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Some analysts state that the US stock market is over-valued and also that the stock market is good at discounting the future. Well, it can’t be both! If the stock market is good at discounting the future then current valuations are reasonable based on the profits that will be earned by companies over the next few years. On the other hand, if the stock market is over-valued then it is, by definition, doing a poor job of discounting the future.

Perhaps the stock market was once good at discounting the future, but a knowledgeable observer couldn’t claim with a straight face that the US stock market has been a good discounting mechanism over the past 20 years. Over this period we’ve seen valuations reach stratospheric levels in response to delusions about tech and internet company earnings, and then a collapse to bring prices into line with reality, followed by another rise to stratospheric valuations based on delusions that global growth knew no bounds and low-quality loans could be bundled together to create investment-grade securities, and then another collapse to bring prices into line with reality, followed by yet another upward ramp to stratospheric valuations.

The most recent multi-year ramp-up in stock prices was supposedly due to the discounting of an imminent ramp-up in corporate earnings, but S&P500 earnings during the second quarter of this year were no higher than they were three years earlier.

It is not difficult to come up with a superficial explanation for the US stock market’s abysmal 20-year record as a discounting mechanism. The explanation begins with the observation that from 1996 through to 2007 the market was dominated by the public, and, as the saying goes, the public will believe the most preposterous of bullish stories as long as the price is rising. As a result of the 2008 collapse, the public left the market and has not returned. At an earlier period in history this might have resulted in longer-term value-oriented investors taking control, but this time around it resulted in the market becoming dominated by computerised trading systems designed to scalp profits from extremely short-term fluctuations. That is, the market is now dominated by traders that make no attempt to discount the future beyond the next few hours or minutes.

The above explanation contains some truth, but for two main reasons it is far from complete. First, the general public hasn’t changed — it always has been and always will be the dumb money. Second, computerised trading systems are equally ‘happy’ to scalp profits by going short during declines or going long during advances. They are directionally neutral.

A better explanation begins with the realisation that the stock market as a whole has NEVER been a discounting mechanism. It has, instead, always reacted with a lag to changes in the monetary backdrop. The big difference over the most recent two decades is that for the most part the monetary backdrop has been far more supportive of asset prices than in the past. One consequence has been the stock market’s ability to spend a lot more time than usual in a condition called “extreme over-valuation”.

When I posted the “Trump will not really cut taxes” article in February there was a realistic chance that some form of tax-slashing proposal would be implemented before year-end. That’s no longer the case, but as far as the US economy’s health is concerned it makes less difference than most people think. What really matters is the total amount of government spending; not how the spending is financed.

To understand what I mean, it helps to think of the government as a giant parasite that feeds on the economy. The parasite uses part of what it eats to foster its own growth, while the remainder passes through and is excreted back into the economy. The parasite’s food is a mixture of taxation and borrowing, and provided that it is growing or maintaining its current size then a reduction in one food source MUST be offset by an equivalent increase in the other food source. For example, if the parasite doesn’t shrink then a reduction in taxation must be made up by an increase in borrowing.

The above is an over-simplification because the method by which the parasite gets its sustenance will have some influence on the economic outcome, but it hopefully explains why the Trump tax cuts are not a ‘make or break’ issue as far as the US economy’s health is concerned. The crux of the matter is that as long as the amount of government spending doesn’t shrink, less wealth being sucked out by direct taxation will result in more wealth being sucked out by another method.

That’s why the only genuine tax cut is the one that’s funded by reduced government spending.

[The following is an excerpt from a TSI commentary published about one month ago, but with updated charts.]

Some commentators on the financial markets still refer to something called the “commodity supercycle”. This is remarkable considering that the inflation-adjusted (IA) GSCI Commodity Index (GNX) made a new all-time low early last year and that relative to the Dow Industrials Index the GNX is not far from the all-time low reached in 1999. The relevant charts are displayed below. Just how badly would commodities have to perform to completely bust the supercycle myth?

We’ve been debunking the “commodity supercycle” in TSI commentaries for at least 10 years. The following lengthy excerpt from an August-2007 commentary is an example:

“…when it comes to the “commodity supercycle” we are definitely sceptics. We concur with the view that commodity prices in general and metal prices in particular are in long-term upward trends, but we do not think these trends are being driven by the strong growth of “Chindia” or the global spread of capitalism or the industrialisation of Asia or the movement of billions of people to the ranks of the “middle class” or any of the other catchphrases routinely used to neatly explain the price action. In our opinion, these explanations rank alongside slogans such as “new economy” and “technology-driven productivity miracle” that were used to legitimise the price action of tech stocks during the boom of the late-1990s.

