Gold’s support at 1270$/oz fundamentally not sustainable

Gold managed to close around 10$/oz higher this week compared with the close on Thursday before the major trading centers closed for the Easter Holiday weekend. Also other precious metals posted gains in the weekly comparison. However, we have some doubts that these gains are sustainable.

On Thursday, gold fell to a low of 1268$/oz shortly after noon GMT. From this level, gold slightly recovered and rocketed to 1291.5$/oz at the London PM fixing. There were no complaints that gold had been manipulated higher from the usual conspiracy theorists this time. Technical analysts argue that gold had found support and this triggered a short-covering rally. In-deed, there are several reaction highs and lows located around the 1270$/oz level. And according to the chart theory, those previous highs or lows often serve as support or resistance and lead to market reversals.

However, we are not convinced that it was a technical reaction, which led to the strong rebound, and that gold has a solid basis at around 1270$/oz. Often, when those support or resistance levels are approached, one sees attempts by professional traders to fish stop orders and causing false break-outs with a strong and rapid countermove. This was not the case in the gold market. After hitting the low, gold remained in a consolidation mode for an hour. The strong rise later seems to have taken the market by surprise.

Furthermore, the US durable goods orders data had just been released and it came in much better than Wall Street economists had predicted. Core durable goods orders in March rose 2.0% on the month, while the consensus predicted an increase of only 0.6%. Stronger US economic data is currently not positive for the gold market. Also the reaction in stock markets was positive, which also argues against a technical driven short-covering rally only because gold hit a support level.

The recovery of gold only gained momentum and the price rocketed after stock markets pared gains and turned negative. The reason for this reversal in equity markets had been the recent developments in the geo-political tensions about the Ukraine. Russia’s defense minister announced that he ordered a military drill of forces near the border to Ukraine. Furthermore, the compromise reached before the Easter Holiday did not lead to the agreed results. Ukraine’s acting interim president ordered again troops to move to the eastern parts of the country and to disarm the separatists as well as to regain control over occupied government buildings.

Thus, it is the currently negative correlation between the price of gold and US or other major stock indices, which helped gold to rebound from a technical support level. Our quantitative model for the S&P 500 index, based on macroeconomic indicators, is still long positioned. Furthermore, the recovery of gold was not accompanied by an inflow of fresh capital to gold ETFs. While the holdings of the biggest ETF, the SPDR Gold Trust remained unchanged at 792.14 tons on Thursday and Friday (after falling by 3 tons at the start of the week), gold holdings of all ETFs declined on Thursday according to data compiled by Thomson Reuters.

Therefore, the fundamental factors still indicate that the risks for gold are biased to the downside. The support at 1270$/oz might not be as strong as expected by some technical analysts. However, in the short-run, the geo-political tensions about the Ukraine could remain a dominating factor.    

On the ECB Plans for QE

The development of the US dollar against the major currencies remains one of the crucial factors for the price trends of precious and also base metals. Of course, the policy of the Fed is one decisive determinants of exchange rate fluctuations. However, the monetary policy of other major central banks is also an important component in the price discovery process in foreign exchange rate markets. In this past week, ECB president Draghi stepped up verbal interventions which failed to drive the euro weaker against the US dollar. However, the ECB prepares the blueprint for implementing quantitative easing. Once the ECB embarks on QE, the US dollar could strengthen, which would have a negative impact on metal prices.

As the ECB is the central bank of 18 independent countries, implementing a common quantitative easing policy is not as easy as it was for the Fed or the Bank of England. The ECB has to decide, how to split the amount of quantitative easing among its member countries. According to the online edition of a German weekly magazine, the ECB staff considers currently two proposals. The first one is to allocate the funds for asset purchases based on the share, which each national central banks hold of the ECB capital. This would imply that the ECB would purchase for 26% of the QE volume German bonds, for 20% French and for 18% Italian bonds. When the ECB introduced the outright monetary transaction (OMT) program, which was not used so far, the Deutsche Bundesbank complaint that this program would be a transfer program. This argument also played a role in the decision of the German constitutional court. However, the argument of transfers could now also be applied to this proposal. As the ECB earns interest on the bonds purchased, the profit resulting from QE will be distributed to the national central banks. But German bonds bear the lowest yields. Thus, countries with higher yields could rightly complain that they would subsidize Germany, which would profit from interest earned by the ECB on buying bonds of countries with a higher yield level.

