Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models

This paper introduces a new specification for the heterogeneous autoregressive (HAR) model for the realized volatility of S&P 500 index returns. In this modelling framework, the coefficients of the HAR are allowed to be time-varying with unspecified functional forms. The local linear method with the cross-validation (CV) bandwidth selection is applied to estimate the time-varying coefficient HAR (TVC-HAR) model, and a bootstrap method is used to construct the point-wise confidence bands for the coefficient functions. Furthermore, the asymptotic distribution of the proposed local linear estimators of the TVC-HAR model is established under some mild conditions. The results of the simulation study show that the local linear estimator with CV bandwidth selection has favorable finite sample properties. The outcomes of the conditional predictive ability test indicate that the proposed nonparametric TVC-HAR model outperforms the parametric HAR and its extension to HAR with jumps and/or GARCH in terms of multi-step out-of-sample forecasting, in particular in the post-2003 crisis and 2007 GFC periods, during which financial market volatilities were unduly high

Nutrients in Wastewater from a Phosphate Fertilizer Manufacturing Plant Stored for Irrigation

Wastewater from a fertilizer manufacturing plant in southern Idaho was pumped into a storage impoundment during the winter months and stored for irrigating and fertilizing agricultural crops the next summer. Analyses of water samples from the impoundment taken monthly showed the following mean annual nutrient concentrations: Total Kjeldahl Nitrogen (TKN) 94, NH+4-N 61, NO-3–N 8, total P 17, ortho P 15, and K 17 mg/L. The impoundment surface area averaged 10.5 ha with a maximum pond volume during the year of 362,000 m3 . Accumulated nutrients in the impounded wastewater available for irrigating and fertilizing agricultural crops at the beginning of the growing season was TKN 30.2, NH+4–N 23.2, NO3-N 4.3, total P 9.7, and K 6.2 metric tons. Nitrification in the pond was minimal. Redox potentials were between 480 and 500 mv at all depths and locations measured in the pond in the summer and denitrification was minimal. The redox potential indicated that the water was near oxygen saturation

Farmland Prices: Is This Time Different?

The historical behavior of farmland prices, rental rates, and rates of return are examined by treating farmland as an asset with an infinitely long life. It is found that high (low) farmland prices relative to rents have historically preceded extended periods of low (high) net rates of return, rather than greater (smaller) growth in rents. Our analysis shows that this attribute is shared with stocks and housing, and the financial literature provides ample evidence that other assets feature it as well. The long-run relationship linking farmland prices, rents, and rates of return is analyzed. Based on this relationship, we conclude that recent trends are unlikely to be sustainable. The study explores the expected paths that farmland prices and rates of return might follow if they were to eventually conform to the average values observed in the historical sample, and concludes with a discussion of the policy implications. Recommendations for policy makers include close monitoring of farmland lending practices and institutions to allow early identification of potential problems, and identifying in advance appropriate interventions in case recent farmland market trends were to suddenly change

Size-dependent decoherence of excitonic states in semiconductor microcrystallites

The size-dependent decoherence of the exciton states resulting from the spontaneous emission is investigated in a semiconductor spherical microcrystallite under condition $a_{B}\ll R_{0}\leq\lambda$. In general, the larger size of the microcrystallite corresponds to the shorter coherence time. If the initial state is a superposition of two different excitonic coherent states, the coherence time depends on both the overlap of two excitonic coherent states and the size of the microcrystallite. When the system with fixed size is initially in the even or odd coherent states, the larger average number of the excitons corresponds to the faster decoherence. When the average number of the excitons is given, the bigger size of the microcrystallite corresponds to the faster decoherence. The decoherence of the exciton states for the materials GaAs and CdS is numerically studied by our theoretical analysis.Comment: 4 pages, two figure

A review of the Dividend Discount Model: from deterministic to stochastic models

This chapter presents a review of the dividend discount models starting from the basic models (Williams 1938, Gordon and Shapiro 1956) to more recent and complex models (Ghezzi and Piccardi 2003, Barbu et al. 2017, D'Amico and De Blasis 2018) with a focus on the modelling of the dividend process rather than the discounting factor, that is assumed constant in most of the models. The Chapter starts with an introduction of the basic valuation model with some general aspects to consider when performing the computation. Then, Section 1.3 presents the Gordon growth model (Gordon 1962) with some of its extensions (Malkiel 1963, Fuller and Hsia 1984, Molodovsky et al. 1965, Brooks and Helms 1990, Barsky and De Long 1993), and reports some empirical evidence. Extended reviews of the Gordon stock valuation model and its extensions can be found in Kamstra (2003) and Damodaran (2012). In Section 1.4, the focus is directed to more recent advancements which make us of the Markov chain to model the dividend process (Hurley and Johnson 1994, Yao 1997, Hurley and Johnson 1998, Ghezzi and Piccardi 2003, Barbu et al. 2017, D'Amico and De Blasis 2018). The advantage of these models is the possibility to obtain a different valuation that depends on the state of the dividend series, allowing the model to be closer to reality. In addition, these models permit to obtain a measure of the risk of the single stock or a portfolio of stocks

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance