June 2019

JUNE 2019

Agriculture and Climate Change

Agriculture image

Robin Tunnicliffe has farmed for almost 20 years, growing a wide range of organic vegetables for local restaurants and farmer’s markets. She remembers that “when I first started farming, my mentor gave me a list of planting dates.” This essential farmer-to-farmer teaching gave her confidence thanks to its hard-won wisdom, and she recalls thinking “Good! Now I know what I’m doing!” But she soon found that the lessons of tradition and experience were expiring, thanks in part to climate change.

Tunnicliffe began to notice that the changing climate was throwing reliable, longstanding patterns and expectations out the window. She notes that unpredictable seasonal weather now means “the map has been wiped clean a little bit,” and says: “I mentor a lot of new growers. I wish I could give them that list of planting dates that I got. But I can’t do that.”

Farmers know all too well that agriculture is highly dependent on weather. Modern methods, techniques, and technologies have made today’s crop and livestock farms increasingly productive, but agricultural success still depends on getting just the right amount of rain and just the right amount of heat at just the right time of year.

  • The planting, maturing, and harvesting of crops all depend on consistent seasonal patterns.
  • Livestock depend on feed, water, and a tolerable range of heat and humidity for healthy, productive growth.
  • Climate helps determine which pests and diseases will spread, and so how much time, effort, and money farmers must spend on herbicides, insecticides, and other defences.
  • Beyond the harvest, patterns of temperature and weather affect the entire supply chain of storage and transportation that brings food from the field to the dinner plate.

From the largest farm to the smallest market garden, from planting to eating, and at every stage in the cycle of production –from choosing seed to transporting livestock – agriculture and agri-business thoroughly depend on climate. And the climate is changing.

Farming in a hotter climate

Seasonal temperatures are very important to farming. The length of the growing season, typical average temperatures, and the timing and severity of hot and cold spells all work together to determine what crops can be grown. Climate models show that Canada’s cold season will shrink, leaving a longer growing season. But with that possibly good news comes a huge increase in high temperature events and changes in precipitation patterns – especially the increasing likelihood of flooding and drought in the same year – which will require farmers to make significant changes.

The Climate Atlas map of very hot days shows large increases in heat coming to many of Canada’s agricultural regions, including the Okanagan Valley, the Prairies, southern Ontario, and the Maritimes.

Roy McLaren has a long lifetime of farming experience – he’s farmed in southern Manitoba for over 70 years – and looks at these projections with concern. “That is pretty bad,” he says. “With that kind of heat,” McLaren concedes, “we’d have to change our farming methods. We’d have to adopt new crops.”

Temperature changes don’t just affect crops. Hot temperatures also reduce weight gain and milk production in cattle. Heat can even be deadly: in 2002, for example, heat waves in Quebec killed half a million poultry, despite the use of modern shelter and ventilation systems [1], and during 2010-2012 hundreds of dairy cattle died in Ontario because of extreme heat [2].

Farming and changes in precipitation

Water supply and water management are fundamental to farming. McLaren is plain-spoken on the topic: “Without water, you don’t have anything. I don’t care where you farm.”

Climate models show that Canada’s agricultural regions will likely see drier summers from coast to coast, but increased winter and spring precipitation. This means that farmers may have to deal with both too much water during the seeding season and too little water during the growing season, all in the same year. Projections also show that although much of southern Canada will be drier overall in the summer, it could also face an increase in short-lived but very intense rainfall events.

august-april delta precip_1.jpg

The projected change in monthly precipitation for April and August (for the “high carbon” climate scenario) shows that much of southern Canada is expected to become much wetter during the spring, but drier during the summer. These maps show the percent difference in total monthly precipitation between the 2051-2080 and 1976-2005 time periods.

Canada’s prairie provinces have recently experienced the consequences of such seasonal shifts in precipitation: in 2016 a hot, dry spring caused widespread drought. This extended dry weather was followed by torrential rains in the late summer that caused flooding in many areas, from northern Alberta to eastern Manitoba. And in 2017, southern Saskatchewan experienced the driest July in over 130 years of record-keeping. For farmers in the region the heat and dryness was especially damaging because it followed a rainy spring that had been so wet that they’d been unable to properly seed their fields [3].

In addition to the increased threat of drought and flooding, wet springs and autumns may make it challenging for farmers to take advantage of the longer growing season promised by rising temperatures. Early or late rain can simply make the land too wet to support farm machinery, and can hinder important seeding, maturing, or drying phases of many crops.


Farmers are used to planning for uncertainty, but climate change is bringing new extremes, seasonal shifts, and increased variability that are likely to push the boundaries of our climate beyond anything they are used to managing.

Some aspects of climate change look promising for farming: longer frost-free seasons, increases in growing degree days, and even increased atmospheric CO2 can, in theory, lead to better crop yields and productivity. However, as Natural Resources Canada warns: “An increase in climate variability and the frequency of extreme events would adversely affect the agricultural industry. A single extreme event (later frost, extended drought, excess rainfall during harvest period) can eliminate any benefits from improved ‘average’ conditions” [1].

Some of the existing tools the farming sector uses to handle climate risks (such as crop insurance or sprinkler irrigation) mostly rely on poor conditions being unusual and intermittent. But short-term and one-off crisis management strategies aren’t sustainable responses to the enduring effects of climate change.

The Food and Agriculture Organization of the United Nations cites research that identifies six major classes of agricultural climate adaptation [4]:

  • seasonal changes and sowing dates;
  • different varieties or species;
  • water supply and irrigation systems;
  • inputs (fertilizer, tillage methods, grain drying, other field operations);
  • new crop varieties; and
  • fire risk management.

Tunnicliffe reflects on her farm’s adaptation to climate change and notes that “our strategy now is just being more resilient.” She is experimenting with new varieties of produce, over-planting in expectation of higher losses, and breeding plants that are adapted to local conditions. “Your best strategy is diversity” she says, so that “a crop failure isn’t a disaster.” Asked to define resilience, she laughs and says “many layers of backup!”


Agriculture has an important part to play in reducing the severity of climate change.

Modern agriculture – like most modern industry – relies on high-carbon energy. Farming generates about 8% of Canada’s greenhouse gas emissions [5]. These greenhouse gases come from a variety of sources. Diesel- and gas-powered machinery is used to till fields, plant seeds, apply fertilizers, harvest crops and transport the food to market. Manufacturing nitrogen fertilizer uses large quantities of natural gas, and when this fertilizer is applied to fields it produces nitrous oxide, a greenhouse gas that is 300 times more potent than carbon dioxide. Industrial-scale livestock operations can release large volumes of both nitrogen and methane (another powerful greenhouse gas).

The agricultural sector has begun to look at inventive ways to reduce these emissions and to pursue land-use practices that can help mitigate climate change. Strategies range widely, and include different crop cultivation and rotation strategies, using conservation tillage, transitioning to lower-carbon fuel sources, improving fertilizers and fertilizer application approaches, improving soil carbon sequestration, and using gas-capture systems for livestock and manure. There are many opportunities in this sector for technical innovation that can help ensure both climate mitigation and economic benefits.

