The Stock Is Dead, Long-Live The Flow: Perpetual QE Has Arrived

Thursday, June 14th, 2012

Two months ago, as we were carefully reading the latest Goldman explanation of how the firm had completely missed something Zero Hedge predicted back in January, namely the record warm winter’s impact on skewing seasonal adjustments for payroll data (which has since validated our day 1 of 2012 predication that 2012 will be a carbon-copy replica of 2011, and which has made the comedy value of another Goldman masterpiece, that of Jim O’Neill’s idiotic “2012: Not a Repeat of 2010 or 2011″ soar through the roof) we stumbled upon something we knew was about to get much, much more airplay: Goldman’s quiet and out of place admission that what matters for a country’s central bank is the flow of its purchases, not the stock (another massive economic misconception we have been trying to debunk since the beginning). Recall these words: “…we have found some evidence that at the very long end of the yield curve, where Operation Twist is concentrated, it may be not just the stock of securities held by the Fed but also the ongoing flow of purchases that matters for yields…” This is how we summarized this observation two months ago (pardon the all caps): “UNLESS THE FED IS ACTIVELY ENGAGING IN MONETIZATION AT EVERY GIVEN MOMENT, THE IMPACT FROM EASING DIMINISHES PROGRESSIVELY, ULTIMATELY APPROACHING ZERO AND SUBSEQUENTLY BECOMING NEGATIVE!”

All caps aside, what this means is simple: if it is indeed flow that matters (and it is), then Fed intervention can never stop, period. If the stock of a central banks’ assets is irrelevant, the Fed can have $1 on the left side of the balance sheet or $1 quadrillion: it does not matter – if the market expects the Fed to stop buying assets tomorrow, then the crash is as good as here. That has precisely been the biggest flaw with the Fed-accepted stock model, per which Bernanke can buy up a few trillion in MBS and the stock market will be flat as a frozen lake. Alas, this is increasingly becoming obvious is not the case. Hence flow.

Which is why today, two months later, and a week before Bernanke will almost certainly announce the NEW QE, we were not surprised at all to see that Goldman has actually made the case for flow in the form a of a white paper titled “Flow Effects at the Ultra-Long end of the Curve.”

For monetary theory purists this is equivalent to Martin Luther walking up to the front door of the Marriner Eccles building and nailing his 95 theses: we have now entered the era of the monetary reformation, which incidentally as more and more classical economists follow suit, will throw all of Keynesian and neo-classical economics into a tailspin where virtually every core assumption will have to be reevaluated.

Congratulations economists: in their pursuit of another record year of bonuses at any cost, Goldman just sacrificed your precious voodoo. Because where Goldman goes, everyone else promptly follows.

From Goldman Sachs:

Flow Effects at the Ultra-Long End of the Curve (Shan/Stehn)

• With the scheduled end of the Fed’s twist approaching, market participants are debating the extent to which the end of the Fed’s purchases will affect the yield curve. The “stock view” – which Fed officials and we have generally subscribed to – suggests that markets tend to price in the Fed’s purchases at announcement and then show little responsiveness to the subsequent flow (and end) of purchases. The “flow view,” however, would suggest that yields increase when the twist concludes.
• Using a simple model of the Treasury yield curve, we revisit this issue in today’s daily. Our estimates suggest that the flow effect is negligible for short and intermediate maturities (of less than 20 years) but statistically significant at the ultra-long end of the curve (with maturities of 20+ years). Although the uncertainty is significant, these estimates suggest that – all else equal – the end of the twist will have negligible effects on the short and intermediate part of the curve, but might push up yields at the ultra-long end of the curve by around 5 basis points.

With the scheduled end of the Fed’s twist approaching, market participants are debating the extent to which the end of the Fed’s purchases will affect the yield curve. Economic theory suggests that we need to distinguish between the effects of the announced stock of Fed purchases and the flow of actual purchases. In forward-looking and liquid markets, bond yields should primarily depend on the announced stock of purchases. Therefore, markets should price in the size of the purchase program at announcement and show little response to the subsequent flow of purchases. This means that when the flow of Fed purchases is discontinued—but the size and duration of the Fed’s balance sheet is unchanged—there should be little effect on yields. Empirical evidence has generally reinforced this prediction. Our own work, for example, has confirmed that stock effects dominate flow effects. (See Sven Jari Stehn, “Stocks vs. Flows Revisited: End of QE2 Unlikely To Have Significant Effect on Bond Yields,” US Daily, April 13, 2011.)