Furthermore, allocating the highest share of QE funds for buying German assets does not make much economic sense. One should keep in mind, what the reason for QE is: namely to prevent deflation. Germany profited from the financial crisis in the Eurozone already by having the lowest yields in the Eurozone and by growing relatively strong compared to the rest of the Eurozone. The deflation risk in the Eurozone is the result of the wrong economic policy, which Germany pushed through at EU summits. If the ECB will decide to allocate funds for QE according to the share on its capital, then Germany would be the biggest winner again. Another argument against the highest share for Germany is that German companies already have lower funding costs compared with companies located in other Eurozone member states. They need less support from the ECB than others.

The second proposal is to allocate the funds according to the size of national government bond markets. In this case, the ECB would allocate 25% for buying Italian bonds and about 22% for French and German bonds respectively. This would make more sense because some countries with higher borrowing costs for companies compared with German entities would receive a bigger slice of the cake. However, from our point of view, this is still not an optimal solution.

The two proposals do not take into account the reason for QE. To prevent deflation, countries where the deflation risk is high should receive relatively more funds than countries with less deflation risk. Thus, one criteria could be the difference between the ECB target inflation rate and the actual inflation rate. As the ECB’s target is an inflation rate close, but below 2%, a good starting point might be the difference to 1.9% inflation rate. According the Eurostat, the statistical office of the EU, the harmonized CPI inflation in Germany is 0.9% in March 2014. Thus, Germany is 1.0% below target. However, in Greece, the inflation rate is the lowest with -1.9%, which implies that Greece is 2.8 percentage points below the target. In Cyprus, harmonized consumer prices dropped 0.9% from the same month one year earlier and in Spain the inflation rate was -0.2%. At the other end of the spectrum are Finland with +1.3% and Austria with 1.4%, which would need less monetary stimulus.

Another indicator of deflation risk would be the output gap. The risk of deflation is increasing, the more the actual output is below the potential output. Thus, countries with a bigger negative output gap should receive relatively more monetary stimulus than countries with a small negative output gap. Given the GDP development over the last few years, it is also not difficult to guess that the Southern European countries would need a relatively higher monetary stimulus than Germany.

It should be clear, that neither the difference between actual and target inflation rate nor the size of the output gap alone are a good weighting factor for the allocation of QE funds by the ECB. The size of the bond markets should also play a role because the financial markets have to absorb the volume of QE measures. What we would propose is a two-step process to calculate the allocation weights. In a first step, weighting factors would be calculated based on the inflation gap. In the second step, the size of bond markets would be multiplied with this inflation based weighting factor. The volume of QE would then be allocated according to the share of the weighted bond market size in relation to the sum of weighted bond market size over all member countries.

Precious metals rise, but less than fundamentals sugges

This week, all four precious metals posted gains compared with the close of the Friday before. However, given the development of the major fundamental drivers, the performance was a bit disappointing.  The only exception was palladium, which rose 1.75%. Gold came in second with an increase of 1.2% over the week. However, after rising again above the psychological resistance of 1,300$/oz, a stronger rebound had to be expected against the backdrop of the fundamentals. Silver and platinum did not even manage to increase by 0.5%.

Not only the fundamentals, but also geo-political factors would have argued for a stronger increase of gold as the metal is usually regarded as a safe haven. Russians are a strong part of the population in the eastern parts of the Ukraine. The occupation of government buildings in some cities in the eastern Ukraine increased the tensions instead of deescalating it. NATO warns that Russian forces might invade the Ukraine and US President Obama already announced there would be further sanctions against Russia. In such a situation, there is usually a stronger demand for safe haven assets.

