Year: 2015

Young people around the world will be familiar with this paradox. In order to get a job you need experience, but how do you get experience if you cannot get a job? It is a concept that every graduate or school leaver will be familiar with. At least they will be once the initial excitement of the job search wears off, after they are regretfully informed for the umpteenth time that their application has failed to impress because they don’t have the relevant experience.

In order to escape the torment of a lifetime in unemployment limbo, many youngsters are turning to internships as a means of breaking the paradox and gaining some valuable experience that will hopefully help them take the first step in securing a full-time role. However, competition in the paid internships market is just as fierce as it is applying for a permanent position. Out of sheer desperation many end up applying for expenses only or even completely unpaid roles just to get their hands on that most elusive of things – experience.

Many youngsters are turning to internships as a means of breaking the paradox and gaining some valuable experience that will hopefully help them take the first step in securing a full-time role

Upping the expectations
The growth in internships – particularly unpaid ones – is raising some serious concerns. According to a report by The Sutton Trust, a think-tank that works to combat educational inequality in the UK, working for nothing favours the rich and hinders social mobility, which is why it is campaigning for all internships to pay at least the minimum wage.

With many of the best opportunities existing in big capital cities like London and Manhattan, for those that are thinking about embarking on an unpaid internship they face being hit by high living costs, and when considering that the average stint at one of these unpaid internships is usually for a minimum of three months, the price of experience adds up quickly.

When a close friend of mine took an unpaid placement in order to try and gain some experience at a production company, he had to commute to central London from the suburbs. His travel alone was £280 a month. But at least he had the benefit of living on the outskirts of the Big Smoke, along with the knowledge that once his long hard day of being paid absolutely nothing was finally over; he could head back to a home-cooked meal from mum and rest in the warmth of his own bed.

For those living a little further afield, a daily commute is simply impossible. The only other options open to someone looking to gain experience in the big city are to a) find a family member or two who do not mind a bit of couch surfing; or b) look for some form of accommodation nearby. For those who opt to live in London, the price of a three-month stint is bordering on extortion. The Sutton Trust’s report calculated that interns could expect to pay at least £926 per month (and that is excluding transport costs), which will add at least a further £120 onto your bill.

Prices like these mean that unpaid internships and, therefore, potentially valuable experience is restricted to those with the necessary means. What that really equates to is that those graduates, whose parents can afford to bankroll their little one through the process, will have access to these unpaid opportunities that give them an edge in the job market. While those on the other side of the tracks, whose parents make a moderate wage or those who are barely scraping by, will have to accept work closer to home.

City living
No doubt many will be wondering why that it is a problem? Why is everyone so obsessed with working in London anyway? Well, that has a lot to do with the investment gap between the capital and the rest of England, which has grown substantially in recent years. Figures from a research report carried out by the Institute for Public Policy Research (IPPR) show that Londoners receive £5,203 more per person in terms of capital investment than residents in the northeast of England, making London a highly attractive place to do business. This leads to top companies establishing operations in the capital, bringing with them highly sought after employment opportunities.

The cost of living in London, where most of the best opportunities lie, means that access to unpaid internships is restricted disproportionately to those from wealthier families, which in turn is dramatically hampering social mobility for those that come from more modest backgrounds. A recent report by the UK government’s Social Mobility and Child Poverty Commission showed that 71 percent of senior judges, 55 percent of the most senior civil servants, 43 percent of newspaper columnists, and 33 percent of MPs were privately educated – compared with only seven percent of the general population.

Social mobility has always been a topic for debate, as a result of individuals from privileged backgrounds historically having an edge in the job market, but looking at it objectively, why should we fix it? Why should we put a stop to unpaid internships?