Although the “stock view” appears to be a good description of the effects of Fed purchases at the short and intermediate maturities, flows might be more important at the ultra-long end of the Treasury curve. Intuitively, this would fit with the observation of investment habitat – how purchases of 20-30 year bonds are mostly conducted by more heterogeneous investors that are less sensitive to changes in demand and supply in the Treasury market. Consistent with this view, we found tentative evidence for flow effects at the ultra-long end of the curve in earlier work (see US Daily cited above). However, the number of observations was very small and so the estimates were very imprecise.

With more data on hand and the end of the twist in sight, we revisit the issue of flow effects from Fed asset purchases at the long end of the curve in today’s daily.

Following our previous work, we focus not just on one particular point on the yield curve at a time but also explore how the Fed’s purchase program has affected the entire yield curve. Doing so allows us to better separate the effects of economic factors (which affect the entire yield curve) from the Fed purchases (which differ across the yield curve). Making use of the relative movement of yields at different maturities provides more information and should thus provide better identification. (This disaggregated approach is motivated by Stefania D’Amico and Thomas King, “Flow and Stock Effects of Large-Scale Treasury Purchases,” Finance and Economics Discussion Series, Federal Reserve Board, 2010-52.)

Specifically, we construct our model in a number of steps.

First, we use the New York Fed’s Treasury yield curve estimates, which provide coupon-equivalent par yields for maturities between one year and 30 years.

Second, we construct a dataset of daily flows of Treasury purchases from the New York Fed’s website and allocate these into different “maturity buckets.” For example, we match purchases of bonds that have remaining maturity of between 9.5 and 10.5 years with the 10-year bond yield discussed above. Our sample period – which runs from March 2009 through April 2012 – can be divided into three phases: QE1 (March 2009 through October 2010), QE2 (November 2010 through August 2011), and the twist (since September 2011). The distribution of the purchases is shown in Exhibit 1 below.

Third, we control for the announced stock of Treasury purchases. Given our focus on testing for flow effects and the difficulty of identifying the announcement effect at individual maturities, we use a very flexible approach to capture the effect of the stock of purchases on yields. (Specifically, we use an intercept dummy and a linear trend for each maturity bucket in each QE phase.) The advantage of this approach is that we do not have to make a priori assumptions on the magnitude of the stock effect and doing so should raise the bar for finding flow effects. The drawback, of course, is that our model focuses solely on generating a flow estimate and cannot provide an estimate for the magnitude of the stock effect.

Finally, we combine the data on yields and flows with our stock dummy variables to construct a panel model for these thirty maturity buckets with daily data since March 2009. To take into account variations in duration and/or liquidity factors across maturity buckets, we allow the constant in our model to vary across maturities (that is, we include so-called maturity “fixed effects”). And to disentangle the effect of the Fed’s purchases at the different maturity buckets from economic factors that affect yields across the maturity spectrum, we allow the whole yield curve to shift over time (that is, we include so-called “time fixed effects”). In a nutshell, we estimate the following panel regression:

yield = ?*flow + ?*stock+ fixed effects

where the flow variable captures the purchases, the stock variable is given by the dummies described above and the fixed effects represent maturity and time fixed effects as discussed above. If there is a flow effect, then we should find a negative ? in this regression. To explore whether the flow effect differs at different parts of the curve, we allow ? to vary across different maturity buckets. In our baseline specification, we split the yield curve into seven segments (namely, 1-2 years, 3-4, 5-7, 8-10, 11-14, 15-20, and 21-30 years).

Our results are summarized in Exhibit 2 below. (For the full set of details, see Table 1 in the appendix). Our estimates reveal statistically insignificant ? coefficients at the short and intermediate maturities (up to 20 years), but negative and statistically significant estimates of ? at the ultra-long end of the curve (with 21-30 years maturity). In other words, our estimates confirm previous findings that the flow effect is negligible for short and intermediate maturities but significant at the ultra-long end of the curve. In terms of magnitudes, our results suggest that a $1bn purchase at the ultra-long end of the curve (all other things equal) lowers the yield by 3.3bp at that part of the curve.

We performed a few robustness checks. First, we split the regressions for the 1-10 maturities and 11-30 maturities in two regressions to address the concern that the daily time effects are not appropriate when grouping all 30 maturities together in one regression. The results are qualitatively similar: the flow effect at the very long end of the curve remains significant but the size of the effect drops from 3.3 to 2.3bp per $1bn (see Table 1 in the appendix). Second, we omitted the 1-2 years and 1-3 years maturities since the yields of these maturities have effectively been pinned down by the Fed’s guidance language. Again the results are qualitatively unchanged (not shown).