Of course, the agricultural sector cannot singlehandedly mitigate climate change. Mitigation is ultimately a society-wide problem, and climate solutions and possibilities developed in any one sector will benefit everyone.

The vulnerability of farming to climate change could threaten food security for millions upon millions of people [6]. This essential yet threatened sector means that agricultural producers have a unique opportunity to demonstrate climate leadership. Agricultural adaptation and mitigation are necessary to create a sustainable future for Canada’s farms, and the rest of society has a fundamental role to play in supporting the development of the resilient agricultural systems so necessary to us all.

May 2019

May 2019 

China: The Land That Failed to Fail

The pull of the past: Aerospace workers wearing Long March-style uniforms.

The West was sure the Chinese approach would not work. It just had to wait. It’s still waiting.

In the uncertain years after Mao’s death, long before China became an industrial juggernaut, before the Communist Party went on a winning streak that would reshape the world, a group of economics students gathered at a mountain retreat outside Shanghai. There, in the bamboo forests of Moganshan, the young scholars grappled with a pressing question: How could China catch up with the West?

It was the autumn of 1984, and on the other side of the world, Ronald Reagan was promising “morning again in America.” China, meanwhile, was just recovering from decades of political and economic turmoil. There had been progress in the countryside, but more than three-quarters of the population still lived in extreme poverty. The state decided where everyone worked, what every factory made and how much everything cost.

The students and researchers attending the Academic Symposium of Middle-Aged and Young Economists wanted to unleash market forces but worried about crashing the economy — and alarming the party bureaucrats and ideologues who controlled it.

Late one night, they reached a consensus: Factories should meet state quotas but sell anything extra they made at any price they chose. It was a clever, quietly radical proposal to undercut the planned economy — and it intrigued a young party official in the room who had no background in economics. “As they were discussing the problem, I didn’t say anything at all,” recalled Xu Jing’an, now 76 and retired. “I was thinking, how do we make this work?”

The Chinese economy has grown so fast for so long now that it is easy to forget how unlikely its metamorphosis into a global powerhouse was, how much of its ascent was improvised and born of desperation. The proposal that Mr. Xu took from the mountain retreat, soon adopted as government policy, was a pivotal early step in this astounding transformation.

China now leads the world in the number of homeowners, internet users, college graduates and, by some counts, billionaires. Extreme poverty has fallen to less than 1 percent. An isolated, impoverished backwater has evolved into the most significant rival to the United States since the fall of the Soviet Union.

China today might be unrecognizable to its Communist founders, but the past still holds a powerful allure. “Red tourism” is a big industry.

It is less worried now about catching up to the West. Instead, it wonders how to pull ahead.

The country leads the world in the number of internet users and college graduates. It is now working to land a person on the moon.

Gone are the days when the state decided where everyone worked and what every factory made.

The world thought it would change China, but China’s success has been so spectacular that it has changed the world.

An epochal contest is underway. With President Xi Jinping pushing a more assertive agenda overseas and tightening controls at home, the Trump administration has launched a trade war and is gearing up for what could be a new Cold War. Meanwhile, in Beijing the question these days is less how to catch up with the West than how to pull ahead — and how to do so in a new era of American hostility.

The pattern is familiar to historians, a rising power challenging an established one, with a familiar complication: For decades, the United States encouraged and aided China’s rise, working with its leaders and its people to build the most important economic partnership in the world, one that has lifted both nations.

During this time, eight American presidents assumed, or hoped, that China would eventually bend to what were considered the established rules of modernization: Prosperity would fuel popular demands for political freedom and bring China into the fold of democratic nations. Or the Chinese economy would falter under the weight of authoritarian rule and bureaucratic rot.

But neither happened. Instead, China’s Communist leaders have defied expectations again and again. They embraced capitalism even as they continued to call themselves Marxists. They used repression to maintain power but without stifling entrepreneurship or innovation. Surrounded by foes and rivals, they avoided war, with one brief exception, even as they fanned nationalist sentiment at home. And they presided over 40 years of uninterrupted growth, often with unorthodox policies the textbooks said would fail.

In late September, the People’s Republic of China marked a milestone, surpassing the Soviet Union in longevity. Days later, it celebrated a record 69 years of Communist rule. And China may be just hitting its stride — a new superpower with an economy on track to become not just the world’s largest but, quite soon, the largest by a wide margin.

The world thought it could change China, and in many ways it has. But China’s success has been so spectacular that it has just as often changed the world — and the American understanding of how the world works.

There is no simple explanation for how China’s leaders pulled this off. There was foresight and luck, skill and violent resolve, but perhaps most important was the fear — a sense of crisis among Mao’s successors that they never shook, and that intensified after the Tiananmen Square massacre and the collapse of the Soviet Union.

Even as they put the disasters of Mao’s rule behind them, China’s Communists studied and obsessed over the fate of their old ideological allies in Moscow, determined to learn from their mistakes. They drew two lessons: The party needed to embrace “reform” to survive — but “reform” must never include democratization.

China has veered between these competing impulses ever since, between opening up and clamping down, between experimenting with change and resisting it, always pulling back before going too far in either direction for fear of running aground.

Many people said that the party would fail, that this tension between openness and repression would be too much for a nation as big as China to sustain. But it may be precisely why China soared.

Whether it can continue to do so with the United States trying to stop it is another question entirely.

Apparatchiks Into Capitalists

None of the participants at the Moganshan conference could have predicted how China would take off, much less the roles they would play in the boom ahead. They had come of age in an era of tumult, almost entirely isolated from the rest of the world, with little to prepare them for the challenge they faced. To succeed, the party had to both reinvent its ideology and reprogram its best and brightest to carry it out.

Mr. Xu, for example, had graduated with a degree in journalism on the eve of Mao’s violent Cultural Revolution, during which millions of people were purged, persecuted and killed. He spent those years at a “cadre school” doing manual labor and teaching Marxism in an army unit. After Mao’s death, he was assigned to a state research institute tasked with fixing the economy. His first job was figuring out how to give factories more power to make decisions, a subject he knew almost nothing about. Yet he went on to a distinguished career as an economic policymaker, helping launch China’s first stock market in Shenzhen.

Among the other young participants in Moganshan were Zhou Xiaochuan, who would later lead China’s central bank for 15 years; Lou Jiwei, who ran China’s sovereign wealth fund and recently stepped down as finance minister; and an agricultural policy specialist named Wang Qishan, who rose higher than any of them.

Mr. Wang headed China’s first investment bank and helped steer the nation through the Asian financial crisis. As Beijing’s mayor, he hosted the 2008 Olympics. Then he oversaw the party’s recent high-stakes crackdown on corruption. Now he is China’s vice president, second in authority only to Xi Jinping, the party’s leader.

The careers of these men from Moganshan highlight an important aspect of China’s success: It turned its apparatchiks into capitalists.

Bureaucrats who were once obstacles to growth became engines of growth. Officials devoted to class warfare and price controls began chasing investment and promoting private enterprise. Every day now, the leader of a Chinese district, city or province makes a pitch like the one Yan Chaojun made at a business forum in September.

