A Preference-based Model for Dynamic Asset Allocation in Diversified Portfolio with Home Event Risk

Multi-period stochastic optimization models for dynamic asset allocation

Dynamic task allocation is an essential aspect in modeling ant behaviour [1],[2]. In this paper, we propose a new (abstract) model for dynamic task allocation of agents that combines a nested layered architecture with a threshold mechanism. We apply this new model to achieve flexible ant behaviour.

We study a new model for dynamic processor allocation in multicomputer systems. The model, originally proposed in (Chen at al., 1994) for hypercube systems, uses Boolean functions to represent free processors and allocates processors by applying Boolean operations on the functions. With the model, existing techniques for handling Boolean functions, such as the binary decision diagram (BDD), can be applied directly. This paper extends previous results in several ways. First, a technique called lazy combining is introduced, which uses the current free processor composition as much as possible-changing only when an incoming request fails to find a match. Second, when recombining the free processors is necessary, a comprehensive literal reordering technique for BDD is presented to identify matching free subcubes. Third, we extend the new model to general k-ary n-cube mesh or torus systems. Due to the generality of our model, the extension is straightforward as long as some restrictions are observed. Finally, complexities and performance evaluation of the algorithms are presented.

This paper investigates the drivers of hot money in China. It develops a model based on expectation‐variance utility theory in the theoretical analysis section. The model considers a foreign investor who faces the question of how to distribute his wealth between foreign and domestic assets. The model’s analysis suggests that economic variations, such as expected domestic currency appreciation, rise in domestic asset return, drop in foreign asset return, domestic economic growth, decrease in domestic inflation, and rise in foreign asset risk will cause foreign investors to distribute more wealth in domestic assets. Therefore, hot money flows in, and vice versa. In the empirical analysis section, the paper estimates structural VAR models using data from 2000 to 2019 in China. The impulse response functions are consistent with the theoretical predictions: when there is a positive domestic inflation shock, hot money outflows increase (inflows decline) in the current period, but the response is not significant. When there is a positive domestic growth rate shock or positive domestic asset return rate shock, hot money inflows increase (outflows decline) in the current period, and the response reaches its peak in the next period. Furthermore, when there is a positive expected exchange rate shock, hot money outflows increase (inflows decline) in the current period. Of these drivers, the expected exchange rate has the largest impact on hot money, and the domestic growth rate has the most enduring effect.

Distributed processing is an effective way to improve performance of database systems. Therefore, fragmentation and proper allocation of fragments across various sites of the network is considered as a key research area in distributed database environment. However, the issue of allocating fragments to the most appropriate sites is not an easy task to perform. In this paper, a synchronized horizontal fragmentation, replication and allocation model in the context of relational database is proposed. A heuristic technique to satisfy horizontal fragmentation and allocation using a cost model to minimize the total cost of distribution is developed. Experimental results are consistent with the hypothesis confirming that the proposed model can efficiently solve dynamic fragmentation and allocation problem in a distributed relational database systems.

Task dynamic allocation is the key in the Multi-agents System's realization, an important problem is how to simulate the task allocation process dynamically and visually. Based on contractor Network Protocol and Colored Petri Nets, a task dynamic allocation model among multiple agents is constructed, by simulating the model on software platform, the related conclusions concerning boundness, deadlock-free, and liveness are obtained. Then, the model of task dynamic allocation is proved correct and reasonable. This formal and visual simulating method and model evaluating method have not been realized by other validating methods by far.

Many randomized trials measure means and standard deviations of anesthesia recovery time (e.g., times to tracheal extubation). We show how to use generalized pivotal methods to compare the probabilities of exceeding a tolerance limit (e.g., > 15min, prolonged times to tracheal extubation). The topic isimportant because the economic benefits of faster anesthesia emergence depend onreducing variability, not means, especially prevention of very long recovery times. Generalized pivotal methods are applied using computer simulation (e.g., using two Excel formulas for one group and three formulas for two group comparisons). The endpoint for each study with two groups is the ratio between groups of the probabilities of times exceeding a threshold or the ratio of the standard deviations. Confidence intervals and variances for the incremental risk ratio of the exceedance probabilities and for ratios of standard deviations are calculated using studies' sample sizes, sample means in the time scale of recovery times, and sample standard deviations in the time scale. Ratios are combined among studies using the DerSimonian-Laird estimate of the heterogeneity variance estimate, with Knapp-Hartung adjustment for the relatively small (N = 15) numbers of studies in the meta-analysis. We show larger absolute variability among studies' results when analyzed based on exceedance probabilities rather than standard deviations. Therefore, if an investigator's primary goal is to quantify reductions in the variability of recovery times (e.g., times until patients are ready for post-anesthesia care unit discharge), we recommend analyzing the standard deviations. When exceedance probabilities themselves are relevant, they can be analyzed from the original studies' summary measures.

To describe inter- and intraobserver reliability of 3D measurements of female pelvic floor structures. Twenty reconstructed MR datasets of primiparas at 6-12 months postpartum were analyzed. Pelvic organ measurements were independently made twice by three radiologists blinded to dataset order. A "within-reader" analysis, a "between-reader" analysis, and the intraclass correlation (ICC), and standard deviation ratio (SDR) were computed for each parameter. Fifteen continuous variables and one categorical variable were measured. Eight continuous parameters showed excellent agreement (ICC >0.85 / SDR <0.40), five parameters showed relatively good agreement (ICC >0.70 / SDR >or=0.40, <0.60). Two parameters showed poor agreement (ICC <or=0.70 and/or SDR >or=0.60). The categorical variable showed poor agreement. Agreement was best where landmark edges were well defined, acceptable where more "reader judgment" was needed, and poor where levator defects made landmarks difficult to identify. Automated measurement algorithms are under study and may improve agreement in the future.

