Long-term equity anticipation securities and stock market volatility dynamics

Recent empirical findings suggest that the long-run dependence in U.S. stock market volatility is best described by a slowly mean-reverting fractionally integrated process. The present study complements this existing time-series-based evidence by comparing the risk-neutralized option pricing distributions from various ARCH-type formulations. Utilizing a panel data set consisting of newly created exchange traded long-term equity anticipation securities, or leaps, on the Standard and Poor's 500 stock market index with maturity times ranging up to three years, we find that the degree of mean reversion in the volatility process implicit in these prices is best described by a Fractionally Integrated EGARCH (FIEGARCH) model. © 1999 Elsevier Science S.A. All rights reserved.

Simulation of mackerel (Scomber scombrus) recruitment with an individual-based model and comparison with field data

An individual-based model (IBM) for the simulation of year-to-year survival during the early life-history stages of the north-east Atlantic stock of mackerel (Scomber scombrus) was developed within the EU funded Shelf-Edge Advection, Mortality and Recruitment (SEAMAR) programme. The IBM included transport, growth and survival and was used to track the passive movement of mackerel eggs, larvae and post-larvae and determine their distribution and abundance after approximately 2 months of drift. One of the main outputs from the IBM, namely distributions and numbers of surviving post-larvae, are compared with field data as recruit (age-0/age-1 juveniles) distribution and abundance for the years 1998, 1999 and 2000. The juvenile distributions show more inter-annual and spatial variability than the modelled distributions of survivors; this may be due to the restriction of using the same initial egg distribution for all 3 yr of simulation. The IBM simulations indicate two main recruitment areas for the north-east Atlantic stock of mackerel, these being Porcupine Bank and the south-eastern Bay of Biscay. These areas correspond to areas of high juvenile catches, although the juveniles generally have a more widespread distribution than the model simulations. The best agreement between modelled data and field data for distribution (juveniles and model survivors) is for the year 1998. The juvenile catches in different representative nursery areas are totalled to give a field abundance index (FAI). This index is compared with a model survivor index (MSI) which is calculated from the total of survivors for the whole spawning season. The MSI compares favourably with the FAI for 1998 and 1999 but not for 2000; in this year, juvenile catches dropped sharply compared with the previous years but there was no equivalent drop in modelled survivors.

Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model

Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Stock-recruitment relations controlled by feeding interactions alone

Stock-recruitment (S-R) relationships are the centrepiece of fisheries management aimed at achieving maximum sustainable yield (MSY). Here we consider the possibility that the density dependence evident in S-R relations is controlled by feeding interactions alone. We simulate a food-web model with dynamic representations of intra- and interspecific size structure and a linear relation between food intake and hatchling production of adults. Population sizes of individual stocks are modified by imposing additional mortality. The predominant functional forms and the steepness of resulting S-R relationships agree well with observations. We conclude that recruitment is plausibly regulated by feeding interactions alone.

Avoiding Negligence and Profusion: The failure of the Joint-Stock form in the Anglo-Indian Tea Trade, 1840-1870

In the 19th century, firms operating in the Anglo-Indian tea trade were organised using a variety ownership forms including the partnership, joint-stock and a combination of the two known as the Managing agency. Faced with both an increasing need for fixed capital and high agency costs caused by the distance between owners and managers, the firms adapted and increasingly adopted the hybrid managing agency model to overcome these problems. Using new data from Calcutta and Bengal Commercial Registers and detailed case studies of the Assam Company and Gillanders, Arbuthnot and Co, this paper demonstrates that British entrepreneurs did not see the choice of ownership as a dichotomy or firm boundaries as fixed, but instead innovatively drew on the strengths of different forms of ownership to compete and grow successfully.

Identifying the relative importance of stock characteristics

There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Overall, this study provides strong evidence to support that the momentum characteristic can best explain stock returns in the UK market. The econometric approach employed in this study is a novel way to assess relevant investment risk in international financial markets outside U.S. Moreover, multinational institutions and investors can use this approach to identify regional factors in order to diversify their portfolios.

The Adaptiveness in Stock Markets: Testing the Stylized Facts in the DAX 30

By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.