“Sanya,” Mr. Yan said, referring to the southern resort town he leads, “must be a good butler, nanny, driver and cleaning person for businesses, and welcome investment from foreign companies.”

It was a remarkable act of reinvention, one that eluded the Soviets. In both China and the Soviet Union, vast Stalinist bureaucracies had smothered economic growth, with officials who wielded unchecked power resisting change that threatened their privileges.

Mikhail Gorbachev, the last leader of the Soviet Union, tried to break the hold of these bureaucrats on the economy by opening up the political system. Decades later, Chinese officials still take classes on why that was a mistake. The party even produced a documentary series on the subject in 2006, distributing it on classified DVDs for officials at all levels to watch.

Afraid to open up politically but unwilling to stand still, the party found another way. It moved gradually and followed the pattern of the compromise at Moganshan, which left the planned economy intact while allowing a market economy to flourish and outgrow it.

Once an impoverished backwater, China is now the most significant rival to the United States. Wuhan, a former river town, has swelled into a metropolis of over 10 million.

A businessman stretched before a round of video golf at a hotel he built in Kunming.

Rising incomes have turned China into a nation of consumers.

In cities like Shanghai, Chinese schoolchildren outperform peers around the world.

Western economists doubted that innovation could take place under China’s rigid bureaucracy. They were proved wrong.

Party leaders called this go-slow, experimental approach “crossing the river by feeling the stones” — allowing farmers to grow and sell their own crops, for example, while retaining state ownership of the land; lifting investment restrictions in “special economic zones,” while leaving them in place in the rest of the country; or introducing privatization by selling only minority stakes in state firms at first.

“There was resistance,” Mr. Xu said. “Satisfying the reformers and the opposition was an art.”

American economists were skeptical. Market forces needed to be introduced quickly, they argued; otherwise, the bureaucracy would mobilize to block necessary changes. After a visit to China in 1988, the Nobel laureate Milton Friedman called the party’s strategy “an open invitation to corruption and inefficiency.”

But China had a strange advantage in battling bureaucratic resistance. The nation’s long economic boom followed one of the darkest chapters of its history, the Cultural Revolution, which decimated the party apparatus and left it in shambles. In effect, autocratic excess set the stage for Mao’s eventual successor, Deng Xiaoping, to lead the party in a radically more open direction.

That included sending generations of young party officials to the United States and elsewhere to study how modern economies worked. Sometimes they enrolled in universities, sometimes they found jobs, and sometimes they went on brief “study tours.” When they returned, the party promoted their careers and arranged for others to learn from them.

At the same time, the party invested in education, expanding access to schools and universities, and all but eliminating illiteracy. Many critics focus on the weaknesses of the Chinese system — the emphasis on tests and memorization, the political constraints, the discrimination against rural students. But mainland China now produces more graduates in science and engineering every year than the United States, Japan, South Korea and Taiwan combined.

In cities like Shanghai, Chinese schoolchildren outperform peers around the world. For many parents, though, even that is not enough. Because of new wealth, a traditional emphasis on education as a path to social mobility and the state’s hypercompetitive college entrance exam, most students also enroll in after-school tutoring programs — a market worth $125 billion, according to one study, or as much as half the government’s annual military budget.

Another explanation for the party’s transformation lies in bureaucratic mechanics. Analysts sometimes say that China embraced economic reform while resisting political reform. But in reality, the party made changes after Mao’s death that fell short of free elections or independent courts yet were nevertheless significant.

The party introduced term limits and mandatory retirement ages, for example, making it easier to flush out incompetent officials. And it revamped the internal report cards it used to evaluate local leaders for promotions and bonuses, focusing them almost exclusively on concrete economic targets.

These seemingly minor adjustments had an outsize impact, injecting a dose of accountability — and competition — into the political system, said Yuen Yuen Ang, a political scientist at the University of Michigan. “China created a unique hybrid,” she said, “an autocracy with democratic characteristics.”

As the economy flourished, officials with a single-minded focus on growth often ignored widespread pollution, violations of labor standards, and tainted food and medical supplies. They were rewarded with soaring tax revenues and opportunities to enrich their friends, their relatives and themselves. A wave of officials abandoned the state and went into business. Over time, the party elite amassed great wealth, which cemented its support for the privatization of much of the economy it once controlled.

The private sector now produces more than 60 percent of the nation’s economic output, employs over 80 percent of workers in cities and towns, and generates 90 percent of new jobs, a senior official said in a speech last year. As often as not, the bureaucrats stay out of the way.

“I basically don’t see them even once a year,” said James Ni, chairman and founder of Mlily, a mattress manufacturer in eastern China. “I’m creating jobs, generating tax revenue. Why should they bother me?”

In recent years, President Xi has sought to assert the party’s authority inside private firms. He has also bolstered state-owned enterprises with subsidies while preserving barriers to foreign competition. And he has endorsed demands that American companies surrender technology in exchange for market access.

In doing so, he is betting that the Chinese state has changed so much that it should play a leading role in the economy — that it can build and run “national champions” capable of outcompeting the United States for control of the high-tech industries of the future. But he has also provoked a backlash in Washington.

‘Opening Up’

In December, the Communist Party will celebrate the 40th anniversary of the “reform and opening up” policies that transformed China. The triumphant propaganda has already begun, with Mr. Xi putting himself front and center, as if taking a victory lap for the nation.

He is the party’s most powerful leader since Deng and the son of a senior official who served Deng, but even as he wraps himself in Deng’s legacy, Mr. Xi has set himself apart in an important way: Deng encouraged the party to seek help and expertise overseas, but Mr. Xi preaches self-reliance and warns of the threats posed by “hostile foreign forces.”

In other words, he appears to have less use for the “opening up” part of Deng’s slogan.

Of the many risks that the party took in its pursuit of growth, perhaps the biggest was letting in foreign investment, trade and ideas. It was an exceptional gamble by a country once as isolated as North Korea is today, and it paid off in an exceptional way: China tapped into a wave of globalization sweeping the world and emerged as the world’s factory. China’s embrace of the internet, within limits, helped make it a leader in technology. And foreign advice helped China reshape its banks, build a legal system and create modern corporations.

The party prefers a different narrative these days, presenting the economic boom as “grown out of the soil of China” and primarily the result of its leadership. But this obscures one of the great ironies of China’s rise — that Beijing’s former enemies helped make it possible.

President Xi Jinping has shown no sign of abandoning what he calls “the great rejuvenation of the Chinese nation.” The observation deck of the Shanghai Tower, the world’s second-tallest building.

A Communist Party Congress. Mr. Xi seems to believe that China has been so successful that the party can return to its authoritarian past.

China tapped into a wave of globalization and emerged as the world’s factory. Advertising for day laborers in Shenzhen.

A fashion design employee at a bridal wear exhibition in Beijing may have taken the opportunity for a break, but no one calls China a sleeping giant anymore.

Installing solar panels on a 47-story residential development. China succeeded by leaving a planned economy intact and allowing a market economy to flourish and outgrow it.

