21 The results are much the same. On average, the dispersion in banking returns is statistically significantly lower than for non-banks, at the 1% level, both for UK and global institutions. And, in general, we observe a compression of returns during credit booms and a dispersion in busts. There is evidence of an increase in the degree of coordination of global banks’ activities after the financial liberalisation of the 1980s. This suggests credit cycles may have become increasingly synchronous globally. To test this formally, we construct pair-wise correlations between countries’ credit cycles for two post-war sub-samples, 1945–79 and 1980–2008. We plot the cumulative distributions of these cross-country correlations in Chart 16. The same technique can be applied to correlations between countries’ medium term fluctuations in GDP (Chart 17). In each chart, a shift to the right of the cumulative distribution indicates an increase in the degree of crosscountry correlation. Chart 12 Dispersion of equity returns of US banks and top 100 US PNFCs (by market cap)  (1), (2) and (3) represent medium term credit booms. Outside of these areas represent medium term credit busts. Source: Thomson Reuters Datastream and Bank calculations. 20  Theoretical explanations have been put forward by, among others, Campbell and Cochrane (1999) and Mele (2007), who show that habits and cyclically asymmetric risk premia respectively may generate counter cyclical volatility in asset pricing models. 21  This global group of banking institutions included UK and US banks as a subset.
But it also drives up volatility due to risk illusion. Because riskadjusted returns are constant, this must entail an increase in the probability of there being a severe negative shock, so the probability of a crash rises. Chart 2 shows a simulation of the model when for 100 periods with normally distributed shocks. The frictionless benchmark model generates the path shown by the maroon line. As specified, the path is mean reverting, with movements in the macro state around trend. Allowing for reputational effects generates the blue path, giving a threshold level of fundamentals shown by the green dashed line. As the macro state hits the threshold, banks adopt risky policies to signal high ability. In this simulation this happens four times, in periods 3, 50, 68 and 72. Consider the threshold breach in period 72. As during the Great Moderation, the good macro state at first persists. The credit boom fuels high fundamentals. But while headline fundamentals have improved, risk-adjusted fundamentals have not. Eventually, this results in a crunch in credit and a sharp deterioration in the macro state, as risk is realised. 10  In particular, the Sharpe ratio (the expected value of fundamentals relative to their standard deviation) is constant across both regimes. BIS Review 168/2010  7  Now suppose that financial liberalisation generates heightened competition between banks, in the model. increasing the market premium on reputation. This raises the value of Chart 3 shows the effects of the reputational weight being raised . The threshold for risky policies falls.