Gold CoT Improving, But…

Gold’s CoT data predictably improved again this week, but here I think some discussion is needed just in case it starts to get hyped too much. Below is the CoT on an improving trend of Commercial short covering and large Speculator long reduction. Okay, that’s good. But here is the part where the hype needs […]

MiB: Joe Saluzzi of Themis Trading

This week, the “Masters in Business” radio podcast features Joe Saluzzi of Themis Trading. He and his partner Sal Arnuk are co-authors of the book Broken Markets: How High Frequency Trading and Predatory Practices on Wall Street Are Destroying Investor Confidence and Your Portfolio.

In our podcast, Joe discusses how regulatory changes and a shift in ownership from Non-profit to For-profit status for the exchanges led to a major shift in how markets were structured. These have led to all manners of problems, including the May 6, 2010 Flash Crash.

Since then we have seen mini crashes in individual stocks, and more recently, Treasuries and even Currencies. Listen to the podcast live here at 6pm, on BloombergApple iTunes or SoundCloud. All of our prior podcasts are available on iTunes.

Next week, we speak with Michelle Meyer of Bank America Merrill Lynch.

Schedule for Week of March 1, 2015

The key report this week is the February employment report on Friday.

Other key indicators include the January Personal Income and Outlays report on Monday, February ISM manufacturing index also on Monday, February vehicle sales on Tuesday, the ISM non-manufacturing index on Wednesday, and the January Trade Deficit on Friday.

----- Monday, March 2nd -----

8:30 AM ET: Personal Income and Outlays for January. The consensus is for a 0.4% increase in personal income, and for a 0.1% decrease in personal spending. And for the Core PCE price index to increase 0.1%.

ISM PMI10:00 AM: ISM Manufacturing Index for February. The consensus is for a decrease to 53.0 from 53.5 in January.

Here is a long term graph of the ISM manufacturing index.

The ISM manufacturing index indicated expansion in January at 53.5%. The employment index was at 54.1%, and the new orders index was at 52.9%

10:00 AM: Construction Spending for January. The consensus is for a 0.3% increase in construction spending.

----- Tuesday, March 3rd -----

Vehicle SalesAll day: Light vehicle sales for February. The consensus is for light vehicle sales to increase to 16.7 million SAAR in February from 16.6 million in January (Seasonally Adjusted Annual Rate).

This graph shows light vehicle sales since the BEA started keeping data in 1967. The dashed line is the January sales rate.

8:15 PM: Speech, Fed Chair Janet L. Yellen, Bank Regulation and Supervision, At the Citizens Budget Commission's Annual Awards Dinner, New York, New York

----- Wednesday, March 4th -----

7:00 AM: The Mortgage Bankers Association (MBA) will release the results for the mortgage purchase applications index.

8:15 AM: The ADP Employment Report for February. This report is for private payrolls only (no government). The consensus is for 220,000 payroll jobs added in February, up from 213,000 in January.

10:00 AM: ISM non-Manufacturing Index for February. The consensus is for a reading of 56.5, down from 56.7 in January. Note: Above 50 indicates expansion.

2:00 PM: Federal Reserve Beige Book, an informal review by the Federal Reserve Banks of current economic conditions in their Districts.

----- Thursday, March 5th -----

8:30 AM: The initial weekly unemployment claims report will be released. The consensus is for claims to decrease to 300 thousand from 313 thousand.

10:00 AM: Manufacturers' Shipments, Inventories and Orders (Factory Orders) for January. The consensus is for no change in January orders.

4:30 PM: Dodd-Frank Act Stress Test Results

----- Friday, March 6th -----

8:30 AM: Employment Report for February. The consensus is for an increase of 230,000 non-farm payroll jobs added in February, down from the 257,000 non-farm payroll jobs added in January.

The consensus is for the unemployment rate to decline to 5.6% in February from 5.7% in January.

Year-over-year change employmentThis graph shows the year-over-year change in total non-farm employment since 1968.

In January, the year-over-year change was 3.21 million jobs. This was the highest year-over-year gain since the '90s.

As always, a key will be the change in real wages - and as the unemployment rate falls, wage growth should start to pickup.

U.S. Trade Deficit8:30 AM: Trade Balance report for January from the Census Bureau.

This graph shows the U.S. trade deficit, with and without petroleum, through December. The blue line is the total deficit, and the black line is the petroleum deficit, and the red line is the trade deficit ex-petroleum products.

The consensus is for the U.S. trade deficit to be at $41.8 billion in January from $46.6 billion in December.

3:00 PM: Consumer Credit for January from the Federal Reserve.  The consensus is for credit to increase $15.0 billion.

