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Asset Markets Formula Sheet

December 8, 2011 Leave a comment

Asset Markets – Formula (pdf)

Zynga IPO to raise $1 billion dollars

December 4, 2011 Leave a comment

Games maker Zynga is hoping to raise $1 billion in tough market conditions with an IPO price of $8.50-$10 – giving it a valuation of $7 billion.  Zynga is offfering 14% of its float or 100 million shares, which is higher than most tech companies.

Lead underwriters Morgan Stanley and Goldman Sachs have an additional option to sell 15 million shares. Like Groupon and LNKD, I expect downward pressure on the price when the cost of shorting becomes feasible. If you are one of the lucky few who got in early through private placement it may be time to cash out!

It’s worth noting that a fund raising in February this year valued the company at $10 billion.

I cannot for the life of me understand why any ‘ethical’ investor would invest in a company that generates the bulk of its profits from the sale of virtual goods. (We are NOT talking e-commerce here.) Does it play a socially benefiting role?? We need more clean tech or bio tech!!! Game makers like Rockstar, which makes the highly successful Grand Theft Auto series, actually make money from selling games! Virtual goods are on another level!  How productive?

Retail investors should ask themselves: “Can I live in my virtual farm in Farmville when Fannie Mae repossess my home??!?”

For a copy of their IPO prospectus click on the link below:

Zynga IPO Roadshow Prospectus

 

Zynga IPO Roadshow Prospectus

Sovereign Debt Crisis 101

December 3, 2011 2 comments

Commodities Investing: Demand, Supply and Speculation

July 24, 2011 2 comments

First published on BBeyond Magazine blog – an ultra niche publisher that caters exclusively for the global UNHW market and community: http://bbpublications.org/BBblogs/commodities-investing-demand-supply-and-speculation/

An unsophisticated forecaster uses statistics as a drunken man uses lampposts –
for support rather than for illumination.

– Andrew Lang

The price of a commodity is determined by demand and supply. At least that is what most of us are taught in ‘Economics 101’. The relationship between supply and demand forms the cornerstone of economic models. The most fundamental concept in economics – price – is therefore a reflection of supply and demand. Or is it? Ask anyone who has traded Brent Crude or Light Sweet Crude (WTI) oil contracts and they will tell you the oil market is driven as much by speculation and momentum as it is by demand and supply. To put it in perspective, the CFTC (Commodity Futures Trading Commission) recently revealed that almost 95% of US crude oil futures volume is generated by day trading and OPEC president Mohammad Aliabadi noted futures contract trade an astonishing 18 times higher than the volume of daily traded physical crude.

The world’s population currently stands at 6.93 billion (and counting). It is expected to surpass nine billion by 2050. As such, there has been a lot of brouhaha about our capacity to accommodate the rising demand. The rise of emerging economies like BRIC (Brazil, Russia, India, China) has pushed the prices of commodities to new highs. In the post-2007 credit crunch economic climate, despite the possibility of prolonged spells of slow growth in the developed world, demand is expected to be robust. Chinese GDP per capita alone more than doubled from $3600 in 2001 to $7600 in 2011 and is forecast to surpass $12,000 by 2016. This is a large demand explosion and the question is: How quickly can supply response to that? The prices of commodities will thus be determined using supply-side fundamentals.

In India, 60% of farmers’ produce spoils before it reaches the market. The problem therefore is not supply per se, but infrastructure (which constricts the supply chain).  New technologies can lower production costs while increasing the supply of the commodity. A technology is classified as ‘disruptive’ when it significantly lowers the supply-demand equilibrium price while it simultaneously causes a surge in production capacity. For example, the natural gas market was hit by a disruptive technology in the form of horizontal drilling. Each horizontal rig can surge production by 5-10x the previous capability of vertically drilled wells. In the past, natural gas needed to trade near $6–$7 per mmbtu (million British thermal unit) to encourage new production. Now natural gas is expected to remain under $5.50 per mmbtu for the foreseeable future. The key to successful commodities investing is to spot these disruptive technologies in the wings.

The ideas in this blog post stem from a panel discussion on Commodities Investing the author recently attended at JP Morgan, London. Chartered Alternative Investment Analyst Association sponsored the event.

 

 

If Hedge Funds are the good child of Capitalism, are Banking Institutions their Evil Twin?