In a final step, we can look at the implication of our estimates for the yield curve should the twist end in June as currently scheduled. As discussed, our model suggests that – all other things equal – we should not expect to see significant effects on the short and intermediate parts of the yield curve. But – again all other things equal – our model would point to an increase in yields at the ultra-long end of the curve. A simple approach to gauging the implied magnitude of this effect is to look at the average monthly purchases at this part of the curve over the last few months and ask by how much yields would move if this dried up. The Fed has purchased around $13bn per month at the ultra-long end of the curve (21-30 years) since the start of the twist. Taking into account that no purchases were actually made at the 21-23 year maturity (see Exhibit 1 above), this comes to an average of around $1.8bn per month in each of the maturity buckets where purchases actually took place. Applying our estimates of the flow effect – the 2.3bp to 3.3bp range per $1bn of purchases – this would imply that an increase in yields at the ultra-long end of the curve of around 5bp.

While we have reasonable confidence in the qualitative conclusion of our analysis – that flows tend to perturb yields only at the ultra-long end of the curve – it is important to keep in mind a number of caveats when interpreting the quantitative implications of our model. First, disentangling the influence of stocks, flows and other variables on the yield curve is a very difficult exercise and the uncertainty is therefore considerable. Second, our estimated magnitudes are only about as large as the average daily volatility of yields over the last three years (around 6bp at the 30-year maturity). Finally, it is important to note that our model’s estimate only refers to the effect of the end of the flow of purchases on yields and does not take into account other factors that might influence yields at the same time. For example, the end of the twist could have a significant effect on the yield curve beyond the analysis presented here if Fed officials deliver something different from what the market is expecting for the June meeting.

Tags: Balance Sheet, Carbon Copy, Central Banks, Goldman, Masterpiece, Mbs, Misconception, Monetization, O Neill, Payroll Data, Predication, Qe, Quadrillion, S Central, Seasonal Adjustments, Stock Market, Stock Model, Warm Winter, What This Means, Yield Curve
Posted in Markets | Comments Off

Goldman’s Jan Hatzius: 3 Reasons to Expect Fed to Still Ease in April or June

Friday, March 16th, 2012

Based on some of the “action” and commentary in the past few days, it appears many believe the Fed is potentially stepping away from the monetary easing parade based on comments from the last FOMC meeting.  I don’t believe that, nor does Goldman’s top economist honcho, Jan Hatzius.

“It has definitely become a closer call, but we still expect another asset purchase program that involves purchases of both mortgage-backed securities and Treasurys,” he said.

Below he outlines the 3 reasons he expects the Fed to announce an easing in April or June, I particular want to highlight the last one  i.e. no continued easing = tightening! since the market has priced in further easing.

Also note Hatzius highlights the potential impact of warmer weather (which many have noted) and seasonal adjustment distortions.  If you have not read the piece from December on this, it is important to note - it gets very little play in the financial media but we’ve seen spikes up in economic activity in Q4′s and Q1′s and down in Q2′s and Q3′s (which lead to more monetary easing!).  Hence the government economic data, if it follows the pattern of the past few years should begin to weaken in April-June if for nothing else than the distortions 2008-2009 have had on traditional seasonal adjustments.

On to Hatzius:

1. The improvement might not last.

With real GDP growth tracking just 2% in the first quarter and signs that at least some of the recent strength is probably due to the unusual warm weather and perhaps some seasonal adjustment distortions, question marks still surround the true pace of activity growth. In addition, there are still several actual or potential “headwinds” for growth, including a reduced boost from inventory accumulation, the recent increase in oil and gasoline prices, continued risks from the crisis in Europe, and the specter of fiscal retrenchment after the presidential election.

2. Even if the improvement does last, faster growth would be desirable to push down the unemployment rate more quickly.

Fed officials believe that the level of economic activity and employment is still far below potential. This means a large number of individuals are involuntarily unemployed, which not only causes hardship in the near term but may also translate into higher structural unemployment in the long term…This creates an incentive to find policies that speed up the return to full employment.

3. Not easing might be equivalent to tightening.

At a minimum, the bond market currently discounts some probability of QE3. This has kept financial conditions easier than they otherwise would have been, which has presumably supported economic activity. A decision not to ratify expectations of QE3 could therefore result in a tightening of financial conditions.