Well, the reason has nothing to do with a moral imperative or anything to do with social justice. It comes down to economics. In macroeconomics, an investment multiplier is a term that relates to the idea that if capital is ploughed into a public or private venture, a ripple effect occurs, generating a positive impact for the overall economy. For example, the billions being invested on infrastructure projects, such as London’s Crossrail will have untold benefits for the British economy. Why? Because the extra cash supplied by the UK government to improve the railways will mean that contractors hired to carry out the work on the project will see their incomes increase, leaving them more disposable cash that they may choose to splurge in the retail sector, which in turn boosts that sectors overall income and so on. You get the picture.

Now consider internships. Imagine the government worked alongside business to put some serious investment behind apprenticeship programmes, creating a system that resembled the kind our grandparents’ generation were privy to. Imagine apprenticeships that offered a means of gaining hands on experience in a particular trade or profession, along with adequate remuneration. It would do more than just help young people find work. It would give them independence, and not just from parents, but from the state. It would give them disposable income that would help fuel and sustain the economy, and would allow companies to compliment formal education in order to develop the talent necessary to meet the growing skills gap. In short, putting an end to unpaid internships would be great for everyone’s finances.

Money poisons the mind, argue studies splurged across the pages of international media over the past few years. Such studies have resulted in interesting findings – a recent paper published in November in the Journal of Experimental Social Psychology, for example, found that thinking about money made people less inclined to approve of, and show, emotion in public. The researchers surmised that this could be down to the notion of professionalism associated with finance; great bursts of emotion in the workplace tend to be considered as somewhat inappropriate.

Researchers at both Harvard and the University of Utah meanwhile, found in a 2013 study that exposure to words and images associated with money could lead to unethical behaviour, with money-primed participants more inclined to lie for the sake of economic gain. According to the researchers, “a cost-benefit analysis ensues which focuses on the self to the exclusion of others.” A UC Berkeley study in 2012 monitored two students playing a game of Monopoly and concluded that the player given the most money from the start (and collecting extra when passing Go) acted more aggressively than the poorer participant.

More money, more problems
That potential link between the notion of money and the way we behave is intriguing. It gets precarious, however, when the studies – and moreover the media – suggest that actually having more money has the same effect as thinking about it as a concept.

In some cases the immoral, misogynistic and self-seeking Wolf of Wall Street-style stereotypes probably ring true – but that ‘some’ seems to get awkwardly confused with ‘most’

Psychologist Paul Piff, who led the Monopoly study, didn’t hesitate to make that link. “Putting someone in a role where they’re more privileged and have more power in a game makes them behave like people who actually do have more power, more money, and more status”, New York Magazine quoted him saying. How much of that is grounded in actual reality is questionable, but that didn’t stop it hitting the headlines and fuelling dangerously negative perceptions.

Another study carried out in 2012 by Piff and fellow UC Berkeley researchers took it to a greater extent, arguing that wealthy people were more likely to “lie, cheat, steal, and break the law”, in the words of Business Insider. The findings sparked wide-scale controversy with a divisive mixture of excitement and abomination flooding Piff’s inbox and the media.

Piff and the other researchers wrote in the report that “the increased want associated with greater wealth and status can promote wrongdoing” and that the “upper class”, to use his terminology, view greed as positive. He added that self-centred behaviour accompanies rising status, telling Bloomberg: “It’s not that the rich are innately bad, but as you rise in the ranks… you become more self-focused.”

In some cases the immoral, misogynistic and self-seeking Wolf of Wall Street-style stereotypes probably ring true – but that ‘some’ seems to get awkwardly confused with ‘most’ when such generalisations are made and sent out to sensationalist media outlets hungry for a good story.

The damage caused by such studies, or rather the media’s uptake of them, is two-fold; firstly it implies an awkward binary of ‘rich’ and ‘poor’, evoking some sort of 16th-century ideology where the one is not to mix with the other for fear of contagion on either part; such a binary ignores the complexities of a modern, fluid and liberal society. Secondly it perpetuates the very stereotypes that cause divisions and negative perceptions in the first place; those stereotypes, which permeate all areas of society, can become dangerously self-fulfilling.

