Posts tagged ‘Jamie Dimon’

Investing in a World of Black Swans

In the world of modern finance, there has always been the search for the Holy Grail. Ever since the advent of computers, practitioners have looked to harness the power of computing and direct it towards the goal of producing endless profits. Today the buzz words being used  across industries include, “AI – Artificial Intelligence,” “Machine Learning,” “Neural Networks,” and “Deep Learning.” Regrettably, nobody has found a silver bullet, but that hasn’t slowed down people from trying. Wall Street has an innate desire to try to turn the ultra-complex field of finance into a science, just as they do in the field of physics. Even banking stalwart JPMorgan Chase (JPM) and its renowned CEO/Chairman Jamie Dimon suffered billions in losses in the quest for infinite income, due in large part to their over-reliance on pseudo-science trading models.

Preceding JPM’s losses, James Montier of Grantham Mayo van Otterloo’s asset allocation team gave a keynote speech at a CFA Institute Annual Conference in Chicago, where he gave a prescient talk explaining why bad models were the root cause of the financial crisis. Montier noted these computer algorithms essentially underappreciate the number and severity of Black Swan events (low probability negative outcomes) and the models’ inability to accurately identify predictable surprises.

What are predictable surprises? Here’s what Montier had to say on the topic:

“Predictable surprises are really about situations where some people are aware of the problem. The problem gets worse over time and eventually explodes into crisis.”

 

When Dimon was made aware of the 2012 rogue trading activities, he strenuously denied the problem before reversing course and admitting to the dilemma. Unfortunately, many of these Wall Street firms and financial institutions use value-at-risk (VaR) models that are falsely based on the belief that past results will repeat themselves, and financial market returns are normally distributed. Those suppositions are not always true.

Another perfect example of a Black Swan created by a bad financial model is Long Term Capital Management (LTCM) – see also When Genius Failed. Robert Merton and Myron Scholes were world renowned Nobel Prize winners who single-handedly brought the global financial market to its knees in 1998 when LTCM lost $500 million in one day and required a $3.6 billion bailout from a consortium of banks. Their mathematical models worked for a while but did not fully account for trading environments with low liquidity (i.e., traders fleeing in panic) and outcomes that defied the historical correlations embedded in their computer algorithms. The “Flash Crash” of 2010, in which liquidity evaporated due to high-frequency traders temporarily jumping ship, is another illustration of computers wreaking havoc on the financial markets.

The problem with many of these models, even for the ones that work in the short-run, is that behavior and correlations are constantly changing. Therefore any strategy successfully reaping outsized profits in the near-term will eventually be discovered by other financial vultures and exploited away.

Another pundit with a firm hold on Wall Street financial models is David Leinweber, author of Nerds on Wall Street.  As Leinweber points out, financial models become meaningless if the data is sliced and diced to form manipulated and nonsensical relationships. The data coming out can only be as good as the data going in – “garbage in, garbage out.”

In searching for the most absurd data possible to explain the returns of the S&P 500 index, Leinweiber discovered that butter production in Bangladesh was an excellent predictor of stock market returns, explaining 75% of the variation of historical returns. By tossing in U.S. cheese production and the total population of sheep in Bangladesh, Leinweber was able to mathematically “predict” past U.S. stock returns with 99% accuracy. To read more about other financial modeling absurdities, check out a previous Investing Caffeine article, Butter in Bangladesh.

Generally, investors want precision through math, but as famed investor Benjamin Graham noted more than 50 years ago, “Mathematics is ordinarily considered as producing precise, dependable results. But in the stock market, the more elaborate and obtuse the mathematics, the more uncertain and speculative the conclusions we draw therefrom. Whenever calculus is brought in, or higher algebra, you can take it as a warning signal that the operator is trying to substitute theory for experience.”

If these models are so bad, then why do so many people use them? Montier points to “intentional blindness,” the tendency to see what one expects to see, and “distorted incentives” (i.e., compensation structures rewarding improper or risky behavior).

