Twitter / MasterMetals: RT @PlattsOil: #Iranian #s
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Friday, June 29, 2012
#Iranian #sanctions: major shifts in global #oil supply landscape look inevitable #MasterMetals @PlattsOil
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Tracking social media: The mood of the market | The Economist
the classical economists instructed, rely on information. But what if there is too much of it, not too little?
Tracking social media
The mood of the market
Jun 28th 2012, 12:31 by K.N.C. | LONDON
MARKETS, the classical economists instructed, rely on information. But what if there is too much of it, not too little?
The web and social-networking platforms have resulted in an explosion of words. Many firms apply artificial intelligence technology to get the gist, and use that as a trading signal. One study in 2010 by researchers at Indiana University analyzed millions of tweets to predict the movement of the stock market three days later with an 87% accuracy. Such success has unleashed a new fashion for Wall Street quants to plug so-called "sentiment analysis" of social media into their massive models.
Until now these indicators have been fairly blunt, usually tracking a handful of companies on a two-dimensional scale of positive or negative sentiment. But on June 25th Thomson Reuters unleashed no fewer than 18,864 new indices, updated each minute. The system, developed by MarketPsych, a start-up in California, can analyze as many as 55,000 news sites and 4.5m social media sites, blogs and tweets (though on an everyday basis, the number it crunches will be much smaller). The indices quantify emotional states like optimism, gloom, joy, fear, anger—even things like innovation, litigation and conflict. And it does it across a slew of assets: 40 equity sectors, 29 currencies, 22 types of energy and materials, 12 agricultural commodities and 119 countries.
Parsing tweets to measure "innovation" or "litigation" might seem of little value, even if it can be measured accurately—a big if. The techniques of natural language processing are embryonic and highly imperfect. Tweets for example, are often ironic or sarcastic, which humans immediately understand but computers do not. However, presuming that the indices actually denote what they purport to measure, they are not so much meant for a person to use directly, but for hefty computer algorithms to factor in on a continuous basis. In that sense, relative changes over time may have merit.
This may help prevent what is known as "model crowding" or "quantagion" (a neologism of "quant" and "contagion"), explains Rich Brown of Thomson Reuters. The idea is that many funds' models rely on similar underlying data, so that when one melts-down, they all do, as happened in August 2007. And because everyone trades on mostly the same signals, the effects get exaggerated. Hence, quant investors are keen for new data sources to add to their models, to give them a unique trading strategy.
The new indices associated with an asset or country cost around $1,000 a month and go north from there. Yet are they useful? The verdict is out. Take the index that is informally called the "Bubbleometer" (pictured below), which is a measure of "speculative" conversations among investors over the web and social media platforms.
When the Bubbleometer is compared against the Standard & Poor's 500 Index between September 2009 and May 2012, it mostly follows the big swoops. But examined closely, one sees the Bubbleometer act erratically. For example, in late 2009 and early 2010 it showed speculative sentiment cooling just as prices were rising. In Spring 2010 it was first a lagging indicator that share prices would rise, then a leading indicator they would retreat. At midyear, sentiment and prices were inversely correlated. In autumn 2010 the Bubbleometer held steady within a narrow band, while the index jumped almost 15%.
Of course, this is not to say that a bit of clever maths won't uncover interesting patterns that are not visible to the human eye. It is useful measure of "bubbleocity," stresses Mr Brown of Thomson Reuters.
Successes from harnessing online sentiment analysis remain to be seen. One fund that famously began trading on Twitter signals in 2011, Derwent Capital in London, recently closed its fund (it plans to offer the metrics for free to retail investors who use its trading platform later this year). Similarly, MarketPsych, the firm that compiles Thomson Reuters' sentiment indices, formerly used the data for an in-house fund that has since been shuttered as well.
True, the value of data or an index can often be better exploited by third parties than the firm that cobbled it together—no one would think that Dow Jones would be filthy rich if it kept the industrial average to itself. However, it raises eyebrows that the firms capable of measuring market sentiment are willing to provide that data to others rather then keep it to itself. If it were so valuable, why would they make it available at all? The telling is in the using: let's see how investment performance improves or deteriorates with yet another signal on which to base trading decisions. After all, the classic economists aspired for perfect information.