Piff’s conclusions, as with the Monopoly game, seem to lack solid evidence; one of the tests in the study, for example, found that drivers in more expensive cars – watched at an intersection – were more likely to cut up other vehicles and less likely to stop at a pedestrian crossing. That led reporters to conclude that the rich were more likely to break the law. But taking an expensive car as an indicator of overall wealth is problematic in itself, as Professor Meredith McGinley pointed out in a Bloomberg report. It also picks up and amplifies the minority, overlooking the two thirds who didn’t cut up other cars, for example.

Other research papers have made similarly sweeping and far-reaching conclusions. A study in 2010 by different UC Berkeley researchers found that those with less money were better at interpreting facial expressions. “Lower-class individuals have to respond chronically to a number of vulnerabilities and social threats”, co-author of the study Michael Kraus told Time. “You really need to depend on others … that makes you more perceptive of emotions.” Although in some cases there may well be truth in that, it’s another generalisation that uses the divisive lower-class/upper-class terms – ignoring the “complex mosaic” (to use the words of Stefan Trautmann, a Dutch researcher who led a more nuanced study in 2013) that shapes our actions. Education, profession and a host of other factors can influence our behaviour just as much as, if not more than, money.

Jumping to conclusions
What these studies seem to do is serve as a means of showcasing a pre-conceived ideology and set of stereotypes without solid evidence. That’s certainly suggested by Piff’s reaction to the results. “Would I be less excited if we found that higher-status people were more generous?” he asked, according to New York Magazine. “I’d probably be less excited, but that’s not what we found.”

Such pre-conceived stereotypes are damaging on any level and, in terms of wealth, can lead to harmful perceptions; according to a study by the University of Pennsylvania, researchers found that people linked higher-earning industries and businesses with unethical behaviour, even when those perceptions weren’t grounded in reality.

Those negative stereotypes disregard the flipside; perhaps most obviously demonstrated through world-renowned philanthropists like Bill Gates, who has pledged his fortune to the charity he and his wife set up, or Warren Buffett, who recently pledged $37bn to the same foundation, or indeed the 125 plus billionaires who have signed the Giving Pledge, promising to donate at least half of their fortune before they die.

Those inspirational acts of kindness risk being eclipsed by the negative stereotypes that these polarising studies, or at least the media’s portrayal of them, exasperate. They encourage unnecessary social divisions that ignore the nuances and fluidity of modern society, provoking leaping conclusions and ungrounded perceptions, and encouraging an oversight of the very real positive action that can come out of all areas of society – regardless of how much money individuals do or do not possess.

In the spring of 2014, Li Keqiang finally took to the stage and declared a “war on pollution”, describing the smog that had enveloped China’s major cities as “nature’s red-light warning against inefficient and blind development.”

Here the premier finally acknowledged the challenges facing China’s mask-wearing millions, and took on board widespread criticisms of the country’s inaction on climate change. This said, likening the government’s anti-pollution drive to a war brings to mind certain connotations, some of which are unhelpful, given the gulf that exists between the country’s military and environmental spending.

A brief look at China’s environmental budget shows that the country’s leadership is perhaps not as committed to fighting pollution as it is to making military threats

Undeterred by cuts in the western world, China’s military budget for 2014 amounted to a cool $132bn, which was 12.2 percent greater than in 2013, despite headline economic growth clocking in at a modest 7.5 percent. In fact, Chinese military spending has exhibited double-digit growth in each of the past 20 years and amounted to one of the most impressive budgets of its kind worldwide.

As a means for comparison, the country’s military expenditure was second only to the US in 2013, and more than double the size of third placed Russia – a measly $85bn. Home to advanced warships, fighter jets, cyber weapons and even drones, China has pumped billions into a military modernisation programme designed to bring the country’s might up to par with its more developed counterparts.