July 12, 2011 42 comments

First published on BBeyond Magazine blog – an ultra niche publisher that caters exclusively for the global UNHW market and community: http://bbpublications.org/BBblogs/if-hedge-funds-are-the-good-child-of-capitalism-are-banking-institutions-their-evil-twin/

Give me control of a nation’s money supply, and I care not who makes its laws.

– Mayer Amschel Rothschild

Post-credit crisis, the spotlight was already trained on large ‘unregulated’ investment vehicles. Then we had the Bernie Madoff ponzi scandal. This was followed closely by one of the largest insider trading cases worthy of a Hollywood script – the Raj Rajaratnam Galleon case, which snared senior management from some of the most prestigious Wall Street and consultancy firms.

Main Street was hit with a triple whammy – reeling from the fact that taxpayers’ money is being used to bail out banks that took on too much risk, against a backdrop of the steepest recession since the Great Depression of the 1930s, which was further exacerbated by the unpopular war on two fronts. Obama said he did not run for president to bail out a bunch of fat cat bankers. A witch-hunt was inevitable.

The opaque nature of the hedge fund industry proved an easy target. In theory, hedge funds are just capitalist. They will tear a firm down if it makes money and build it back up if it makes even more. Capitalism at its very best – hedge funds help allocate capital more efficiently by punishing inefficient firms (through short-selling) and rewarding the well-managed ones (by purchasing their stocks). As part of a group of international private investors with a sizeable war chest measuring hundreds of billions, hedge funds can significantly affect global markets and the economies of nations. As such, hedge fund failures are often well documented as their strategies are laid bare for the ensuing media scrutiny.

Long Term Capital Management’s spectacular implosion destroyed $4.6 billion. Most of it belonged to the firm’s partners. Despite its trillion dollar off-balance sheet derivative positions (due to leverage), no taxpayers’ money was used to bail them out. Subsequent academic studies noted that the Fed’s intervention, despite its good intentions, was misguided and unnecessary as it set precedence for regulating hedge fund activity. The Fed may have helped shareholders and managers of LTCM to get a better deal than they would have otherwise obtained in a rescue effort that involved a consortium of Wall Street and international banks.

When Amaranth blew up in a $6 billon bet on natural gas that went bad, another hedge fund, Citadel, stepped in and took over Amaranth’s books. This time, the markets barely flinched. As Sebastian Mallaby, author of More Money than God, puts it: “hedge funds can be a fire-starter as well as a fire-fighter”.

The global financial system and banking institutions are so intertwined that recent events have shown some banks are clearly too big to fail. Hedge funds, on the other hand, are generally small enough to fail. When hedge funds blow up, taxpayers do not foot the bill. The same cannot be said for banking institutions.

During the recent credit crisis triggered by the bursting of the US housing bubble, two of the most hallowed investment banks on Wall Street converted to bank holding companies to take advantage of a lifeline from the Fed. The rest either went bankrupt, got taken over or got bailed out. Beyond the euphemisms, firms like Citigroup, JP Morgan, Wells Fargo, Bank of America, Goldman Sachs, Merill Lynch, and Morgan Stanley were bailed out by the American taxpayers through the Troubled Assets Relief Program (TARP).  In the UK, the Royal Bank of Scotland and Northern Rock ran into the arms of the British government. Northern Rock became the first bank in 150 years to suffer a bank run. Images of the public queuing up to withdraw their money from the branches were plastered on national newspapers and will forever be seared in the minds of Northern Rock’s customers.

Whilst Hedge Funds and Banking Institutions can both be guilty of gambling with OPM (other people’s money), the hedge fund captain is more likely to go down with the ship. Hedge funds go to great lengths to justify their management and performance fees in order to align their interest with that of their investors. Fund partners often (though not always) have a significant proportion of their personal wealth invested in their own funds. In banking, on the other hand, there is a clear dislocation between management incentives and accountability. With the benefit of hindsight, incredulously, the system is essentially rigged to encourage excessive risk taking. Couple that with deregulation and the repeal of the Glass-Steagall Act and we have ourselves a recipe for disaster. History has shown that given enough rope, some of us have a tendency to hang ourselves. The problem then arises when ‘some of us’ (that may hang ourselves i.e. banks) happen to possess enormous financial power by virtue of their control of other people’s money.

