3 resultados para Volatility

em Université de Lausanne, Switzerland


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Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

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Abstract Market prices of corporate bond spreads and of credit default swap (CDS) rates do not match each other. In this paper, we argue that the liquidity premium, the cheapest-to-deliver (CTD) option and actual market segmentation explain the pricing differences. Using the European transaction data from Reuters and Bloomberg, we estimate the liquidity premium that is time- varying and firm-specific. We show that when time-dependent liquidity premiums are considered, corporate bond spreads and CDS rates behave in a much closer way than previous studies have shown. We find that high equity volatility drives pricing differences that can be explained by the CTD option.

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In forensic investigation of firearm-related cases, determination of the residual amount of volatile compounds remaining inside a cartridge could be useful in estimating the time since its discharge. Published approaches are based on following the decrease of selected target compounds as a function of time by using solid phase micro-extraction (SPME). Naphthalene, as well as an unidentified decomposition product of nitrocellulose (referred to as "TEA2"), are usually employed for this purpose. However, reliability can be brought into question given their high volatility and the low reproducibility of their extracted quantities. In order to identify alternatives and therefore develop improved dating methods, an extensive study on the composition and variability of volatile residues in nine different types of cartridges was carried out. Analysis was performed using headspace sorptive extraction (HSSE), which is a more exhaustive technique compared to SPME. 166 compounds were identified (several of which for the first time), and it was observed that the final compositional characteristics of each residue were strongly dependent on its source. Variability of single identified compounds within and between different types of cartridge, as well as their evolution over time, was also studied. Many explosion products containing up to 4 aromatic rings were found to be globally present in high proportions amongst residues. 27 of them (excluding naphthalene) also presented detectable decreases during the first 24 h. Therefore, they could be used as complementary target analytes in future dating methods.