Using a market segmentation argument, this paper uses the interest rate derivative's arbitrage-free methodology to value both demand deposit liabilities and credit card loan balances in markets where deposits/loan rates may be determined under imperfect competition. In this context, these financial instruments are shown to be equivalent to a particular interest rate swap, where the principal depends on the past history of market rates. Solutions are obtained which are independent of any particular model for the evolution of the term structure of interest rates.

We employ a natural experiment from the 1980s, predating the ubiquitous clamor for independence influenced corporate governance structures, to examine which governance mechanisms are associated with firm survival and failure. We find that thrifts were more likely to survive the thrift crisis when their CEO also chaired the firm’s board of directors. On average, chair-holding CEOs undertook less aggressive lending policies than their counterparts who did not chair their boards. Consequently, taxpayer interests were protected by thrifts that bestowed both leadership posts to one person. This is an important policy issue, because taxpayers become the residual claimants for depository institutions that fail as a result of managers adopting risky strategies to exploit underpriced deposit insurance. Our findings corroborate recent evidence that manager-dominated firms resist shareholder pressure to adopt riskier investment strategies to exploit underpriced deposit insurance.

We propose a new measure of price discovery, New Leadership Share (NLS), that attributes permanent information flow to individual markets using a uniquely identified structural moving average model. NLS quantifies each market’s contribution to permanent price innovations as a proportion of total informational leadership and offers key technical advantages, including uniqueness and adherence to standard statistical asymptotics. We derive closed-form solutions and analytical standard errors for bivariate markets and provide a framework that extends naturally to multiple markets without the variable ordering problem. Simulation results show that NLS consistently outperforms three widely used benchmarks. Empirical analysis of 2023 data finds that exchange-traded funds and front-month futures markets share equal leadership relative to the S&P 500 spot index.