As we see it, inflation (money supply growth) is causing a rolling boom/bust cycle whereby the combination of relative valuation and scarcity determines which sectors will be the major beneficiaries of inflation during the current cycle and which sectors will be relegated to the investment ‘scrap heap’.

The analysts who concoct simple explanations based on real (non-monetary) changes in the world and repeat these explanations in mantra-like fashion will look incredibly prescient for a long time, even though they largely ignore the monetary factors that are actually at the root of the price changes. Some of these analysts will even take-on the status of prophets due to their apparent abilities to see the future. But the inflation-fueled boom will eventually turn into a bust, even if the touted fundamental bases for the boom persist. For example, the growth of the internet and technological progress in general did not ‘miss a beat’ when the NASDAQ crashed. All that happened was that the primary focus of inflation shifted, causing the “new economy” prophets to fade away and bringing to the fore a new bunch of prophets who chant “commodity supercycle”.”

The above three paragraphs can be summarised as: There never has been and there is never likely to be a “commodity supercycle”. Instead, during some periods financial assets are the main beneficiaries of monetary inflation and during other periods commodities are among the main beneficiaries of monetary inflation.

It’s as simple as that.

The periods when financial assets are the main beneficiaries of monetary inflation are, on average, much longer than the periods when commodities are among the main beneficiaries of monetary inflation. This is because central bankers generally view large multi-year rises in commodity prices as evidence of an inflation problem and large multi-year rises in financial-asset prices as evidence that everything is fine. Consequently, steps are taken to curtail the monetary inflation more quickly when commodity prices are leading the charge.

The situation today presents an asset-allocation challenge because it’s far too soon for a new long-term commodity boom to get underway, but the major financial assets (stocks and bonds) are near their highest valuations ever. We are dealing with this situation by becoming more short-term-oriented in our thinking, which for us means not looking beyond the next 6-12 months when deciding what to own.

Globalisation, a term that when used in economics refers to the integration of national economies into a global marketplace, is perceived to be part of the reason for economic weakness in some countries. This is a perception that the politically-astute feed upon, often by invoking the “we” fallacy.

According to the “we” fallacy, anyone who happens to be located inside an arbitrary border is one of “us” and deserves preferential treatment at the expense of anyone who happens to be located outside the border. The “we” fallacy underpins the concerns that are routinely expressed about trade deficits, the thinking being that “we” are being hurt because “they” sell more stuff to us than we sell to them*.

To expose the flawed logic that initially leads to teeth-gnashing over trade deficits and subsequently leads to protectionist trade policies, I’ll use a hypothetical example involving two pig farmers (Bill and Bob) and a butcher (Arthur). Bill, Bob and Arthur live and work in a small US town located 1 mile south of the US-Canada border. Bill is a more efficient pig farmer than Bob and is thus able to sell his pigs at a 10% lower price. Consequently, Arthur buys twenty pigs per year from Bill and none from Bob. This arrangement continues for several years, at which point Bill decides to move his farm 2 miles to the north (to the other side of the US-Canada border).

Business-wise, nothing changes and Arthur continues to buy 20 pigs per year from Bill. However, due to the minor change in the physical location of Bill’s farm the business that Bill and Arthur have been conducting for many years now adds to the US trade deficit. In other words, a business relationship that nobody was previously concerned about suddenly becomes a problem for the collective “we”, even though nothing has really changed. Bob, sensing an opportunity, complains to the US government that he will have to fire his farmhand unless something is done to prevent his business from being undercut by cheap imports. In response, the US government slaps a 15% tariff on Canadian pigs, prompting Arthur to start using Bob as his pig supplier.

In this hypothetical example Bob has clearly benefited from the government’s interference in the pig market, but only at Arthur’s expense. Arthur is now forced to pay 10% more for his pigs, which will either cut into his profits — and, perhaps, curtail his plans to invest in the growth of his business — or cause him to raise his prices. Whatever happens, Bob’s gain will be matched by the loss incurred by other people within the US. In other words, the US “we” will not actually benefit, even in the unlikely event that the Canadian government doesn’t take counter-measures in an effort to protect its own collective “we”.

