was not the case in 2007-2008 and before.

The next thing to understand is value. What is the value in the market that makes it go up? We can simplify this with an example. Let’s say a special doll has come out on the market. It cost $5 to manufacture and sells for $10. They start to sell out fast. In fact, some people buy them and resell them which pushes the price up. That pulls more people into the market which pushes the price up even more. Now you are paying $20 for the doll. In order to buy a doll you need to find somebody to sell. As long as the price goes up, people get greedy and hold out for more, which makes the price go up even more.

There is a percieved value that creates demand and pushes the price up but what happens in the inverse? Let’s imagine that the doll was made in China and suddenly news came out that the paint was toxic and making people sick. Suddenly nobody wants to buy. The price goes from $20 down to $3. The value just evaporates. In fact, the doll becomes worthless and drops to 0. Nobody wants to buy because the percieved value is 0. Who wants to buy something that will make them sick?

Now let’s go back to the markets. Just like the doll, the markets will keep going up “as long as” there is percieved value, however, if investors suddenly get worried, that value could evaporate like the value of the doll did. If a stock is trading at $200, but the percieved value becomes $20, the next buyer will be at $20 and just like that the value is evaporated (there are many companies that have alot of value and wouldn’t be expected to lose so much value, but the more extended the price the greater the potential drop). To make matters worst, HFT are basically computer programs. They are unemotional, however, when the people who are running them identify a shock to the market, they shut the machines off. These machines are currently creating most of the bids in the market. If they disappear, the bid disappears and falls like a rock. This is what happened during the flash crash of 2010.

So what about the central banks? They can just come in and print money if the market falls and help to push it back up again. There is some false logic in there because for every action there is a reaction. The money that the Fed prints does not disappear from the system. It will eventually have an effect on the US dollar. Let’s go back to the doll. Imagine the Fed was producing the dolls (they were not produced in China and the paint was not toxic). The thing is the Fed suddenly produced so many dolls that they were found in every shop on every corner. What would happen to percieved value? Well, the idea of scarcity would no longer be there. The dolls are no longer special and people are no longer going out of the way to buy them so the value would drop. It could keep dropping even below the cost price if people have no interest in buying.


This could happen to the US dollar. If the perception is that the US dollar is no longer that valuable, its percieved value would drop. What happens when it goes down? Everything becomes more expensive for everybody holding dollars. What happens if your dollars keep declining in value? You will want to get rid of them and change for something else. The US stock markets are priced in US dollars. So, if the central banks continue to print, the US dollar could lose its value to the point where people will sell their dollar denominated assets, such as stocks and bonds.

Is there anything else? Well actually yes. Over the past few years low interest rates have spurred a large number of companies to borrow in order to buyback stock. In addition, investors have been borrowing in order to purchase stock pushing up margin debt to extremely high levels. If the markets were to fall, there is a point which these individuals will get margin calls forcing them to sell their stock pushing prices lower. The same will be true for companies holding large amounts of debt that need to be paid back.

So, we have a few potential forces that could cause an incredible amount of damage to the stock markets. What will cause the start of it? That is what a few of us are trying to identify. What about everybody else? Well, it looks as though they are still pushing the price up of dolls made with toxic paint.

The Hutch Report

What Is The New Economy?

By | Cryptocurrency, Economics, Startups, Technology

We often talk about the “new economy” but it is a bit of a misnomer as it can be argued that the economy is always new. It is dynamic and always changing. In spite of that, the name has become a buzzword describing new, high-growth industries that are on the cutting edge of technology and are the driving force of economic growth.

One of the main features of the new economy is the extraordinary rate of productivity improvement. It is not just that computers and software are getting better or that communications are becoming more rapid. They are improving at sustained rates that have never been seen in the recorded economic statistics.

A large part of the new economy – particularly software – is characterized by a cost structure that is peculiar to information: it is expensive to produce but inexpensive to reproduce. Combined with the communications power of the Internet, this means that any digitized information can be reproduced and transmitted around to world in virtually limitless numbers at virtually the speed of light. These are the most powerful economies of scale known to date.

