Successful efficient rare-event simulation typically involves using importance sampling tailored to a specific rare event. However, in applications one may be interested in simultaneous estimation of many probabilities or even an entire distribution. In this paper, we address this issue in a simple but fundamental setting.
We assemble bank-level and other data for Fed member banks to model determinants of bank failure. Fundamentals explain bank failure risk well. The first two Friedman-Schwartz crises are not associated with positive unexplained residual failure risk, or increased importance of bank illiquidity for forecasting failure. The third Friedman-Schwartz crisis is more ambiguous, but increased residual failure risk is small in the aggregate. The final crisis (early 1933) saw a large unexplained increase in bank failure risk.
This paper develops rare-event simulation methods for the estimation of portfolio credit risk—the risk of losses to a portfolio resulting from defaults of assets in the portfolio. Portfolio credit risk is measured through probabilities of large losses, which are typically due to defaults of many obligors (sources of credit risk) to which a portfolio is exposed.
The newsvendor model captures the trade-off faced by a decision maker that needs to place a firm bet prior to the occurrence of a random event. Previous research in operations management has mostly focused on deriving the decision that minimizes the expected mismatch costs. In contrast, we present two methods that estimate the unobservable cost parameters characterizing the mismatch cost function. We present a structural estimation framework that accounts for heterogeneity in the uncertainty faced by the newsvendor as well as in the cost parameters.
The economy of India is growing at a rate of 8 percent per year, and its exports of goods and services have more than doubled in the past three years. Considering these trends, economists, scholars, and political leaders across the globe are beginning to wonder whether India's growth can be sustained.
We are currently experiencing a major shock to the financial system, initiated by problems in the subprime mortgage market, which spread to securitization products and credit markets more generally. Banks are being asked to increase the amount of risk that they absorb (by moving off-balance sheet assets onto their balance sheets), but losses that the banks have suffered limit their capacity to absorb those risky assets.
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.
Using a large hand-collected data set from 2001 to 2006, we find that activist hedge funds in the United States propose strategic, operational, and financial remedies and attain success or partial success in two-thirds of the cases. Hedge funds seldom seek control and in most cases are nonconfrontational. The abnormal return around the announcement of activism is approximately 7%, with no reversal during the subsequent year. Target firms experience increases in payout, operating performance, and higher CEO turnover after activism.
We develop a structural demand model that captures the effect of out-of-stocks on customer choice. Our estimation method uses store-level data on sales and partial information on product availability. Our model allows for flexible substitution patterns which are based on utility maximization principles and can accommodate categorical and continuous product characteristics. The methodology can be applied to data from multiple markets and in categories with a relatively large number of alternatives, slow moving products and frequent out-of-stocks.