Some members of the FOMC feared, according to the minutes of the recent meeting, that financial markets might not understand the dot charts with the forecasts for the Fed Funds target rate. Obviously, they were right as the reactions after the FOMC meeting, Mrs. Yellen’s speech on March 31, and now after the release of the minutes showed. The messages is again that the first rate hike has to be expected only as early as mid-2015. We have pointed out several times that the FOMC has not changed its course. Even under the chairmanship of Mr. Bernanke, the Fed always indicated during 2013 that until mid-2015 the Fed Funds target rate would remain at the exceptional low level of less that 0.25%.

After the release of the FOMC minutes, the US stock market rallied. However, this rally was very short lived. Already the next day, the market gave the gains back. Profit-taking and the earnings season had a stronger impact. Especially technology stocks suffered most. But also the broader S&P 500 index lost 2.6% in the week over week comparison.

Over the recent couple of months, there was a negative correlation between the US stock market and gold. Given the decline of the US stock market, one would have expected a stronger flow into gold. However, investors have reduced their exposure to gold. The large speculators have reduced their net-long position in gold futures from 100,145 to 88,599 contracts in the week ending April 8, according to the recent CFTC report on the “Commitment of Traders”. Compared to the high, the non-commercials have reduced their net-long position by more than one third. Also the holdings of the biggest gold ETF, the SPDR Gold Trust, fell by almost 5 tons during last week.

But not only should the stock market have contributed to a stronger flow into gold. Also other fundamentals were positive for gold. The US dollar rebounded as markets have now understood that the first rate hike by the Fed will not take place earlier as some economists and market strategists suggested. The US dollar index fell by almost one full point to 79.45 and the euro rose to 1.3905, a gain of 2ct compared to the close of the Friday before. The head of the Deutsche Bundesbank, Mr. Weidmann, played down the risk of deflation in the Eurozone earlier this past week. However, one should not make the mistake to interpret this statement as an indication that the ECB would not embark on QE. A central bank cannot warn of deflation risks for psychological reasons. Such a warning could just increase the risk of deflation, which is clearly unwelcome as the experience of Japan demonstrates. However, as the Eurozone is just a currency union of independent states, implementing QE is far more complicated than it had been for the Fed or the Bank of England. Thus, we still expect that the ECB staff is working on the technical details of QE. From our point of view, the most likely scenario is still that the ECB will vote for QE before the summer recess. This should have a weakening impact on the euro against major currencies, which would be negative for gold and other precious metals.

Also the US Treasury market reacted positively on the FOMC minutes. The yield on the 10yr US T-Note fell by 11bp to 2.62%. This reduction of opportunity costs of holding precious metals should have a positive impact on the demand for all four metals. However, the crucial question is how far the yields on the 10yr benchmark Treasury note could fall. As long as the expansion of the US economy keeps on track, we regard US T-Notes at a yield below 2.5% as expensive. Thus, the most likely scenario remains that the US bond market will not provide much more support for gold. In the medium-term, rising yields are likely, which would be negative for gold.

Another fundamental driver of gold is the price of crude oil, which rose by 2.6$/bbl to 103.74$/bbl for the front-month WTI future at Nymex. Brent increased by only 0.6$/bbl for the front month future. However, also for this factor, the medium-term outlook remains not favorable for gold and other precious metals. In the short-run, the re-opening of ports in eastern parts of Libya remains a crucial factor. OPEC released its monthly report recently and also has reduced the forecast for crude oil demand. Thus, the risk for crude oil appears currently to be more on the downside.

Despite all fundamental drivers were positive, gold rose just 1.2% over the week. A stronger reaction had to be expected. Furthermore, it seems that major investors have reduced their exposure in gold by selling into the rallies. The outlook for the fundamental drivers of precious metals over the medium-term horizon remains negative for precious metals. At best they remain neutral but will not provide much support for a further rally. Only the supply situation for the PGMs remains supportive and should lead to an outperformance, especially of palladium. But for gold and silver, the risks are more biased to the downside in the medium-term. But this does not rule out that the markets edge up further in the short-run. 