Tags: Asset Purchase, Distortions, Economic Activity, Economic Data, Fiscal Retrenchment, Fomc, Gasoline Prices, GDP Growth, Goldman, Headwinds, Presidential Election, Q4, Question Marks, Real Gdp, Seasonal Adjustment, Seasonal Adjustments, Specter, Spikes, Treasurys, Warm Weather
Posted in Markets | Comments Off

What “Seasonal Adjustments” Actually Mean and Do For Data (Tchir)

Tuesday, March 13th, 2012

Via Peter Tchir of TF Market Advisors,

There has been a lot of talk lately about “seasonal adjustments” and what they actually mean and do for the data.

Reporting today’s forecast in “seasonally adjusted” terms would not be incorrect. The temperature today is almost 30 degrees higher than the average March temperature in NYC, so reporting it as 30 degrees higher than the annual temperature is fine. You instantly know that today is abnormally warm for the time of year. It doesn’t necessarily help you choose what to wear unless you know the monthly and annual averages. It isn’t wrong, but the information isn’t perfect either. If you only had national average temperatures, how would you seasonally adjust today’s NYC temperature? That gets more complicated.

We like “seasonally” adjusted numbers because it “smooths” the data. We don’t get big jumps due to the time of year and we can apply trend lines, etc. to the graphs. There is nothing wrong per se with that, but the adjustments can also mask things in the data. On unemployment, is the BLS adjustment better or worse than what other people model? What variables does it account for? Does it properly account for potential effects of how long a recession has been going. How often does “seasonality” change. In theory, the market could see a -200k number and realize that if normally this time of year it would have been -400k, then it is a good number. It would be a good sign, but it is only +200k for example if the seasonality is consistent. Anyways, enough on that subject. Seasonality isn’t bad, and is useful in many ways, but so is the raw data and trying to figure out if the adjustments make sense or need to be modified a lot due to the particular circumstances at the time (like great warm weather).

The markets are almost all doing well so far this morning. Corporate and financial credit in Europe is significantly tighter, with Main 3 tighter, XOVER 11 tighter, and the Financials CDS index 4 tighter. Partly on the back of some German confidence numbers (which don’t seem to be a leading indicator) and hopes that the EU is becoming less austere. Spain has been told to get to a 5.3% budget deficit, rather than the 4.4% one they reneged on last week. Both sides are maintaining the farce that the 3% target for 2013 will be met.

Spanish bond yields are higher again, and CDS is unchanged – about the only asset that doesn’t seem to be doing better today. According to Bloomberg, the EFSF will be releasing money to Greece, €5.9 billion in March, €3.3 billion in April, and €5.3 billion in May. That is good, because the ECB has €4.7 billion of GGB bonds maturing in March, and €3.3 billion of GGB bonds maturing in May.

After a flurry of early numbers, we can all wait for the Fed statement. If there was ever a day designed to be waiting for the Fed statement sitting outside at Bryant Park or somewhere, today would be that day. But inside, staring at screens, the market will be closely watching the statement. There is some concern the Fed may acknowledge that inflation is actually a concern for the first time, reducing chances of further QE. As the election gets closer, it will become harder for the Fed to move on QE without compellingly bad data (not just bad in the eyes of the Fed, but to general person tracking the economy). There is still hope that the Fed has been downplaying growth in order to justify QE and will signal its intentions to move before it is too late, and the bank stress tests may be another reason the Fed can justify QE, especially in the mortgage market, where the Fed insisted on scenarios worse than most investors expected.

Tags: Annual Temperature, Average Temperatures, Circumstances, Europe, Graphs, Mask, Raw Data, Recession, Seasonal Adjustments, Seasonality, Time Of Year, Trend Lines, Unemployment, Variables, Warm Weather
Posted in Markets | Comments Off

TrimTabs Biderman: Is BLS Data Skewed?

Sunday, February 5th, 2012

The biggest headline for all financial media today is that the US economy added a much more than expected 243,000 jobs in January, and 446,000 jobs over the past two months. That is many more new jobs than our estimate of less than 50,000 for January and our estimate of 90,000 for December and January.

Our estimate of a slowly growing economy is based primarily upon daily income tax collections. Either there is something massively changed in the income tax collection world, or there is something very suspicious about today’s Bureau of Labor Statistics hugely positive number. We continue to check and recheck our analysis of income tax collections. We are aware that another service believes that incomes are growing faster than we do. So far we have not found any errors or discrepancies in our work, but if we do, we will let you know.

The BLS each month reports two data series, but only one jobs number is reported by the media. Actual jobs outstanding, not seasonally adjusted, are down 2.9 million over the past two months. It is only after seasonal adjustments – made at the sole discretion of the Bureau of Labor Statistics economists that 2.9 million less jobs gets translated into 446,000 new seasonally adjusted jobs for January and December.