Montier’s solution to dealing with these models is not to completely eradicate them, but rather recognize the numerous shortcomings of them and instead focus on the robustness of these models. Or in other words, be skeptical, know the limits of the models, and build portfolios to survive multiple different environments.

Investors seem to be discovering more financial Black Swans over the last few years in the form of events like the Lehman Brothers bankruptcy, Flash Crash, and Greek sovereign debt default. Rather than putting too much faith or dependence on bad financial models to identify or exploit Black Swan events, the over-reliance on these models may turn this rare breed of swans into a large bevy.

See Full Article on Montier: Failures of Modern Finance

Wade W. Slome, CFA, CFP®

Plan. Invest. Prosper.

www.Sidoxia.com

DISCLOSURE: Sidoxia Capital Management (SCM) and some of its clients own JPM and certain exchange traded funds, but at the time of publishing SCM had no direct position in Lehman Brothers, or any other security referenced in this article. No information accessed through the Investing Caffeine (IC) website constitutes investment, financial, legal, tax or other advice nor is to be relied on in making an investment or other decision. Please read disclosure language on IC “Contact” page.

April 15, 2017 at 10:25 am Leave a comment

Broken Record Repeats Itself

Article is an excerpt from previously released Sidoxia Capital Management’s complementary June 2012 newsletter. Subscribe on right side of page.

Traditional music records have been replaced with CDs (compact discs) and digital downloads. Although the problem of a broken record repeating itself is no longer an issue, our financial markets have not conquered the problem of repetition. More specifically, the timing of the -6.3% stock market decline during May (as measured by the S&P 500 index), coincides with the same broken sell-offs we have temporarily experienced over the last two summers. First, we had the “Flash Crash” in the summer of 2010, and then the debt ceiling debate and credit downgrade of 2011.

So far, the “Sell in May and go away” mantra has followed the textbook lessons over the last few years, but as you can see from the chart below, the short-lived seasonal sell-offs have been followed by significant advances (up +33% from 2010 lows and up +29% from the 2011 lows). Given the global challenges, a two-steps forward, one-step back pattern in equity markets should not be seen as overly surprising by investors.

Source: Yahoo Finance

Although the late-spring and summer doldrums have not been a joy-ride in recent years, these overly simplistic seasonal trading rules of thumb have not been exceedingly reliable either. For example, even though the months of May in 2010-2012 produced negative returns, the previous 25 Mays going back to 1985 produced positive returns more than 2/3 of the time. Rather than fiddle with these unreliable, unscientific trading rules, individuals would be better served by listening to famous Jedi Master Yoda from Star Wars, who so astutely noted, “Uncertain, the future is.”

Voting Machines and Scales

Given the spread of globalization and technology, the speed of news dissemination has never been faster. With the 2008-2009 financial crisis still burned into investors’ minds, the default response to any scary news item is to shoot first and ask questions later. Renowned long-term investing legend Ben Graham famously highlighted, “In the short run the market is a voting machine. In the long run it’s a weighing machine.”

As it relates to short-run current events, here are some of the items that investors were voting on (no pun intended) this month:

Europe, Europe, Europe: This problem has been with us for some time now, and there are no signs it will disappear anytime soon. In a game of chicken between the EU (European Union) and Greek legislators, fresh elections are taking place on June 17th, which will ultimately determine if Greece will exit the Euro monetary union or stick to the bitter medicine of austerity prescribed by the key European decision-makers in Germany. As Greece attempts to clean up its own mess, European politicians and G-20 leaders around the globe are scrambling to create plans that ring-fence countries like Spain and Italy from succumbing to a Greek-born contagion.

Presidential Politics: If you haven’t been living in a cave for the last six months, you probably know that 2012 is a presidential election year. Regardless of your politics, there are big questions surrounding the economy, jobs, deficits, debt, taxes, entitlements, defense, gay marriage, and other important issues. Answers to many of these questions will remain unclear until we get closer to the elections. The financial markets do not like uncertainty, so probabilities would indicate volatility will remain par for the course for the foreseeable future.