The recent credit crisis may have provided ammunition to opponents of the laissez-faire approach to managing economies. One of the basic tenets of the free-market capitalist approach is that firms should be allowed to fail. Like Social Darwinism, only the strong survive and the weak die out. On the other hand, ideas of socialism, while appealing, begin a slippery slope down into communism. The problem with capitalism is the inherent disparity of wealth that creates fault lines between the ‘haves and the have nots’. The problem with socialism is that it undoubtedly leads to ‘free riding and slacking’, or as Margaret Thatcher once said: “The problem with socialism is that eventually you run out of other people’s money [to spend]”. Recent financial events have drawn parallels with a common joke that begins:

A beautiful and shallow woman said to an intelligent and ugly man: “We should get married, so our children will be as beautiful as me and as smart as you”. The man replied: “What if our children turn out to be dumb like you and ugly like me?”

This worst of both worlds approach seems to caricaturize the recent tumultuous events of our financial markets post-2007. When we have ‘too big to fail’ in a supposedly capitalistic economy, we end up with the problems of capitalism (huge disparity of wealth) AND the problems of socialism (spending other people’s money) BUT with NONE of their benefits.

Thomas Jefferson, principal author of the Declaration of Independence and Founding Father of the United States of America, the last bastion of free-market capitalism once said that “banking institutions are more dangerous to our liberties than standing armies”.

What about hedge funds that take on excessive risk through high leverage and speculation? Hedge fund luminary George Soros is infamous for being “the Man Who Broke the Bank of England” when his currency trade forced the United Kingdom out of the Exchange Rate Mechanism (a precursor to the Euro). He netted $1bn by betting on the devaluation of the pound sterling in 1992. The total cost to British taxpayers by the botched attempt to prop up the pound was put at $6.1bn (£3.3bn). Subsequent information obtained through the Freedom of Information Act noted that “if the British government had maintained $24bn foreign currency reserves and the pound had fallen by the same amount, the UK would have made a £2.4bn profit on sterling’s devaluation”.

During the 1997 Asian financial crisis, former Malaysian prime minister Dr Mahatir Mohamad publicly criticized Soros as an ‘immoral financial speculator’ while Soros described Mahatir as a ‘menace to his country’ (Mahatir later accepted that Soros was not responsible for the 1997 Asian Financial Crisis). The crisis started in Thailand when the Thai baht collapsed. Thailand had already acquired a burden of foreign debt that effectively made the country bankrupt before the collapse of its currency. Soros defended his actions by saying “speculation could benefit poor societies if it serves as a signal, not a sledgehammer”. It is worth noting that Soros held back from an all-out attack on the Thai baht. In 1992, Soros sold $10bn worth of sterling at around 2.5x the firm’s capital. The $2bn Thai trade was only one-fifth of the firm’s capital. An all-out attack would have precipitated a crisis rather than encourage the Thai government to avoid one.

In the wake of the Thai baht devaluation, Soros funds gained about $750m whilst Thailand’s economic output plunged 17% and millions fell into poverty. Hedge funds were inevitably vilified. But in a larger context, the roots of the crisis stretched back several years where ‘hot money’ pushed the Thai economy into bubble territory. The Soros team had indeed led the short selling but the actions of hedge funds were in part vindicated when the crisis spilled over to other Asian countries that engaged in ‘crony capitalism’ like Indonesia and Malaysia. What is not usually cited is the fact that Soros lost $800m buying the rupiah as he wrongly believed the turmoil in Thailand had spilled over to neighboring Indonesia without justification. This essentially wiped out all the gains he made in Thailand.  President Suharto and his cronies who controlled Indonesia’s banks drove the country to a crisis, which resulted in his own downfall. Hedge funds may have triggered the avalanche, but it was the government officials who allowed snow to build up to such dangerous levels in the first place.

Hedge funds reap the rewards when they are right and pay the price when they are wrong. Banks reap the rewards when they are right but taxpayers pay the price when they (banks) are wrong. This case of ‘heads I win, tails you lose’ has played a key role in precipitating the recent capricious events resulting from the credit crunch.

 

What role did Hedge Funds play in the credit crisis?

July 3, 2011 2 comments

I have been asked numerous times questions along the lines of “What was the role of hedge funds in precipitating the credit crisis?”

The short and simple answer is: They are NOT responsible for the credit crunch. (If anything, Hedge Funds as unregulated investment vehicles probably help keep the markets in check).

