Area-power-delay trade-off in logic synthesis

This thesis introduces new concepts to perform area-power-delay trade-offs in a logic synthesis system. To achieve this, a new delay model is presented, which gives accurate delay estimations for arbitrary sets of Boolean expressions. This allows use of this delay model already during the very first steps of logic synthesis. Furthermore, new algorithms are presented for a number of different optimization tasks within logic synthesis. There are new algorithms to create prime irredundant Boo lean expressions, to perform technology mapping for use with standard cell generators, and to perform gate sizing. To prove the validity of the presented ideas, benchmark results are given throughout the thesis

Risk management during the reconstruction of the underground metro station Rotterdam Central Station

Practical Applications and Case Studie

Dynamic asset allocation and downside-risk aversion

This paper considers dynamic asset allocation in a mean versus downside-risk framework. We derive closed-form solutions for the optimal portfolio weights when returns are lognormally distributed. Moreover, we study the impact of skewed and fat-tailed return distributions. We find that the optimal fraction invested in stocks is V-shaped: at low and high levels of wealth the investor increases the stock weight. The optimal strategy also exhibits reverse time-effects: the investor allocates more to stocks as the horizon approaches. Furthermore, the investment strategy becomes more risky for negatively skewed and fat-tailed return distributions.optimal asset allocation;downside-risk

Investing in a real world with mean-reverting inflation.

People are concerned about maintaining purchasing power in times of rising inflation. We formulate investment objectives in terms of real wealth, assuming investors derive utility from the number of goods they can buy with their monetary wealth. We derive closed-form solutions for the portfolio choice problem of constant relative risk averse investors, under the assumption that inflation rates are mean-reverting. We consider alternative specifications for the inflation compensation offered by the available assets, in order to study the effect on portfolio choice and welfare. Moreover, we study the added value of inflation-indexed bonds for the investor in our real framework

From boom til bust: how loss aversion affects asset prices

In 1996 Alan Greenspan warned that stock prices were "unduly escalated" and reflected "irrational exuberance". In this paper we describe an economy that can support a prolonged surge of asset prices, accompanied by a sharp increase of volatility. We study an equilibrium model where some agents are risk averse while others have loss averse preferences over wealth, according to prospect theory. We derive closed-form solutions for the equilibrium prices. In good states of the world, the loss averse investors with wealth above the threshold are momentum traders, thereby pushing prices far above the level in the benchmark economy. In moderately bad states of the world, the loss averse investors are contrarian, and equilibrium prices are kept relatively high and stable. Finally in extremely bad states, the loss averse investors are forced to retreat from the stock market in order to avoid bankruptcy, resulting in a sharp price drop

Optimal portfolio choice under loss aversion

Prospect theory and loss aversion play a dominant role in behavioral finance. In this paper we derive closed-form solutions for optimal portfolio choice under loss aversion. When confronted with gains a loss averse investor behaves similar to a portfolio insurer. When confronted with losses, the investor aims at maximizing the probability that terminal wealth exceeds his aspiration level. Our analysis indicates that a representative agent model with loss aversion cannot resolve the equity premium puzzle. We also extend the martingale methodology to allow for more general utility functions and provide a simple approach to incorporate skewed and fat-tailed return distributions.loss aversion;behavioral finance;optimal asset allocation

Dynamic asset allocation and downside-risk aversion

This paper considers dynamic asset allocation in a mean versus downside-risk framework. We derive closed-form solutions for the optimal portfolio weights when returns are lognormally distributed. Moreover, we study the impact of skewed and fat-tailed return distributions. We find that the optimal fraction invested in stocks is V-shaped: at low and high levels of wealth the investor increases the stock weight. The optimal strategy also exhibits reverse time-effects: the investor allocates more to stocks as the horizon approaches. Furthermore, the investment strategy becomes more risky for negatively skewed and fat-tailed return distributions

Retirement saving with contribution payments and labor income as a benchmark for investments.

In this paper we study the retirement saving problem from the point of view of a plan sponsor, who makes contribution payments for the future retirement of an employee. The plan sponsor considers the employee's labor income as investment-benchmark in order to ensure the continuation of consumption habits after retirement. We demonstrate that the demand for risky assets increases at low wealth levels due to the contribution payments. We quantify the demand for hedging against changes in wage growth and find that it is relatively small. We show that downside-risk measures increase risk-taking at both low and high levels of wealth

Optimal portfolio choice under loss aversion

Prospect theory and loss aversion play a dominant role in behavioral finance. In this paper we derive closed-form solutions for optimal portfolio choice under loss aversion. When confronted with gains a loss averse investor behaves similar to a portfolio insurer. When confronted with losses, the investor aims at maximizing the probability that terminal wealth exceeds his aspiration level. Our analysis indicates that a representative agent model with loss aversion cannot resolve the equity premium puzzle. We also extend the martingale methodology to allow for more general utility functions and provide a simple approach to incorporate skewed and fat-tailed return distributions