Another aspect identified with the new economy is its strong network characteristics. Networks can have powerful economic impacts in several dimensions. They have strong rates of adoption and a strong tendency toward market dominance or even monopoly.

In order to survive in the new economy it is necessary to understand the changes that are happening and embrace them. Those that resist will be left behind. We have seen it before. When the personal computer was first introduced on the market there were many that refused to adopt it. Their resistance quickly found them segregated from the rest of the market in terms of opportunities and skills.  Now we find ourselves in a world where not a day goes by where we have some kind of interaction with a computer. In fact you can’t avoid it.

To help understand some of the changes and disruptions that are happening in this new economy we look at a few below that are making the biggest impact.

The Sharing Economy

The sharing economy is thought of as an umbrella term which encapsulates a wide variety of ideas. However, there has been a lot of criticism around the idea. Critics have said that it’s not really “sharing” if people have to pay for a service. It might seem like semantics, but the implication is more communal than corporate, and in that sense, misleading. It is also known as the On-Demand Economy, or the Gig Economy. Gig Economy is a fitting term for people interested in supplementing their income by taking small, temporary side jobs. But for workers that do this full-time or even beyond, their work should certainly be considered more than a gig. Especially when companies like Lyft offer incentives to work 50 hours a week, this service has become their livelihood. Calling their work a “gig” is almost reductive.

For argument sake we define the sharing economy as a socio-economic ecosystem built around the sharing of human, physical and intellectual resources. It includes the shared creation, production, distribution, trade and consumption of goods and services by different people and organisations.

To include this in the new economy seems slightly banal considering the fact that sharing is nothing new. Giving someone a ride, having a guest in your spare room, running errands for someone, participating in a supper club—these are not revolutionary concepts. The revolutionary part is the fact that it has become part of the economic structure and for that to happen money has to change hands.

The best current examples of the “sharing economy” include the following:


Airbnb is an online marketplace and hospitality service, enabling people to lease or rent short-term lodging including vacation rentals, apartment rentals, homestays, hostel beds, or hotel rooms. The company does not own any lodging; it is merely a broker and receives percentage service fees (commissions) from both guests and hosts in conjunction with every booking. It has over 3,000,000 lodging listings in 65,000 cities and 191 countries, and the cost of lodging is set by the host. In short, anyone can rent a room out in their house or apartment for a fee. The impact it has had on the hotel/hospitality industry is not to be trivialised in the New economy.


These companies all do essentially the same thing. For consumers looking for a ride somewhere, they are a convenient, inexpensive taxi service. You can hire a private driver to pick you up and take you to your destination by means of an application installed on your smart phone. The nearest driver is often at your pickup location within minutes. Not only is this an on-demand car service, but you can even watch as your driver is en-route to come pick you up. For drivers, these companies provide allow you to be your own boss/set your own hours. Take on fares whenever you wish (work as much or as little as you desire).


Etsy is an online buyer and seller community similar to eBay, except it focuses on hand-crafted or vintage goods. Most products sold fall into the category of arts, crafts, jewelry, paper-goods, housewares, and artisan candies or baked goods. Vintage items must be at least 20-years old to qualify and can range from costumes, clothing, jewelry, photos and housewares. In the past, most crafters and artisans sold their goods at fairs, open markets, and on consignment. While the Internet opened doors to reaching consumers beyond their local area, many craftsman didn’t want the hassle of setting up their own website, credit card processor or ecommerce platform in order to sell their goods online.  While eBay and other e-commerce DIY sites helped, Etsy provided a marketplace specifically for crafters. Etsy currently has well over 54 million users registered as members.


TaskRabbit is a marketplace that connects people who need help with something, with a network of pre-approved and background checked individuals, who have the time and skills needed to complete the listed task. The company allows people to outsource small jobs and tasks to others in their neighbourhood. Since the inception of TaskRabbit there have been numerous startups following the same model.

