Category Archives: Chinese economy

Links – February 28

Data Science and Predictive Analytics

Data Scientists Predict Oscar® Winners Again; Social Media May Love Leo, But Data Says “No”

..the data shows that Matthew McConaughey will win best actor for his role in the movie Dallas Buyers Guide; Alfonso Cuaron will win best director for the movie Gravity; and 12 Months a Slave will win the coveted prize for best picture – which is the closest among all the races. The awards will not be a clean sweep for any particular picture, although the other award winners are expected to be Jared Leto for best supporting actor in Dallas Buyers Club; Cate Blanchet for best actress in Blue Jasmine; and Lupita Nyong’o for best supporting actress in 12 Years a Slave.

10 Most Influential Analytics Leaders in India

Pankaj Kulshreshtha – Business Leader, Analytics & Research at Genpact

Rohit Tandon – Vice President, Strategy WW Head of HP Global Analytics

Sameer Dhanrajani – Business Leader, Cognizant Analytics

Srikanth Velamakanni – Co founder and Chief Executive Officer at Fractal Analytics

Pankaj Rai – Director, Global Analytics at Dell

Amit Khanna – Partner at KPMG

Ashish Singru – Director eBay India Analytics Center

Arnab Chakraborty – Managing Director, Analytics at Accenture Consulting

Anil Kaul – CEO and Co-founder at Absolutdata

Dr. N.R.Srinivasa Raghavan, Senior Vice President & Head of Analytics at Reliance Industries Limited

Interview with Jörg Kienitz, co-author with Daniel Wetterau of Financial Modelling: Theory, Implementation and Practice with MATLAB Source

JB: Why MATLAB? Was there a reason for choosing it in this context?

JK: Our attitude was that it was a nice environment for developing models because you do not have to concentrate on the side issues. For instance, if you want to calibrate a model you can really concentrate on implementing the model without having to think about the algorithms doing the optimisation for example. MATLAB offers a lot of optimisation routines which are really reliable and which are fast, which are tested and used by thousands of people in the industry. We thought it was a good idea to use standardised mathematical software, a programming language where all the mathematical functions like optimisation, like Fourier transform, random number generator and so on, are very reliable and robust. That way we could concentrate on the algorithms which are necessary to implement models, and not have to worry about a programming a random number generator or such stuff. That was the main idea, to work on a strong ground and build our house on a really nice foundation. So that was the idea of choosing MATLAB.

Knowledge-based programming: Wolfram releases first demo of new language, 30 years in the making


Credit Card Debt Threatens Turkey’s Economy – kind of like the subprime mortgage scene in the US before 2008.

..Standard & Poor’s warned in a report last week that the boom in consumer credit had become a serious risk for Turkish lenders. Slowing economic growth, political turmoil and increasing reluctance by foreign investors to provide financing “are prompting a deterioration in the operating environment for Turkish banks,”

A shadow banking map from the New York Fed. Go here and zoom in for detail.

China Sees Expansion Outweighing Yuan, Shadow Bank Risk

China’s Finance Minister Lou Jiwei played down yuan declines and the risks from shadow banking as central bank Governor Zhou Xiaochuan signaled that the nation’s economy can sustain growth of between 7 percent and 8 percent.

Outer Space

715 New Planets Found (You Read That Number Right)

Speaks for itself. That’s a lot of new planets. One of the older discoveries – Tau Boötis b – has been shown to have water vapor in its atmosphere.

Hillary, ‘The Family,’ and Uganda’s Anti-Gay Christian Mafia


I heard about this at the SunDance film gathering in 2013. Apparently, there are links between US and Ugandan groups in promulgating this horrific law.

An Astronaut’s View of the North Korean Electricity Black Hole


Links – February 14

Global Economy

Yellen Says Recovery in Labor Market Far From Complete – Highlights of Fed Chair Yellen’s recent testimony before the House Financial Services Committee. Message – continuity, steady as she goes unless a there is a major change in outlook.