In the same way that the overall US economy failed to benefit from the pig tariff in my hypothetical example, “we” can never benefit from policies that restrict international trade. This is because from an economics perspective there is no “we”, there are just individuals trading with each other for their mutual benefit. A consequence is that when measures are taken by the government to protect the collective “we”, what actually results is the artificial creation of both winners and losers. The benefits gained by some individuals within the economy will be offset by the losses of others within the same economy.

The upshot is that protectionist measures are, at best, a zero-sum game, although in most cases they will turn out to have a net-negative effect on the ‘protected’ economy because they will interfere with price signals, keep inefficient businesses alive, and generally make both the cost of doing business and the cost of living higher than would otherwise be the case.

Protectionist measures are often popular, though, especially during hard economic times. Here’s why:

First, you generally need only a superficial understanding of economics to see the immediate and direct effects of a policy, whereas a deeper understanding of economics is often required to see the long-term and indirect effects. Very few people have this deeper understanding, so all they see are the immediate and direct effects of protectionism, which could be positive.

Second, the immediate benefits of the protectionist policy are typically concentrated, whereas the costs are widely spread. As a result, a politician can adopt a protectionist stance to gain the support of the relatively small number of people who are advantaged without losing the support of the much larger number of people who are disadvantaged. It’s an example of robbing Peter to pay Paul, where Paul notices and Peter doesn’t.

Third, when things are obviously going wrong it’s convenient to point the finger of blame outward at “them”. It certainly beats trying to identify the real source of the problem when doing so would lead to the finger of blame being pointed inward.

I guess we should be thankful that the same flawed logic that is often applied to international trade is usually not applied to interstate trade and is never applied to trade between towns, neighbourhoods and individuals within the same state, because if it were then there would be a lot less trade and a lot less wealth. The only reason the flawed logic isn’t applied at a more micro level is that the collective “we” is arbitrarily defined as everyone on a particular side of a country border.

*Refer to my 13th February blog post for an explanation of why a trade deficit is never a problem.

The following monthly chart shows that the year-over-year (YOY) growth rate of US True Money Supply (TMS) made a multi-year peak in late-2016 and has since fallen sharply to an 8-year low. The downward trend in US monetary inflation since late last year has been driven by the commercial banks, meaning that the pace of commercial-bank credit creation has been declining. The Fed, on the other hand, hasn’t yet done anything to tighten US monetary conditions. All the Fed has done to date is edge its targeted interest rates upward in a belated reaction to rising market interest rates.

That the Fed has been tagging along behind the market is evidenced by the following chart comparison of the US 2-year T-Note yield (in blue) and the Effective Fed Funds Rate (in red). The chart shows that a) the 2-year T-Note yield bottomed and began trending upward in the second half of 2011, b) the Effective FFR bottomed and began trending upward in early-2014, and c) the Fed made its first rate hike in December-2015. The market has therefore been pushing the Fed to raise its targeted interest rates for several years.

Interestingly, the Fed has caught up with and is possibly now even a little ahead of the market. This suggests scepticism on the part of the market that economic and/or financial conditions will be conducive to additional Fed rate hikes over the coming few months.

Based on the prices of Fed Funds Futures contracts we know that the market does not expect the Fed to make another rate hike until December at the earliest. This expectation is probably correct. Rather than make an additional ‘baby step’ rate hike there’s a good chance that the Fed’s next move will be to start reducing the size of its balance sheet by not reinvesting all the proceeds from maturing debt securities. Unless the stock market tanks in the meantime, this balance-sheet reduction will probably be announced on 20th September (following the FOMC Meeting) and kick off in October.

When the aforementioned balance-sheet reduction does start happening it will constitute the Fed’s first genuine attempt to tighten monetary conditions, although, as mentioned above, US monetary conditions have been tightening since late last year thanks to the actions of the commercial banks.

The job of a judge or juror is to impartially weigh the evidence and arguments put forward by both sides in an effort to determine which side has the stronger case. The job of a lawyer is to argue for one side, regardless of whether that side happens to be right or wrong. As a speculator it is important to think like a judge or a juror, not a lawyer.

Unlike a lawyer, a speculator can change sides ‘mid-stream’ if necessary to keep himself on the side favoured by the current evidence. There is no need for him to stick to a position come what may. However, changing sides is easier said than done, which is why so many speculators and commentators aren’t able to do it. Rather than let the evidence determine their stance, they adopt a stance and then look for confirming evidence. If they come across conflicting evidence, they downplay it. They aren’t aware of it, but their goal is to prove a particular case rather than align themselves with the strongest case.

