The difficulties of staging Shakespeare in the high school

Thesis (M.A.)--Boston Universit

Real Estate Portfolio Management : Optimization under Risk Aversion

This paper deals with real estate portfolio optimization when investors are risk averse. In this framework, we determine several types of optimal times to sell a diversified real estate and analyze their properties. The optimization problem corresponds to the maximization of a concave utility function defined on the terminal value of the portfolio. We extend previous results (Baroni et al., 2007, and Barthélémy and Prigent, 2009), established for the quasi linear utility case, where investors are risk neutral. We consider four cases. In the first one, the investor knows the probability distribution of the real estate index. In the second one, the investor is perfectly informed about the real estate market dynamics. In the third case, the investor uses an intertemporal optimization approach which looks like an American option problem. Finally, the buy-and-hold strategy is considered. For these four cases we analyze numerically the solutions that we compare with those of the quasi linear case. We show that the introduction of risk aversion allows to better take account of the real estate market volatility. We also introduce the notion of compensating variation to better compare all these solutions.Real estate portfolio, Optimal holding period, Risk aversion, Real estate market volatility

Optimal Time to Sell in Real Estate Portfolio Management

This paper examines the properties of optimal times to sell a diversified real estate portfolio. The portfolio value is supposed to be the sum of the discounted free cash flows and the discounted terminal value (the discounted selling price). According to Baroni et al. (2007b), we assume that the terminal value corresponds to the real estate index. The optimization problem corresponds to the maximization of a quasi-linear utility function. We consider three cases. The first one assumes that the investor knows the probability distribution of the real estate index. However, at the initial time, he has to choose one deterministic optimal time to sell. The second one considers an investor who is perfectly informed about the market dynamics. Whatever the random event that generates the path, he knows the entire path from the beginning. Then, given the realization of the random variable, the path is deterministic for this investor. Therefore, at the initial time, he can determine the optimal time to sell for each path of the index. Finally, the last case is devoted to the analysis of the intertemporal optimization, based on the American option approach. We compute the optimal solution for each of these three cases and compare their properties. The comparison is also made with the buy-and-hold strategy.Real estate portfolio, Optimal holding period, American option.

Weak Convergence of Hedging Strategies of Contingent Claims

This paper presents results on the convergence for hedging strategies in the setting of incomplete financial markets. We examine the convergence of the so-called locally risk-minimizing strategy. It is proved that such a choice for the trading strategy, when perfect hedging of contingent claims is infeasible, is robust under weak convergence. Several fundamental examples, such as trinomial trees and stochastic volatility models, extracted from the financial modeling literature illustrate this property for both deterministic and random time intervals shrinking to zero.Weak convergence; Incomplete financial markets; Locally risk-minimizing strategy; Hedging strategy; Minimal martingale measure

Global-scale analysis of satellite-derived time series of naturally inundated areas as a basis for floodplain modeling

Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993–2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges

Experimental investigation of laminar turbulent intermittency in pipe flow

In shear flows turbulence first occurs in the form of localized structures (puffs/spots) surrounded by laminar fluid. We here investigate such spatially intermittent flows in a pipe experiment showing that turbulent puffs have a well defined interaction distance, which sets the minimum spacing of puffs as well as the maximum observable turbulent fraction. Two methodologies are employed here. Starting from a laminar flow puffs can be created by locally injecting a jet of fluid through the pipe wall. When the perturbation is applied periodically at low frequencies, as expected, a regular sequence of puffs is observed where the puff spacing is given by the ratio of the mean flow speed to the perturbation frequency. On the other hand, at large frequencies puffs are found to interact and annihilate each other. Varying the perturbation frequency an interaction distance can be determined. In the second set of experiments, the Reynolds number is reduced suddenly from fully developed turbulence to the intermittent regime.The resulting flow reorganizes itself to a sequence of constant size puffs which, unlike in Couette and Taylor Couette flow are randomly spaced. The minimum distance between the turbulent patches is identical to the puff interaction length. The puff interaction length is found to be in excellent agreement with the wavelength of regular stripe and spiral patterns in plane Couette and Taylor-Couette flow. We propose that the same interaction mechanism is present in these flows

Hedging global environment risks: An option based portfolio insurance

This paper introduces a financial hedging model for global environment risks. Our approach is based on portfolio insurance under hedging constraints. Investors are assumed to maximize their expected utilities defined on financial and environmental asset values. The optimal investment is determined for quite general utility functions and hedging constraints. In particular, our results suggest how to introduce derivative assets written on the environmental asset.utility maximization, hedging, environmental asset, martingale theory

A Risk Management Approach for Portfolio Insurance Strategies

Controlling and managing potential losses is one of the main objectives of the Risk Management. Following Ben Ameur and Prigent (2007) and Chen et al. (2008), and extending the first results by Hamidi et al. (2009) when adopting a risk management approach for defining insurance portfolio strategies, we analyze and illustrate a specific dynamic portfolio insurance strategy depending on the Value-at-Risk level of the covered portfolio on the French stock market. This dynamic approach is derived from the traditional and popular portfolio insurance strategy (Cf. Black and Jones, 1987 ; Black and Perold, 1992) : the so-called "Constant Proportion Portfolio Insurance" (CPPI). However, financial results produced by this strategy crucially depend upon the leverage - called the multiple - likely guaranteeing a predetermined floor value whatever the plausible market evolutions. In other words, the unconditional multiple is defined once and for all in the traditional setting. The aim of this article is to further examine an alternative to the standard CPPI method, based on the determination of a conditional multiple. In this time-varying framework, the multiple is conditionally determined in order to remain the risk exposure constant, even if it also depends upon market conditions. Furthermore, we propose to define the multiple as a function of an extended Dynamic AutoRegressive Quantile model of the Value-at-Risk (DARQ-VaR). Using a French daily stock database (CAC 40) and individual stocks in the period 1998-2008), we present the main performance and risk results of the proposed Dynamic Proportion Portfolio Insurance strategy, first on real market data and secondly on artificial bootstrapped and surrogate data. Our main conclusion strengthens the previous ones : the conditional Dynamic Strategy with Constant-risk exposure dominates most of the time the traditional Constant-asset exposure unconditional strategies.CPPI, Portfolio insurance, VaR, CAViaR, quantile regression, dynamic quantile model.