Facebook Folly: Despite my warnings, Facebook’s initial public offering (IPO) failed to live up to the social media giant’s hype – the share price has fallen -22% since the shares originally priced. Great companies do not always make great stocks, especially when a relatively new kid on the block has his company’s stock initially valued at a hefty price-tag of more than a $100 billion. Finger pointing is being spread liberally on the botched Facebook deal (e.g., Morgan Stanley, NASDAQ, Facebook), but no need to shed a tear for 28-year-old founder Mark Zuckerberg since his ownership stake in the company is still valued at around $15 billion – enough to cover a European trip to McDonald’s with his newlywed wife.

Dimon in a Rough Spot: Jamie Dimon, the poster child of the banking industry (and CEO of JP Morgan Chase – JPM), dropped a bomb on the investment community earlier in the month by explaining how a rogue “whale” trader racked up $2 billion in initial losses (and growing) by taking excessive risk and throwing controls into the wind.

Chinese Dragon Losing Steam: The #2 global economy has been losing some steam as witnessed by slowing industrial production and GDP growth (Gross Domestic Product). In turn, the self correcting economic forces of supply and demand have provided relief to consumers and corporations in the form of lower fuel, energy, and commodity prices. Chinese leaders are not sitting still – there are plans of accelerating infrastructure spending and assisting banks in the form of capital injections and lower reserve requirements.

As I discussed in a previous Investing Caffeine article (see The European Dog Ate My Homework), although the current headlines remain gloomy, that will always be the case. Just a few years ago, Bear Stearns, Lehman Brothers, AIG, CDS (credit default swaps), and subprime mortgages were the boogeymen. In the 1980s, we had the Savings & Loan financial crisis and the infamous 1987 Crash. During the 1970s, the Vietnam War, Nixon’s impeachment proceedings, and rising inflation were the dominating issues. Since then, the equity markets are up over 20x-fold – time will always reward those patient long-term investors. Despite all the doom and gloom, stock markets have roughly doubled over the last three years and all the major indexes remain solidly in the black for the year. Choppy waters are likely to remain as we approach this year’s elections, but for those who understand broken records often repeat themselves, there’s a good chance the music will eventually sound much better.

Wade W. Slome, CFA, CFP®

Plan. Invest. Prosper.

www.Sidoxia.com

DISCLOSURE: Sidoxia Capital Management (SCM) and some of its clients own certain exchange traded funds (including commodities, inflation protection, floating rate bonds, real estate, dividend, and alternative investment ETFs), but at the time of publishing SCM had no direct position in FB, MCD, JPM, MS, NDAQ, AIG, Lehman Brothers, Bear Stearns, or any other security referenced in this article. No information accessed through the Investing Caffeine (IC) website constitutes investment, financial, legal, tax or other advice nor is to be relied on in making an investment or other decision. Please read disclosure language on IC “Contact” page.

June 2, 2012 at 6:51 pm Leave a comment

Investing in a World of Black Swans

In the world of modern finance, there has always been the search for the Holy Grail. Ever since the advent of computers, practitioners have looked to harness the power of computing and direct it towards the goal of producing endless profits. Regrettably, nobody has found the silver bullet, but that hasn’t slowed down people from trying. Wall Street has an innate desire to try to turn the ultra-complex field of finance into a science, just as they do in the field of physics. Even JPMorgan Chase (JPM) and its CEO Jamie Dimon are already on their way to suffering more than $2 billion in losses in the quest for infinite income, due in large part to their over-reliance on pseudo-science trading models.

James Montier of Grantham Mayo van Otterloo’s asset allocation team was recently a keynote speaker at the CFA Institute Annual Conference in Chicago. His prescient talk, which preceded JP Morgan’s recent speculative trading loss announcement, explained why bad models were the root cause of the financial crisis. Essentially these computer algorithms under-appreciate the number and severity of Black Swans (low probability negative outcomes) and the models’ inability to accurately identify predictable surprises.