Sometimes the case that a speculator desperately wants to prove also happens to be the case supported by the strongest evidence, enabling him to make large gains. However, if he continues to think like a lawyer he will eventually run into the problem that the weight of evidence shifts. After the inevitable shift happens he will steadfastly maintain his earlier position and lose whatever advantage he previously gained from being on the right side of the market.

In my speculations and financial-market writings I’m sometimes guilty of thinking like a lawyer. That’s why I developed the gold model (the Gold True Fundamentals Model – GTFM) that was discussed in a blog post last month. This model prevents my own biases and opinions from getting in the way when assessing whether the fundamental backdrop is bullish or bearish for gold.

The bottom line is that there is never a requirement for a speculator to defend a position. Unlike a lawyer, he is free to change with the evidence.

Many investors pigeon-hole themselves as “inflationists” or “deflationists”, where an inflationist is someone who expects more inflation over the years ahead and a deflationist is someone who expects deflation. I am grudgingly in the inflation camp, because the overall case for more inflation is strong.

I use the word “grudgingly” in the above sentence for two reasons. First, more inflation adds to the existing economic problems and will eventually result in major social upheaval, so when I predict that there will be inflation as far as the eye can see I don’t want to be right. Second, it means that I get lumped together with the perennial forecasters of imminent hyperinflation, even though my only mentions of hyperinflation over the past 17 years were to explain why it had zero probability of happening anytime soon.

With regard to the US situation, the main reason the case for more inflation is strong is that it doesn’t depend on private-sector credit expansion; it depends on the ability and willingness of the Fed to monetise sufficient assets to keep the total supply of money growing. A consistent theme in my commentaries over the 17 years since the birth of the TSI subscription service has been that the Fed could and would keep the inflation going after the private sector became saturated with debt.

Prior to 2008 there was very little in the way of empirical evidence to support the belief that the Fed could keep the inflation going in the face of a private-sector credit contraction, but that’s no longer the case. Thanks to what happened during 2008-2014 we can now be certain that the Fed has the ability to counteract the effects on money supply, asset prices and the so-called “general price level” of widespread private-sector de-leveraging. The only question left open to debate is: will the Fed CHOOSE to do whatever it takes to keep the inflation going in the future?

Based on the publicly-stated views of those who operate the monetary levers as well as on the economic remedies prescribed by today’s most influential economists and financial journalists, there’s a high probability that the answer is yes. At least, there is a high probability that the answer will be yes until the fear of inflation becomes much greater than the fear of deflation. However, the Fed is faced with a difficult challenge. It does not (I assume) want to engineer a steep decline in the dollar’s purchasing power, so every step of the way it tries to do no more than the minimum necessary to ensure a steady and modest rate of purchasing-power loss, with 2%-per-year having become the semi-official target.

The challenge is actually more than difficult; it’s impossible. The impossible-to-solve problem faced by the Fed and all the other central banks is that it can never be determined, in real time, what the aforementioned “minimum” is, because money-supply changes affect the economy in unpredictable ways and with large/variable delays. The economy therefore ends up careening all over the place and we occasionally get deflation scares, which are periods when it seems as if genuine deflation is about to happen. Paradoxically, the deflation scares are highly inflationary because they always prompt the Fed to ramp up the rate of money pumping, but while a deflation scare is in progress it can feel like the deflationists are finally going to be right.

I’m not ruling out the possibility that the deflationists will eventually be right. I hope that they will be right in the not-too-distant future, because more inflation will only add to the economic distortions and lead to an even bigger problem down the track. It’s just that they are, in effect, betting that devotees to the central planning ideology will suddenly realise the error of their ways and let nature take its course. The odds are very much against this bet paying off.

[This post is a modified excerpt from a recent TSI commentary]

In a 12th June blog post I revisited the potential pitfalls in using sentiment as a market timing tool. As an example of a pitfall, the post included a chart of the Investors Intelligence (II) bull/bear ratio suggesting that US stock market sentiment had been consistent with a bull-market top for the bulk of the past four years. Even though the chart helped to make my point it is appropriate to question how sentiment, when used as a contrary indicator, could be so wrong for so long.

