Remember when even the worst of all trading desks on Wall Street, that of Bank of America could do no wrong and disclosed a trading quarter of pure perfection? Yeah, that's over. The bank, which just jolted shareholders with news of material common dilution, in the form of $2.5 billion in new equity capital to be raised, has released its trading days data for Q3. Per the 10-Q: "During the three months ended September 30, 2011, positive trading-related revenue was recorded for 69 percent (44 days) of the trading days of which 47 percent (30 days) were daily trading gains of over $25 million, nine percent (six days) of the trading days had losses greater than $25 million, three percent (two days) of trading days had losses greater than $100 million and the largest loss was $119 million." On the flip side, BAC had not one $100MM+ trading win. In other words, BAC posted losses on a whopping 31% of the trading days (compared to 0% two quarters ago), something that indicates a very violent return to normalcy: after all if banks, with ZIRP, legal frontrunning, profit from default risk surges, and POMO are unable to make money 100% of the time, who else, besides all the day traders on twitter and the fine men and women on Fast Money of course, will post flawless trading records in the future?
And a very convenient chart which we hope other banks will follow suit in providing is the following presentation of the bank's VaR alongside its daily P&L. Granted, BAC could actually go ahead and mark the second axis properly, but what is most interesting is that, aside from the two $100MM+ losses distinctly highlighted (one of which obviously occurred around the time of the US debt ceiling fiasco, and the other in late August) is that the higher VaR goes, the lower the P&L trends! This has huge implications for market practice as it goes contrary to most prevailing conceptions, namely that the greater the risk, the greater the payoff on average, and, naturally, the greater the risk of a disastrous blow up. If confirmed by other banks this could serve as a policy guideline to limit excess risk-taking during times of high stress due to empirically proven adverse results on average.