The United States and Japan, both routinely vilified by party propagandists, became major trading partners and were important sources of aid, investment and expertise. The real game changers, though, were people like Tony Lin, a factory manager who made his first trip to the mainland in 1988.

Mr. Lin was born and raised in Taiwan, the self-governing island where those who lost the Chinese civil war fled after the Communist Revolution. As a schoolboy, he was taught that mainland China was the enemy.

But in the late 1980s, the sneaker factory he managed in central Taiwan was having trouble finding workers, and its biggest customer, Nike, suggested moving some production to China. Mr. Lin set aside his fears and made the trip. What he found surprised him: a large and willing work force, and officials so eager for capital and know-how that they offered the use of a state factory free and a five-year break on taxes.

Mr. Lin spent the next decade shuttling to and from southern China, spending months at a time there and returning home only for short breaks to see his wife and children. He built and ran five sneaker factories, including Nike’s largest Chinese supplier.

“China’s policies were tremendous,” he recalled. “They were like a sponge absorbing water, money, technology, everything.”

Mr. Lin was part of a torrent of investment from ethnic Chinese enclaves in Hong Kong, Taiwan, Singapore and beyond that washed over China — and gave it a leg up on other developing countries. Without this diaspora, some economists argue, the mainland’s transformation might have stalled at the level of a country like Indonesia or Mexico.

The timing worked out for China, which opened up just as Taiwan was outgrowing its place in the global manufacturing chain. China benefited from Taiwan’s money, but also its managerial experience, technology and relationships with customers around the world. In effect, Taiwan jump-started capitalism in China and plugged it into the global economy.

Before long, the government in Taiwan began to worry about relying so much on its onetime enemy and tried to shift investment elsewhere. But the mainland was too cheap, too close and, with a common language and heritage, too familiar. Mr. Lin tried opening factories in Thailand, Vietnam and Indonesia but always came back to China.

Now Taiwan finds itself increasingly dependent on a much more powerful China, which is pushing ever harder for unification, and the island’s future is uncertain.

There are echoes of Taiwan’s predicament around the world, where many are having second thoughts about how they rushed to embrace Beijing with trade and investment.

The remorse may be strongest in the United States, which brought China into the World Trade Organization, became China’s largest customer and now accuses it of large-scale theft of technology — what one official called “the greatest transfer of wealth in history.”

Many in Washington predicted that trade would bring political change. It did, but not in China. “Opening up” ended up strengthening the party’s hold on power rather than weakening it. The shock of China’s rise as an export colossus, however, was felt in factory towns around the world.

In the United States, economists say at least two million jobs disappeared as a result, many in districts that ended up voting for President Trump.

Selective Repression

Over lunch at a luxurious private club on the 50th floor of an apartment tower in central Beijing, one of China’s most successful real estate tycoons explained why he had left his job at a government research center after the crackdown on the student-led democracy movement in Tiananmen Square.

“It was very easy,” said Feng Lun, the chairman of Vantone Holdings, which manages a multibillion-dollar portfolio of properties around the world. “One day, I woke up and everyone had run away. So I ran, too.”

Until the soldiers opened fire, he said, he had planned to spend his entire career in the civil service. Instead, as the party was pushing out those who had sympathized with the students, he joined the exodus of officials who started over as entrepreneurs in the 1990s.

“At the time, if you held a meeting and told us to go into business, we wouldn’t have gone,” he recalled. “So this incident, it unintentionally planted seeds in the market economy.”

Such has been the seesaw pattern of the party’s success.

The pro-democracy movement in 1989 was the closest the party ever came to political liberalization after Mao’s death, and the crackdown that followed was the furthest it went in the other direction, toward repression and control. After the massacre, the economy stalled and retrenchment seemed certain. Yet three years later, Deng used a tour of southern China to wrestle the party back to “reform and opening up” once more.

Many who had left the government, like Mr. Feng, suddenly found themselves leading the nation’s transformation from the outside, as its first generation of private entrepreneurs.

Now Mr. Xi is steering the party toward repression again, tightening its grip on society, concentrating power in his own hands and setting himself up to rule for life by abolishing the presidential term limit. Will the party loosen up again, as it did a few years after Tiananmen, or is this a more permanent shift? If it is, what will it mean for the Chinese economic miracle?

The fear is that Mr. Xi is attempting to rewrite the recipe behind China’s rise, replacing selective repression with something more severe.

For decades, China has veered between openness and repression, including of the ethnic Uighur minority.

Since the Tiananmen movement, the government has been vigilant about crushing potential threats. Surveillance cameras in Beijing.

China’s high-speed rail network, the largest in the world, has changed the way its people move. In Hangzhou, passengers waited outside the railway station.

As China opened up, farmers were allowed to grow and sell their own crops, while the state retained ownership of the land. Greenhouses filled with bok choy and yellow cabbage abut investment properties and golf courses.

Under Mao, many educated Chinese were sent to “cadre schools,” where they did manual labor. In May, these real estate agency employees went for a morning run as part of a company team-building exercise.

The party has always been vigilant about crushing potential threats — a fledgling opposition party, a popular spiritual movement, even a dissident writer awarded the Nobel Peace Prize. But with some big exceptions, it has also generally retreated from people’s personal lives and given them enough freedom to keep the economy growing.

The internet is an example of how it has benefited by striking a balance. The party let the nation go online with barely an inkling of what that might mean, then reaped the economic benefits while controlling the spread of information that could hurt it.

In 2011, it confronted a crisis. After a high-speed train crash in eastern China, more than 30 million messages criticizing the party’s handling of the fatal accident flooded social media — faster than censors could screen them.

Panicked officials considered shutting down the most popular service, Weibo, the Chinese equivalent of Twitter, but the authorities were afraid of how the public would respond. In the end, they let Weibo stay open but invested much more in tightening controls and ordered companies to do the same.

The compromise worked. Now, many companies assign hundreds of employees to censorship duties — and China has become a giant on the global internet landscape.

“The cost of censorship is quite limited compared to the great value created by the internet,” said Chen Tong, an industry pioneer. “We still get the information we need for economic progress.”

A ‘New Era’

China is not the only country that has squared the demands of authoritarian rule with the needs of free markets. But it has done so for longer, at greater scale and with more convincing results than any other.

The question now is whether it can sustain this model with the United States as an adversary rather than a partner.

The trade war has only just begun. And it is not just a trade war. American warships and planes are challenging Chinese claims to disputed waters with increasing frequency even as China keeps ratcheting up military spending. And Washington is maneuvering to counter Beijing’s growing influence around the world, warning that a Chinese spending spree on global infrastructure comes with strings attached.

The two nations may yet reach some accommodation. But both left and right in America have portrayed China as the champion of an alternative global order, one that embraces autocratic values and undermines fair competition. It is a rare consensus for the United States, which is deeply divided about so much else, including how it has wielded power abroad in recent decades — and how it should do so now.

Mr. Xi, on the other hand, has shown no sign of abandoning what he calls “the great rejuvenation of the Chinese nation.” Some in his corner have been itching to take on the United States since the 2008 financial crisis and see the Trump administration’s policies as proof of what they have always suspected — that America is determined to keep China down.