What are predictable surprises? Here’s what Montier had to say on the topic:

“Predictable surprises are really about situations where some people are aware of the problem. The problem gets worse over time and eventually explodes into crisis.”

 

Just a month ago, when Dimon was made aware of the rogue trading activities, the CEO strenuously denied the problem before reversing course and admitting the dilemma last week. Unfortunately, many of these Wall Street firms and financial institutions use value-at-risk (VaR) models that are falsely based on the belief that past results will repeat themselves, and financial market returns are normally distributed. Those suppositions are not always true.

Another perfect example of a Black Swan created by a bad financial model is Long Term Capital Management (LTCM). Robert Merton and Myron Scholes were world renowned Nobel Prize winners who single handedly brought the global financial market to its knees in 1998 when LTCM lost $500 million in one day and required a $3.6 billion bailout from a consortium of banks. Their mathematical models worked for a while but did not fully account for trading environments with low liquidity (i.e., traders fleeing in panic) and outcomes that defied the historical correlations embedded in their computer algorithms. The “Flash Crash” of 2010, in which liquidity evaporated due to high frequency traders temporarily jumping ship, is another illustration of computers wreaking havoc on the financial markets.

The problem with many of these models, even for the ones that work in the short-run, is that behavior and correlations are constantly changing. Therefore any strategy successfully reaping outsized profits in the near-term will eventually be discovered by other financial vultures and exploited away.

Another pundit with a firm hold on Wall Street financial models is David Leinweber, author of Nerds on Wall Street.  As Leinweber points out, financial models become meaningless if the data is sliced and diced to form manipulated and nonsensical relationships. The data coming out can only be as good as the data going in – “garbage in, garbage out.”

In searching for the most absurd data possible to explain the returns of the S&P 500 index, Leinweiber discovered that butter production in Bangladesh was an excellent predictor of stock market returns, explaining 75% of the variation of historical returns. By tossing in U.S. cheese production and the total population of sheep in Bangladesh, Leinweber was able to mathematically “predict” past U.S. stock returns with 99% accuracy. To read more about other financial modeling absurdities, check out a previous Investing Caffeine article, Butter in Bangladesh.

Generally, investors want precision through math, but as famed investor Benjamin Graham noted more than 50 years ago, “Mathematics is ordinarily considered as producing precise, dependable results. But in the stock market, the more elaborate and obtuse the mathematics, the more uncertain and speculative the conclusions we draw therefrom. Whenever calculus is brought in, or higher algebra, you can take it as a warning signal that the operator is trying to substitute theory for experience.”

If these models are so bad, then why do so many people use them? Montier points to “intentional blindness,” the tendency to see what one expects to see, and “distorted incentives” (i.e., compensation structures rewarding improper or risky behavior).

Montier’s solution to dealing with these models is not to completely eradicate them, but rather recognize the numerous shortcomings of them and instead focus on the robustness of these models. Or in other words, be skeptical, know the limits of the models, and build portfolios to survive multiple different environments.

Investors seem to be discovering more financial Black Swans over the last few years in the form of events like the Lehman Brothers bankruptcy, Flash Crash, and Greek sovereign debt default. Rather than putting too much faith or dependence on bad financial models to identify or exploit Black Swan events, the over-reliance on these models may turn this rare breed of swans into a large bevy.

See Full Article on Montier: Failures of Modern Finance

Wade W. Slome, CFA, CFP®

Plan. Invest. Prosper.

www.Sidoxia.com

DISCLOSURE: Sidoxia Capital Management (SCM) and some of its clients own certain exchange traded funds, but at the time of publishing SCM had no direct position in JPM, Lehman Brothers, or any other security referenced in this article. No information accessed through the Investing Caffeine (IC) website constitutes investment, financial, legal, tax or other advice nor is to be relied on in making an investment or other decision. Please read disclosure language on IC “Contact” page.

May 20, 2012 at 6:02 pm Leave a comment


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