OECD admits overstating growth forecasts amid eurozone crisis and global crash The Paris-based organisation said it repeatedly overestimated growth prospects for countries around the world between 2007 and 2012. The OECD revised down forecasts at the onset of the financial crisis, but by an insufficient degree, it said….

The biggest forecasting errors were made when looking at the prospects for the next year, rather than the current year.

10 Books for Understanding China’s Economy

Information Technology (IT)

Predicting Crowd Behavior with Big Public Data


Internet startups


Alternative Technology

World’s Largest Rooftop Farm Documents Incredible Growth High Above Brooklyn

Links – February 1, 2014

IT and Big Data

Kayak and Big Data Kayak is adding prediction of prices of flights over the coming 7 days to its meta search engine for the travel industry.

China’s Lenovo steps into ring against Samsung with Motorola deal Lenovo Group, the Chinese technology company that earns about 80 percent of its revenue from personal computers, is betting it can also be a challenger to Samsung Electronics Co Ltd and Apple Inc in the smartphone market.

5 Things To Know About Cognitive Systems and IBM Watson Rob High video on Watson at Valuable to review. Watson is probably different than you think. Deep natural language processing.

Playing Computer Games and Winning with Artificial Intelligence (Deep Learning) Pesents the first deep learning model to successfully learn control policies directly from high-dimensional sensory input using reinforcement learning. The model is a convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards… [applies] method to seven Atari 2600 games from the Arcade Learning Environment, with no adjustment of the architecture or learning algorithm…outperforms all previous approaches on six of the games and surpasses a human expert on three of them.

Global Economy

China factory output points to Q1 lull Chinese manufacturing activity slipped to its lowest level in six months, with indications of slowing growth for the quarter to come in the world’s second-largest economy.

Japan inflation rises to a 5 year high, output rebounds Japan’s core consumer inflation rose at the fastest pace in more than five years in December and the job market improved, encouraging signs for the Bank of Japan as it seeks to vanquish deflation with aggressive money printing.

Coup Forecasts for 2014


World risks deflationary shock as BRICS puncture credit bubbles Ambrose Evans-Pritchard does some nice analysis in this piece.

Former IMF Chief Economist, Now India’s Central Bank Governor Rajan Takes Shot at Bernanke’s Destabilizing Policies

Some of his key points:

Emerging markets were hurt both by the easy money which flowed into their economies and made it easier to forget about the necessary reforms, the necessary fiscal actions that had to be taken, on top of the fact that emerging markets tried to support global growth by huge fiscal and monetary stimulus across the emerging markets. This easy money, which overlaid already strong fiscal stimulus from these countries. The reason emerging markets were unhappy with this easy money is “This is going to make it difficult for us to do the necessary adjustment.” And the industrial countries at this point said, “What do you want us to do, we have weak economies, we’ll do whatever we need to do. Let the money flow.”

Now when they are withdrawing that money, they are saying, “You complained when it went in. Why should you complain when it went out?” And we complain for the same reason when it goes out as when it goes in: it distorts our economies, and the money coming in made it more difficult for us to do the adjustment we need for the sustainable growth and to prepare for the money going out

International monetary cooperation has broken down. Industrial countries have to play a part in restoring that, and they can’t at this point wash their hands off and say we’ll do what we need to and you do the adjustment. ….Fortunately the IMF has stopped giving this as its mantra, but you hear from the industrial countries: We’ll do what we have to do, the markets will adjust and you can decide what you want to do…. We need better cooperation and unfortunately that’s not been forthcoming so far.

Science Perspective

Researchers Discover How Traders Act Like Herds And Cause Market Bubbles

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed in a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P 500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while that of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.