At the same time, there is also widespread anxiety over the new acrimony, because the United States has long inspired admiration and envy in China, and because of a gnawing sense that the party’s formula for success may be faltering.

Prosperity has brought rising expectations in China; the public wants more than just economic growth. It wants cleaner air, safer food and medicine, better health care and schools, less corruption and greater equality. The party is struggling to deliver, and tweaks to the report cards it uses to measure the performance of officials hardly seem enough.

“The basic problem is, who is growth for?” said Mr. Xu, the retired official who wrote the Moganshan report. “We haven’t solved this problem.”

Growth has begun to slow, which may be better for the economy in the long term but could shake public confidence. The party is investing ever more in censorship to control discussion of the challenges the nation faces: widening inequality, dangerous debt levels, an aging population.

Mr. Xi himself has acknowledged that the party must adapt, declaring that the nation is entering a “new era” requiring new methods. But his prescription has largely been a throwback to repression, including vast internment campstargeting Muslim ethnic minorities. “Opening up” has been replaced by an outward push, with huge loans that critics describe as predatory and other efforts to gain influence — or interfere — in the politics of other countries. At home, experimentation is out while political orthodoxy and discipline are in.

In effect, Mr. Xi seems to believe that China has been so successful that the party can return to a more conventional authoritarian posture — and that to survive and surpass the United States it must.

Certainly, the momentum is still with the party. Over the past four decades, economic growth in China has been 10 times faster than in the United States, and it is still more than twice as fast. The party appears to enjoy broad public support, and many around the world are convinced that Mr. Trump’s America is in retreat while China’s moment is just beginning.

Then again, China has a way of defying expectations.

Philip P. Pan is The Times’s Asia Editor and author of “Out of Mao’s Shadow: The Struggle for the Soul of a New China.” He has lived in and reported on China for nearly two decades.

Jonathan Ansfield and Keith Bradsher contributed reporting from Beijing. Claire Fu, Zoe Mou and Iris Zhao contributed research from Beijing, and Carolyn Zhang from Shanghai.

Design: Matt Ruby, Rumsey Taylor, Quoctrung Bui Editing: Tess Felder, Eric Nagourney, David Schmidt Photo Editing: David Furst, Craig Allen, Meghan Petersen, Mikko Takkunen Illustrations: Sergio Peçanha

March 2019

March 2019


Everyone’s going to the WTO to complain these days.

Brazil is complaining about sugar.    The US is after how the Chinese calculate grain subsidies.    And yes,  Canada will be involved in a hearing this week about how India justifies government interference in our biggest specialty crop export market.   

China and India account for 36% of the world population and 18% of available farmland.   The 5% that live in North America have 11% of the farmland available worldwide.   This leaves North America with a 4:1 surplus of farmland to population compared to its counterparts in Asia.   One would expect the flow of staple agricultural goods from North America to Asia to be self-evident as both sides will have a strong need to ensure an unobstructed flow from one place to the next.     

Mike Tyson said, “everyone has a plan until you get punched in the mouth.”   When India faced droughts in 2015-2016 which rolled into China in 2017 the devastation changed everything.   North American lentil prices appreciated 225% during this period while income for 330 million people in India who work in agriculture was reduced to near zero.   It makes sense that the government is going to react in a way that puts a barrier between the world and its vulnerable population to prevent this from happening again.   Government-controlled stockpiles and duties to encourage local production are a natural reaction to such events.   Two years later North Americans are taking offense that India would take such a position which has resulted in reducing profits on this side of the Pacific to near zero.   

This week, like every week at the WTO, a bunch of suits will travel to Geneva with a basket of spreadsheets and legal documents to argue these injustices.   Each side will put forward an “America First” type argument and someone will win.  What does winning really mean?   This is not a zero-sum game.   Winning does not mean sending violators directly to jail or claiming one of their small islands in the Pacific as compensation.   

The process reminds me Robbin Williams comedy segment where he quips about British police officers trying to chase down criminals with only their baton:   “STOP, or I will say STOP again!”  In the end, the WTO cannot provide a timely remedy.   Years later, if the violating country does not comply the WTO will allow the damaged country to retaliate with sanctions of their own.   Of course,  the world being what it is will move on and the affected industries will adjust.  

Who is still talking about the USA imposing a 25% tariff on Canadian Steel and 10% on Canadian aluminum one year ago?  It is affecting 35000 people in Canada and 10 billion dollars in trade.   This is the reality of unfair trade.   Complain, adjust, and move on.  

Maybe there is not a better way of addressing trade issues.   Like the close button on an elevator,  the WTO provides us a feeling that we can at least “do something” to get this thing moving.  Maybe, at least, someone is writing it down.   I believe markets work.   They work really well where participants can trade within a sound/identifiable market structure and where there is no outside government interference on price.

What we really should be working on as market participants are improving our trading structures between countries so no one gets punched in the mouth and force governments to step in and make a mess of it all.   Then no one is pretending to solve problems by going to the WTO.  

It would be interesting to be part of a discussion where countries with symbiotic supply and demand needs are able to allow a market to move within a wide range but limit the extreme price movements that cause reactions that inevitably hurt real people on both sides.

Something to think about.

Have a great month.







February 2019

February 2019


This year my life of 50 years of eating is officially split in two.   The first 25 as a prairie kid in the 70’s growing up on bacon and eggs, fish sticks, microwave dinners, holiday turkeys, and on the most special occasions sirloin steaks.   During the last 25 I have walked the other side as a ‘west coast’ vegetarian.   Yes, be warned, there are different kinds!    Out here, a healthy dose of social consciousness comes standard with every tofurky dinner.   

So it’s been on my mind for more than 2 decades how our food choices affect our health, the planet we leave behind for our kids, but also realizing we need to exist in the real world earning a living and finding comfort in our families daily life.   I have never found a magic bullet.   All ‘good decisions’ seem to be packaged in compromise.   

A couple of weeks ago, my daughter (a lifetime vegetarian) came home from work raving about a Panago beyond meat pizza her supervisor bought for the crew.   I’ve noticed she conveniently stays at the university for dinner on days I announce we’re making pizza at home, yet, this one enthusiastically hit the mark.    

This is good news, even great news for the pulse industry.   Protein extracted from vegetable sources fetches triple the value of the raw product and offers the opportunity to create exponential demand.     It makes a lot of sense adding value where the product is grown.    Fracturing pulses at home will create less reliance on volatile export markets and reduce risk.   Even for a socially conscious (read: glass half empty) west coast veggie guys like me it checks a lot of boxes.   Could this be one of those elusive good decisions that exist without compromise?

I always accepted the conflict in consuming fake meat products as a vegetarian as a product of my upbringing.    If you don’t need meat to stay alive, why pretend to eat it?    Why go through so much effort to make a bunch of beans taste like bacon?  I do not see any companies trying to turn chickens into a block of tofu.   Apparently, there is a something primally appealing going on within this experiment in food science.   Good enough to make a mainstream impact.   There is no doubt that the trend is just starting to catch steam.   It is probably a good thing.