A brief look at China’s environmental budget shows that the country’s leadership is perhaps not as committed to fighting pollution as it is to making military threats. In 2013, the government’s environmental spend, at only $30bn, was down 10 percent on the year previous, according to a budget report seen at the country’s annual parliamentary gathering. Meanwhile, the $34bn dedicated to fighting environmental catastrophe in 2014 is poles apart from the sum set aside for defence.

Budget battle
Granted, a military budget of China’s size is far from unusual for a country of close to 1.5 billion people, though the chasm that exists between defence and environmental spending serves to illustrate exactly how much of a war on pollution we are actually seeing.

Clearly the phrase ‘war on pollution’ itself wasn’t intended to be taken literally, though the idea that climate change is a challenge similar in scale to an all-out war is one that shouldn’t be dismissed so lightly. And for as long as the state refuses to back its war with a war-like budget, criticisms of the government’s inaction on climate change will remain.

Conventional wisdom stipulates that military and defence spending makes up a sizeable share of any country’s budget, and that environmental considerations fall far behind in line.

However, the extent of China’s pollution problem merits that an exception be made to the rule. Look out onto any of the country’s major metropolises and there sits as visible a reminder as you’re ever likely to see that the country’s head-lunge into industrialisation has not been without consequence. Of the many problems ignited by China’s overzealous expansion bid, pollution is perhaps the worst, if not the costliest, in terms of public health, not to mention the financial implications environmental degradation has brought for its economy.

Figures released by the World Bank in 2008 showed that nine percent of national GDP was lost to environmental degradation in only that year, whereas a 2005 study by MIT found that the same issue had cost over $100bn in lost productivity – up from $22bn in 1975. More recently, findings released by the Chinese Academy of Environmental Planning, an organisation linked to the Ministry of Environmental Protection, stated that environmental degradation had cost China $230bn in 2010, representing a threefold increase on 2004. Yet the biggest wake-up call came last year, when the Chinese Academy of Environmental Planning asserted that environmental degradation and pollution had cost the economy $9.3trn in lost GDP.

Switching focus
Approximately three and half decades ago, China’s decade-long cultural revolution left the country in tatters, leaving its inspired leaders to focus on economic development and a road to rapid growth. GDP expansion has since sat at the forefront of the country’s strategic considerations, and China has turned from a country worth $59bn in 1978 to one worth over $9.2trn as of 2013, according to the World Bank. Now, in 2015, the time has finally come to do away with the rapid growth mentality and take into account how the country might achieve more sustainable gains.

Uninhibited energy consumption and a rising population have together given rise to new challenges – not so much in relation to economic growth but in sustaining the pace of development that has been thrust upon it. On the one hand, policymakers mustn’t stray too far from the rate of expansion posted in previous years, so as not to appear a dwindling investment prospect, but, on the other, they must introduce a greater measure of sustainability to proceedings.

Growth at all costs
The thick fog of pollution clouding China’s major cities and the legion of facemask-wearing city dwellers are proof, if ever it were needed, that the scales have been tilting in favour of the growth-at-all-costs approach for too long, though it’s high time policymakers arrived at a trade-off between environmental protection and economic gains.

If the world’s number two economy is to finally realise a greater measure of sustainable prosperity, it must first see pollution for what it is and acknowledge the crippling implications it is having on its economic and social wellbeing. And though some might see Li’s declaration of war on pollution as nothing more than headline fodder, the financial costs of environmental degradation are comparable to a war, and so, the solution worthy of the same budget.

“Nobody, neither the experts nor us amateurs have the least idea what is going to happen with the economy in the future… I don’t think the economists really know”, argued former British Conservative member of parliament, Matthew Parris, in an interview with BBC World Business Report. “I don’t see why we should accord to them any more authority than we accord to palm readers or astrologers. They’re a bit of fun and they sometimes get it right, but it’s not a serious science.”

Though many economists would beg to differ that the complex mathematical models they employ in attempt to forecast the future are unscientific, sentiments such as these are common among those that see the futility in trying to predict the upticks and downturns of the economy. Though it has done little to prevent people from trying.

