Trading operations are a necessary evil for the nation's biggest banks, including Bank of America (NYSE:BAC). While the activity generates high-margin income, profits and losses from trading are notoriously volatile.
You can see this by looking at the sequential change in Bank of America's trading profits -- that is, the change from quarter to quarter, as opposed to year over year. Since the beginning of 2009, the bank's quarterly trading profits have fluctuated sequentially by a median of 25.7%. Conversely, the median change in noninterest income from investment banking, asset management and brokerage, and credit and debit cards are all less than 4%, and the latter two are below 1%.
You can also see this by looking at the raw numbers. What you find is that Bank of America's trading profits fluctuate widely, though in an identifiable pattern. They're highest in the first quarter, lowest in the fourth quarter, and at various in-between stages in the second and third quarters. While income from credit/debit cards and asset management also moves, the change is barely perceptible compared to the jagged peaks and valleys that characterize Bank of America's trading income.
Trading also exposes a bank to substantial losses. JPMorgan Chase was reminded of this in 2012 when a purportedly rogue trader based in London entered into trades that cost the nation's biggest bank by assets more than $6 billion to unwind. A similar series of events led to the failure of the 233-year-old Barings Bank in 1995. The events that led to its downfall are immortalized in the book and movie Rogue Trader, written by the trader himself, Nick Leeson.
This risk, coupled with the volatility inherent in trading operations, is one of the reasons that Bank of America's shares are valued at a substantial (27%) discount to book value, while shares of simpler peers such as Wells Fargo and U.S. Bancorp are priced at healthy premiums to book value. The impact from trading, which the latter two banks largely avoid, filters through the capital asset pricing model (CAPM), which is used to price securities.
The CAPM model holds that a security's price depends on three variables:
- the risk-free rate of return on government securities,
- the expected return of the broader market, and
- the volatility of a specific stock (measured by beta), which, in turn, is affected by earnings volatility.
The higher these numbers are with respect to a particular stock, the higher the stock's return must be to compensate investors for the added risk or opportunity cost of holding it. This is why large trading operations weigh on the valuation of bank stocks, such as Bank of America's, as the volatility in its trading operations translates into earnings volatility, which is then reflected in a higher beta (i.e., share price volatility).