I’ve come up with a possible explanation for why measures of US stock-market sentiment that worked well as contrary indicators in the past have not been useful of late. The reason relates to the third of the potential pitfalls outlined in the above-linked blog post. Specifically:

“…regardless of what sentiment surveys say, there will always be a lot of bears and a lot of bulls in any financial market. It must be this way otherwise there would be no trading and the market would cease to function. As a consequence, if a survey shows that almost all traders are bullish or that almost all traders are bearish then the survey must be dealing with only a small — and possibly not representative — segment of the overall market.”

The explanation I’ve come up with is that prior to the past few years the II sentiment survey, which is a survey of investment advisors who regularly publish their views via newsletters, reflected the sentiment of the investing public, but this is not so much the case anymore. Prior to the past few years the advisors and the general public would become increasingly bullish or increasingly bearish together, with high levels of optimism invariably following persistent price strength and high levels of pessimism invariably following either persistent or dramatic price weakness. Over the past few years, however, the perceptions of these two groups took separate paths. Investment advisors became very optimistic in reaction to the strong upward trend in prices, but for the most part the general public remained unenthusiastic about the stock market.

The change described above can be illustrated by comparing the II bullish percentage with the AAII (American Association of Individual Investors) bullish percentage, which has been done on the chart displayed below. The AAII survey is based on the opinions of retail investors, that is, the general public.

The chart shows that prior to 2014 the II (the blue line) and AAII (the black line) bullish percentages typically moved up and down together within a similar range, but that from 2014 onward the II bullish percentage tended to be significantly higher. Furthermore, the distance between the two survey results has increased since early this year, with the II bullish percentage remaining above 50 and the AAII bullish percentage spending most of its time in the 25-35 range. The most recent results show an II bullish percent of 54.9 and an AAII bullish percent of 29.7.

It seems that the general public’s stock-market sentiment has not reached an optimistic extreme during the current cycle. Does this mean that there’s a lot more price strength to come or does it mean that the next major price top will happen without the general public having fully embraced the upward trend?

I don’t know, but it’s definitely possible that the public will never fully embrace the latest bullish trend for the simple reason that it is financially incapable of doing so. Having had its savings decimated when earlier Fed-fueled investment booms inevitably collapsed it may not have the financial wherewithal to enthusiastically participate in the Fed’s latest bubble-blowing venture.

A 23rd June post at the TSI Blog described the model (the Gold True Fundamentals Model – GTFM) that I developed to indicate the extent to which the fundamental backdrop is bullish for gold. The GTFM is an attempt to determine a single number that incorporates the most important fundamental drivers of the gold price, where I define “fundamental driver” as something that happens in the economy or the financial markets that causes a significant change in the desire/urgency to own gold in some form. Keith Weiner subsequently posted an article objecting to some of my “fundamental drivers”, which would be fine except that his article contains several misunderstandings of these price drivers and/or how I am using them. The purpose of this post is to address these misunderstandings and provide a little more information on the GTFM’s components.

1. The ‘Real’ Interest Rate

Keith states: “The Real Interest Rate is the Nominal Interest Rate – inflation.” No, that’s not what the real interest rate is, although many people wrongly calculate it that way.

Keith and I agree that it is not possible to calculate the economy-wide change in money purchasing-power (PP), but even if it were possible to come up with a single number that represented prior “inflation” the real interest rate would not be the nominal interest rate minus this number. The reason, to explain using an example, is that the real return that will be obtained by someone who makes a 12-month investment today in an interest-bearing security will have nothing to do with the change in the PP of money over the preceding 12 months. Instead, the real return that will be obtained by this person will be determined by the change in money PP over the ensuing 12 months.

Now, we can obviously never know in advance what the real return on any interest-bearing security or deposit will be, but since the advent of Treasury Inflation-Protected Securities (TIPS) in 2003 it has been possible to roughly determine the real return on Treasury debt expected by the average bond trader. The TIPS yield, which is based on the EXPECTED rate of currency depreciation, is my ‘real’ interest rate proxy.

If there had been a TIPS market in the 1970s then it would probably be apparent that the large gains made by the gold price during that decade were related to a low/falling real interest rate, where the real interest rate is defined as the nominal interest rate minus the expected rate of currency depreciation. In any case, there has definitely been an inverse correlation between the TIPS yield (10-year or 5-year) and the gold price over the past 10 years. Furthermore, the correlation has strengthened over the past 2 years.

By the way, it’s the DIRECTION, not the value, of the TIPS yield that matters to gold and that is taken into account by the GTFM.

The inverse relationship between the TIPS yield and the gold price is far from perfect, the reason being that there are times when other price drivers are more influential. That’s why the ‘real interest rate’ has only a one-seventh weighting in the GTFM.

