Error Calculus and Path Sensitivity in Financial Models

In the framework of risk management, for the study of the sensitivity of pricing and hedging in stochastic financial models to changes of parameters and to perturbations of the stock prices, we propose an error calculus that is an extension of the Malliavin calculus based on Dirichlet forms. Although useful also in physics, this error calculus is well adapted to stochastic analysis and seems to be the best practicable in finance. This tool is explained here intuitively and with some simple examples.     

Strategic formulation of high technology projects using the support graph

The life cycle of technology projects comprises 10 phases: identification, conception, formulation, feasibility, evaluation, decision, realization, control, termination and post-evaluation. One of the most important phases is formulation, foar which an interdisciplinary tool, the 'support graph', was conceived and used for more than 200 high technology projects in such areas as chemicals, biotechnology, electronics, software (artificial intelligence), telecommuniocation, energy and aerospace. This paper descrones how to build an effective support graph. The general objective, the partial objectives, the tasks and the means are the principal components. The management of change during the implementation of high technology projects is largely facilitated by the use of the support graph. It also creates a common language between the technologists and the managers and gives information on when to alter the goals of a high technology project. Support graphs for an expert system and for a telecommunication project are used to illustrate the proposed approach.     

Optimal contract design: For whom?

In designing a derivative contract, an exchange carefully considers how its attributes affect the expected profits of its members. On November 3, 1997, the Chicago Mercantile Exchange doubled its tick size of its S&P 500 futures contract and halved the denomination, providing a rare opportunity to examine empirically the search for an optimal contract design. This article measures changes in the trading environment that occurred in the days surrounding the contract redesign. We find a discernible change in the incidence of price clustering, an increase in the bid/ask spread, a reduction in trading volume, and no meaningful change in dollar trade size. These results suggest that the contract redesign did not increase accessibility but did increase market maker revenue. Despite the increase, however, the bid/ask spread of the S&P 500 futures contract remains low relative to the costs of market making and the spreads in markets for competing instruments. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:719–750, 2003     

Dynamic portfolio optimization with liquidity cost and market impact: a simulation-and-regression approach

We present a simulation-and-regression method for solving dynamic portfolio optimization problems in the presence of general transaction costs, liquidity costs and market impact. This method extends the classical least squares Monte Carlo algorithm to incorporate switching costs, corresponding to transaction costs and transient liquidity costs, as well as multiple endogenous state variables, namely the portfolio value and the asset prices subject to permanent market impact. To handle endogenous state variables, we adapt a control randomization approach to portfolio optimization problems and further improve the numerical accuracy of this technique for the case of discrete controls. We validate our modified numerical method by solving a realistic cash-and-stock portfolio with a power-law liquidity model. We identify the certainty equivalent losses associated with ignoring liquidity effects, and illustrate how our dynamic optimization method protects the investor's capital under illiquid market conditions. Lastly, we analyze, under different liquidity conditions, the sensitivities of certainty equivalent returns and optimal allocations with respect to trading volume, stock price volatility, initial investment amount, risk aversion level and investment horizon.     

Manufacturers and retailers in the global economy

We develop a model with multi‐product retailers acting as intermediaries between manufacturers and consumers. We show that the rise in retailer product assortment, the rise of up‐front payments in many retail markets and the observed shift in employment from manufacturing to retailing may be the consequence of the global integration of product markets. We also identify a novel benefit from market integration consisting of efficiency gains in the vertical distribution chain.     

Some comments on the inverse problem for thinned renewal processes

Abstract

The following problem is considered: for which p ∈ (0, 1) and completely monotone functions g is g/[p+(1-p)g] completely monotone? This problem is shown to be equivalent to the inverse problem for thinned renewal processes. Some applications to gamma renewal processes are also discussed.     

What explains the lagged-investment effect?

The best predictor of current investment at the firm level is lagged investment. This lagged-investment effect is empirically more important than the cash-flow and Q effects combined. We show that the specification of investment adjustment costs proposed by Christiano et al. (2005) predicts the presence of a lagged-investment effect and that a generalized version of their model is consistent with the behavior of firm-level data from Compustat.     

Cementing the case for collusion under the National Recovery Administration

Macroeconomists have long debated the aggregate effects of anti-competitive provisions under the “Codes of Fair Conduct” promulgated by the National Industrial Recovery Act (NIRA). Despite the emphasis on these provisions, there is only limited evidence documenting any actual effects at the micro-level. We use a combination of narrative evidence and a novel plant-level dataset from 1929, 1931, 1933, and 1935 to study the effects of the NIRA in the cement industry. We develop a test for collusion specific to this particular industry. We find strong evidence that before the NIRA, the costs of a plant's nearest neighbor had a positive effect on a plant's own price, suggesting competition. After the NIRA, this effect is completely eliminated, with no correlation between a plant's own price and its neighbor's cost.