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The Swiss Franc, Pseudo-Mathematics and Financial Charlatanism

Originally published in April 2014. Bank research suggests that both euro and dollar appreciate against CHF. Many of these arguments based on very simple assumptions and restrictions; might be called Pseudo-Mathematics and Financial Charlatanism.

Our research is also available on Seeking Alpha.


Research from most banks regularly suggests that both the euro and dollar will appreciate against CHF (FXF) in the future. Common arguments are:

  1. “The SNB is your friend and will support your trade.” – See in our critique that the SNB might exit your trade when Swiss inflation rises and that this does not mean that it will go bankrupt.
  2. “The Swiss franc is clearly overvalued.” – See in our critique that the overvaluation talk disregards the strong immigration into Switzerland and the huge current account surpluses since 1999.
  3. “Foreign investors hold cash or safe bonds in Swiss francs; they will sell these soon.” – The 2013 net outflow in bonds was 4 bln. CHF compared to an 80 bln. CHF current account surplus, source Balance of Payment (BoP) data.
  4. “Less fear and risk appetite will drive investors out of Swiss assets.” – During the so-called “US recovery” of 2013, the BoP data show that Swiss investors bought 15 bln. CHF of foreign equities, while foreigners kept nearly unchanged holdings of Swiss stocks, in particular Swiss multi-nationals that generate safe profits all over the world.
  5. “Swiss banks will lend to foreign banks in foreign currency.” – This game may be too risky for Swiss banks due to their Basel III ratios. In early 2013 this lending started but has already stopped in Q4 (BoP data) .
  6. “The ECB will hike interest rates before the SNB.” – See why during an upcoming boom, the Swiss CPI might soon be higher than Eurozone inflation.
  7. When euro zone deflation killed argument 6, they claimed: “Real interest rates are higher in the euro zone than in Switzerland.” – Even if Italian and Spanish bond yields have fallen close to U.S. levels, CHF remains strong (details about this bank advice).



Many of these arguments are based on very simple assumptions and restrictions (see our critique for each one above). We reckon that the only question as for the Swiss franc is:
Can the persistent Swiss current account surpluses be neutralized by capital account outflows?”

This implies that only a combination of the seven major factors – the ones of the balance of payments – together can generate a capital outflow that is able to counter the huge Swiss current account surplus and the CHF strength. For us this is only possible:

  • During phases of high global (over-) spending and strong global growth, potentially based on cheap debt in CHF.
  • During weak Swiss economic phases, for example, after the real estate bust in the 1990s.

The combination of these two factors led to excessive CHF weakness between 2004 and 2007.

The main issue with the above research is a conflict of interest because the clients invest based on this so-called “independent research”, which is enforced by “Chinese walls” between bank departments. Professional traders in the investment bank have more accurate mathematical models: they eventually trade against their own clients. CHF has been a typical battlefield for such a violation of conflict of interest guidelines for years, proving that Chinese walls are not that thick.

One client might have been the German drug store baron Ernst Müller who lost three times more with bets against CHF than he gained with his business.

In a new paper the mathematicians DH Bailey, JM Borwein, ML de Prado and Qiji Jim Zhu accuse simplified quantitative investment strategies of pseudo-mathematics and financial charlatanism.

Via the Financial Times

When use of pseudo-maths adds up to fraudBy Stephen Foley

Many models tweak strategy to fit data or are just statistical flukes. An academic journal called the Notices of the American Mathematical Society may seem an unlikely periodical to have exposed fraud on a massive scale. The investigation, published in the current edition, is certainly not going to sit among the nominees for next year’s Pulitzer prizes. But a quartet of mathematicians have just published a piercing article in the public interest and in the nick of time.

In their paper, entitled Pseudo-Mathematics and Financial Charlatanism, they make the case that the vast majority of claims being made for quantitative investment strategiesare false.*
By calling it fraud, the academics command attention, and investors would be wise to beware. With interest rates about to turn, and a stock market bull run ageing fast, there have never been such temptations to eschew traditional bond and equity investing and to follow the siren sales patter of those who claim to see patterns in the historical data.