2. The Yield Curve

There has never been a strong and consistent short-term correlation between the gold price and the yield curve, but near major turning points the yield curve tends to be the dominant driver.

In broad terms, the boom phase of the central-bank-promoted boom-bust cycle is generally associated with a flattening yield curve and the bust phase is generally associated with a steepening yield curve. Gold generally performs better during the bust phase, when the curve is steepening. Somewhat counterintuitively, banks tend to do best during the long periods of yield-curve flattening. This can be demonstrated empirically and makes sense if you understand how the central-bank-promoted boom-bust cycle works.

A major flattening trend in the US yield curve got underway during the second half of 2011 and continues to this day. This flattening trend is associated with a boom, which, in turn, has temporarily helped the banks and reduced the desire to own gold.

3. Credit Spreads

The trend in credit spreads is one of the best measures of the overall trend in economic confidence, with widening spreads (yields on lower-quality bonds rising relative to yields on higher-quality bonds) being indicative of declining economic confidence. Gold tends to do relatively well during periods when economic confidence is on the decline, that is, during periods when credit spreads are widening. I have demonstrated this in the past using charts.

4. The Relative Strength of the Banking Sector

Keith writes: “We haven’t plotted it, but we assume bank stocks will outperform the broader stock market when the yield curve is steeping by way of falling Fed Funds rate. This is when the banks’ net interest margin is rising, and they are getting capital gains on their bond portfolio too. At the same time, credit spreads are narrowing, so the banks are getting capital gains on their junk bonds.”

No, that’s not how it works. Refer to my yield curve comments above for a very brief explanation.

The banking sector will often fare poorly during major yield-curve steepening trends because a banking crisis is often a primary cause of the steepening trend. In any case, this indicator is based on the concept that the investment demand for gold will be boosted by declining confidence in the banking system and reduced by rising confidence in the banking system.

5. The US Dollar’s Exchange Rate

More often than not, the US$ gold price trends in the opposite direction to the Dollar Index. However, there are times when a crisis outside the US causes both a rise in the US$ on the FX market and a large rise in the US$ gold price. The fact that the inverse correlation between the gold price and the Dollar Index can break down in a big way at times is why the US dollar’s performance on the FX market only has a one-seventh weighting in the GTFM. To put it another way, if the gold price always moved in the opposite direction to the Dollar Index then there would be no reason for gold traders to consider anything except the Dollar Index.

6. The General Trend in Commodity Prices

I have included the general trend in commodity prices as indicated by the S&P GSCI Commodity Index (GNX) in the GTFM for the practical reason that there are times when it tips the balance. That is, there are times when a strong upward trend in commodity prices enables the US$ gold price to rise despite an otherwise slightly-bearish (for gold) fundamental backdrop and there are times when a strong downward trend in commodity prices causes the US$ gold price to fall despite an otherwise slightly-bullish fundamental backdrop.

7. The Bond/Dollar Ratio

There are fundamental reasons for the existence of a positive correlation between the bond/dollar ratio (the T-Bond price divided by the Dollar Index) and the US$ gold price, but I currently don’t have the time or the inclination to go into these reasons. Instead, for the sake of brevity I present the following chart-based comparison of the gold price and the bond-dollar ratio. The positive correlation is obvious and is evident over much longer periods than the 3-year period covered by this chart.

I hope the above goes at least part of the way towards explaining the components of my gold model.

[This post is a modified excerpt from a TSI commentary published a few weeks ago]

To paraphrase Jim Grant, gold’s perceived value in US$ terms is the reciprocal of confidence in the Fed and/or the US economy. Consequently, what I refer to as gold’s true fundamentals are measures of confidence in the Fed and/or the US economy. I’ve been covering these fundamental drivers of the gold price in TSI commentaries for almost 17 years. It doesn’t seem that long, but time flies when you’re having fun.

Note that I use the word “true” to distinguish the actual fundamental drivers of the gold price from the drivers that are regularly cited by gold-market analysts and commentators. According to many pontificators on the gold market, gold’s fundamentals include the volume of metal flowing into the inventories of gold ETFs, China’s gold imports, the volume of gold being transferred out of the Shanghai Futures Exchange inventory, the amount of “registered” gold at the COMEX, India’s monsoon and wedding seasons, jewellery demand, the amount of gold being bought/sold by various central banks, changes in mine production and scrap supply, and wild guesses regarding JP Morgan’s exposure to gold. These aren’t true fundamental price drivers. At best, they are distractions.