‚A Slippery New Rule for Gauging Fiscal Policy‘

Greg Mankiw:

A Slippery New Rule for Gauging Fiscal Policy: the case for dynamic over static scoring is strong in theory. Yet three problems make the task difficult in practice.
First, any attempt to estimate the impact of a policy change on G.D.P. requires an economic model. Because reasonable people can disagree about what model, and what parameters of that model, are best, the results from dynamic scoring will always be controversial. ...
Second, accurate dynamic scoring requires more information than congressional proposals typically provide. ...
Third, dynamic scoring matters most over long time horizons. Some policy changes, such as those aimed at encouraging capital investments, take many decades to have their full impact on economic growth. Yet congressional budgeting usually looks only five or 10 years ahead. ...
So there are good reasons for the economists hired by Congress to pursue dynamic scoring. But there are also good reasons to be wary of the endeavor. ...

Another worry is the politicization of the CBO. See here and here. Also see here and here on the application of dynamic scoring to things such as Head Start and infrastructure spending.

John Whitehead comments:

Mankiw on dynamic scoring: ...Mankiw:

First, any attempt to estimate the impact of a policy change on G.D.P. requires an economic model. Because reasonable people can disagree about what model, and what parameters of that model, are best, the results from dynamic scoring will always be controversial. Just as many Republicans are skeptical about the models of climatologists when debating global warming, many Democrats are skeptical about the models of economists when debating tax policy.

My read of the article was going just fine until the climate model analogy. Two assumptions are made:

  1. All economists agree on "the models of economists" 
  2. Reasonable people can disagree about climatology models

In terms of #1, there is significant disagreement amongst economists about macroeconomic models (i.e., have you read Krugman lately?). In terms of #2, science is different than social science. Climatology involves forecasts so it is different than tests of the law of gravity, but still, ninety-x percent of climate scientists agree. That is a bit higher than the number of economists who agree on anything macro

My stance is that we should accept that the earth is likely warming and people contribute to it (even the U.S. Senate, including those Republicans that Mankiw mentions [did he miss that vote?], overwhelming thinks so). That moves us to the debate on whether we should do anything it or learn to adapt. I think that reasonable people can disagree on that second question. 

Brad DeLong's Grasping Reality… 2015-02-28 18:57:06

Morning Must-Read: Boris Nemtsov: A Final Interview: "I have no doubt that the struggle for the revival of Russians will be tough...

...People see what this crazy politics led to, they see widespread corruption, they have firsthand experience with the inadequacy of the state. But they still believe in the leader because for the past several years, the leader was doing one thing very well: He was brainwashing the Russians. He implanted them with a virus of inferiority complex towards the West, the belief that the only thing we can do to amaze the world is use force, violence and aggression. [Putin] programmed my countrymen to hate strangers. He persuaded them that we need to rebuild the former Soviet order, and that the position of Russia in the world depends entirely on how much the world is afraid of us. He managed to do all these things with Goebbels-style propaganda.... The responsibility for spilling both Russian and Ukrainian blood... lies not only with Putin, but also with such gentlemen as Konstantin Ernst [director general of Channel One] or Dmitry Kiselyov [head of the new, Russian-government-owned news agency Rossiya Segodnya]. They operate in accordance with the simple principles of Joseph Goebbels: Play on the emotions; the bigger the lie, the better; lies should be repeated many times. This propaganda is directed to the simple men; there is no room for any questions, nuances. Unfortunately, it works.... We need to work as quickly as possible to show the Russians that there is an alternative, that Putin’s policy leads to degradation and a suicide of the state. There is less and less time to wake up...

Momentum vs. Mean Reversion

Salil Mehta is a statistician and risk strategist. He served for two years as Director of Analytics in the U.S. Department of the Treasury for the Administration’s $700 billion TARP program. He is the former Director of the Policy, Research, and Analysis Department in the Pension Benefit Guaranty Corporation. Salil is on the Editorial Board for the American Statistical Association, is a Chartered Financial Analyst, a fellow member of the American Statistical Association and Royal Statistical Society, as well as being a current dual candidate member of the Society of Actuaries. He is the author of the mathematics book, Statistics Topics


Which is a better trading strategy, momentum or mean-reversion?

Try this mathematical thought experiment.  Look at these four anonymized stocks below, each trading from the mid-1980s.  Each stock chart starts indexed at $100.  What do you see in each of these stocks?  Are there some hints in each of them, which indicate that one of the two trading strategies is better?  Are stocks A and C better buys, versus stock D?






Let’s look at applying a trading strategy to these companies.  Say a momentum strategy, where we focus on if the stock moves up (relative to its trend) for two years straight, then one invests in that stock until the first relative down-year of that company.  What types of returns would you make from this (“don’t fight the uptrend”) strategy?

Next let’s look at a mean-reversion strategy, where we focus on if the stock moves down (relative to its trend) two years straight,then one invests in that stock until the first relative up-year of that company.  Which of these strategies is easier to use (momentum, or the “buy the dip”)?  And what sort of returns would you get from just these simple trading rules described here?