Where the Sharing Economy leads only time will tell. Will we live in a world of empowered entrepreneurs who enjoy professional flexibility and independence? Or will we become disenfranchised digital labourers jumping between platforms in search of the next short term gig?


What is cryptocurrency? A Cryptocurrency is simply an online version of money, a digital asset to be precise. The name is derived from the Cryptography, which is used to encrypt transactions and control the production of the currency. It is a strictly monitored process, as it uses the Blockchain Technology.

Blockchain technology is a distributed database that is used to used to manage & maintain a growing list of data blocks, using a peer to peer network collectively. These data blocks may be situated in different locations and not connected to the same Processor. A database is a collection of records. A distributed database is one which may be located in different locations and not be attached to a common Processor – but it may be located in the same or different physical locations and dispersed over a computer network. In a Blockchain, once a piece of data is recorded, it cannot be edited or changed.

There are predictions that the underlying technology of the blockchain is going to impact our world more than the internet has. This is seen as the technology that could democratize the global financial system so everybody has equal access. The peer to peer concept allows online payments to be sent directly from one party to another without going through a financial institution, and cryptocurrencies are considered by their supporters to be a faster, cheaper and a more convenient alternative to other payment mechanisms such as sending payments via banks, transferring money via money transfer operators or buying goods and services over the internet, using a credit card. For this reason, the payments industry players are closely watching these developments, because of the ability that cryptocurrencies have to potentially disrupt and transform the existing global financial infrastructure.

As of June 25, 2017 there were approximately 900 currencies currently available with the most popular being Bitcoin and Ethereum. Yet while world economies, business and consumers have been caught up in the whirlwind of activity surrounding cryptocurrencies, the benefits and risks are still unclear and the future of any one particular cryptocurrency is not yet secured. In addition, there are a number of legal and political interpretations still developing.

Virtual Reality / Augmented Reality

This is by no means the first appearance of virtual reality. It has actually been around since the 1950’s. As technology has become more sophisticated over the years, every so often the dream of experiencing a virtual world is revisited. We are now back here again.

Virtual reality immerses a user in an imagined or replicated world (such as video games, movies, or flight simulators) or simulates presence in the real world. Examples of hardware players in virtual reality include the highly mediatised Oculus, now owned by Facebook, Sony PlayStation VR, HTC Vive, and Samsung Gear VR.

Augmented reality overlays digital imagery onto the real world. Examples of hardware players in augmented reality include Microsoft HoloLens and Google Glass.

The difference between the two is where VR uses an opaque headset (which you cannot see through) to completely immerse the user in a virutal world as opposed to AR which uses a clear headset so the users can see the real world and overlay information and imagery on to it. We recently saw an excellent example of AR with the success of the game Pokeman Go, although for various reasons its user base is in decline.

The promises of Virtual Reality to revolutionize the fields of medicine, marketing or entertainment are many yet there are also a long list of challenges before we see significant adoption. We already know that spending too much time staring at a screen can harm our vision over the long term. VR headsets are essentially a digital display mounted directly in a user’s face, raising real questions about the effects over time. Some people are also prone to nausea, dizziness and vertigo after just a little time spent in VR. For the industry, that motion sickness issue remains a largely unsolved problem.

Virtual Reality has come and gone a few times over the years and has yet to really solidify its mark on society.

Big Data

A large part of the new economy is about information. This is not only about information that we have access to but also our means of acquiring information. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. These multiple sources makes it difficult to link, match, cleanse and transform data across systems. Data also comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.

Big data is a term we use in the New economy that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. While the term “big data” is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old.

The amount of data that is now being created and stored on a global level is almost inconceivable, and it just keeps growing. However, it’s not the amount of data that’s important. It’s what organizations do with the data that matters. At the moment only a small percentage of data is actually analyzed. The promise of big data in the New economy is precisely that, to gain key insights from all kinds of information in the hopes of making key discoveries.