The web and social-networking platforms have resulted in an explosion of words. Many firms apply artificial intelligence technology to get the gist, and use that as a trading signal. One study in 2010 by researchers at Indiana University analyzed millions of tweets to predict the movement of the stock market three days later with an 87% accuracy. Such success has unleashed a new fashion for Wall Street quants to plug so-called "sentiment analysis" of social media into their massive models.
Until now these indicators have been fairly blunt, usually tracking a handful of companies on a two-dimensional scale of positive or negative sentiment. But on June 25th Thomson Reuters unleashed no fewer than 18,864 new indices, updated each minute. The system, developed by MarketPsych, a start-up in California, can analyze as many as 55,000 news sites and 4.5m social media sites, blogs and tweets (though on an everyday basis, the number it crunches will be much smaller). The indices quantify emotional states like optimism, gloom, joy, fear, anger—even things like innovation, litigation and conflict. And it does it across a slew of assets: 40 equity sectors, 29 currencies, 22 types of energy and materials, 12 agricultural commodities and 119 countries.
Parsing tweets to measure "innovation" or "litigation" might seem of little value, even if it can be measured accurately—a big if. The techniques of natural language processing are embryonic and highly imperfect. Tweets for example, are often ironic or sarcastic, which humans immediately understand but computers do not. However, presuming that the indices actually denote what they purport to measure, they are not so much meant for a person to use directly, but for hefty computer algorithms to factor in on a continuous basis. In that sense, relative changes over time may have merit.
This may help prevent what is known as "model crowding" or "quantagion" (a neologism of "quant" and "contagion"), explains Rich Brown of Thomson Reuters. The idea is that many funds' models rely on similar underlying data, so that when one melts-down, they all do, as happened in August 2007. And because everyone trades on mostly the same signals, the effects get exaggerated. Hence, quant investors are keen for new data sources to add to their models, to give them a unique trading strategy.
The new indices associated with an asset or country cost around $1,000 a month and go north from there. Yet are they useful? The verdict is out. Take the index that is informally called the "Bubbleometer" (pictured below), which is a measure of "speculative" conversations among investors over the web and social media platforms.
Of course, this is not to say that a bit of clever maths won't uncover interesting patterns that are not visible to the human eye. It is useful measure of "bubbleocity," stresses Mr Brown of Thomson Reuters.
Successes from harnessing online sentiment analysis remain to be seen. One fund that famously began trading on Twitter signals in 2011, Derwent Capital in London, recently closed its fund (it plans to offer the metrics for free to retail investors who use its trading platform later this year). Similarly, MarketPsych, the firm that compiles Thomson Reuters' sentiment indices, formerly used the data for an in-house fund that has since been shuttered as well.
True, the value of data or an index can often be better exploited by third parties than the firm that cobbled it together—no one would think that Dow Jones would be filthy rich if it kept the industrial average to itself. However, it raises eyebrows that the firms capable of measuring market sentiment are willing to provide that data to others rather then keep it to itself. If it were so valuable, why would they make it available at all? The telling is in the using: let's see how investment performance improves or deteriorates with yet another signal on which to base trading decisions. After all, the classic economists aspired for perfect information.
See the article online here: Tracking social media: The mood of the market | The Economist
Thursday, June 21, 2012
The Most Important Chart In #Europe Is Getting Dramatically Better - Business Insider #Italy #Spain
The Most Important Chart In Europe Is Getting Dramatically Better
Simone Foxman
Yields on Italian and Spanish bonds are dropping fast this morning, after a bond auction in Spain saw decent demand from investors.
Borrowing costs remained high at auction; for example, yields on two-year notes rose from 2.069 percent last month to 4.706 percent. However, the fact that primary market borrowing costs were below where yields in the secondary market--they started at over 5 percent today--suggests that the bearish reaction to the Spanish bank bailout deal might be overblown.