No one I know has any idea as to how the BLS does this seasonal adjustment. BLS historic data is changed almost every month until the income tax returns for each year are available three years in arrears. In other words, the BLS currently has accurate data for 2008 and before.

I keep repeating that the BLS refuses to use the data embedded in income tax collections to be able to report real time jobs and wages. Why does it refuse? Could the reason it refuses to use real time data on jobs and incomes be because perhaps this jobs number is politically motivated? The entire world is looking at US job creation as a proxy on how well Obama is doing? Could the Obama administration be pressuring its economist employees to create the best possible new jobs number?

Obviously I am quite suspicious of the numbers that I see in today’s BLS press release. Remember most financial journalists and even stock market strategists do nothing more than rewrite government press releases. So do not expect very few others to question the good news.

For those of you who care, look at Table B-1, Total Nonfarm Employment in today’s BLS press release attached to this video on our blog site. Start with the non seasonally adjusted table that shows that in November 2011, there were 133.172 million actual jobs. Actual jobs dropped by 220,000 jobs in December and actual jobs dropped an additional 2.7 million in January. Only as a result of unknown seasonal adjustments, could the BLS report 243,000 new hires in January.

Yes, the labor market contracts during the winter and expands in the spring and summer. Could this number be manipulated? Of course it could. Is it? I don’t know.Am I the only suspicious soul out here? Hope not. Certainly feels lonely right now.

Charles Biderman
President & CEO
TrimTabs Investment Research

Tags: Accurate Data, Arrears, Bls Data, Bureau Of Labor, Bureau Of Labor Statistics, Discrepancies, Economist, Economists, Entire World, Income Tax Collections, Income Tax Returns, Job Creation, Jobs And Incomes, New Jobs, Real Time Data, Seasonal Adjustment, Seasonal Adjustments, Sole Discretion, Time Jobs, Wages
Posted in Markets | Comments Off

Emerging Markets Radar (January 16, 2012)

Saturday, January 14th, 2012

Emerging Markets Radar (January 16, 2012)

Strengths

• The People’s Bank of China (PBOC) 2011 financial statistics show that M2 growth rebounded significantly to 13.6 percent year-over-year at the end of December. With seasonal adjustments, this represents a 26.8 percent month-over-month increase on an annualized basis. Many attribute the monetary expansion to fiscal expansion measures taken by the Chinese government. In an early December Investor Alert, we discussed that we were at the beginning of a monetary easing cycle in China as the government tries to fine-tune the economy.
• The amount of new loans in China during December was Rmb 640.5 billion, higher than the estimated Rmb 575 billion.
• After targeting Rmb 7.5 trillion in 2011, China may set its 2012 new bank loan target at Rmb 8 trillion. Money supply growth is expected to be 14 percent and CPI at 4 percent, the Oriental Morning Post reported. The government may ease lending to infrastructure projects and local government financing vehicles (LGFV) this year.
• China’s online gaming revenue rose 32.4 percent (year-over-year) to Rmb 2.85 billion in 2011, while the mobile game market’s revenue rose 86.8 percent year-over-year to Rmb 1.7 billion, Xinhua News reported.
• After sinking 28 percent in value during 2011, China’s domestic stock markets (as measured by the CSI300 Index) have started 2012 by posting a 6.5 percent gain after the first five days of trading. The increase is driven by monetary easing policy and market participations by domestic institutions. After Premier Wen Jiabao called for boosting confidence in the domestic stock market, the China Securities Regulatory Commission (CSRC) will pursue reforms in IPO pricing mechanisms to prevent excessive high pricing, will encourage improving corporate dividend payouts, and will try to increase the proportion of corporate bonds financing.
• China’s December CPI dropped to 4.1 percent, a 15-month low, after peaking in July. This drop will provide room for China to increase money supply. China’s December PPI dropped 1 percent from November, indicating core input prices are declining faster than the market expectation.
• Korea’s December PPI rose 4.3 percent from the previous year but was down 5.1 percent from the previous month. The Bank of Korea maintained its benchmark interest rate at 3.25 percent for the seventh straight month, a widely-expected move.
• The China Auto Association announced that December 2011 passenger car sales were up 4.6 percent. The market had expected no gain due to a high base effect in December 2010 when the stimulus plan came to expire. The Association also forecast 2012 passenger car sales to grow 7 percent after growing 5.19 percent in 2011.
• Macau gaming names gained in the week after reporting 850 million a day (Macanese pataca) in gaming revenues for the first eight days of the year. This is similar to last year’s Golden Week in October.
• China’s National Energy Administration plans to double solar capacity this year and add four times the capacity by 2015. Solar stocks globally jumped on the news this week.
• Russia’s inflation dropped lower than post-Soviet lows, falling to 6.1 percent on a year-over-year basis. December’s inflation number is significantly lower than the 2010 average annual figure of 8.8 percent. However, Roubini Global Economics is forecasting inflationary pressures to reemerge in the latter part of 2012.

