Affine jump-diffusion (AJD) processes constitute a large and widely used class of continuous-time asset pricing models that balance tractability and flexibility in matching market data. The prices of e.g., bonds, options, and other assets in AJD models are given by extended pricing transforms that have an exponential-affine form; these transforms have been characterized in great generality by Duffie et al. [2000. Transform analysis and asset pricing for affine jump-diffusions. Econometrica 68, 1343–1376].
Portfolio credit derivatives are contracts that are tied to an underlying portfolio of defaultable reference assets and have payoffs that depend on the default times of these assets. The hedging of credit derivatives involves the calculation of the sensitivity of the contract value with respect to changes in the credit spreads of the underlying assets, or, more generally, with respect to parameters of the default-time distributions. We derive and analyze Monte Carlo estimators of these sensitivities.
Much of the puzzle of underissuance of national bank notes can be resolved for the period 1880–1900 (the period when detailed, bank-level data are available) by disaggregating, taking account of regulatory limits, and considering differences in banks' opportunity costs cross-sectionally and over time. Banks with poor lending opportunities issued more, within regulatory limits. Banks tended to issue more when bond yields (the backing for notes) were high relative to lending opportunities.
This paper, the second in CEASA's White Paper series on accounting issues, lays out principles under which fair value accounting satisfies the objective of reporting to shareholders. Its "principles-based" approach embraces broad economic concepts but is also pragmatic and specific enough to guide practice.
A German broker's clients place similar speculative trades and therefore tend to be on the same side of the market in a given stock during a given day, week, month, and quarter. Aggregate liquidity effects, short sale constraints, the systematic execution of limit orders (coordinated through price movements) or the correlated trading of other investors who pick off retail limit orders, do not fully explain why retail investors trade similarly. Correlated market orders lead returns, presumably due to persistent speculative price pressure.