We have argued in the past that yields on two-year bonds in Spain and Italy may prove the most important data points in Europe, since two-year borrowing costs take into account the effects of the European Central Bank's two liquidity-providing long-term refinancing operations. With Spain under fire from investors after its bank bailout, indicators of Spanish government following stress have become urgent. See our full reasoning here >
Yields on Spanish two-year notes have fallen a dramatic 28 basis points today. This seems to be continuing a trend that began early this week, Take a look at 2-year notes today:
Spanish 2 year yields
Read more here: The Most Important Chart In Europe Is Getting Dramatically Better - Business Insider
Simone Foxman
Yields on Italian and Spanish bonds are dropping fast this morning, after a bond auction in Spain saw decent demand from investors.
Borrowing costs remained high at auction; for example, yields on two-year notes rose from 2.069 percent last month to 4.706 percent. However, the fact that primary market borrowing costs were below where yields in the secondary market--they started at over 5 percent today--suggests that the bearish reaction to the Spanish bank bailout deal might be overblown.
We have argued in the past that yields on two-year bonds in Spain and Italy may prove the most important data points in Europe, since two-year borrowing costs take into account the effects of the European Central Bank's two liquidity-providing long-term refinancing operations. With Spain under fire from investors after its bank bailout, indicators of Spanish government following stress have become urgent. See our full reasoning here >
Yields on Spanish two-year notes have fallen a dramatic 28 basis points today. This seems to be continuing a trend that began early this week, Take a look at 2-year notes today:
Spanish 2 year yields
Read more here: The Most Important Chart In Europe Is Getting Dramatically Better - Business Insider
Monday, June 18, 2012
David Rosenberg Charts - Business Insider
David Rosenberg outlines why the economy still has a long way to go to improve.
David Rosenberg Charts - Business Insider
________________________ The MasterBlog
David Rosenberg Charts - Business Insider
________________________ The MasterBlog
Saturday, June 16, 2012
Peak Monthly #Inflation In 1945 Hungary: 12,950,000,000,000,000% And Other Hyperinflationary Facts | ZeroHedge
Peak Monthly Inflation In 1945 Hungary: 12,950,000,000,000,000% And Other Hyperinflationary Facts
By Tyler Durden
Created 06/15/2012 - 12:45
[1]
Submitted by Tyler Durden [1] on 06/15/2012 12:45 -0400
For some reason, whenever people want to make a historical example of a hyperinflationary period, they always bring up the Weimar Republic, aka Germany in 1920-1923. Yet with a highest monthly inflation of just under 30,000%, Weimar was a true walk in the park compared to the 309,000,000% monthly inflation in 1992-1994 Serbia, but especially to the 12,950,000,000,000,000% inflation that Hungarians had to deal with in the aftermath of WWII. For these and more comparative examples of hyperinflation, particularly relevant now that the entire world is rumored (for now) to be getting ready to print, see below.
See the article on zerohedge.com: Peak Monthly Inflation In 1945 Hungary: 12,950,000,000,000,000% And Other Hyprinflationary Facts | ZeroHedge
By Tyler Durden
Created 06/15/2012 - 12:45
[1]
Submitted by Tyler Durden [1] on 06/15/2012 12:45 -0400
For some reason, whenever people want to make a historical example of a hyperinflationary period, they always bring up the Weimar Republic, aka Germany in 1920-1923. Yet with a highest monthly inflation of just under 30,000%, Weimar was a true walk in the park compared to the 309,000,000% monthly inflation in 1992-1994 Serbia, but especially to the 12,950,000,000,000,000% inflation that Hungarians had to deal with in the aftermath of WWII. For these and more comparative examples of hyperinflation, particularly relevant now that the entire world is rumored (for now) to be getting ready to print, see below.
See the article on zerohedge.com: Peak Monthly Inflation In 1945 Hungary: 12,950,000,000,000,000% And Other Hyprinflationary Facts | ZeroHedge
Friday, June 15, 2012
Meanwhile In #Switzerland... | ZeroHedge
The entire bond curve through the 5 year point is now negative (for the first time ever). At this rate, courtesy of the FX peg and the SNB's free put option, whereby EURs are converted into CHFs at a furious pace even as the facade of a collapsing Eurozone is itself crumbling, and the proceeds are use to buy Swiss bonds ever further into negative territory, we may soon have an entire bond curve trading at negative territory. Which, paradoxically, would lead to that Keynesian wet dream: the more debt Switzerland issues, the more money it would make courtesy of negative interest expense, literally, and the faster it would pay down its debt. Curiously, this may not be a bad offset to losses that the SNB is currently experiencing due to its currency peg. And some thought bizarro world was a sitcom construct.