Blogs review: Getting rid of the Euler equation – the equation at the core of modern macro The Euler equation is one of the fundamentals, at a deep level, of dynamic stochastic general equilibrium (DSGE) models promoted as the latest and greatest in theoretical macroeconomics. After the general failures in mainstream macroeconomics with 2008-09, DGSE have come into question, and this review is interesting because it suggests, to my way of thinking, that the Euler equation linking past and future consumption patterns is essentially grafted onto empirical data artificially. It is profoundly in synch with neoclassical economic theory of consumer optimization, but cannot be said to be supported by the data in any robust sense. Interesting read with links to further exploration.

BOSTON COLLOQUIUM FOR PHILOSOPHY OF SCIENCE: Revisiting the Foundations of Statistics – check this out – we need the presentations online.

Global Economy Outlook – Some Problems

There seems to be a meme evolving around the idea that – while the official business outlook for 2014 is positive – problems with Chinese debt, or more generally, emerging markets could be the spoiler.

The encouraging forecasts posted by bank and financial economists (see Hatzius, for example) present 2014 as a balance of forces, with things tipping in the direction of faster growth in the US and Europe. Austerity constraints, sequestration in the US and draconian EU policies, will loosen, allowing the natural robustness of the underlying economy to assert itself – after years of sub-par performance. In the meanwhile, growth in the emerging economies is admittedly slowing, but is still is expected at much higher rates than in heartland areas of the industrial West or Japan.

So, fingers crossed, the World Bank and other official economic forecasting agencies show an uptick in economic growth in the US and, even, Europe for 2014.

But then we have articles that highlight emerging market risks:

China’s debtfuelled boom is in danger of turning to bust This Financial Times article develops the idea that only five developing countries have had a credit boom nearly as big as China’s, in each case leading to a credit crisis and slowdown. So currently Chinese “total debt” – a concept not well-defined in this short piece – is currently running about 230 per cent of gross domestic product. The article offers comparison with “33 previous credit binges” and to smaller economies, such as Taiwan, Thailand, Zimbabwe, and so forth. Strident, but not compelling.

With China Awash in Money, Leaders Start to Weigh Raising the Floodgates  From the New York Times, a more solid discussion – The amount of money sloshing around China’s economy, according to a broad measure that is closely watched here, has now tripled since the end of 2006. China’s tidal wave of money has powered the economy to new heights, but it has also helped drive asset prices through the roof. Housing prices have soared, feeding fears of a bubble while leaving many ordinary Chinese feeling poor and left out.

The People’s Bank of China has been creating money to a considerable extent by issuing more renminbi to bankroll its purchase of hundreds of billions of dollars a year in currency markets to minimize the appreciation of the renminbi against the dollar and keep Chinese exports inexpensive in foreign markets; the central bank disclosed on Wednesday that the country’s foreign reserves, mostly dollars, soared $508.4 billion last year, a record increase.


Source: New York Times

Moreover, the rapidly expanding money supply reflects a flood of loans from the banking system and the so-called shadow banking system that have kept afloat many inefficient state-owned enterprises and bankrolled the construction of huge overcapacity in the manufacturing sector.

There also are two at least two recent, relevant posts by Yves Smith – who is always on the watch for sources of instability in the banking system

How Serious is China’s Shadow Banking/Wealth Management Products Problem?

China Credit Worries Rise as Large Shadow Banking Default Looms

In addition to concerns about China, of course, there are major currency problems developing for Russia, India, Chile, Brazil, Turkey, South Africa, and Argentina.


From the Economist The plunging currency club

So there are causes for concern, especially with the US Fed, under Janet Yellen, planning on winding down QE or quantitative easing.

When Easy Money Ends is a good read in this regard, highlighting the current scale of QE (quantitative easing) programs globally, and savings from lower interest rates – coupled with impacts of higher interest rates.