In the interview, the former MP did eventually conceded that economists and forecasters are proficient at predicting certain things, but that sadly for us, none of them tend to be very useful. “They’re very good at looking into the far distant future and predicting very long-term trends, you know, looking at the way China is growing looking at the way [the] European manufacturing industry has been struggling and predicting a change in balance over decades”, says Parris. “But the one thing where we most [need] economists is where they most regularly fail, and that is not saying what is going to happen tomorrow, but what is going to happen next week, next month, next year.”

In short, forecasters are very good at explaining why the proverbial horse has bolted after the fact, but not very useful in providing insights prior to the event in order to prevent it from happening in the first place. But why do they struggle to get it right where it counts, and will they ever be able to predict the future – or will they always be at the mercy of the market?

Different perspectives
One man that seemed to have succeeded in the business of financial fortune telling where others had failed was Jerome Levy. Back in 1929, the businessman and economist managed to see what so many did not; leading him to making the right call and pulling out of the positions he held in the market just ahead of the October crash. While you would be forgiven for thinking his decision that day was merely a fluke, he and the consultancy company that now bears his name would be more than happy to argue otherwise.

The profit perspective he developed in order to make that impressive judgement call at the beginning of the 20th Century is the same model used by his grandson David, and the company he now runs – The Jerome Levy Forecasting Center – that successfully predicted that the next recession would be caused by a deflating housing bubble.

The company then went on to correctly predict that shortcomings in the subprime-mortgage market would eventually infect “virtually all financial markets”, and be the catalyst for the global financial crisis that broke out in 2008. The company clearly boasts an impressive track record, which is why when it released a forecast predicting, with a 65 percent probability, that a worldwide recession would force contraction in the US by the end of 2015, it got a number of people’s attention.

But how does the profit perspective work, and why do their forecasts fly in the face of those made by investment banks, such as Morgan Stanley and Goldman Sachs, who believe the polar opposite? “We are always a little contrarian, but the most important thing to remember is that we look at the economy from a completely different perspective”, says Srinivas Thiruvadanthai, Director of Research at The Jerome Levy Forecasting Center. “Most Wall Street economists, in fact most economists in the forecasting business, » use conventional macroeconomic forecasting, which relies on large-scale macroeconomic models.

“The problem with them is that they are by their very nature, extremely linear and do not pick out the turning points.” Such models, he argues, tend to focus attention on deviations from trends or what is known as full capacity growth. This method tends to look at the world using a certain lens, which sees economies as either operating above or below full capacity.

This means if a particular economy is running under this benchmark (known as underproduction), it has room to expand, which will lead to a rise in GDP, but when full capacity is exceeded (known as overproduction), the opposite will occur. But it is this same lens that investment banks use, and which leads them down the wrong road, often restricting them from seeing the complete picture. “In reality, if you think about the economy, GDP is not what drives it; what drives the economy is profits, because corporate businesses making profits and their expectation of profits is what drives those same companies to hire new staff and to invest in the economy, which is what really promotes growth.”

This difference in perspective in how they view the economic landscape is what allows the half a dozen experts at the centre to draw more accurate conclusions from the vast amounts of data available and, therefore, make better predictions on the future state of the economy.

The profit perspective
The forecasting centre admits in its publication Where Profits Come From, which explains its models methodology, that it is no secret that profits are a huge motivation for many activities in a capitalist economy, with them playing a large role in the decision making process of individual companies on issues, such as whether to expand or contract production, employ more staff or let people go, as well as being the guiding force behind most investment choices.

Profits, therefore, are crucial in microeconomic models, which attempt to make predictions about the economy through the study of individual markets and the companies, workers and consumers that compose them. But the Levy Center takes this notion a step further. It believes that in the same way an individual company’s profits play a vital part in dictating its behaviour in decision making, aggregate profits – the combined profits of all corporations – have a huge influence on the direction and behaviour of the overall economy.