Chart: BBG
Meanwhile In Switzerland... | ZeroHedge
_______________________________________
Chart: BBG
Meanwhile In Switzerland... | ZeroHedge
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The Diminishing Returns Of Central Planning, And Why More Printing Would Have No Impact | ZeroHedge
Because it now appears that only an absolute currency devaluation would work, not a relative one. What is another way of saying this: a global devaluation of all currencies relative to some benchmark... say gold.... and what happens when the market realizes that suddenly, Syriza not winning the Greek elections is the downside case as it would mean no coordinated central bank intervention. Great job central planners - you have just shot yourself in the foot once again.
The Diminishing Returns Of Central Planning, And Why More Printing Would Have No Impact
Now that all the rage is now just the NEW QE, but global coordinated NEW QE, it would make sense to observe the impact the last three episodes of quantitative easing, QE1, QE2 and Twist, have had on the market. And more importantly, whether such impact is rising, dropping, or staying the same. Well, as the following chart from BofA shows, we may be lucky if there is any favorable impact on risk assets following the announcement of more easing, and incidentally perhaps global easing is what is necessary (if not sufficient) now that the devaluation of the US dollar has become an exercise in futility. Because it now appears that only an absolute currency devaluation would work, not a relative one. What is another way of saying this: a global devaluation of all currencies relative to some benchmark... say gold. Most importantly, the only question now is how long before the entire "global intervention rumor" is faded, and what happens when the market realizes that suddenly, Syriza not winning the Greek elections is the downside case as it would mean no coordinated central bank intervention. Great job central planners - you have just shot yourself in the foot once again.
The full thoughts of BofA:
Or, as the chart actually implies, more easing would have no impact whatsoever...There are low rates, and then there are low rates
Of course, rates are already quite low. But it matters why they are low. Right now, much is due to a flight to safety; fear is not a good environment for growth or market rallies. Replacing that fear with a policy commitment to further support the recovery should be a net positive for the outlook. Indeed, this confidence channel is an important one: the Fed can put a floor under sentiment and prevent a selffulfilling negative spiral like what immediately followed the collapse of Lehman. Moreover, QE3 should price out deflation and “Japanification” fears.
One counter to these potential benefits is that low rates hurt savers. While true in isolation, the plausible alternative is not higher rates. It is an even deeper economic quagmire, even more negative sentiment, and likely similarly low rates. No one — savers or otherwise — would benefit from that situation.
The law of diminishing returns
The other counter is that QE3 will have less benefit per dollar than earlier programs. That might well be correct — a recent San Francisco Fed study lends support to that view (Chart 7) — and Bernanke and Yellen both acknowledged that risk recently. But it is worth exploring the reasons why.
QE1 may have had a large effect because of nonlinearities that increase in size. If so, that argues for a larger QE3 program (and against a small extension of Twist). QE1 also improved market functioning during a crisis and signaled easy policy for a while. Forward guidance has since usurped the latter effect. Market functioning was much less of a problem during QE2 or Twist; if fears of European contagion lead US market liquidity to falter, however, QE3 could have larger effects.
Read the article online here: The Diminishing Returns Of Central Planning, And Why More Printing Would Have No Impact | ZeroHedge
Friday, June 01, 2012
Relative performance of GLD, SLV and CEF since 2009
Relative performance of GLD, SLV and CEF since 2009
GLD +102.09%
SLV +156.93%
CEF +91.79%
http://www.google.com/finance?chdnp=1&chdd=1&chds=1&chdv=1&chvs=maximized&chdeh=0&chfdeh=0&chdet=1337976000000&chddm=365275&chls=IntervalBasedLine&cmpto=NYSEARCA:GLD;NYSEARCA:SLV&cmptdms=0;0&q=NYSEAMEX:CEF&ntsp=0
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