What is interesting is that the explosion of fake meat in the marketplace is taking place at the same time every health organization is warning against the dangers of processed foods.    The idea of the four food groups engrained in my brain from childhood has evolved to eat whatever the fuck you want as long as it is as close to the original form as possible.       

Unfortunately, the process of fracturing pulses to create protein isolate is going the opposite direction.   

The problem is saying something is plant-based does not mean it is made with vegetables.   Fake meat is full of derivative ingredients.   Like overprocessing wheat for white bread which tastes great but results in gluing your insides together; peas, lentils, and beans lose their nutrient value with processing and basically become highly absorbable carbohydrates which will just make you fatter.   In their new form, they barely contain a fraction of the fiber, vitamins, minerals, and phytochemicals that existed in their original form.   To go “beyond meat” requires adding the same level of saturated fat through coconut oil and five times the salt for no cholesterol compared to an unseasoned beef patty.   (see chart)

Here is how the burgers stack up:                

                         85% Lean Beef      Beyond Meat

Calories                 283                       290

Total Fat (g)          17.5                      22          

Saturated Fat (g)  6.7                        5

Cholesterol (mg)   100                      0

Sodium (mg)           82                       450

Protein (g)              29.4                     20

Iron (daily %)         16%                     25%


I have often told people one of the things I love about this business is being able to watch in real time how the fundamental elements of food/money/politics co-exist and evolve on a global level.     Once again, we have a front row seat to watch how fake meat moves into the mainstream and heralded as the new industry champion despite all of the contradictions and clear benefit.     

As humans, the rational thing to do is to eat a little bit of whole meats, some beans, a bunch of veggies, and a few grains.    Eat them simply without a whole lot of fuss and you will live pretty well without too many worries.    People have been doing this with lentils and peas for over 2000 years and it’s one thing that’s worked out pretty well for humankind.   Somehow, the new exciting food trend is to take something perfectly healthy, bleed all the nutrition out of it and turn it into an alternative to a product that has been demonized for decades without any real nutritional benefit.

Our ability to rationalize adding value by wrecking something that is perfectly fine to get more of something that isn’t is absolutely fascinating.   

I guess my glass is still half-empty.   Have a great month.   





December 2018

December 2018

Have a safe and happy holdiay season.  

Please Note:

Our plant and trading office will be closed Monday, December 24 and will re-open on Tuesday January 2 



November 2018

Phase Transition of Finance

Chia Cheng Chang

Introduction to Two-phase Phenomena Observed in Finance

Phase transition in nature is understood to be emergent phenomena due to the collective behavior of individual particles. In the 􏰃nancial market, phase transitions are also observed while people replace the role of particles. In a demand-driven market, the collective behavior of buyers and sellers have lead Plerou, Gopikrishnan and Stanley to conclude that the collective tendency to buy or sell may be characterized as an order parameter. The tendency to buy or sell is quantitatively described by the volume imbalance, Ω(t), and undergoes a phase transition as the absolute deviation of Ω(t) exceeds a critical threshold Σc. In light of the observations made by Plerou, the model behind the two-phase phenomenon was explored by Zheng, Qiu and Ren. Zheng proposed that the two-phase phenomena could possibly be explained by either the minority games model or the herding model; the predictions made by the models were then compared to the German DAX in order to verify the validity of the theoretical models.

The demand of the market is quantfi􏰃ed by the volume imbalance functionΩ(t) which is de􏰃ned to be the difference between the number of buyer initiated transations QB and seller initiated transactions QS over a small time interval∆t. The equation below is taken from the article written by Plerou1.

Ω(t)≡QB −Qs =􏰋qiai (1)


Equation 1 describes the number of shares traded qi per transaction with N total transactions over a time interval ∆t. The values of ai = ±1 indicating repectively whether the transaction is buyer or seller initiated. Over any partic- ular interval, there will be a distribution on the number of shares traded; that is, if we analyze the distribution of the Ωi(t0) for any t0, it is possible to calculate the absolute deviation of Ω(t0). The absolute deviation of Ω(t) is de􏰃ned to be the 􏰀local noise intensity Σ􏰁1. Quantitatively the local noise intensity for a speci􏰃c time interval ∆t is de􏰃ned to be1

Σ(t) ≡ ⟨|qiai − ⟨qiai⟩|⟩ (2)

It was discovered that the probability distribution P(Ω,Σ) of the volume imbalance, and consequently the most probable value of Ω undergoes a phase transition as the local noise Σ exceeds a critical value Σc. Below the critical value, P(Ω,Σ) is a single peaked function centered around zero. This suggests that when buyers and sellers are generally inactive the mean value of the volume imbalance is zero and the market is in a stable equilibrium. However, the more interesting situation is when buyers and sellers become very active, possibly as

a result of market panic or news of impending doom on the future economy; Plerou observed that as the panic level reaches above the critical value Σc, the probability distribution P (Ω, Σ), becomes double peaked. As a result, players in the market will collectively end up either selling or buying in a situation where there is a large disparity in the number of shares traded; a situation most likely resulting from signs of depression or economic revival. The empirical evidence of such behavior is presented by Plerou and is reproduced below in Figure 1.

Figure 1: Three values of Σ are represented here. The solid black line indicates the region where Σ < Σc. The dotted red line plots the probability distribution when Σ = Σc. The dotted green line shows what happens when Σ > Σc. These graphs hold true for ∆t = 15mins up to half a day.1

From Figure 1, we see that for Σ below the critical value, the probability distribution of Ω, represented by the black line is sharply peaked at zero indi- cating the market being at a stable state. At the critical point, the distribution 􏰄attens out as shown by the red dotted line. For values of Σ greater than the critical value, the distribution undergoes a change and becomes double peaked. The empirical results discovered by Plerou suggest that socially, there is a pa- rameter in which the group behavior of participants in the market undergoes a phase transition. Understanding how this parameter may be measured in practice may provide an indication as to when the market will shift from a stable state to a dynamical state. Understanding qualitatively what P (Ω, Σ) indicates from emprical data prompted Potters and Bouchaud to discuss qualitatively the form of the probability distribution. The form of the probability distribution


function suggested by Potters is given to be2
1 􏰈 Ω2 􏰅βΩ2−Σ􏰆2􏰉

P(Ω,Σ)=Z(Σ)exp −2 − 2σ2 (3)

where Z(Σ) is the normalization while β and σ2 parameterize the magnitude and variance of the noise on Σ respectively. It is then natural to treat the term in the exponent as the action. After varying the action with respect to Ω and minimizing it, the classical solutions to the action are

1􏰌 σ2
Ωc=±√β Σ−2β (4)

As a result, we can conclude that the critical value for Σ is2σ2

Σc = 2β (5)

Given that only the real roots are kept, for values of Σ < Σc, the classical solution for Ω is zero. However, for values of Σ above the critical point, the classical solution yields two roots. Therefore, this hypothesis of the probability distribution function is in agreement with the empirical data gathered by Plerou. From equation 5, it can be seen that the value of Σc depend on the statistical characteristics of Σ. Therefore it was concluded by Potters that emergence of a two-phase phenomenon results from the nature of how trading is collectively executed. In the language of statistics, the critical value Σc is proportional to the variance while Σ itself describes the absolute deviation of Ω. This strongly suggests that the critical value Σc might be related to either the skewness or kurtosis of the volume imbalanace Ω. This was not a claim made by Potters, however, this appears to be an interesting direction for further investigation.

