868 resultados para Asset allocation


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In finance risk capital allocation raises important questions both from theoretical and practical points of view. How to share risk of a portfolio among its subportfolios? How to reserve capital in order to hedge existing risk and how to assign this to different business units? We use an axiomatic approach to examine risk capital allocation, that is we call for fundamental properties of the methods. Our starting point is Csóka and Pintér (2011) who show by generalizing Young (1985)'s axiomatization of the Shapley value that the requirements of Core Compatibility, Equal Treatment Property and Strong Monotonicity are irreconcilable given that risk is quantified by a coherent measure of risk. In this paper we look at these requirements using analytic and simulations tools. We examine allocation methods used in practice and also ones which are theoretically interesting. Our main result is that the problem raised by Csóka and Pintér (2011) is indeed relevant in practical applications, that is it is not only a theoretical problem. We also believe that through the characterizations of the examined methods our paper can serve as a useful guide for practitioners.

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This dissertation discussed resource allocation mechanisms in several network topologies including infrastructure wireless network, non-infrastructure wireless network and wire-cum-wireless network. Different networks may have different resource constrains. Based on actual technologies and implementation models, utility function, game theory and a modern control algorithm have been introduced to balance power, bandwidth and customers' satisfaction in the system. ^ In infrastructure wireless networks, utility function was used in the Third Generation (3G) cellular network and the network was trying to maximize the total utility. In this dissertation, revenue maximization was set as an objective. Compared with the previous work on utility maximization, it is more practical to implement revenue maximization by the cellular network operators. The pricing strategies were studied and the algorithms were given to find the optimal price combination of power and rate to maximize the profit without degrading the Quality of Service (QoS) performance. ^ In non-infrastructure wireless networks, power capacity is limited by the small size of the nodes. In such a network, nodes need to transmit traffic not only for themselves but also for their neighbors, so power management become the most important issue for the network overall performance. Our innovative routing algorithm based on utility function, sets up a flexible framework for different users with different concerns in the same network. This algorithm allows users to make trade offs between multiple resource parameters. Its flexibility makes it a suitable solution for the large scale non-infrastructure network. This dissertation also covers non-cooperation problems. Through combining game theory and utility function, equilibrium points could be found among rational users which can enhance the cooperation in the network. ^ Finally, a wire-cum-wireless network architecture was introduced. This network architecture can support multiple services over multiple networks with smart resource allocation methods. Although a SONET-to-WiMAX case was used for the analysis, the mathematic procedure and resource allocation scheme could be universal solutions for all infrastructure, non-infrastructure and combined networks. ^

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Liquidity is an important attribute of an asset that investors would like to take into consideration when making investment decisions. However, the previous empirical evidence whether liquidity is a determinant of stock return is not unanimous. This dissertation provides a very comprehensive study about the role of liquidity in asset pricing using the Fama-French (1993) three-factor and Kraus and Litzenberger (1976) three-moment CAPM as models for risk adjustment. The relationship between liquidity and well-known determinants of stock returns such as size and book-to-market are also investigated. This study examines the liquidity and asset pricing issues for both intertemporal as well as cross-sectional data. ^ The results indicate an existence of a liquidity premium, i.e., less liquid stocks would demand higher rate of return than more liquid stocks. More specifically, a drop of 1 percent in liquidity is associated with a higher rate of return of about 2 to 3 basis points per month. Further investigation reveals that neither the Fama-French three-factor model nor the three-moment CAPM captures the liquidity premium. Finally, the results show that well-known determinants of stock return such as size and book-to-market do not serve as proxy for liquidity. ^ Overall, this dissertation shows that a liquidity premium exists in the stock market and that liquidity is a distinct effect, and is not influenced by the presence of non-market factors, market factors and other stock characteristics.^

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With the rapid globalization and integration of world capital markets, more and more stocks are listed in multiple markets. With multi-listed stocks, the traditional measurement of systematic risk, the domestic beta, is not appropriate since it only contain information from one market. ^ Prakash et al. (1993) developed a technique, the global beta, to capture information from multiple markets wherein the stocks are listed. In this study, the global betas are obtained as well as domestic betas for 704 multi-listed stocks from 59 world equity markets. Welch tests show that domestic betas are not equal across markets, therefore, global beta is more appropriate in a global investment setting. ^ The traditional Capital Asset Pricing Models (CAPM) is also tested with regards to both domestic beta and global beta. The results generally support the positive relationship between stocks returns and global beta while tend to reject this relationship between stocks returns and domestic beta. Further tests of International CAPM with domestic beta and global beta strengthen the conclusion.^