Existing conventional modes of transportation of people consists of four unique types: rail, road, water, and air. These modes of transport tend to be either relatively slow (i.e., road and water), expensive (i.e., air), or a combination of relatively slow and expensive (i.e., rail).

Enter the Hyperloop. Hyperloop is a new mode of transport that seeks to change this situation by being both fast and inexpensive for people and goods. It is unique in that it is considered an open source transportation concept. The authors encourage all members of the community to contribute to the Hyperloop design process. Iteration of the design by various individuals and groups can help bring Hyperloop from an idea to a reality.

Hyperloop consists of a low pressure tube with capsules that are transported at both low and high speeds throughout the length of the tube. The capsules are supported on a cushion of air, featuring pressurized air and aerodynamic lift. The capsules are accelerated via a magnetic linear accelerator affixed at various stations on the low pressure tube with rotors contained in each capsule. Passengers may enter and exit Hyperloop at stations located either at the ends of the tube, or branches along the tube length.

The goal is to get people from LA to SF (for example) in just about 30 minutes, which is almost three times faster than flying, while producing its own electricity from solar power, with round-trip tickets projected to cost between $40-$60.

Hyperloop One on July 12,  announced that it had conducted a successful first test of a specially designed vehicle to travel in a vacuum environment. In the test, which took place earlier this year, the company achieved controlled propulsion and levitation of a Hyperloop One vehicle at 70 mph on a 315-foot test track in the Nevada desert. The test vehicle reached nearly 2Gs of acceleration during its brief 5.3 second test run on the specially built track.

There are still a number of technical challenges to address with the Hyperloop but it is advancing. Should this project be fully realised it would revolutionise transportation in the new economy.

Artificial Intelligence

Of all the areas of the new economy artificial intelligence (AI) is, without a doubt, the most hyped and the least understood. According to technopedia the definition of AI is “a branch of computer science that aims to create intelligent machines.” More precisely, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving.” Otherwise said, machines that can think for themselves and make autonomous decisions and in turn learn from their decisions. All this leads to questioning to what point will machines control humans?

The machines haven’t taken over yet, however, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioural algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intelligence in use today.

What many companies are calling AI are not truely AI. Software outputs due to an algorithm that responds based on pre-defined multi-faceted input or user behaviour can’t be considered AI.

A true artificially-intelligent system is one that can learn on its own, such as neural networks from the likes of Google’s DeepMind, which can make connections and reach meanings without relying on pre-defined behavioral algorithms. True AI can improve on past iterations, getting smarter and more aware, allowing it to enhance its capabilities and its knowledge. That will lead us to give them more responsibility, even as the risk of unintended consequences rises. We know that “to err is human,” so it is likely impossible for us to create a truly safe system.

The Hutch Report

10 Ways Governments Could Stop Cryptocurrencies

By | Cryptocurrency, Economics, Law

Governments do not react well to threats to their center of control. As of November 2017 there are roughly 1340 cryptocurrencies with a market capitalisation of roughly $450 Billion (when we first published this piece in June it was $114 Billion) of which Bitcoin makes up about 62%. So, it is no surprise that governments are becoming more vocal and putting together tasks forces on how to deal with it.

The bankers seem to be even more worried. They don’t take kindly to non centralised competitors moving in on their turf. After all, they wield an enormous amount of influence and make staggering amounts of profits.

As cryptocurrencies are now gaining more exposure and interest among the general public, bankers are now becoming more fond of government regulators. It is the hope of the bankers that the government will try and regulate the cryptocurrencies out of existence should they become too menacing.

“Virtual currency, where it’s called a bitcoin vs. a U.S. dollar, that’s going to be stopped,” said Dimon. “No government will ever support a virtual currency that goes around borders and doesn’t have the same controls. It’s not going to happen.” — JP Morgan CEO Jamie Dimon


So, should the US government, or any other government attempt to take on Bitcoin, Monero, Steemit or any of the large number of cryptocurrencies, what could they actually do?