It is of interest to compare empirical evidence with current models used to analyze 􏰃nancial markets. While empirically the transition between a single peak to double peaked probability distribution function is due to the statistics of Σ, theoretically, emergent behavior is a result of a model exhibiting long range correlations. In the 􏰃nancial markets, these are long ranged temporal correlations; the participants in these models make decisions to buy or sell according to results which occured in past time steps. Zheng, Qiu and Ren investigated the possibility of reproducing the emergent behavior though the minority games model.3


The Minority Games

The minority game is a generic model used to describe competing and adap- tive participants in the economy.4 In this game, there are N agents who are forced to select one of two choices and the reward is awarded to the minority choice. In order to make this choice, each agent is given a set number of S strate- gies which they will use to determine the choice they will pick. To more closely model a real economy, agents may be divided into speculators and producers. Speculators are characterized as being more versatile in their strategies and therefore are given more strategies to determine their choice. Producers how- ever, are less 􏰄exible, possibly due to 􏰃xed assets associated with the industry and therefore are given less strategies. In Zheng’s approach, a modi􏰃ed version of the original minority game was applied and an inactive state was added in order to allow the size of the participants to vary. This is the manifestation of long range temporal correlation in this model.3 The resulting probability distri- bution function which arises from the minority games model is shown in 􏰃gure 2.3

Figure 2: The axis here is equivalent to Figure 1. Z ≡ Ω and r ≡ Σ. There are 501 speculators and 1000 producers. Here speculators have an inactive strategy while producers are forced to play. Both speculators and producers are given s=2 strategies and base their decision on the outcome of the strategies on up to m=2 time steps before the current state. Probability distributions for di􏰂erent noise levels (r) are plotted.

From 􏰃gure 2 it can be seen that for increasing values of Σ (denoted by r in the 􏰃gure), the probability distribution gains two peaks. However, the peak



centered around zero does not disappear as values of Σ increase. This is in dis- agreement with the empirical data described by 􏰃gure 1. This result suggests that the minority games model is inadequate in describing the two-phase phe- nomena since the probability distribution of volume imbalance simulated does not evolve in the same way that was observed experimentally. Zheng suggests that the origin of the descrepency may be traced back to the periodic nature of the minority games. The periodic nature of the solution is a result of the par- ticipants having short term memory.6 In the simulation that Zheng proposed, the participants were set to make decisions based on experiences up to m=2 time steps in the past. In the introductory guide to minority games written by Moro, he points out that if only recent information is used to make decisions, then the participants will periodically play the game in exactly the same way.

Figure 3: Time evolution of Attendence for m=2, 7, 15 from top to bottom. Periodic pattern observed for m=2 and 7.6 Attendence is de􏰃ned to be the sum of all options A(t) = 􏰊ai for ai = ±1. Here the two options are given a numerical value ±1 although the contents of the options may be arbritrary (eg. go to Disneyland or stay home and watch TV).

Figure 3 is a graph from Moro’s paper showing that for relatively lower values of m, the way the game is played out, quanti􏰃ed by the function A(t), will be periodic in nature. This is especially clear for the m=2 case which Zheng’s simulation was set to. One possible avenue for further investigation of the minority games model is to increase the parameter m to a large enough value (for example m=15 as suggested by Moro). If indeed the origin of the disagreement between theory and experiment stems from the periodic nature of the minority games, then allowing participants with bigger brains and longer


memory retention rates may be the next step towards improving this model.

The Herding Model

The herding model describes a system of interacting agents who share in- formation and make decisions based on the collective action of the group. The model was 􏰃rst introduced by Eguiluz and Zimmermann, hence is also called the EZ herding model. In the paper Eguiluz published5, the algorithm of the herding model is described as follows. The herd is played by N agents. The state of agent i is described by φi = {−1,0,1} corresponding to selling, inac- tive or buying state respectively. Initially all agents are inactive, however for each time step, one agent (denoted by agent j) selected at random is allowed to become active (φ = ±1) with probability described by a constant a. Interac- tion between the agents is introduced by allowing agents to share information. This is described by having inactive agents form links with other agents. When an agent belonging in the cluster becomes active, the cluster then immediately make the same decision as the active agent. After the decision to act is made my the cluster, all links within the cluster are then removed. After the decision to buy or sell is made, all agents in the cluster are again set to the inactive state, however, agent j (the initiator) has only a probability of (1 − a) of becoming inactive. If agent j becomes inactive, then the agent will establish a link with other agents and become part of a cluster. The whole process is then repeated. If agent j stays active however, it will only be a singular decision as agent j in this case is not part of any cluster.

Applied to the real market, the N agents describe participants in the market. At any given time step, most participants are inactive because there are no rumors or information to indicate whether buying or selling is bene􏰃cial. During inactivity however, Eguiluz suggests that participants may use similar analysis tools and arrive at similar opinions on the current market situation. Therefore, when a participant belonging in the group is motivated to act due to a rumor or other relevent information (insider trading?), other members will immediately come to the same conclusion and act in the same manner. The reason why all link are dropped after the cluster becomes active is because any information and opinion pertaining to that particular market situation will no longer be relevent anymore.5 Finally, the initiator, agent j, is given a probability (1 − a)of becoming inactive probably because the person is in a position that allows him to make more informed decisions, possibly legally. A more logical reason though, is to ensure that as the parameter a is set to 1, that the model approaches a logical steady state solution.

The most important parameter in this model is the probability of activation a. Therefore to check that this model behaves as expected, extremum values for the parameter a should be discussed. If the parameter a is set to 1, then any time an initiator is chosen, agent j will become active. Also, due to the fact that agent j possesses a (1 − a) probability of becoming inactive, with a = 1, the agent will never become inactive. The equilibrium state of this market will result

in all agents acting individually with no group behavior. In the other extreme, by setting a ≪ 1 participants will have an increasing tendency of forming large clusters since agent j is almost never active to trigger o􏰂 an event which then breaks the links. Therefore for small values of a, the model describes highly correlated group behavior. It is then suitable to de􏰃ne a parameter5

h ≡ ‘1 − 1 (6)a

de􏰃ned to be the herding parameter. For small values of a, we observe large group behavior and therefore is associated with a large herding param- eter. When a = 1, no group behavior is observed and therefore we arrive at a herding parameter of zero. In real life, the herding parameter describes the rate of information dispersion.5 The faster information is passed around, the more likely larger and larger groups of people will act according to the same information while on the other extreme, if nobody talks then everyone may only act individually.

