Download PDF, Issue 26 - Swiss Futures and Options Association

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Hedge Funds 36 so that the transitive principle may not apply and P B(2%) > P A(0.5%) > P A(2%) The relative size of P B(0.5%) and P A(2%) is not known but does not matter for the purposes of this explanation. In the specific example, the Terminal Value of Strategy B is 112.7, or 47 bp. greater than Strategy A’s. Note from the example that the latter underperforms despite having experienced no catastrophic draw-down during the period (as one would sooner or later have to expect of positive carry-style strategies such as this one). Two important psychological biases are at work over here: • Extrapolation bias, whereby investors form their future projections by extrapolating from past experience. With this bias, investors fail to adjust their expectations for the regression to the mean. This bias is a subset of representativeness (Kahneman & Tversky, 1974), a psychological tendency whereby individuals, when faced with samples A and B, tend to deem A as representative of B. This is embodied in the use of frequency, a measure from the past, to form expectations on probability, which concerns the future. The sequence of events in the past is assumed to be a good proxy for the series of future returns and their probability. • Hedonic framing (Thaler, 1985), the psychological bias whereby investors prefer savouring a series of little wins and lumping together losses. This bias is appealing on two counts: a) A series of positive returns is associated with the idea that one’s portfolio is growing steadily over time. As investors are rewarded in dollars, rather than in probabilityweighted dollars, this overlooks the fact that a portfolio’s value may be progressively eroded in probability-weighted terms. Credit portfolios, with their stream of creditspread income and occasional major draw-downs, are the classic case in point. b) It is far easier to dismiss the occasional major draw-down from selling risk insurance as an “aberration” or as an “exceptional” event than when a stream of tiny losses occur. Simply put, frequency may be used as a proxy for the probability of returns but has little to do with them, since the “Intelligent investors will be looking for some creative tension between risk and trading functions.” former is derived from the past and the latter refers to the future, respectively. Due to mental conditioning that includes “be right” attitudes that are taught since one’s early school days, investors keep associating the frequency of wins with strong performance. That is then reflected in managers’ evaluation and selection. Unfortunately, the 80–20 rule applies, in that 80% of trading profits usually come from less than 20% of one’s trades and over half result from just between 3% and 10% of the trades (Kiev, 2002). These statistics alone should make investors think twice about inferring stability in performance when presented with a series of positive returns. Counterintuitive as it may sound, no downside volatility is more worrisome than some. Short of clairvoyance, the lack of volatility betrays the selling of some insurance on some events that may look remote from a statistical point of view, or, worse, even some smoothing of P&L by accounting means. Thaler (1999) states: … we should expect to see that some of the discretion inherent in any accounting system will be used to avoid to experience losses. Risk adjustment based on historical volatility Hedge funds are not known for their eagerness to provide detailed position information. Accordingly, investors use what they have to draw conclusions, namely historical information. Using the standard deviation of returns to calculate volatility, the so-called Historical Simulation (HS) method – is indeed one of the earliest methodologies used to calculate market risk in banks and financial institutions. Advances in Risk Management theory and the impressive rise in computing power enabled the development of more advanced methodologies, such as the Variance- Covariance (VCV) Method or the Monte-Carlo Simulation. These have progressively replaced HS over time. While reasonable for market risk, the HS method can become dangerously inaccurate when credit risk is involved. Credit is involved directly with credit arbitrage or distressed strategies and indirectly with equity strategies. Unlike market risk, credit involves lumpy losses. Take the example of an investor who is presented with a pure market-risk strategy, typically a macro fund, and a credit strategy. If these have experienced the same return and the same historical volatility to date, the HS method may make their risk-adjusted performance look very close. Nevertheless, the credit fund’s performance is exposed to losses that are positively correlated with time SWISS DERIVATIVES REVIEW 26 – NOVEMBER 2004
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Page 1 and 2: SWISS DERIVATIVES ISSUE 26 - NOVEMB
Page 3 and 4: Contents Contents SWISS FUTURES AND
Page 5 and 6: Dear Members and Friends of SFOA Ed
Page 7 and 8: Focus Treasury. Then came Ginnie Ma
Page 9 and 10: “This approach moves us in the di
Page 11 and 12: WHEN YOUR FIRST NAME IS “NEW,”
Page 13 and 14: Focus Union’s regulators in terms
Page 15 and 16: “There’s no rule saying banks c
Page 17 and 18: The rush of endless opportunity. Li
Page 19 and 20: Further your future: team up with a
Page 21 and 22: “Investor interest in gold was re
Page 23 and 24: A new standard in the derivatives i
Page 25 and 26: “The Stone Age didn’t end becau
Page 27 and 28: A blazing sponsor for Friday night
Page 29 and 30: CNBC Europe reporting live from Bü
Page 31 and 32: A fascinating presentation by ballo
Page 33 and 34: “Swiss taxation is very advantage
Page 35: “These results seriously question
Page 39 and 40: “ ‘Carry’ strategies and even
Page 41 and 42: Education Chart 2 Overbought zone (
Page 43 and 44: Bollinger Bands Let’s briefly rev
Page 46 and 47: Emerging Markets A Perspective on E
Page 48 and 49: Profile IFRI - The International Fi
Page 50 and 51: Profile 50 Official Publication of

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