Below is the long answer I posted on a discussion forum which attracted recommendations and interests; as such, I am reposting here.

If you have to draw the line somewhere, like with all market cycles, then post-dot-com crash or 9-11 in 2001 would be a good arbitrary starting point. The key points to remember are:

1) Greenspan kept interest rates for far too low after 9-11 and the dot-com crash – fuelling a credit bubble.

2) This cheap credit meant a housing bubble, as low rates = low mortgage = let’s all buy a house! Happy days!

3) As house prices went up, banks ran out of people to loan money to, they went to subprime or Alt-A (alternative to A-paper).

4) From subprime/Alt-A, greed led us to NINJA loans. No income, no jobs and no asset. These people can’t even prove their income but they can get a mortgage. Happy days!

5) House prices were going up, banks kept lending at record low rates, paying themselves huge bonuses. Everyone was doing it. Can’t beat ’em join ’em mentality. Risk was perceived to be low as everyone believed this housing boom was going to continue. Therefore, banks can easily repossess and sell the houses on, fuelling predatory lending.

6) The loans were packaged up, sliced up and sold on worldwide (e.g. European/Japanese pension funds/institutions).

7) ‘Experts’ argue that never in the US history has there been a NATIONWIDE simultaneous fall in the housing market. (Blackswan event, God I hate that word.) This led to the belief that securitized mortgages are relatively ‘safe’.

8) Pension funds can only buy triple A or AAA rated investments. Investment banks got around that problem by mixing up subprime loans with top rated ones. Paid good money to Moodys and S&P to rate them triple A. The rationale was that not everyone is going to default at the same time (see no. 7). The CDOs (Collateralized Debt Obligations) spread the risk around…

9) Hedge funds act like vultures. They are like the market vigilante. Some of the top guys like Michael Burry, John Paulson, Andrew Lahde (my favorite because he knew when to call it quits) begin to explore ways to short housing.

10) This proved to be almost impossible. They could short firms like NATIONWIDE or homebuilders but naked short selling = their losses can be unlimited and the market can remain irrational then we can remain solvent. (Some managers who correctly foresaw the crash lost money because they bet too early and the market still kept going up.)

11) So smart guys like Paulson found a way to bet against housing by buying Credit Default Swaps (CDS). It is sort of like an insurance policy in case the loan goes bad. His line of reasoning is that, when the shit hits the fan, everyone will be scrambling to buy insurance because their loans will be worthless.

12) As Nouriel Roubini puts it: “It is weird that these CDSs (insurance policy) can be traded around freely. For example if you own a house, only YOU can buy fire insurance for it. But in the case of this credit crunch, I or anyone can buy insurance for your house insuring it multiple times, and then sell it on later, essentially betting on your house burning down.”

13) On a sideshow, Goldman Sachs got hauled up to Congress to explain the fact that they helped Paulson & co pick the worst tranches to bet against. GS later turned around and bet against housing themselves.

14) Those that did not bet against housing were geared and long – and as it turns out they were also ‘long and wrong’. Banks were highly leveraged: 30:1 for Lehman 42:1 in Bear Stearns’ case. It was a case of the sausage makers keeping all the sausages on their books despite knowing what went into them.

15) It was only a matter of time when homeowners started defaulting. It became a snowball effect. When half your neighbourhood is being foreclosed, the value of your home plummets. You bought your house for 500k, now it is worth 300k. You hand in the keys and walk away. So more defaults again!

16) Now all the banks are scrambling to buy CDS. House is on fire! CDS shot through the roof. Guess who is holding it? The hedge funds who correctly bet on them like Paulson.

17) AIG (yup, US taxpayers money bailed them out) wrote most of the CDS and sold it dirt cheap. In traders’ lingo – you have AIG making money paying huge bonuses selling insurance policy for houses built from flammable material next to a pyrotechnic factory located on an earthquake fault line. It was a case of ‘picking up nickels and dimes in front of a steamroller/freight train’.

18) No problem – when AIG was about to go down, we have TOO BIG TO FAIL. Lehman was Goldman Sachs’ number one competitor but they were allowed to fail. If AIG went down, Goldman Sachs was on the hook. But no problem, the then Secretary Hank Paulson was former CEO of Goldman Sachs (conflict of interest?). Hank played a key role in bailing out AIG. AIG straight away paid back Goldman.  Make of this what you will. “It is Government Sachs mate. GS is a branch of the US government.” (That was what a friend said to me.)