By answering such math questions, we learn a lot about the risks and rewards, of these fundamentally exclusive trading ideas. These are the same ideas that are mathematically embedded into modern ARIMA econometric models.  Pause for a moment and try to determine by looking at the four stock returns above, which sort of trading signal and profile would be generated:

I.    <$100
II.   $100-$200
III.  >$200

What we see below is that both technical rules produce the same results!  About $75 growth (or answer I above), off of the $100 initial price.  So in other words the implementation of one successful strategy (after all we profited $75) mathematically means we would not be able to profit on the other strategy.  Aren’t we therefore -by nature- still leaving money on the table?





Inspecting the above stock chart more closely, we might also notice that both trading signals only worked about 7 or 8 of the years, per company (or a quarter of the time).  This also implies nearly half of the time neither trading style exclusively applied, even though the stocks were in an overall uptrend.  We also notice that fairly equal returns from stocks A and C, have differing results within the same strategies!  Worse yet, we notice the risks involved in any strategy, since neither strategy just moved in an up direction over time.  Both can suffer losses from mistiming still.

Putting this altogether, we see all of the mixed prospects of using one of these trading strategies.  And we only reach results of$175 after 30 years, falling short of the results of typically $400 if we instead just kept a buy-and-hold strategy the entire time (see the top-most chart.)  This is likely less than any optimistic market participant would have guessed a-priori (e.g., the IIIIII choices above).

Also notice that the interpretation of both momentum and mean-reversion are the same, in a short-term view, in that one is waiting for a a slight trend in order to same the same decision (in this case to buy stocks).  This means that both strategies are in fact the same to some degree (and offer the same returns as noted above!), differing only in the hope of the investor about where stocks should head.  We say “hope” because again at the end of waiting for the same signal, the future direction of the stock is still random.

Still not convinced buy-and-hold would be the best approach to these stocks above?  Think there is a better rule-based algorithm you could apply to better tune your approach to each of these four stocks?  Unfortunately, think again.  The stock chart above isbogus, and in fact each series is just a random number generator.  See the de-trended chart below.



Source: Statistical Ideas


While starting at $100 each variable A, through D, annually fluctuates between -$20, to +$20.  Whatever happens in any given year has no influence on what happens the following year.  And the key probability insight for this article is: ogling at a random trend to provide a signal also has no value.  We added a +$10 trend each year, on top of the random value of -$20, to +$20.  Of course the reality of economic compounding should have been an early tip-off that the top-most chart isn’t perfectly right.

One is essentially being fooled.  Not by me, but by randomness, and that can happen in more ways then we might think. Articulating ideas from stock chart patterns, which can speak to someone if they hope them to.  But signals mislead with false-positives in this article, just as they often do in real-life (herehereherehere).  In this case we also see that we could unfortunately have been fooled into thinking that the underlying trend of the “companies” A and C, were different from D.  In fact they were, and are all the same.

Also recall just a month ago that all chart-devoted technicians adamantly accepted that markets were “consolidating” into a multi-month top, with nowhere to go but down.  Instead volatility fell and we are now yet again at all-time highs, including the once-bubbled Nasdaq.  And just as quick, the same folks have gone back to update and rely on the charts to pick up new “signs” of what this all might mean.  It means nothing.  More importantly, it is just random where it will ever matter to you.
A legendary portfolio manager, who self-terminated his portfolio management career after a nice run, said of those who try timing the market:
Far more money has been lost by investors preparing for corrections, or trying to anticipate corrections, than has been lost in corrections themselves.
Peter Lynch’s wisdom in this regard works for individuals who consider the mutually-exclusive success of momentum or mean-reversion strategies, and falsely believe that either is the best way to gain an upper-hand over the market.

Liveblogging World War II: February 28, 1945: Food in the Low Countries

George C. Marshall: 5-045 Memorandum for the President:


SUBJECT: Food Relief for Belgium and Liberated Holland.

General Eisenhower informed us in his message (SCAF 210) that a serious situation exists in the 21st Army Group (Montgomery’s command) area by reason of retarded deliveries of civilian supplies and urgently requested that 100,000 tons of food be made available immediately from UK stocks for the 21st Army Group.

In an exchange of messages between the Combined Chiefs of Staff and General Eisenhower it developed that a total of 109,000 tons of supplies were required. Provision has already been made for approximately half of this.

The problem of meeting the remaining 69,000 tons is now being considered in London. If the 69,000 tons are taken from the stockpile now being held in England against Dutch requirements, which is the probable course, it will be necessary to secure replacement from the UK stockpile in order to protect Eisenhower against anticipated Dutch needs.

It is recommended that you communicate with the Prime Minister and there is attached a draft of such a message.

President Roosevelt sent the message as drafted to Prime Minister Churchill on February 28:

I hope you will see your way clear to have the U.K. agree to replace the Dutch B-2 stockpile to the extent required to protect SCAEF against anticipated Dutch civilian supply needs

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