Precious metals re-bounced but danger is ahead

It was a trading week with two different halves for precious metals. All four precious metals ended the week higher compared to the Friday before. However, at the start of the week, especially gold was weaker and fell to 1.277$/oz, the lowest level since February 11, 2014. Thus, gold corrected more than 50% of the rise from the low of this year. While silver traded sideways at the start of the week, the PGMs already continued to recover.

On the one hand, the weakness of gold at the start of the week could be explained by the fall below the 1,300$/oz level, which triggered further selling and physical demand in Asia was not sufficient to prevent the slide. However, it was also the development of stock markets, which weighed on gold as investors switched funds from gold into equities. This could be seen by the gold holdings of the SPDR Gold Trust ETF, which declined by 6 tons in total on Monday and Tuesday to 800.9 tons.

What has driven US stocks higher and gold lower on Monday was a speech given by Fed chair, Mrs. Yellen. She stated that the US economy would still need support by a monetary stimulus. Some analysts and traders interpreted this statement as an indication that the Fed might not hike the Fed Funds target rate as soon as the market expected after the recent FOMC meeting. However, the FOMC remained on track, and neither the remark of Mrs. Yellen at the press conference nor the statement made last Monday are a hint of a policy change. The sentence, which excited traders on Monday, is just underlining what is obvious for those with some understanding of monetary policy. If the FOMC were not thinking that the US economy still need the monetary stimulus, the committee would have terminated QE3 already completely. That the Fed pumps $55bn into the US bond market this month could not be justified if the FOMC were convinced that this stimulus would not be needed!

Furthermore, this statement also does not alter the outlook for the first hike of the Fed Funds target rate. The most likely scenario is still that the first increase will take place in mid-2015. Currently, the FOMC reduces the volume of bond purchases by $5bn for the US Treasuries and the mortgage bonds respectively. Maintaining this pace implies, that the FOMC would decide at the October meeting to end buying mortgage bonds and at the December meeting to terminate purchases of US Treasury paper. Thus, six month after the December 2014 meeting is right in the middle of 2015. And this date had been mentioned by Mr. Bernanke already about one year ago. Thus, the words might be different, but the message remains the same. However, that the Fed Funds target rate will be positive again in real terms could only be expected to take place in 2016 given the FOMC projections for the Fed Funds rate and the inflation rate. Thus, the Fed monetary policy will remain expansionary for two more years.

The turn-around for gold came on Wednesday when the market shifted its focus on the forthcoming US labor market report. The ADP estimate already provided an indication that the non-farm payroll figure would be solid. With an increase of 191,000 jobs created, the actual figure was very close to the consensus among Wall Street economists. However, the figures for the first two months of 2014 had been revised considerably higher. The unemployment rate remained unchanged at 6.7%. The FOMC already takes into account that further improvements of the unemployment rate might be harder to achieve as persons who left the labor force might return with a better outlook for finding a job. The average hourly earnings remained unchanged in March. All in all, this labor market report provides just confirmation that the FOMC is likely to maintain its current policy.

The labor market report triggered the rise of gold above the 1,300$/oz level. However, we don’t regard this move as justified by the fundamentals. The ECB kept rates unchanged. However, ECB president Draghi talked about measures of quantitative easing during the press conference. The ECB council has not yet made a decision. But it looks like that the ECB staff is working on a blue print for QE. Some of the details have to be finalized. Overall, it appears to be only a question of time. According to a report in a German paper, the ECB would simulate the impact of QE in the volume of 1,000bn Euro. If such a package would be implemented, gold might get on the same path as after the announcement of Abenomics in Japan. The Euro would probably weaken against the US dollar, which is likely to send gold lower.    

Shanghai Copper Price and the Inventories Puzzle

After the financial crisis in 2008, there had been a structural break in the copper market. Until this break, the development of the copper price could be well explained by economic and financial market data of industrialized countries, like LME warehouse inventories, total OECD leading indicator, the US dollar index and the S&P 500 stock index. Although China had already risen to the world’s top copper consumer, this data provided a better fit for the LME copper price than the OECD leading indicator for China or the Shanghai Stock Exchange Composite index. After the financial crisis, Chinese data explained the copper price development better.