Weaknesses

• China’s December exports were up 13.4 percent while imports were up 11.8 percent. Imports were lower than the market consensus, indicating slower export/import growth and increased pressure for China to further ease money supply.
• Continued weakness in electronics shipments drove Philippine exports to drop 19.4 percent year-over-year in November, the seventh-straight month of declines. Consensus estimates were for a 10 percent drop. Nevertheless, Philippine exports are a small share of the country’s GDP. The 2012 Philippine economy will be driven by domestic consumption, infrastructure investments and overseas remittance.
• Malaysia’s industrial production gained 1.8 percent year-over-year in November, the slowest pace in four months, as mining contracted and manufacturing eased.
• China’s foreign-exchange reserves dropped for the first time in more than a decade as foreign investment moderated. The holdings fell to $3.1 trillion on December 30 from $3.2 trillion on September 30, data released on the People’s Bank of China shows.
• China’s power use growth may slow to 8.5 percent this year, Xinhua reported, citing the deputy director of China’s State Electricity Regulatory Commission. Electricity consumption slowed to 11.7 percent last year from 14.5 percent in 2010.
• Signs that Chinese lenders will postpone losses on trillions of yuan loans made to local governments may undermine investor confidence in the banking sector, Standard & Poor’s said on Thursday. This local government loan issue can never be fully understood or go away by the like-minded institutions and speculators. We believe it is a huge issue but resolvable given time and time is always on the side of the Chinese government.

Opportunities

• Russian producer TNK-BP’s PetroMonagas venture with Petroleos de Venezuela SA plans to boost output of heavy oil by 20 percent to 145,000 barrels a day in 2013.
• Weibo, a Chinese microblogging service run by Sina, has seen its user base reach more than 50 percent of the country’s entire Internet population of 500 million people, according to J.P. Morgan. As a leader in microblogs, Sina Weibo possesses unique opportunities to monetize the phenomena. Proliferation of tablets and smartphones should also give additional push to the microblogging trend.

Threats

• With China in a monetary easing cycle and the U.S. experiencing a slow but steady recovery, the European sovereign debt issue is the single biggest question for the market. Therefore, it is still advisable to not be surprised by short-term market volatility.
• BCA Research published a piece this week highlighting themes among the emerging market space. Among them, a U.S. dollar breakout coupled with emerging market currency weakness was mentioned. Unlike in 2008, the problems are now in Europe and developing countries, while U.S. growth is set to outperform other regions. BCA believes this only reinforces the case for a strong U.S. dollar as global capital favors U.S. assets, while emerging market currencies remain more volatile than they have been in the recent past.

Tags: Bank Of China, China Securities Regulatory Commission, Corporate Bonds, Csrc, Domestic Institutions, Domestic Stock Market, Fiscal Expansion, Game Market, Gaming Revenue, Infrastructure Projects, Investor Alert, Local Government Financing, Monetary Expansion, Money Supply Growth, Oriental Morning, Pboc, Seasonal Adjustments, Securities Regulatory Commission, Target, Xinhua News
Posted in Markets | Comments Off

Are ‘Seasonal Adjustments’ Overstating Economic Performance in Q4+Q1s, but Understating Q2+Q3s?

Friday, December 23rd, 2011

A fascinating piece of research by Nomura via FTAlphaville which makes the case that ‘seasonal adjustments’ might be altering economic data to the point we are getting overstatements of economic activity in the fourth and first quarters of a year, but understatements during the middle two quarters.  This has certainly been the pattern the past 2 years as economic activity seems to weaken dramatically during the late spring and summer…. causing Mr. Bernanke to come down from the mountains at Jackson Hole, WY (both of the past two years) with promises of free and easy money to all.  Just as the economic data begins to once more turn more rosy.  Now in 2011 one could blame the Japan tsunami (and ending of QE2?) for the reason the slowdown happened April-Mayish, but strangely we had the almost exact same pattern in 2010.  Food for thought as the implications are interesting from a stock market perspective – we should expect poorer than usual data spring through end of summer, then expect better data in fall and winter – for nothing more than the way our government statistics make their numbers.