Oil tanker traffic constitutes a vital part of the maritime operations in the High North and is associated with considerable risk to the environment. As a consequence, the Norwegian Coastal Administration (NCA) administers a number of vessel traffic services (VTS) centers along the Norwegian coast, one of which is located in the town of Vardo, in the extreme northeast part of Norway. The task of the operators at the VTS center in Vardo is to command a fleet of tug vessels patrolling the northern Norwegian coastline such that the risk of oil tanker drifting accidents is reduced. Currently, these operators do not use computer algorithms or mathematical models to solve this dynamic resource allocation problem but rely on their own knowledge and experience when faced with constantly changing weather and traffic conditions. We therefore propose a novel sustainable model called the receding horizon mixed integer programming (RHMIP) model for optimal dynamic allocation of patrol vessels to oil tankers. The model combines features from model predictive control and linear programming. Simulations run with real-world parameters highlight the performance and quality of our method. The developed RHMIP model can be implemented as an operational decision support tool to the NCA.

Chapter 13 - Stochastic programming models for strategic and tactical asset allocation—A study from Norwegian life insurance

Portfolio Reallocation and Exchange Rate Dynamics

ABSTRACTTwo parallel forms of a test are considered “equated” when for a single group of examinees the standard deviations on the two forms are equal and the means on the two forms are equal. Since present test construction procedures are not sufficiently precise to produce forms with equivalent score scales, it is necessary to conduct an equating experiment for the purpose of collecting data for use in adjusting the initial raw score scales. Although the definition of equated score scales is given in terms of equivalence of the first two moments for a single group of examinees, the tests to be equated need not be administered to the same examinees. This paper considers two types of experiments in which the tests to be equated are administered to different examinees.Both types of experiments can be characterized as follows: If two tests (X and Y) are to be equated, X is administered to the first and Y to the second of a pair of samples. In addition, a third test (V) is administered to both samples. V may be either a separate test from. X and Y or a number of items contained in both X and Y. In either case, V may be considerably shorter than X and Y. The two types of experiments are identical with respect to these test administration procedures, but they differ with respect to the assumptions made about the characteristics of the two samples of examinees.The first type of experiment calls for the use of samples of examinees that are randomly drawn from, the same population, F. M. Lord has considered this general model for the case of equally reliable tests; in this paper a solution is given for the case when X and Y are unequally reliable. Using the statistics for the random samples, maximum likelihood estimates are made of the means and variances of true scores in the population from which the samples were drawn. Thus, the first two moments are estimated for a single group of examinees (the population). For this purpose it is necessary to assume that true scores on X, Y, and V intercorrelate unity.The second type of experiment allows the use of samples that are selected in a non‐random manner from a common population. In this case the equating of equally reliable X and Y as well as unequally reliable X and Y is considered. The equations are derived on the assumption that true scores on all tests intercorrelate unity; however, for the case of equally reliable tests a solution is possible so long as true scores on V correlate unity with true scores on either X or Y. It is shown that, if true scores on two tests correlate unity, for pairs of samples of different ability three quantities will remain invariant: 1) the ratio of standard deviations of true scores on the two tests; 2) the difference between the mean on one test and the product of the mean on the second and the ratio of true score standard deviations, and 3) the standard error of measurement.Data are presented which indicate that the equations derived for both types of experiments are sound.

SummaryThe channel availability problem reaches a higher degree in mobile ad hoc networks (MANETs) and garners a lot of attention in communication networks. Because increased mobile usage might result in a lack of channel allocation, an improved channel allocation technique is presented to tackle the availability problem. The distributed dynamic channel allocation (DDCA) model is built in this paper using the hybrid memory dragonfly with imperialist competitive (HMDIC) method. Based on optimization logic, this strategy assigns the channel to mobile hosts. The MANET provides a dispersed network within the coverage region in the absence of base station infrastructure. The HMDIC optimizer approach in this circumstance randomly begins every respective node to update and store their pbest value utilizing RAM dragonfly employing satellite images. The constraint values are then used to construct the cost function, which results in a strong kind of global optimum solution. The channels are therefore distributed in an effective manner. The HMDIC algorithm is used in this research to build a novel channel allocation system. It makes advantage of the exploration capabilities to successfully explore the individual node using MDA (Modified Dragonfly Algorithm) and locate the global best solution using imperialist competitive algorithm (ICA). Both of these combined tactics are more effective in accelerating the convergence of the allocation model. To validate the performance, the HMDIC‐based DDCA system provides promising results in terms of assigning available channels, thereby enhancing channel reuse efficiency and fractional interference.

This study presents a methodology to convert an RBDO problem requiring very high reliability to an RBDO problem requiring relatively low reliability by increasing input standard deviations for efficient computation in sampling-based RBDO. First, for linear performance functions with independent normal random inputs, an exact probability of failure is derived in terms of the ratio of the input standard deviation, which is denoted by δ. Then, the probability of failure estimation is generalized for any random input and performance functions. For the generalization of the probability of failure estimation, two coefficients need to be determined by equating the probability of failure and its sensitivity with respect to the standard deviation at the current design point. The sensitivity of the probability of failure with respect to the standard deviation is obtained using the first-order score function for the standard deviation. To apply the proposed method to an RBDO problem, a concept of an equivalent standard deviation, which is an increased standard deviation corresponding to the low reliability model, is also introduced. Numerical results indicate that the proposed method can estimate the probability of failure accurately as a function of the input standard deviation compared to the Monte Carlo simulation results. As anticipated, the sampling-based RBDO using the surrogate models and the equivalent standard deviation helps find the optimum design very efficiently while yielding relatively accurate optimum design which is close to the one obtained using the original standard deviation.

Multi-sensor data fusion in the nondestructive measurement of kiwifruit texture