However, focusing on Chinese data had led to another problem, especially for the analysis of refined copper supply and demand. The identity equation that production plus net imports have to equal consumption plus change of inventories is the basis for the supply and demand analysis. The left hand side of this equation can be estimated with sufficient reliability. The Chinese Customs Office records exports and imports. Also the copper production could be estimated by China’s National Bureau of Statistics as companies have to report their production figures. The problems are on the right hand side of the equation as copper consumption is not directly observable.

Therefore, a concept of estimating apparent consumption is applied. Consumption is estimated by subtracting the change of inventories from the sum of copper production plus net imports. But the problem with this approach is that data on inventories is available for the state reserves and inventories in SHFE warehouses. However, private inventories – mostly held in bonded warehouses in the Shanghai region – are hidden. Thus, apparent consumption would be overestimated if the change of hidden inventories is underestimated and vice versa. Therefore, having a reliable estimate of the change in hidden inventories is essential for an analysis of supply and demand (consumption).

Since the report for global copper supply and demand in November 2013, the International Copper Study Group (ICSG) provides an estimate for adjusting apparent consumption in China. The ICSG applies the estimates of three consulting companies for this adjustment. If there is a significant change in the relationship of hidden inventories to official SHFE warehouse copper stocks then there should be a structural break in the link between SHFE copper price and inventories.

The chart above shows the development of the 3^rd month copper price at the Shanghai Futures Exchange and the inventories held in warehouses licensed by the SHFE. Already a visual inspection shows that there was a close relationship between the development of the copper price and the inventories in the period from the beginning of 2009 until the end of 2011. Since 2012, there appears to be a structural break. This could be verified empirically by an econometric test.

For a quantitative analysis, it is not sufficient to estimate just a linear relationship between the copper price and the inventories. If other factors have an influence on the copper price, then the regression coefficient would be overestimated in the case those other factors were excluded. Therefore, econometric models are usually formed to explain the price development by some more explanatory variables than merely the copper inventories. As the chart below shows, there is also a close relationship between the Shanghai Stock Exchange Composite index and the copper price. What is important for the analysis is that this relationship is also staple in the period after the start of 2012. This is also confirmed by econometric test for a structural break. The same applies for the SHFE 3^rd month copper price and the US dollar index. If a trend variable is included also in the model for the copper price, then there is also a structural break at the start of 2012.

Thus, in a typical model, the price of copper would be a function of inventories, the Shanghai Stock Exchange index and the US dollar index. It is well known from basic algebra, that this function could be rearranged that the inventories are a function of the other variables. Under the assumption that the relationship, which held in the period between the start of 2009 and the end of 2011, also held after 2011 if the development of the hidden inventories were taken into account in the inventory variable, one might derive an estimate for the change of hidden inventories. First, the regression coefficients for the period from 2009 until 2011 are estimated. Second, based on these parameters for the period from 2012 on, the copper inventories are estimated. Finally, the difference between the estimated inventories and the actual SHFE warehouse inventories provide an estimate of the development of hidden inventories since 2012. However, it should be noted that this figures would only be an estimate of the change in hidden inventories and not an estimate of the absolute level.

The empirical results of those estimates provide some surprises. First, there is a positive regression coefficient for the relationship between the price of copper and the SHFE warehouse inventories. This is in clear contrast to the theory of inventories, which postulates that prices should rise if inventories are falling and vice versa. This theory is also widely used to explain the development of the convenience yield of commodities.

The empirical results of those estimates provide some surprises. First, there is a positive regression coefficient for the relationship between the price of copper and the SHFE warehouse inventories. This is in clear contrast to the theory of inventories, which postulates that prices should rise if inventories are falling and vice versa. This theory is also widely used to explain the development of the convenience yield of commodities.

Therefore, the question arises: “What could explain the positive relationship between inventories and copper prices at the SHFE during the period from 2009 to 2011”? One possible explanation would be that speculation did not only take place in the futures market but also in the cash market. After the collapse of Lehman Brothers, China was very quick to announce measures to stimulate the economy and to prevent a major crisis. Also the state reserve bureau bought copper. Thus, speculators might also have bought copper and stored it in SHFE warehouses. This procedure gave them more flexibility in managing the trade by having the opportunity to sell a future and to deliver into this future at expiration if the market turns against their positions. 