Since the start of the financial crisis, the Fed, the European Central Bank, the Bank of England, and the Bank of Japan have used QE to inject more than $4 trillion of additional liquidity into their economies…If interest rates were to return to 2007 levels, interest payments on government debt could rise by 20%, other things being equal…US and European nonfinancial corporations saved $710 billion from lower debt-service payments, with ultralow interest rates thus boosting profits by about 5% in the US and the UK, and by 3% in the euro-zone. This source of profit growth will disappear as interest rates rise, and some firms will need to reconsider business models – for example, private equity – that rely on cheap capital…We could also witness the return of asset-price bubbles in some sectors, especially real estate, if QE continues. The International Monetary Fund noted in 2013 that there were already “signs of overheating in real-estate markets” in Europe, Canada, and some emerging-market economies. 

Asset Bubbles

It seems only yesterday when “rational expectations” ruled serious discussions of financial economics. Value was determined by the CAPM – capital asset pricing model. Markets reflected the operation of rational agents who bought or sold assets, based largely on fundamentals. Although imprudent, stupid investors were acknowledged to exist, it was impossible for a market in general to be seized by medium- to longer term speculative movements or “bubbles.”

This view of financial and economic dynamics is at the same time complacent and intellectually aggressive. Thus, proponents of the efficient market hypothesis contest the accuracy of earlier discussions of the Dutch tulip mania.

Now, however, there seems no doubt that bubbles in asset markets are both real and intractable to regulation and management, despite their catastrophic impacts.

But asset bubbles are so huge now that Larry Summers suggests, before the International Monetary Fund (IMF) recently, that the US is in a secular stagnation, and that the true, “market-clearing” interest rate is negative. Thus, given the unreality of implementing a negative interest rate, we face a long future of the zero bound – essentially zero interest rates.

Furthermore, as Paul Krugman highlights in a follow-on blog post – Summers says the economy needs bubbles to generate growth.

We now know that the economic expansion of 2003-2007 was driven by a bubble. You can say the same about the latter part of the 90s expansion; and you can in fact say the same about the later years of the Reagan expansion, which was driven at that point by runaway thrift institutions and a large bubble in commercial real estate.

So you might be tempted to say that monetary policy has consistently been too loose. After all, haven’t low interest rates been encouraging repeated bubbles?

But as Larry emphasizes, there’s a big problem with the claim that monetary policy has been too loose: where’s the inflation? Where has the overheated economy been visible?

So how can you reconcile repeated bubbles with an economy showing no sign of inflationary pressures? Summers’s answer is that we may be an economy that needs bubbles just to achieve something near full employment – that in the absence of bubbles the economy has a negative natural rate of interest. And this hasn’t just been true since the 2008 financial crisis; it has arguably been true, although perhaps with increasing severity, since the 1980s.

Re-enter the redoubtable “liquidity trap” stage left.

Summers and Krugman move at a fairly abstract and theoretical level, regarding asset bubbles and the current manifestation.

But more and more, the global financial press points the finger at the US Federal Reserve and its Quantitative Easing (QE) as the cause of emerging bubbles around the world.

One of the latest to chime in is the Chinese financial magazine Caixin with Heading Toward a Cliff.

The Fed’s QE policy has caused a gigantic liquidity bubble in the global economy, especially in emerging economies and asset markets. The improvement in the global economy since 2008 is a bubble phenomenon, centering around the demand from bubble goods or wealth effect. Hence, real Fed tightening would prick the bubble and trigger another recession. This is why some talk of the Fed tightening could trigger the global economy to trend down…

The odds are that the world is experiencing a bigger bubble than the one that unleashed the 2008 Global Financial Crisis. The United States’ household net wealth is much higher than at the peak in the last bubble. China’s property rental yields are similar to what Japan experienced at the peak of its property bubble. The biggest part of today’s bubble is in government bonds valued at about 100 percent of global GDP. Such a vast amount of assets is priced at a negative real yield. Its low yield also benefits other borrowers. My guesstimate is that this bubble subsidizes debtors to the tune of 10 percent of GDP or US$ 7 trillion dollars per annum. The transfer of income from savers to debtors has never happened on such a vast scale, not even close. This is the reason that so many bubbles are forming around the world, because speculation is viewed as an escape route for savers.The property market in emerging economies is the second-largest bubble. It is probably 100 percent overvalued. My guesstimate is that it is US$ 50 trillion overvalued.Stocks, especially in the United States, are significantly overvalued too. The overvaluation could be one-third or about US$ 20 trillion.There are other bubbles too. Credit risk, for example, is underpriced. The art market is bubbly again. These bubbles are not significant compared to the big three above.