  1. Any cryptocurrency is at risk of being made illegal by any government. Owning and operating a money transmitter service in the U.S. is “illegal” unless it is registered with State agencies. This is also true if one uses Bitcoin or any other cryptocurrency to exchange for fiat currency. Bitcoin is not immune from State or Federal laws regulating the flow of money, and agents can track bitcoin transfers over the blockchain.
  2. Regulation to date has been minimal, but history tells us that governments rarely preference light regulation — it just takes them a while to catch up with technology. There are a large number of issues that any government could regulate when it comes to cryptocurrency use among the public. In 2013, the U.S. Senate held the first hearings on Bitcoin. In that same year, FinCEN released the first announcement by any government agency related to the technology. The IRS was also the first tax agency in the world to clarify the tax treatment of Bitcoin and other digital currencies. Additionally, BitLicense in New York was the first licensing regime in the world directed at digital currencies.
  3. Cryptocurrencies do work with an exchange rate, therefore, governments could manipulate the exchange rate of bitcoin, ethereum or other. This is by no means unfamiliar territory for most.
  4. It’s not difficult to imagine the US or the European Union coming up with a new definition for cryptocurrencies as, say, an investment, with all net gains taxed at 30 per cent. For example, the U.S. tax authority, the IRS, has classified cryptocurrencies as “property” for the purpose of federal taxation, whereas the Treasury Department’s FinCEN has classified cryptocurrencies as “value” for the purpose of AML/CFT (Anti-Money Laundering and Countering Financing of Terrorism Act) obligations.Other jurisdictions have taken a different approach, avoiding a formal classification and focusing instead on the nature or type of transaction being conducted.
  5. Governments could exploit the transparency of the blockchain and punish people for holding cryptocurrencies at all. This has been seen in the past as in the case of Gold.
  6. The NSA or some other entity with both the budget and experience create a VLSI (Very Large Scale Integration) project to both develop and deploy an ASIC (application-specific integrated circuit) design that would result in a 51% attack.
  7. International regulation could be developed that significantly inhibits one’s ability to exchange Bitcoins, or other, for local currencies. Essentially forcing the cryptocurrencies underground like a drug cartel thereby adding to de-legitimisation.
  8. It is possible for a mathematician to gain government support in finding a way to break ECDSA (Elliptic Curve Digital Signature Algorithm or ECDSA is a cryptographic algorithm used by Bitcoin to ensure that funds can only be spent by their rightful owners). However, it is very unlikely that this would happen.
  9. The media alongside a covert multi-government effort could conduct several propaganda campaigns to sway public opinion that the cryptocurrencies are either a massive scam or somehow bad. This has already been seen in the example of IMF, government and banking representatives conditioning the public to equate cryptocurrencies with fraud, terrorism financing, money laundering etc.
  10. Regulations could be adopted to monitor and control the crypto exchanges. A government has the purchasing power to buy up large quantities, drive the price up then sell and collapse it, thereby massively increasing volatility. These market fluctuations could be aggravated by a covert government programme of destructive funding and public disinformation. This would make doing business in any cryptocurrency more difficult.

The Treasury Inspector General for Tax Administration commissioned a report last year to study their options. The overall objective of the review was to evaluate the IRS’s strategy for addressing income produced through virtual currencies. It included the following recommendations:

  • IRS management needs to develop an overall strategy to address taxpayer use of virtual currencies as property and as currency.
  • The Deputy Commissioner for Services and Enforcement should request the Large Business and International Division, the Small Business/Self-Employed Division, and Criminal Investigation to develop a coordinated virtual currency strategy that includes outcome goals, a description of how the agency intends to achieve those goals, and an action plan with a timeline for implementation. In addition, the strategy should use the tools available to the IRS and identify how the IRS is going to meet its BSA, criminal investigation, and tax enforcement obligations as related to virtual currencies as well as identify how actions will be monitored and the methodologies used to measure the actions taken.
  • The Deputy Commissioner for Services and Enforcement should take action to provide updated guidance to reflect the documentation requirements and tax treatments needed for the various uses of virtual currencies.
  • The Deputy Commissioner for Services and Enforcement should revise third-party information reporting documents to identify the amounts of virtual currency used in taxable transactions.