Another possible explanation is arbitrage. If the copper market in Shanghai is in a contango, then there could be an incentive to buy copper in the cash market, store the copper in an exchange licensed warehouse and sell short a copper future with a more distant maturity. If the market is in backwardation, then there is an incentive to take out inventory.

Thus, we included another variable in the regression equation for the SHFE inventories, the spread between the 3^rd and the 1^st month copper price. The regression coefficient for the curve spread is highly significant and it also has the right sign. If the difference between the 3^rd and the 1^st month copper price widens then the inventories tend to increase, just as the theory suggests. In addition, including the curve spread as an explanatory variable for the SHFE warehouse inventories leads to a reduction of the regression coefficient of the copper price, but there is still a positive relationship. Therefore, another factor might explain this unusual correlation between the copper price and the inventories during this period.

It has often been reported that copper is used as a collateral for funding. Given the lower interest rates in the US dollar money market and the trend of the Chinese Yuan appreciating against the US dollar, it makes sense to fund in US dollars and to invest the proceeds in Yuan. Thus, the spread of the 3mth Shanghai interbank rate and the 3mth US Dollar Libor has been added as a further independent variable in the regression equation. But this procedure leads to the problem of multicolinearity as the interest rate spread is highly correlated with the copper price development. However, this is exactly what had been sought as the copper price could be dropped out of the equation explaining the development of the inventories. Thus, the four variables – copper curve spread, interest rate spread, Shanghai Stock Exchange Index and US dollar index explain quite well the movements of copper inventories held at the SHFE warehouses. The regression coefficients are all highly significant different from zero.

The second surprise is the comparison between the actual and estimated inventories since the start of 2012. The chart above shows the development of the SHFE inventories and the estimate according to the multiple regression model. Already from visual inspection, it is quite obvious that the model failed to predict the development of inventories, but this had been expected given the discussion about a rather strong build of hidden inventories. The surprise is the sign of the average forecast error.

For the period from 2009 until the end of 2011, over which the regression coefficients have been estimated, the average of the deviations between the actual inventories and the fitted values is zero by definition. However, for the period from January 2012 until the end of March 2014, the average of the difference between actual and estimated inventories is 82,340 tons. The t-test shows that this average is significantly different from zero at less than the 1% (error) level. During the last 2 and a quarter years, the average of inventories held in SHFE warehouses was 180,268 tons. This indicates that the inventories were on average 84.1% higher than what the model predicted based on the relationships prevailing from the start of 2009 until the end of 2011. If the assumption of constant regression coefficients and a stronger build of hidden inventories in bonded warehouses were correct, one would expect that actual inventories since 2012 were lower and not higher than the model estimate.

Thus, there had been a structural break in the model, which is also confirmed by an empirical test. The Chow test also allows to test, which variable caused the structural break. For the stock index, the US dollar index and the curve spread, the hypothesis of no structural break cannot be rejected. However, for the constant term and the interest rate spread, the hypothesis of no structural break can be rejected at the 1% significance level. The constant term alone explains around 62,000 tons of the higher inventories during the out-of-sample period. For the interest rate spread, the sign changed to negative during the period beginning in January 2012.

Thus, there had been a structural break in the model, which is also confirmed by an empirical test. The Chow test also allows to test, which variable caused the structural break. For the stock index, the US dollar index and the curve spread, the hypothesis of no structural break cannot be rejected. However, for the constant term and the interest rate spread, the hypothesis of no structural break can be rejected at the 1% significance level. The constant term alone explains around 62,000 tons of the higher inventories during the out-of-sample period. For the interest rate spread, the sign changed to negative during the period beginning in January 2012. 

The model failed to provide an estimate of the change of hidden copper inventories held in bonded warehouses, which would confirm the prevailing narrative. However, the structural break of the constant term indicates that also a shift of inventories from bonded into registered warehouses is a distinct possibility.