The Caixin author – Andy Xie – goes on to predict inflation as the eventual outcome – a prediction I find far-fetched given the coming reaction to Fed tapering.

And the reach of the Chinese real estate bubble is highlighted by a CBS 60 Minutes video filmed some months ago.

Anatomy of a Bubble

The Great Recession of 2008-2009 alerted us – what goes up, can come down. But are there common patterns in asset bubbles? Can the identification of these patterns help predict the peak and subsequent point of rapid decline?

Macrotrends is an interesting resource in this regard. The following is a screenshot of a Macrotrends chart which, in the original, has interactive features.


Scaling the NASDAQ, gold, and oil prices in terms of percentage changes from points several years preceding price peaks suggests bubbles share the same cadence, in some sense.

These curves highlight that asset bubbles can occur over significant periods – several years to a decade. This is the part of the seduction. At first, when commentators cry “bubble,” prudent investors stand aside to let prices peak and crash. Yet prices may continue to rise for years, leaving investors increasingly feeling they are “being left behind.”

Here are data from three asset bubbles – the Hong Kong Hang Seng Index, oil prices to refiners (combined), and the NASDAQ 100 Index. Click to enlarge.


I arrange these time series so their peak prices – the peak of the bubble – coincide, despite the fact that these peaks occurred at different historical times (October 2007, August 2008, March 2000, respectively).

I include approximately 5 years of prior values of each time series, and scale the vertical dimensions so the peaks equal 100 percent.

This produces a chart which suggests three distinct phases to an asset bubble.

Phase 1 is a ramp-up. In this initial phase, prices surge for 2-3 years, then experience a relatively minor drop.

Phase 2 is the beginning of a sustained period of faster-than-exponential growth, culminating in the market peak, followed immediately by the market collapse. Within a few months of the peak, the rates of growth of prices in all three series are quite similar, indeed almost identical. These rates of price growth are associated with “an accelerating acceleration” of growth, in fact – as a study of first and second differences of the rates of growth show.

The critical time point, at which peak price occurs, looks like the point at which traders can see the vertical asymptote just a month or two in front of them, given the underlying dynamics.

Phase 3 is the market collapse. Prices drop maybe 80 percent of the value they rose from the initial point, and rapidly – in the course of 1-2 years. This is sometimes modeled as a “negative bubble.” It is commonly considered that the correction overshoots, and then adjusts back.

There also seems to be a Phase 4, when prices can recover some or perhaps almost all of their lost glory, but where volatility can be substantial.


It seems reasonable that the critical point, or peak price, should be more or less predictable, a few months into Phase 2.

The extent of the drop from the peak in Phase 3 seems more or less predictable, also.

The question really is whether the dynamics of Phase 1 are truly informative. Is there something going on in Phase 1 that is different than in immediately preceding periods? Phase 1 seems to “set the stage.”

But there is no question the lure of quick riches involved in the advanced stages of an asset bubble can dazzle the most intelligent among us – and as a case in point, I give you Sir Isaac Newton, co-inventor with Liebnitz of the calculus, discoverer of the law of gravitation, and exponent of a vast new science, in his time, of mathematical physics.


A post on Business Insider highlights his unhappy case with the South Seas stock bubble. Newton was in this scam early, and then got out. But the Bubble kept levitating, so he entered the market again near the top – in Didier Sornette’s terminology, near the critical point of the process, only to lose what in his time was vast fortune of worth $2.4 million dollars in today’s money.