So the US IRS is now on the prowl, as I imagine many other international government bodies. Nobody should forget that Bitcoin and all cryptocurrencies are still an experiment. Nobody really knows how this will play out in the future. Stay tuned!

If you enjoyed reading this post, please recommend and share it to help others find it!

The Hutch Report

The Truth about Investment Research

By | Economics

It is out in the open, out of the closet, there for all to see, the emperor has no clothes! Your fees have been bundled!

It is estimated that about 40,000 research reports are produced every week by the world’s top 15 global investment banks. We could therefore hypothesise and estimate that the top 50 produce roughly 140,000 reports a week.

It would be no doubt a daunting task to have to read through all these reports in order to extrapolate the nuggets of wisdom that could help you get a return on your investments or save you from making a bad investment. According to a recent report by Hong Kong-based Quinlan and Associates, less than 1 percent of these reports are actually read by investors. It is not a surprising finding considering the number of hours available in a day!

It is also widely recognised that investment managers are inundated with an oversupply of free and “duplicative” research reports (including sales notes), many of which are considered of questionable value. According to discussions with the buy-side firms, in preparation for the Quinlan report, it was indicated that managers with the greatest capacity to pay (i.e. large funds) appeared to derive the least amount of value from published research. What is not clear are the reasons. They are paying but not reading all the material, therefore producing no return on investment? They are reading the material but the number of potential actionable trades are limited in comparison to the amount of investible money they have under management?

For years banks have been bundling the cost of their research into trading commissions charged to their clients. Therefore, whether the clients read the research or not it is the clients who have been absorbing the cost of it. This has led to new rules, known as Markets in Financial Instruments Directive, or MiFID II, due to take effect in January 2018 aiming to make European securities markets more transparent. This may impact all of us whether or not we are located in Europe.

ESMA (European Securities and Markets Authority) cited a number of key issues with research that MiFID II addresses, including:

  • Limited transparency around research costs and spend by asset managers (given there is little or no disclosure to end investors);
  • Risks to end-investors’ best interests (given research is paid out of client funds); and
  • The absence of a level competitive playing field (given that the lack of price transparency makes it difficult for independent research providers to effectively compete).

Most US and financial institutions worldwide will be impacted in 2018, and therefore indirectly all of their clients as well, even if they do not have any European physical presence. Any firms or their subsidiaries world-wide that are trading European instruments including equity, fixed income, or derivative income will be impacted as well as any that are performing any cross-border services that include Europe whatsoever.

When we became aware of this situation we decided to look deeper into the research being produced by the world’s top 50 largest wealth management institutions. We parsed through thousands of pages of these reports, many being qualitative, often confusing and ambiguous.  They used terms such as “may”, “could”, “potentially”, “perhaps”, or “possibly”, covering every possible angle not to take a strong position.  Our objective was to find patterns of consensus in as many different areas as we could, removing the possibility of duplications. In addition, we wanted to highlight the products which would be best used to follow these recommendations.

This project was an interesting exercise but not one without its challenges. Having a solid understanding of the financial markets, products and the inherent complexities we found that many of the banks lacked support for their hypotheses as well as market scope and product scope in their write ups. This required us to search deeper into additional research reports and interviews. We also found examples of contradictions within their own research teams.

It is clear that considering the new MiFIDII rules, the banks have begun to reorganise their research functions. They have started focusing on top-tier clients in order to minimize costs, and adopting a model where clients pay for research depending on what they need. There are still masses of data being produced daily so this situation will not be alleviated over night.

Recently global investment banks such as Standard Chartered, CLSA, Jefferies and Barclays, among others have begun reducing staff or have completely pulled back from equity research and sales businesses in some markets.