Future Air Quality Related Health Effects in Europe and the Nordic Region—Sensitivity to Changes in Climate, Anthropogenic Emissions, Demography and Building Stock

Future changes in population exposures to ambient air pollution are inherently linked with long-term trends in outdoor air quality, but also with changes in the building stock. Moreover, the burden of disease is further driven by the ageing of the European populations. This study aims to assess the impact of changes in climate, emissions, building stocks and population on air pollution related human health impacts across Europe in the future. Therefore an integrated assessment model combining atmospheric models and health impacts has been setup for projections of the future developments in air pollution related premature mortality. The focus is here on the regional scale impacts of exposure to surface ozone (O3), Secondary Inorganic Aerosols (SIA) and primary particulate matter (PPM).

Essays on Applications of the Factor Model

Thesis (Ph.D.)--University of Washington, 2013

Monetary policy, exchange rates and stock prices in the Middle East region

A structural vector autoregressive model is employed to investigate the impact of monetary policy and real exchange rate shocks on the stock market performance of Kuwait, Oman, Saudi Arabia, Egypt and Jordan. In order to identify the structural shocks both short run and long run restrictions are applied. Unlike previous literature the contemporaneous interdependence between the financial variables are left unrestricted to give a more accurate depiction of the relationships. The heterogeneity of the results reflect the different monetary policy frameworks and stock market characteristics of these countries. Mainly, monetary policy and the real exchange rate shocks have a significant short run impact on the stock prices of the countries that apply a relatively more independent monetary policy and flexible exchange rates.

Three essays on economics of predictability of stock returns

A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics

Modeling and forecasting value-at-risk for the Portuguese stock market

The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.

Modelo de evaluación integrada del stock norte-centro de la anchoveta peruana Engraulis ringens Jenyns

Se presenta un nuevo modelo integrado de evaluación para el stock norte-centro de la anchoveta peruana que permite reconstruir y hacer un seguimiento de la estructura de longitudes del stock desde un modelo basado en edades. El modelo fue calibrado usando estimados acústicos de biomasa y estructuras de tallas provenientes de cruceros científicos y de desembarques de la pesquería. Para la calibración se utilizó un algoritmo evolutivo con diferentes funciones de aptitud para cada variable calibrada (biomasas y capturas). Se presentan los estimados mensuales de biomasa total, biomasa desovante, reclutamiento y mortalidad por pesca obtenidos por el modelo de evaluación integrada para el periodo 1964-2008. Se encontraron tres periodos cualitativamente distintos en la dinámica de anchoveta, entre 1961-1971, 1971-1991 y 1991 al presente, que se distinguen tanto por las biomasas medias anuales como por los niveles de reclutamiento observado.

Evaluación del stock norte – centro de la anchoveta peruana (Engraulis ringens Jenyns) por un modelo estadístico estructurado por edades

Se empleó un modelo poblacional estructurado por edades para estimar la abundancia, biomasa, biomasa desovante y el reclutamiento medio del stock norte – centro de la anchoveta peruana entre los años biológicos (octubre a setiembre) 1962-63 y 2007-08. El modelo, basado en un enfoque hacia adelante, fue optimizado minimizando las diferencias de los estimados del modelo y observaciones independientes de biomasa, desembarque y estructuras por edades de los desembarques. Los resultados muestran que han existido tres regímenes de productividad de dicho stock: el primero, entre 1962-63 y 1970-71, con la abundancia, biomasa, biomasa desovante y reclutamiento medio más altos; el segundo, entre 1971- 72 y 1990-91 con los niveles poblacionales más bajos; y el tercero, entre 1991-92 y 2007-08, con niveles intermedios. Parece claro que luego del colapso de las décadas de 1970 y 1980 el stock se ha recuperado de manera significativa aunque sin alcanzar los niveles de la década de 1960. Desde el año 2001-02 la biomasa desovante se ha mantenido por encima de cinco millones de toneladas, y la mortalidad por pesca ha mostrado una tendencia decreciente. Se demostró que el presente modelo estuvo en capacidad de captar la dinámica poblacional del stock norte – centro de la anchoveta validando su utilidad en las evaluaciones y monitoreo de la población de anchoveta.