“Production, employment, and capital spending for the economy as a whole are strongly influenced by aggregate profitability, therefore understanding the determinants of aggregate profits leads to powerful insights into these activities and other economic phenomena, including inflation, unemployment, and business cycles”, claims the report. “Yet conventional macroeconomics, the study of the economy as a whole, rarely considers the role of total profits.”

The Profits Perspective model is one based on what the centre calls a direct flow-of-funds analysis, rather than on statistical approximations of the economy. Meaning that their forecasting model involves no outlandish mathematics, no unrealistic assumptions about the nature of human behaviour, and no unrealistic expectations about how companies, consumers, and investors operate.

Describing the Profits Perspective model in this manner makes it look rather simplistic, but that is not necessarily a bad thing. The 2008 crash occurred at a time when economists were using supercomputers and highly complex models, but they still managed to miss what David Levy and his team spotted. It would appear simple models are far better than complex ones. Though that has not made their forecasting framework completely immune from making miscalculations. Only four years ago the Levy Center made a prediction that was very much along the same lines as the one they released in October 2014.

In it, they predicted a 60 percent chance of a US recession occurring. Sound familiar? In the end they got it wrong, but issuing a probability of a US downturn with just over a 50/50 chance at a time when the American economy faced challenges, such as high unemployment and a financial industry in the midst of huge regulatory reform, is hardly an impressive call.

Prophesying the eventual downturn of the economy appears ever more pointless, when you take into account the fact that boom-and-bust cycles are built into the fundamental framework of the global financial system. This means that making predictions about its eventual demise are as impressive as foreshadowing someone’s death; it’s going to happen eventually, so why not keep firing out the forecasts, at some point one will hit the mark.

Predicting the unpredictable
The bust that inevitably follows the boom is brought on by the most chaotic of forces – basic human nature. It is this feature of mankind that contains within it one of the major factors for why economists’ attempts to predict the future are often unsuccessful. During the booming years when the economy is stable, businesses, governments and the individuals that comprise them easily become overly optimistic as the good times continue to roll on.

Such sentiments lead to overstretches on financial commitments, which leave them – and the larger economy that they are all a part of – more vulnerable to sliding into free fall. Stability, it seems, is inherently unstable. This paradoxical point is made clear when looking at government attempts to intervene in unpredictable markets in a bid to steer away from the cliff’s edge, only to have their best efforts eventually fail.

“Any kind of policy will work for period of time like a charm, but it will lay the seeds for its own demise, because if it is working the way it should then people will take that into consideration when making their plans, which in turn undermines the effectiveness of the policy”, explains Thiruvadanthai. “To give you an example, suppose you do a great job of stabilising the economy, as an investor I will think, ‘oh look; the economy is more stable; I can take on more risk’ because the possibility of a downturn is lower, but in doing so I will undermine that stability.”

This concept is explored within Hyman Minsky’s Financial Instability Hypothesis, which helps show that one of the fundamental issues when trying to navigate a complex financial system to safety, is that no matter what kind of policy you introduce, within a short space of time the system will incorporate it into its own behaviour, undercutting policy and rendering forecasting models useless over time.

“From time to time, capitalist economies exhibit inflations and debt deflations which seem to have the potential to spin out of control”, says Minsky in his thesis. “In such processes, the economic system’s reactions to a movement of the economy amplifies the movement – inflation feeds upon inflation and debt deflation feeds upon debt deflation.”

Paul McCulley, the economist and former managing director of investment management company PIMCO, called this process a ‘Minsky moment’, with the greater significance of the stability/instability hypothesis being that it demonstrates human beings’ propensity to make investments based on momentum, rather than value.

Back in 1929, entrepreneur and business theorist Roger Babson may have unwittingly played up to our penchant for making decisions in this manner when he said: “Sooner or later a crash is coming, and it may be terrific… factories will shut down… men will be thrown out of work… the vicious circle will get in full swing and the result will be a serious business depression.” His remarks came just before the crash and may have provided the necessary momentum to tip the system over the edge.