———————

• Endless worries about a eurozone disintegration and potential growth slowdowns across the developing world, but at least there’s been a streak of surprisingly not-terrible economic indicators in the US heading into the new year.  Or: feels a lot like December 2010, doesn’t it? Unfortunately, there are some methodological reasons for why the positive indicators and the sense of déjà vu should make you sceptical.

• That chart is of Nomura’s economic surprise index for the US, and it shows how macroeconomic indicators in the last two years have surprised in both directions relative to consensus forecasts.  The similar path of the index in 2010 and 2011 is immediately obvious and has an explanation — one that should dampen at least some of the optimism around the uptick in these indicators recently.
• In two notes, the first from late October and the second from last week, Nomura explains how the severe contraction in the US economy at the end of 2008 and early 2009 was captured by some economic indicators as new seasonal trends (emphasis ours):

The standard empirical techniques used to seasonally adjust US economic data – such as the Census Bureau’s X11 and X12 programs – have interpreted some of the sharp contraction in the fourth quarter of 2008 and the first quarter of 2009 as a change in “seasonal” patterns. As a result, current techniques for seasonal adjustment tend to boost data in the fourth and first quarter of the year, relative to previous patterns, then depress data in the second and third quarters.

• The standard narrative of the last year was that the US economy was showing signs of revival in late 2010, only to be derailed by the increasingly dramatic sovereign debt problems in Europe, the Japan earthquake and tsunami, and the spike in oil and commodity prices. Since the autumn it’s shown signs of an accelerating recovery, if not an overwhelmingly impressive one.  That’s not wrong, but Nomura’s analysis shows that problems in the techniques used to account for seasonal trends have contributed to an exaggerated sense of how well we were doing at this time last year and, relatedly, to the forecast errors on the part of macroeconomists who got a little carried away.

Could be happening again:

The apparent “bias” in seasonal adjustment also helps to explain the pattern of forecasting errors over the last two years. Figure 5 shows the average market “surprises,” weighted by their standard deviation, for five-month indicators — Philadelphia Business Outlook Survey, the NY FRB Empire State Survey, the Chicago PMI, and the ISM manufacturing and non-manufacturing survey – as well as the estimated seasonal “bias” for these series. The correlation between forecast errors and the estimated seasonal “bias” since the beginning of 2010 is 0.66.

More complicated data also may have been affected by this problem. For example, the average seasonal adjustment factors for retail sales excluding autos, a key input for GDP, have been revised in ways that may have been influenced by the recent recession. These changes imply that the current seasonal adjustment factors may tend to overstate the growth nominal retail sales in the fourth quarter by about 2 percent, at an annual rate, and understate growth in the second quarter by about 1-1/2 percent on the same basis. These differences are large enough to have a notable impact on our assessment of economic trends.

• And if you want one bit of compelling evidence to bolster Nomura’s case, here’s a chart comparing the performance of the ISM manufacturing production index against the Fed’s measure of industrial production. Unlike the other indicators Nomura mentions, the Fed measure was adjusted earlier this year to account for the earlier flaws in its seasonal adjustment techniques:

• They’re headed in different directions, and the Fed’s reading for November disappointed and cut against the trends evidenced in other indicators when it came out last week. Now we have a reason why.  Up next, writes Nomura, you can expect exaggeratedly strong readings from the Chicago PMI later this month and the next ISM manufacturing survey at the start of January.

We draw two, very simple conclusions from these notes.

• One is just that methodological issues, a favourite topic of ours, matter an awful lot and continue to be under-appreciated. A push for better data is always welcome, and we can’t think of a good reason for the Bureau of Economic Analysis, for instance, not to start publishing the unadjusted data mentioned above.  (Mark’s note: other than “we can’t handle the truth”)
• But the second and more important point is that this is another reason to temper any burgeoning excitement over the seemingly favourable trends in the US economy over the last few months (in addition to the obvious ones: Europe, political stasis, etc..).
• Nomura does mention one silver lining from this research, which is that it means the recovery has perhaps been smoother and less “stop-go” than we previously thought. Not to be completely dismissive, but “smoothe” has nothing to do with “robust” — and the problem with the plodding recovery is precisely that it’s been plodding, not that it’s been unsteady.