19) When the market tanked, a lot of institutions started pulling funds from hedge funds. Some of which were geared/leveraged. They then had to unload their positions in a thin market, causing a death spiral. The liquidity problem killed them.

20) So do hedge funds have a role in causing the crash? Answer = NO!  They were as much a casualty as a profiteer.

So what caused the credit crunch? Well, no simple answer. I tried to keep it to 20 sentences. I guess it is a case of pluralistic ignorance, greed, hubris and regulation (or the lack of it)?

“If I had known I was going to fall down, I would have sat down” old Polish proverb.

 

The Four Most Dangerous Words in Investing

June 26, 2011 Leave a comment

First published on BBeyond Magazine blog – an ultra niche publisher that caters exclusively for the global UNHW market and community: http://bbpublications.org/BBblogs/the-four-most-dangerous-words-in-investing/

“The four most dangerous words in investing are ‘This time it’s different.’”

– Sir John Templeton (29 November 1912 – 8 July 2008)

In 2005, the late Sir John Templeton penned a memo, which wasn’t discovered until after his passing in 2008.  It was eerily pithy, almost ‘prophetic’  as the first two words were bolded in its original text and begins as follows:

Financial Chaos – probably in many nations in the next five years. The word chaos is chosen to express likelihood of reduced profit margin at the same time as acceleration in cost of living.”

Sir John had already correctly predicted the Dot-com crash and his predictions of a housing bubble (that will eventually burst) and subsequent stock market fall all came to pass. However, those with views similar to Sir John back in 2005 would generally have found their concerns of the housing market pooh-poohed by the proponents of securitization as the US housing market has ‘never experienced’ a simultaneous nationwide fall.

Time and again, investors have always used the words “this time it’s different” or many of its variants to justify our actions when we rush headlong into a bubble. Caught up in the euphoria of a bull run, we post-rationalize our thoughts and seek out ‘evidence’ to support our hypotheses. Much like when we suddenly decide to purchase a car of certain make and color, we tend to notice it a lot more often on the road. As our paper wealth increases, we use that as justification, or worse, as ‘proof’, that our earlier convictions were indeed ‘correct’. Perhaps it is cognitive dissonance – not too dissimilar to a smoker who is perfectly cognizant of the health risks yet continues to feed his habit by inhaling from the cancer stick. Psychologists have shown that we have a tendency to underestimate the risk of an activity when we ourselves are engaged in it. We also have a penchant to indulge in intellectual materialism where we treat our ideas like possessions. We find it difficult to admit we were ‘wrong’ in light of new contradictory information and as a result, we hang on to our ideas for far too long. Perhaps this could be a reason why economic bubbles continue to persist despite ever more efficient markets.

Hindsight is a beautiful thing or, as I always say, “hindsight vision is always 20/20”. From the tulips mania in 1600s and the South Sea bubble in 1720, to the Housing bubble in the 2000s – it was never a bubble in foresight, only in hindsight. To quote the ‘greatest stock operator’ that ever lived:

“There is nothing new in Wall Street. There can’t be because speculation is as old as the hills. Whatever happens in the stock market today has happened before and will happen again.” – Jesse Livermore

The whole premise of efficient markets lies in the fact that overvalued stocks should theoretically attract short sellers to bring it back in line. Arbitrageurs should keep the markets in check. However, as Yogi Berra once said “in theory there is no difference between practice and theory, in practice there is” and as we now accept, the markets are not always rational. In fact, I would go as far as to argue that rationality itself is an arbitrary concept.

Keynes once remarked that “The markets can remain irrational longer than you can remain solvent.”  Even the best investors have painfully discovered that being early and right is the same as being wrong.

Michael Burry of Scion Capital faced an investor revolt when he bet too early on the recent subprime mortgage crisis.  The housing bubble continued to inflate before his predictions came true and the investors that stuck with him made a tidy profit.  Scion ultimately returned almost 500% (net of fees and expenses) from November 2000 until June 2008 whilst the S&P returned just over 2% over the same period.

Even the likes of George Soros, his once right-hand man Stanley Druckenmiller of the Quantum Fund and Julian Roberston were not spared from the ‘irrationality’ of the markets. Titans of the industry and legends in their own right, each man has paid dearly for being ‘right too early’ at one point or another in their careers. If being right too early equals being wrong, does being ‘wrong’ too early equal being ‘right’? Is it homogeneous and symmetrical? (More on this later.)