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In this dissertation, I investigate three related topics on asset pricing: the consumption-based asset pricing under long-run risks and fat tails, the pricing of VIX (CBOE Volatility Index) options and the market price of risk embedded in stock returns and stock options. These three topics are fully explored in Chapter II through IV. Chapter V summarizes the main conclusions. In Chapter II, I explore the effects of fat tails on the equilibrium implications of the long run risks model of asset pricing by introducing innovations with dampened power law to consumption and dividends growth processes. I estimate the structural parameters of the proposed model by maximum likelihood. I find that the stochastic volatility model with fat tails can, without resorting to high risk aversion, generate implied risk premium, expected risk free rate and their volatilities comparable to the magnitudes observed in data. In Chapter III, I examine the pricing performance of VIX option models. The contention that simpler-is-better is supported by the empirical evidence using actual VIX option market data. I find that no model has small pricing errors over the entire range of strike prices and times to expiration. In general, Whaley’s Black-like option model produces the best overall results, supporting the simpler-is-better contention. However, the Whaley model does under/overprice out-of-the-money call/put VIX options, which is contrary to the behavior of stock index option pricing models. In Chapter IV, I explore risk pricing through a model of time-changed Lvy processes based on the joint evidence from individual stock options and underlying stocks. I specify a pricing kernel that prices idiosyncratic and systematic risks. This approach to examining risk premia on stocks deviates from existing studies. The empirical results show that the market pays positive premia for idiosyncratic and market jump-diffusion risk, and idiosyncratic volatility risk. However, there is no consensus on the premium for market volatility risk. It can be positive or negative. The positive premium on idiosyncratic risk runs contrary to the implications of traditional capital asset pricing theory.

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An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.

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Growth, morphology and biomass allocation in response to water depth was studied in white water lily,Nymphaea odorata Aiton. Plants were grown for 13 months in 30, 60 and 90 cm water in outdoor mesocosms in southern Florida. Water lily plant growth was distinctly seasonal with plants at all water levels producing more and larger leaves and more flowers in the warmer months. Plants in 30 cm water produced more but smaller and shorter-lived leaves than plants at 60 cm and 90 cm water levels. Although plants did not differ significantly in total biomass at harvest, plants in deeper water had significantly greater biomass allocated to leaves and roots, while plants in 30 cm water had significantly greater biomass allocated to rhizomes. Although lamina area and petiole length increased significantly with water level, lamina specific weight did not differ among water levels. Petiole specific weight increased significantly with increasing water level, implying a greater cost to tethering the larger laminae in deeper water. Lamina length and width scaled similarly at different water levels and modeled lamina area (LA) accurately (LAmodeled = 0.98LAmeasured + 3.96, R2 = 0.99). Lamina area was highly correlated with lamina weight (LW = 8.43LA − 66.78, R2 = 0.93), so simple linear measurements can predict water lily lamina area and lamina weight. These relationships were used to calculate monthly lamina surface area in the mesocosms. Plants in 30 cm water had lower total photosynthetic surface area than plants in 60 cm and 90 cm water levels throughout, and in the summer plants in 90 cm water showed a great increase in photosynthetic surface area as compared to plants in shallower water. These results support setting Everglades restoration water depth targets for sloughs at depths ≥45 cm and suggest that in the summer optimal growth for white water lilies occurs at depths ≥75 cm.

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Lodging asset management has emerged as one of the most important areas of strategic hotel management. Increasingly, lodging companies are soliciting the services of asset management firms or developing internal asset management competencies. This article synthesizes and discusses the essential components of dynamic lodging asset management. The article provides a detail background on asset management and its importance and explains the role of lodging asset managers and their working relationships with ownership and operators. The article also discusses the competencies and skills of asset managers.

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Survey research of the commercial food service industry with regard to tips and tip allocation revealed that 50 percent of restaurateurs require that employees report a minimum amount or percentage of sales and over 50 percent which allocate tips report them as employee income. The authors discuss these results and point out other problems.

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My dissertation consists of three essays. The central theme of these essays is the psychological factors and biases that affect the portfolio allocation decision. The first essay entitled, “Are women more risk-averse than men?” examines the gender difference in risk aversion as revealed by actual investment choices. Using a sample that controls for biases in the level of education and finance knowledge, there is evidence that when individuals have the same level of education, irrespective of their knowledge of finance, women are no more risk-averse than their male counterparts. However, the gender-risk aversion relation is also a function of age, income, wealth, marital status, race/ethnicity and the number of children in the household. The second essay entitled, “Can diversification be learned ?” investigates if investors who have superior investment knowledge are more likely to actively seek diversification benefits and are less prone to allocation biases. Results of cross-sectional analyses suggest that knowledge of finance increases the likelihood that an investor will efficiently allocate his direct investments across the major asset classes; invest in foreign assets; and hold a diversified equity portfolio. However, there is no evidence that investors who are more financially sophisticated make superior allocation decisions in their retirement savings. The final essay entitled, “The demographics of non-participation ”, examines the factors that affect the decision not to hold stocks. The results of probit regression models indicate that when individuals are highly educated, the decision to not participate in the stock market is less related to demographic factors. In particular, when individuals have attained at least a college degree and have advanced knowledge of finance, they are significantly more likely to invest in equities either directly or indirectly through mutual funds or their retirement savings. There is also evidence that the decision not to hold stocks is motivated by short-term market expectations and the most recent investment experience. The findings of these essays should increase the body of research that seeks to reconcile what investors actually do (positive theory) with what traditional theories of finance predict that investors should do (normative theory).