Having to suddenly pay for and understand how much they are paying, for research, Fund managers will most definitely become more selective and disciplined in their research spending decisions. They will now be able to compare and contrast research pricing among various providers. Greater transparency will also help end-investors to evaluate the value of one research firm in comparison to another and evaluate the return on their research investment spending.

The Hutch Report

The Pension Fund Crisis – It is beginning to boil!

By | Economics, Politics

Reading the news is tough. Most of it is bad, yet we tend to want more of it. For some reason humans are more drawn towards bad news than good news. There is a school of thought in psychology that says we do more to avoid pain than we do to gain pleasure. Could this be the reason why we need to know about all the bad stuff?  Is it merely a defense mechanism to protect ourselves?

At the same time we can ask ourselves if we have become so desensitised by bad news that it doesn’t impact us emotionally anymore. If true, it puts us in a perilous position. This psychological state prevents us from reacting to danger and you can bet that every once in a while a situation does arise that we should be paying attention to. Something that could provoke us to jump into action and protect ourselves, instead of sitting in a pot of boiling hot water like a frog, not realising what is happening, until it is too late. With that, I present you with the following pot of boiling hot water:

Public pensions: America’s Greece? (The Economist, Dec 17th 2014)

States face shaky financial futures; pensions at risk (USA Today, July 6, 2015)

The U.S. is facing a $1 trillion pension shortfall (CNN Money, July 14, 2015)

Connecticut, America’s Richest State, Has a Huge Pension Problem (WSJ, Oct. 5, 2015)

The US government has a $20.4 trillion retirement problem (Business Insider, Apr. 6, 2016)

One of the nation’s largest pension funds could soon cut benefits for retirees (The Washington Post, April 20, 2016)

The US public pensions crisis ‘is really hard to fix’ (FT, May 1, 2016)

Kentucky, home to the worst-funded pension plan in the US (FT, June 10, 2016)

Are State And Local Government Pensions Underfunded By $5 Trillion? (Forbes, JUL 1, 2016)

California’s Pension Funding Crisis Just Got Worse (Forbes, Jul 19, 2016)

Covering Up the Pension Crisis (Wall Street Journal, Aug. 25, 2016)

States Face a $1 Trillion Pension Problem: Here Are the Worst 10 (The Fiscal Times, Aug. 29, 2016)

The pension gap (LA Times, SEPT. 18, 2016)

Pension Funds Face Day of Reckoning as Investment Returns Lag (News Max, 21 Sep 2016)

Will Looming State And Local Government Pension Crisis Bankrupt The U.S.? (Investor’s Business Daily, 10/14/2016)

US state public pension unfunded liabilities to hit $1.75 trillion: Moody’s (CNBC, 7 Oct 2016)

Pension crisis: 50% of States can’t cover their annual pension costs (Value Walk, October 10, 2016)

Pension crisis: Fully funded ones a rarity (Fox News, October 25, 2016)

New Jersey Tops Illinois as State With Worst-Off Pension System (Bloomberg, November 2, 2016)

The State Level Pension Crisis: Pennsylvania (The American Spectator, November 10, 2016)

Era of Low Interest Rates Hammers Millions of Pensions Around World (Wall Street Journal, Nov. 13, 2016)

US Pension Crisis: This is How Families Get Squeezed to Bail Out Pension Funds in Chicago (Wolf Street Nov 17, 2016)

South Carolina’s looming pension crisis (The Post and Courrier, Dec 3, 2016)

A Dallas public pension fund suffers a run (The Economist, Dec 8th 2016)

The Looming Debt Crisis: A State & Local Perspective (Joint Economic Committee, Dec 08 2016)

American Pension Crisis: How We Got Here (Forbes, DEC 9, 2016 @ 08:41 AM)

It is starting to get damned hot in here so now is your chance to jump out or risk becoming a side dish with butter, garlic and parsley poured all over you, AND no retirement savings to show for it.