Julian Roberston’s Tiger Fund paid the ‘ultimate price’. Robertson correctly called the tech bubble in the late ’90s but had to unwind the legendary fund in March 2000  ̶  just before the NASDAQ tanked. Since there was no hope of bucking the trend as momentum traders continued to ride the wave, hedge funds mostly jumped on for the ride. Only the bravest or perhaps the foolhardiest would even dare consider trading against this mania.

Perhaps the bravest of all was Julian Robertson, who suffered heavy losses when everyone else surfing the wave was making extraordinary profits. Faced with a flood of redemption requests from investors as the bubble drove the price of tech stocks to dizzying heights, Robertson, who famously refused to partake in the Internet craze, just couldn’t hang on long enough. He had repeatedly warned the ‘day of reckoning would come’ when Internet companies that had never turned a profit continue to skyrocket against a backdrop of collapsing stocks elsewhere.

In March 2000, Robertson decided he had had enough of waiting and closed down the battered Tiger Fund. At around the same time, the NASDAQ crested to mark the beginning of the end for the tech bubble. But for Robertson and his Tiger Fund, the end just could not have come soon enough. The ‘day of reckoning’ did come on 13 March 2000 when the sell off began, but for Robertson it was too late. The market had remained irrational longer than he could stay solvent. Over the next 20 months, the NASDAQ fell from 5038 to a bottom of 1114. At its peak, Tiger had well over $20 billion in assets under management and Robertson was second to none when it came to stock picking.

Back in 1867 John Stuart Mills noted “Panics do not destroy capital; they merely reveal the extent to which it has been destroyed by its betrayal into hopelessly unproductive work”. The same lesson could still be applied to the Stock Market Crash of 2000-2002, which wiped off $5 trillion in the market value of companies.

Perhaps it is no wonder that Sir Isaac Newton famously said “I can calculate the motions of heavenly bodies, but not the madness of people” when the genius himself got caught up in the South Sea bubble and reportedly lost £20,000 (equivalent to £3 million today).

Earlier, I argued that rationality itself is an arbitrary concept and posed the question “If being right too early equals being wrong, does being ‘wrong’ too early equal being ‘right’?” Think about it: if everyone in the world suddenly became ‘irrational’, would that not make you the irrational one (at least from a medical standpoint)? If rationality is defined by consensus, then by implication rationality is a moving target. Hence, when the market is acting ‘irrationally exuberant’, do you try to remain ‘rational’ and short the market (like Robertson did)? Or do you act ‘rationally’ by jumping on for the ride to profit from it (like Druckenmiller eventually did)?

George Soros famously said “It’s not whether you’re right or wrong that’s important, but how much money you make when you’re right and how much you lose when you’re wrong”. I would venture as far as saying when it comes to the markets, there is no such thing as ‘wrong’ or ‘right’. There are strategies that are profitable, and strategies that blow you up. That’s it.

Fortunately, in finance, economists have another term called ‘profit-maximizing’, which is often used interchangeably with ‘rational expectations’. However, as investors we may not always have the luxury or liberty to consider etymological and philosophical questions when our portfolio is haemorrhaging money. If it walks like a duck, quacks like a duck and looks like a duck, for all intents and purposes, it is a duck!

 

High Frequency Trading vs Behavioural Finance

April 26, 2011 5 comments

*The following post has been edited for clarity from an essay I wrote.

I recently became a voracious reader of finance-related books. Being academically inclined, I would often refer to the original source, and many times contacted the authors directly when I needed further clarification. I found that most authors responded warmly. My relatively simple task of learning about ‘company valuation’ and ‘financial forecasting’ grew into a path of self-discovery. ‘Valuation’ led to ‘CAPM’, which led to ‘Modern Portfolio Theory’, which begat ‘Rational Expectations Theory’, which begat ‘Game Theory’ and ‘Efficient Markets Theory’, which led me to ‘Behavioural Finance’[1] and so forth.