The fact that human beings make decisions in this manner poses a real challenge for economists when trying to develop forecasting models that are capable of making sense of these irrational forces. But there are some that believe a solution might be found through the application of computer software, enabling us to unlock the potential of big data. Unlike many other fields, financial forecasting is one that is never short on data. There is plenty of information available of people making actual decisions to buy and sell, as well as a host of other information for economists to base their models upon. The real problem they face is making some kind of sense out of all the vast reams of information they have at their disposal. Big data, therefore, is both a blessing and a burden.

Big data
Data sets this large and complex offer those that study them the opportunity to gather new insights, but also have the potential to overwhelm. As any economist knows, successful forecasting relies heavily on one’s ability to separate the signal from the noise. Google Trends (see Fig. 1) has been purported to have the potential to do just that, helping economists to unlock the underlying power of big data in order to assist them in making more precise predictions about market moves before they happen – something that, if achieved, would impress even the likes of Matthew Parris.

Google Trends has been in the news a lot recently as it has been hailed as having crystal ball-like properties, with success in tracking Influenza throughout the US, as well as being able to predict the next platinum album before its even been released. And now, a study carried out by Warwick Business School argues that the technology, which uses complex computer algorithms to pick out patterns in peoples search terms on Google, could be used to identify falls in stock market prices, acting as an early warning device for the next financial crash.

In their paper, the researchers explain how technology has grown to become “deeply interwoven into the fabric of our society”, with the internet being the “central source of information for people when making day-to-day decisions.” What they found was that, by running analysis of search terms made by users on Google and online encyclopaedia Wikipedia, they were able to find “evidence of links between internet searches relating to politics or business and subsequent stock market moves.”

Most interestingly of all, they found that when a spike in these searches was observed, it often preceded a fall in market value. In simple terms, their study showed that when people lack confidence or are unsure about something, they tend to go online in order to make sense of things. Their data provides that, statistically when you see a rise in these types of searches, it implies uncertainty, and that this lack of confidence then correlates to subsequent dips in the market.

Their method worked, but just like instances of market intervention through monetary policy, positive results were short lived. “We [found] that the predictive value of these search terms has recently diminished, potentially reflecting increasing incorporation of internet data into automated trading strategies”, the paper concluded. The market appears to want to remain unpredictable.

Cause and effect
In the same way that governments may introduce new fiscal policies in order to improve the economy, investors weaken its effectiveness, in this case by High Frequency Trading (HFT) platforms, incorporating it into their own investment strategy. When a method is devised to observe potential falls in the market, the market eventually incorporates those same strategies, transforming the original application into something more akin to of a magic eight ball, rather than one made of crystal.

In their conclusion, the researchers propose that their forecasting model’s ‘predictive value’ may have diminished, as a result of automated trading platforms incorporating similar techniques into their investment strategies. What this shows is that their model worked while investors were in the dark about the methods they were using in order to make predictions on the market, but that once investors observed the techniques and then incorporated similar practices into their own strategies, their forecasting model became compromised. But why? An answer for its sudden inability to draw conclusive results could be found in different interpretations of quantum mechanics.

In 1957, Hugh Everett came up with the many-worlds theory, which argues that observation changes the outcome or rather, the probability of that outcome. How this relates to forecasting, is that while it may be theoretically possible through quantum computing to filter out noise in the markets, there is a catch, which is it could never be made public knowledge, because once observed the odds would have changed, compromising the forecasting model.

In his book, The Future of Everything, economist David Orrell argues that economic systems are unpredictable as they are too complex. “One of the lessons of complexity science is that systems can be what Stephen Wolfram calls computationally irreducible.” Wolfram contends that the behaviour of complex systems – though composed of simple structures – is capable of throwing up a wide range of behavioural variables, making it impossible to predict the outcome with any degree of certainty, but despite all this it will do little to deter people from the path of prediction.