From 􏰃gure 2, we see that the minority games model did not adequately capture the two-phase phenomena empirically observed by Plerou as shown in 􏰃gure 1. Therefore, as a separate attempt, Zheng tried the EZ herding model. The distribution for P (Ω, Σ) resulting from the simulation as well as the empirical data of the German DAX is shown in 􏰃gure 4 for comparison.3

Figure 4: EZ model: Probability distribution P (Ω, Σ) for N=10,000 agents, h=19. DAX(94-97): Empirical data of P (Ω, Σ). Note that the time of t=100 in the EZ model scales to 10 minutes in real time as is used to generate the DAX plot.3 Notation used: Ω ≡ Z and Σ ≡ r.

Figure 4 shows that the prediction of the herding model results in the double peaked probability distribution with increasing values of Σ. This is in agreement with the empirical data described by the German DAX presented also in 􏰃gure 4. Qualitatively however, the shape of the peaks do not agree with the empirical


data. More speci􏰃cally, for increasing values of Σ, empirically the height of the peaks decrease while the width broadens out as shown in the DAX plot. The EZ model however, shows that the peaks sharpen and increase in height as seen when comparing the probability distribution represented by the squares and crosses. Zheng suggests that the reason why the scaling with respect toΣ of the standard EZ herding model is in disagreement with empirical data is because the herding model only allows for short ranged temporal correlations while in real market situations the correlations are long ranged. The standard herding model is short ranged due to the fact that the herding parameter is held to be a constant throughout the simulation. This however, is not true in real market situations since the rate of information transmission should vary depending on the current market situation.3 A way to incorporate varying rates of transmission is introduced by Zheng in the interacting herding model.

Interacting EZ Herding Model

In the interacting EZ herding model, Zheng suggests that when the market is very sensitive (when no one knows what is going on and therefore characterized by small cluster sizes), agents and news agencies are attentive and prompt at responding to and reporting news regarding the status of the market. However, when the market is stable and there is less interest in the market, the opposite happens; people will form large clusters. Using this idea, Zheng proposed that the probability of activating agent j should equal3

a[s]|t=t′ = b + cs−δ 􏰇􏰇t=t′ −1 (7)

where s(t) is the average size of a cluster at time t, while b, c and δ are constants. An e􏰂ect of de􏰃ning the probability of activation with respect to the cluster size of the previous time step is also pertinent. If a large cluster was activated at t′ − 1 then the average cluster size s would drop rapidly due to the links being dropped. As a result the herding parameter will become big and will allow for larger clusters to form at t′. If a smaller cluster was activated at t′ −1then the average cluster size would have a relatively smaller decrease and the herding parameter will only increase by a small amount. In real situations this would possibly suggest that large clusters (analysis who use the same program or receive the same information) will continue to remain active with a high herding parameter even after the cluster dissolves; on the other hand folks who buy or sell for idiosyncratic reasons (eg. when they see a shooting star) tend to be the only ones who act that way and do not usually gain a large following of investors willing to imitate. Therefore for activation of small clusters, the impact on the herding parameter is very small. With the addition of what amounts to long ranged temporal correlations, the interacting herding model is used to simulate the probability distribution of volume imbalance again and the results are shown in 􏰃gure 5.3


Figure 5: Interacting EZ herding model for N=10,000 agents, b=0.001, c=0.6 andδ=1. Notation: Ω≡Z andΣ≡r.

The problem with the standard EZ herding model is that for increasing val- ues of Σ, the peaks of P(Ω,Σ) do not scale down properly. For the interacting herding model, Zheng claims that the problem has been solved. Refering to 􏰃gure 5, we see that compared to the standard herding model, for values in increasing Σ, the peaks 􏰄atten out and decrease in magnitude as suggested by empirical data. The phase transition from a single peaked probability distribu- tion to a double peaked distribution is also observed. Therefore qualitatively the interacting EZ herding model contains all the important phenomena associ- ated with the two-phase behavior observed empirically by both Plerou and the German DAX. In 􏰃gure 6, Zheng compares the DAX data with the interacting EZ herding model directly. Although the plots have been rescaled by a constant factor, the DAX data 􏰃ts perfectly with the interactive EZ model. Therefore, allowing the herding parameter to vary as a function of cluster size was vital in having the herding model behave similarly to the observed phenomena. The result is very exciting because it would suggest that there is qualitatively a ro- bust model to describe the observed phase transition in 􏰃nance. The next step would be to understand the connection between experimental and theoretical values of Ω, Σ and t in order to make quantitative comparisons between the two sets of data.


Figure 6: Interacting EZ herding model for N=10,000 agents, b=0.001, c=0.6,δ = 1. DAX o􏰂ers experimental data for comparison. Note3: The plots have been rescaled by constant factors. Notation: Ω ≡ Z and Σ ≡ r.


The observation of two-phase phenomena in 􏰃nance sparked great interest particularly in the physics community to understand this socio-economic behavior through classical phase transition methods. In a theoretical standpoint, the probability distribution function suggested by Potters as shown in equation 3 allows for a path integral type formalism understanding of the phenomena; while the transition from a single-valued peak to a double-valued peak is reminiscent to spontaneous symmetry breaking. Further investigation from the direction of statistics is also possible as the kurtosis of the distribution describes the unique shape of the tails and is related to the critical point of the phase transition Σc. The minority games allow for a possible route of understanding these phenomena through a very simpli􏰃ed model of 􏰃nancial markets. Although the model was unsuccessful in describing the phenomena, the possibility of removing the periodic nature of the minority games is worthy for further investigation. The herding model and ultimately the interacting herding model qualitatively describes the phenomena observed initially my Plerou. The success of the interacting herding model is very interesting because it suggests that humans really do tend to act like sheep during decision making. This may be a concept understood ever since grade school, however, to be able to simulate the same behavior with very simple but important considerations (such as varying the herding parameter with cluster size) is incredibly fascinating. As a practical application,


understand which phase the market is in and when the market will switch phases may also be important for 􏰃nancial risk management. In the single peak phase, odds are no matter how reckless one is on buying stock, there is considerably little risk since there is no net demand to sell or buy and prices as a result, will be relatively stable. In the double-peaked phase, there is considerably more risk associated as the market is in search of a new equilibrium price. In any case, the 􏰃eld of quantitative 􏰃nance and behavior 􏰃nance is relatively new; especially true for new 􏰃elds is the possibility to be the 􏰃rst in discovering something new and impactful. The chance of modeling human behavior in a scienti􏰃c way (as opposed to fortune telling) is no doubt very exciting.

[1] V. Plerou, P. Gopikrishnan, and H.E. Stanley, Nature 421, 130 (2003). [2] M. Potters, and J.-P. Bouchaud, arXiv:cond-mat/0304514v1 (2003).
[3] B. Zheng, T. Qiu, and F. Ren, Phys. Rev. E 69, 046115 (2004).
[4] D. Challet, M. Marsili, and Y.-C. Zhang, Physica A 299, 228-233 (2001). [5] V. Eguiluz, and M. G. Zimmermann, Phys. Rev. Lett. 85, 5659 (2000). [6] E. Moro, arXiv:cond-mat/0402651v1 (2004)