In no particular order, the gold market’s six most important fundamental price drivers are the trends in 1) the real interest rate, 2) the yield curve, 3) credit spreads, 4) the relative strength of the banking sector, 5) the US dollar’s exchange rate and 6) commodity prices in general. Even though it creates some duplication, the bond/dollar ratio should also be included.

Until recently I took the above-mentioned price drivers into account to arrive at a qualitative assessment of whether the fundamental backdrop was bullish, bearish or neutral for gold. However, to remove all subjectivity and also to enable changes in the overall fundamental backdrop to be charted over time, I have developed a model that combines the above-mentioned seven influences to arrive at a number that indicates the extent to which the fundamental backdrop is gold-bullish.

Specifically, for each of the seven fundamental drivers/influences I determined the weekly moving average (MA) for which a MA crossover catches the most trend changes in timely fashion with the least number of ‘whipsaws’. It’s a trade-off, because the shorter the MA the sooner it will be crossed following a genuine trend change but the more false trend-change signals it will cause to be generated. I then assign a value of 100 or 0 to the driver depending on whether its position relative to the MA is gold-bullish or gold-bearish. For example, if the yield-curve indicator is ABOVE its pre-determined weekly MA then it will be assigned a value of 100 by the model, because being above the MA points to a steepening yield-curve trend (bullish for gold). Otherwise, it will be zero. For another example, if the real interest rate indicator is BELOW its pre-determined weekly MA then it will be assigned a value of 100 by the model, because being below the MA points to a falling real-interest-rate trend (bullish for gold). Otherwise, it will be zero.

The seven numbers, each of which is either 0 or 100, are then averaged to arrive at a single number that indicates the extent to which the fundamental backdrop is gold-bullish, with 100 indicating maximum bullishness and 0 indicating minimum bullishness (maximum bearishness). The neutral level is 50, but the model’s output will always be either above 50 (bullish) or below 50 (bearish). That’s simply a function of having an odd number of inputs.

Before showing a chart of the Gold True Fundamentals Model (GTFM) it’s worth noting that:

1) The fundamental situation should be viewed as pressure, with a bullish situation putting upward pressure on the price and a bearish situation putting downward pressure on the price. It is certainly possible for the price to move counter to the fundamental pressure for a while, although it’s extremely likely that a large price advance will coincide with the GTFM being in bullish territory most of the time and that a large price decline will coincide with the GTFM being in bearish territory most of the time.

2) The effectiveness of fundamental pressure will be strongly influenced by sentiment (as primarily indicated by the COT data) and relative valuation (as primarily indicated by the gold/commodity ratio). For example, if the fundamental backdrop is bullish and at the same time the gold/commodity ratio is high and the COT data indicate that speculators are aggressively betting on a higher gold price then it is likely that the bullish fundamental backdrop has been factored into the current price and that the remaining upside potential is minimal. The best buying opportunities therefore occur when a bullish fundamental backdrop coincides with pessimistic sentiment and a low gold/commodity ratio.

Getting down to brass tacks, here is a weekly chart comparing the GTFM with the US$ gold price since the beginning of 2011.

A positive correlation between the GTFM and the gold price is apparent on the above chart, which, of course, should be the case if the GTFM is a valid model. If you look closely it should also be apparent that the fundamentals (as represented by the GTFM) tend to lead the gold price at important turning points. For example, the GTFM turned down in advance of the gold price during 2011-2012 and turned up in advance of the gold price in 2015 (the GTFM bottomed in mid-2015 whereas the gold price didn’t bottom until December-2015).

The tendency for gold to react to, rather than anticipate, changes in the fundamentals is not a new development, as evidenced by gold’s delayed reaction to a major fundamental change in the late-1970s. I’m referring to the fact that by the second half of 1978 the monetary environment had turned decisively gold-bearish, but the gold price subsequently experienced a massive rally that didn’t culminate until January-1980.

The GTFM was slightly bearish over the past two weeks, but three of the model’s seven components are close to tipping points so it wouldn’t take much from here to bring about a shift into bullish territory or a further shift into bearish territory. The former is the more likely and could occur as soon as today (23rd June).

Hyman Minsky was an economist who popularised the idea that “stability leads to instability”. According to Minsky and his followers, credit expands rapidly during the good times to the point where a lot of borrowing is being done by financially fragile/vulnerable entities, thus sowing the seeds of a financial crisis. That’s why the start of a financial crisis is now often referred to as a “Minsky moment”. Unfortunately, Minsky’s analysis was far too superficial.