Google Scholar and Amazon.co.uk became my best friends. Consumed by finance, I devoured every book and article I could find on the subject. Seeking the source, the man who started it all, I rummaged through the literature all the way back to Professor Edward Oakley Throp. Many regard Professor Throp as the ‘Godfather of Quants’ ̶ the first academic who used his applied mathematics skills in probability theory to beat the casino game of blackjack. Not content, he eventually took his skills to the biggest ‘casino’ of all: Wall Street, where his early work in warrant pricing paved the way for modern quants. I was mesmerised. Most people probably have not heard of Professor Throp, but they might have seen the Hollywood movie Bringing Down the House/21 or read the book. It is a true story based on the MIT blackjack team who took on Vegas and won. In the game of blackjack, cards dealt are not replaced. In mathematics, this is known as conditional probability. As the shoe (deck of cards) gets dealt the probability of the remaining cards can be established with greater confidence, tipping the usual 0.5% to 2% house edge into a positive edge for the players. Professor Throp was the first to exploit this and published his first ‘mathematical proof’ that the game blackjack was in fact beatable in the book Beat the Dealer. His work paved the way for subsequent MIT blackjack teams and also led to the growth of quant finance where academics took their research skills in applied maths to Wall Street. To this day, blackjack remains the only ‘beatable’ game in a casino, but casino operators have made it increasingly harder by using more decks and shuffling the decks (or shoe) more often. You may wonder why would casinos allow a game where it is beatable and still make money? Well, it is the allure of people who think they can beat blackjack by card counting (and don’t) that makes it worthwhile for casinos to keep that game. This is an interesting behavioural and psychological phenomenon. Even an experienced player playing perfect basic strategy gives up 0.5% on every hand. It takes a truly professional team to tilt the game in their favour. Even then, the player advantage is also minuscule and to make money, they have to play a long time (or leverage up) assuming they don’t get thrown out or chew on some knuckle-dusters first.

When I read Inventing Money by Nicolas Dunbar[2] I knew I had found my true calling.  Perhaps it was the allure of a career that combined elements of my love for physics and psychology with academia that drew me to the financial markets.

Today, as a ‘local’ (proprietary trader) on the NYSE Liffe and Eurex, I primarily trade as a speculative arbitrageur in Euribor futures and German two-year notes (Schatz). Trading as a liquidity provider, I employ a market neutral strategy in which my positions are usually hedged. However, such market-making strategies are the strength of black-box trading techniques such as High Frequency Trading (HFT) and algorithmic trading. Their stochastic models and execution are far superior to any human trader, and they can operate simultaneously in many different markets. I believe that proprietary traders like myself will therefore be redundant within five years.

Algorithmic trading now accounts for more than 60-70% of trading volume on the NYSE. This trend is set to continue as programme trading is also gaining a strong foothold in the futures and currency markets. The Bursa Malaysia (and other emerging markets) presents significant opportunities for such endeavours as these ‘virgin’ markets begin to embrace and incorporate more complex financial derivatives. Trading volume in the Bursa Malaysia is still primarily dominated by three (not profit-orientated) government-linked funds that operate through brokers known locally as Remisiers. Furthermore, CME Globex has recently offered to cash-settle Malaysian crude palm oil futures, paving the way for growth in this arena. (And the recent trend in major Financial Exchange consolidation represents another opportunity altogether.)

Behavioural finance relaxes the rigidly rationalist assumptions of financial economics by incorporating principles from psychology, anthropology and sociology into standard models of financial markets. Herein lies a conundrum. Implicit in the advantages of algo/programme trading system is the belief that human emotion is thoroughly eliminated. But imagine a universe where programme trading has come to completely dominate all aspects of our financial markets. Asset pricing is determined ‘rationally’ by computer models. Algo traders no longer design systems to capture minute mispricing anomalies arising from the fragility of humans  ̶  after all, in this universe there is no such need as humans are no longer active participants in the markets. It is a case of machines against machines. It necessarily follows that ‘behavioural finance theory’ may be ineffective in such a setting.

Both as a student of behavioural finance theory and as a trader watching and participating in the same markets increasingly being dominated by algo trading, I sometimes feel like I have a front-row seat at a ‘train wreck’ waiting to happen.  Hurtling down the fibre optics tracks is the train of data emanating from the co-located exchange servers of algo trading groups. Standing in its path since the 1990s is the research in behavioural finance by Professor Robert Schiller and Professor Richard Thaler, among others.