The (unnamed) targets of the mathematicians’ ire range from individual technical analysts who identify buy and sell signals in a stock chart, all the way up to managed futures funds holding billions of dollars of clients assets. There will be many offenders, too, among investment managers pushing “smart beta” strategies, which aim to construct a portfolio based on signals from history. There is even a worrying do-it-yourself trend: many electronic trading platforms now have tools encouraging retail investors to back test their own half-baked trading ideas, to see how they would have performed in the past.
The authors’ argument is that, by failing to apply mathematical rigour to their methods, many purveyors of quantitative investment strategies are, deliberately or negligently, misleading clients.

Now we come back to the bank research in CHF argument 7 above, and the authors add:

Twisting strategy to fit dataIt is reasonable to want to test a promising investment strategy to see how it would have performed in the past. The trap comes when one keeps tweaking the strategy until it neatly fits the historical data. Intuitively, one might think one has finally hit upon the most successful investment strategy; in fact, one is likely to have hit only upon a statistical fluke, a false positive.

This is the problem of “over-fitting”, and even checks against it – such as testing in a second, discrete historical data set – will continue to throw up many false positives, the mathematicians argue.

Do not despair. The paper does not conclude that history is bunk, just that backtesting ought to require more statistical thought than investment managers need to display to make a sale to investors.

The perennial success of Renaissance Technologies, founded by code-breaking maths genius Jim Simons, suggests that some can separate signal from noise in financial markets.

At least the best quantitative hedge funds are attuned to the problem of overfitting. London’s Winton Capital published a paper last year warning that, even if individual researchers are scrupulous about calculating their probabilities, institutions risk “meta-overfitting”, because the tendency is to only submit the best fitting strategies for approval to the higher-up management committee.

It seems that finance may need the same overhaul as the pharmaceuticals industry did a decade ago.

Statistical flukesAmid a furore over the safety of its antidepressant Paxil in 2004, it was discovered that GlaxoSmithKline had conducted numerous trials that failed to prove the drug was an effective treatment for children. However, a minority of trials did suggest efficacy, to a statistically significant confidence level, and these were the studies that got published. It wasn’t until scientists added together all the unpublished data that it became clear the drug increased the risk of teen suicides, for no offsetting benefit in treating depression, and it was banned for use by minors.

GSK responded by promising to reveal all its trials and to publish all its data, regardless of their outcome, and other large drug companies followed, more or less reluctantly. As a result, we continue to learn that large claims made for blockbuster medicines tend not to stack up over time, Tamiflu being the latest example.

When it comes to quantitative investment strategies claiming to have performed well historically, it is not good enough for managers to stamp “past performance is no guide to future performance” on to a marketing document. A crucial detail, almost never revealed, is how many discarded tweaks and tests led to the miraculous discovery of the strategy….

*Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance – DH Bailey, JM Borwein, ML de Prado and Qiji Jim Zhu

And there we are: the past CHF weakness between 2004 and 2007 is no indicator of future weakness.

Forget all this quantitative rubbish and think logically taking more than just one argument of the ones above into account.

A stronger currency simply means cheaper imports and more expensive exports; cheaper capital and more expensive labour. Almost a null-sum game, in particular for a country like Switzerland that continuously expands its share of global growth with a strong currency. Thanks to cheaper capital and a stronger euro, the weak euro zone member states have stopped the capital flight.
Longer-term currency movements are mostly driven by credit cycles, far less by “risk-on”, “risk-off”.

George Dorgan
George Dorgan (penname) predicted the end of the EUR/CHF peg at the CFA Society and at many occasions on SeekingAlpha.com and on this blog. Several Swiss and international financial advisors support the site. These firms aim to deliver independent advice from the often misleading mainstream of banks and asset managers. George is FinTech entrepreneur, financial author and alternative economist. He speak seven languages fluently.
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1 comment

  1. Karl

    P.s. more Information about Smart Beta ETFs: http://smart-beta.info

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