Disclosure Notice

Any securities mentioned on this page are not held by the author in his personal portfolio. Securities mentioned may or may not be held by the author in the mutual fund he manages, the Paladin Long Short Fund (PALFX). For a list of the aforementioned fund’s holdings at the end of the prior quarter, visit the Paladin Funds website at http://www.paladinfunds.com/holdings/blog

Tags: Bernanke, Consensus Forecasts, Disintegration, Easy Money, Economic Activity, Economic Data, Economic Indicators, Economic Performance, Fall And Winter, Government Statistics, Jackson Hole, Japan Tsunami, Late Spring, Macroeconomic Indicators, Market Perspective, Nomura, Qe2, Seasonal Adjustments, Spring And Summer, Understatements
Posted in Markets | Comments Off

When “Positive Surprises” Are Surprisingly Meaningless (Hussman)

Sunday, December 18th, 2011

When “Positive Surprises” Are Surprisingly Meaningless

by John P. Hussman, Ph.D., Hussman Funds

In recent weeks, investors have abandoned all material concern about the likelihood of oncoming recession, largely because U.S. economic reports – though very tepid on an absolute basis – have come in persistently “better than expectations.” Objectively, the best showing has been in new claims for unemployment. The 4-week average has eased slightly below 400,000 in recent weeks, to a level that would no rmally be consistent with slightly positive payroll growth, though not enough to absorb normal labor force growth (the unemployment rate dropped last month partly because hundreds of thousands of people stopped looking for work). My concern here is in taking these labor numbers as predictive, in the face of an abrupt drop in federal withholding tax deposits.

As economist John Williams observes, “starting in October, a divergence developed: Whereas year-to-year change in BLS estimated payroll earnings continued at a more-or-less constant, positive level, tax receipts fell quite markedly. Where the Treasury numbers reflect full reporting, the BLS data are sampled, heavily modeled and usually heavily revised. The implication is that the BLS has overstated average earnings and payrolls meaningfully in recent months.”

The pattern in withholding tax deposits mirrors what we’ve seen in a whole ensemble of reliable leading economic measures we track – a sharp initial deterioration in early August, followed by a slight bounce into October, followed by resumed weakness that reinforces our concerns about the economy (see Have We Avoided A Recession? )

Labor figures are subject to strikingly large seasonal adjustments. The seasonal adjustment factors for non-farm payroll employment vary between 1.0157 and 0.9920, which doesn’t mean much until you put these numbers in context. Given total non-farm payroll employment of about 132 million workers, these adjustment factors mean that in any given month, the effect of seasonal adjustment on the reported payroll employment figure amounts to something between +2.1 million and -1.1 million jobs. Likewise, two-thirds of the new unemployment claims reports over the past year have been subsequently revised upward by several thousand. That’s not to diminish the importance of these figures in economic analysis, but instead to emphasize the importance of smoothing and other forms of noise-filtering that reduce the impact of short-term volatility. Suffice it to say that the improvement in new unemployment claims strikes me as a legitimately hopeful development, but there is too much short-term noise, and inconsistency with other economic evidence (reliable leading indicators, falling tax withholdings) to draw a convincing signal.

More broadly, the real question is how much importance should we put on the fact that economic data has delivered consistent “positive surprises” in recent weeks? Don’t all these surprises significantly short-circuit the risk of probable recession?

On that question, the evidence is very clear. No, they do not.

In order to properly understand economic “surprises,” it’s important to recognize that unlike actual economic data, where fluctuations have to do with, well, the actual economy, economic surprises are – by definition – measured relative to the subjective expectations of economists and Wall Street analysts. Unfortunately, analysts tend to be all-or-none. Instead of allowing for a normal ebb-and-flow of data, they form expectations that overshoot both on the pessimistic side and on the optimistic side. As a result, once the economy experiences an initial softening, expectations turn lower, often very aggressively. Over the following weeks, economic data can continue to be fairly soft, but because expectations have collapsed, the new data is interpreted as being “above expectations.” After a while, that experience of positive surprises causes analysts to over-correct by forming overly optimistic expectations, which is predictably followed by a period where the data, unless it is spectacular, almost cannot help but disappoint.

My observation is that this cycle of optimism and pessimism tends to run just over 20 weeks in each direction, though that is certainly not a magic number of any kind, and is best interpreted as a tendency. To give you an idea of how this regular pendulum of hope and despair affects the data in practice, the chart below presents the Citigroup Economic Surprises Index (a tally of how often recent economic reports have either beat or fallen short of consensus expectations). The blue line, to the thrill of anyone who enjoys Trigonometry, is a sine wave with a period of 44 weeks.

Notably, the Economic Surprises Index was near current levels just as the market was peaking before the 2007-2009 recession, was at a similarly high level just before the market collapsed violently in 2008, and reached a significant peak in March of this year, not far from where the S&P 500 topped out. Suffice it to say that the trend of positive economic “surprises” in recent weeks says more about the tendency of economic analysts to swing too far between optimism and pessimism than it does about the objective economic evidence, which remains tepid at best.

How broad is your sample?