What would happen if, or when, our financial markets were thoroughly dominated by algo trading? Would behavioural finance be rendered obsolete? Would it spawn a new field of study known as ‘algo finance theory’ that perhaps incorporates AI and neural networks? Would the new ‘algo finance theory’ do unto ‘behavioural finance’ what ‘behavioural finance’ did to the ‘efficient markets’? Will efficient market theory rise like a phoenix from the academic ashes again once the machines take over completely (since algos are ‘rational’ and ‘more efficient’)?

The May 2010 flash crash put the media spotlight on the esoteric field of HFT.  Having spoken to HFT academics and practitioners, I’ve learned that many believe behavioural finance is a moving target  ̶  algo finance will never kill herd behaviour completely. Due to the time scale of HFT, the total dollar amounts are relatively small. HFT scalpers are already all over the Forex market, yet when the US employment figures or interest rate figures are released, the market goes ‘bonkers’, just like it always did. Instead, lower frequency computer trading (where the money stays on a trade for a long time), whether it’s human or computer, can drive the real changes in long-term price. For example, the Black Monday crash in 1987 (when HFT did not exist) was exacerbated by portfolio insurance strategies that used programme trading. Programme trading triggered stop-loss orders, which led to a downward spiral.

I want to bring all these strands together in research that will use the recent financial crisis, the flash crash of May 2010, the explosion of HFT, and the rush for Ultra-low latency Direct Market Access, among other factors, to explore the potential for growth of algorithm trading in emerging markets and the academic as well as investing opportunities that might result. No other subject piques my interest more.


[1] I was already familiar with works by Daniel Kahneman, Amos Tversky and Daniel Ariely, having studied psychology at college. However, revisiting their work from a completely new behavioural finance perspective was like rekindling an ‘old flame’.

[2] Inventing Money is the lesser known but more technical book covering LTCM’s demise (the other being When Genius Failed).

 

 

The Quants – How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It.

February 23, 2010 2 comments

The Quants

I pre-ordered this and received it the day of release. There were some negative comments on Amazon regarding this book that basically went along the lines of ‘the author is bashing quants (quantitative maths whizz) for the economic crisis’. It is clear the ‘reviewer’ did not actually read the book. For starters the author is a staff reporter for the WSJ. Not sure if that is a good thing or a bad thing. (For stories I’ll happily read the WSJ, but for objectivity I’ll stick to the FT.)

This book does NOT blame all quants for the crisis. Don’t judge a book by its cover; the title is probably more of a marketing ploy than anything. Patterson basically covers the alpha and the omega of a small breed of highly influential quants, the big swinging d!cks, the masters of the universe such as hedge fund bosses, head of prop traders and senior management of some major financial institutions on Wall Street.

The biographies and historical anecdotes of the major characters have to be taken with a pinch of salt, nevertheless the author did a good job with narration. Obviously anyone who is reading this book is smart enough to realise that the author is not reconstructing the ‘conversations’ verbatim.

The book begins with Ed Thorp (quant legend) who was the first guy that devised a mathematically ‘proven’ and field tested method to beat blackjack. Not satisfied with beating casinos at their own game Thorp decided to take his math skills to the biggest casino of all, Wall Street. He later ‘discovered’ a mathematical formula for buying and selling warrants. Thorp is perhaps best known for his two books, Beat the Dealer and Beat the Market, both of which are now classics.

Click here for podcast of an interview with Ed Thorp and Scott Patterson

The author then takes the reader through a journey in history to the present day titans of the financial markets such as Ken Griffin of Citidel and Cliff Asness of AQR, Peter Muller, Boaz Weinstein etc. These men each control billions and most of them wield PhDs in the quantitative field from the top academic institutions. They all share one thing in common: the search for THE truth/alpha. The truth/alpha roughly equates to knowing (or ‘predicting’) where the financial markets are heading and/or the world as a matter of fact.

According to them the truth/alpha can be measured a dollar at a time and for every dollar they accumulate, it represents one step closer to THE truth (if there was one). Possession of the truth or alpha promises ethereal riches.

However, the book does not go into detail on how financial modelling caused the crisis nor does it offer any concrete evidence as such. You just have to take the author’s word. Nevertheless the stories itself are worth it.

Try reading this with Fooled by Randomness and the Black Swan by Nassim Taleb. Which is what I did. Not only did these three books change my outlook on the financial markets and the economy in general, they had me re-examining my epistemological and philosophical paradigm of my knowledge (or the lack of it) on the said matter and in general.

Read an excerpt from the book (Chapter 2)

 

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