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The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. ^ However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.^

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A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. ^ In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company's shares. Hence, we jointly examine both the factors, namely, governance and liquidity - in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll's (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.^

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Vegetation patterns of mangroves in the Florida Coastal Everglades (FCE) result from the interaction of environmental gradients and natural disturbances (i.e., hurricanes), creating an array of distinct riverine and scrub mangroves across the landscape. We investigated how landscape patterns of biomass and total net primary productivity (NPPT), including allocation in above- and below-ground mangrove components, vary inter-annually (2001–2004) across gradients in soil properties and hydroperiod in two distinct FCE basins: Shark River Estuary and Taylor River Slough. We propose that the allocation of belowground biomass and productivity (NPPB) relative to aboveground allocation is greater in regions with P limitation and permanent flooding. Porewater sulfide was significantly higher in Taylor River (1.2 ± 0.3 mM) compared to Shark River (0.1 ± 0.03 mM) indicating the lack of a tidal signature and more permanent flooding in this basin. There was a decrease in soil P density and corresponding increase in soil N:P from the mouth (28) to upstream locations (46–105) in Shark River that was consistent with previous results in this region. Taylor River sites showed the highest P limitation (soil N:P > 60). Average NPPT was double in higher P environments (17.0 ± 1.1 Mg ha−1 yr−1) compared to lower P regions (8.3 ± 0.3 Mg ha−1 yr−1). Root biomass to aboveground wood biomass (BGB:AWB) ratio was 17 times higher in P-limited environments demonstrating the allocation strategies of mangroves under resource limitation. Riverine mangroves allocated most of the NPPT to aboveground (69%) while scrub mangroves showed the highest allocation to belowground (58%). The total production to biomass (P:B) ratios were lower in Shark River sites (0.11 yr−1); whereas in Taylor River sites P:B ratios were higher and more variable (0.13–0.24 yr−1). Our results suggest that the interaction of lower P availability in Taylor River relative to Shark River basin, along with higher sulfide and permanent flooding account for higher allocation of belowground biomass and production, at expenses of aboveground growth and wood biomass. These distinct patterns of carbon partitioning between riverine and scrub mangroves in response to environmental stress support our hypothesis that belowground allocation is a significant contribution to soil carbon storage in forested wetlands across FCE, particularly in P-limited scrub mangroves. Elucidating these biomass strategies will improve analysis of carbon budgets (storage and production) in neotropical mangroves and understanding what conditions lead to net carbon sinks in the tropical coastal zone.

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My dissertation consists of three essays. The central theme of these essays is the psychological factors and biases that affect the portfolio allocation decision. The first essay entitled, “Are women more risk-averse than men?” examines the gender difference in risk aversion as revealed by actual investment choices. Using a sample that controls for biases in the level of education and finance knowledge, there is evidence that when individuals have the same level of education, irrespective of their knowledge of finance, women are no more risk-averse than their male counterparts. However, the gender-risk aversion relation is also a function of age, income, wealth, marital status, race/ethnicity and the number of children in the household. The second essay entitled, “Can diversification be learned?” investigates if investors who have superior investment knowledge are more likely to actively seek diversification benefits and are less prone to allocation biases. Results of cross-sectional analyses suggest that knowledge of finance increases the likelihood that an investor will efficiently allocate his direct investments across the major asset classes; invest in foreign assets; and hold a diversified equity portfolio. However, there is no evidence that investors who are more financially sophisticated make superior allocation decisions in their retirement savings. The final essay entitled, “The demographics of non-participation”, examines the factors that affect the decision not to hold stocks. The results of probit regression models indicate that when individuals are highly educated, the decision to not participate in the stock market is less related to demographic factors. In particular, when individuals have attained at least a college degree and have advanced knowledge of finance, they are significantly more likely to invest in equities either directly or indirectly through mutual funds or their retirement savings. There is also evidence that the decision not to hold stocks is motivated by short-term market expectations and the most recent investment experience. The findings of these essays should increase the body of research that seeks to reconcile what investors actually do (positive theory) with what traditional theories of finance predict that investors should do (normative theory).