Minsky described a process during which financing becomes increasingly speculative. At the start, most of the debt that is taken on can be serviced and repaid using the cash flows generated by the debt-financed investment. At this stage the economy is robust. However, financial success and rising asset prices prompt both borrowers and lenders to take on greater risk, until eventually the economy reaches the point where the servicing of most new debt depends on further increases in asset prices. At this stage the economy is fragile, because anything that interrupts the upward trend in asset prices will potentially set in motion a large-scale liquidation of investments and an economic bust.

This description of the process is largely correct, but rather than drilling down in an effort to find the underlying causes Minsky takes the route of most Keynesians and assumes that the process occurs naturally. That is, underpinning Minsky’s analysis is the assumption that an irresistible tendency to careen from boom to bust and back again is inherent in the capitalist/market economy.

In the view of the world put forward by Keynesians in general and Minsky in particular, people throughout the economy gradually become increasingly optimistic for no real reason and eventually this increasing optimism causes them to take far too many risks. The proverbial chickens then come home to roost (the “Minsky moment” happens). It never occurs to these economists that while any individual could misread the situation and make an investing error for his own idiosyncratic reasons, the only way that there could be an economy-wide cluster of similar errors at the same time is if the one price that affects all investments is providing a misleading signal. The one price that affects all investments is, of course, the price of credit.

Prior to the advent of central banks the price of credit was routinely distorted by fractional reserve banking, which is not a natural part of a market economy. These days, however, the price of credit is distorted primarily by central banks, and the central bank is most definitely not a natural part of a market economy. Therefore, what is now often called a “Minsky moment” could more aptly be called a “central-bank moment”.

I expect the next “central-bank moment” to arrive within the coming 12 months. I also expect that when it does arrive it will generally be called a “Minsky moment” or some other name that deftly misdirects the finger of blame, and that central banks will generally be seen as part of the solution rather than what they are: the biggest part of the problem.

In a blog post in March of this year I discussed the limitations of sentiment as a market timing tool. I wrote that while it can be helpful to track the public’s sentiment and use it as a contrary indicator, there are three potential pitfalls associated with using sentiment to guide buying/selling decisions. Here are the pitfalls again:

The first is linked to the reality that sentiment generally follows price, which makes it a near certainty that the overall mood will be at an optimistic extreme near an important price top and a pessimistic extreme near an important price bottom. The problem is that while an important price extreme will always be associated with a sentiment extreme, a sentiment extreme doesn’t necessarily imply an important price extreme.

The second potential pitfall is that what constitutes a sentiment extreme will vary over time, meaning that there are no absolute benchmarks. Of particular relevance, what constitutes dangerous optimism in a bear market will often not be a problem in a bull market and what constitutes extreme fear/pessimism in a bull market will often not signal a good buying opportunity in a bear market.

The third relates to the fact that regardless of what sentiment surveys say, there will always be a lot of bears and a lot of bulls in any financial market. It must be this way otherwise there would be no trading and the market would cease to function. As a consequence, if a survey shows that almost all traders are bullish or that almost all traders are bearish then the survey must be dealing with only a small — and possibly not representative — segment of the overall market.

I went on to write that there was no better example of sentiment’s limitations as a market timing indicator than the US stock market’s performance over the past few years. To illustrate I included a chart from Yardeni.com showing the performance of the S&P500 Index (SPX) over the past 30 years with vertical red lines to indicate the weeks when the Investors Intelligence (II) Bull/Bear ratio was at least 3.0 (a bull/bear ratio of 3 or more suggests extreme optimism within the surveyed group). An updated version of the same chart is displayed below.

The chart shows that while vertical red lines (indicating extreme optimism) coincided with most of the important price tops (the 2000 top being a big exception), there were plenty of times when a vertical red line did not coincide with an important price top. It also shows that optimism was extreme almost continuously from Q4-2013 to mid-2015 and that following a correction the optimistic extreme had returned by late-2016.

Sentiment was at an optimistic extreme late last year, at an optimistic extreme when I presented the earlier version of the following chart in March and is still at an optimistic extreme. In effect, sentiment has been consistent with a bull market top for the bulk of the past four years, but there is still no evidence in the price action that the bull market has ended.

Regardless of what happens from here, four years is a long time for a contrarian to be wrong.