Secondary Indexing in One Dimension: Beyond B-trees and Bitmap Indexes

Let S be a finite, ordered alphabet, and let x = x_1 x_2 ... x_n be a string over S. A "secondary index" for x answers alphabet range queries of the form: Given a range [a_l,a_r] over S, return the set I_{[a_l;a_r]} = {i |x_i \in [a_l; a_r]}. Secondary indexes are heavily used in relational databases and scientific data analysis. It is well-known that the obvious solution, storing a dictionary for the position set associated with each character, does not always give optimal query time. In this paper we give the first theoretically optimal data structure for the secondary indexing problem. In the I/O model, the amount of data read when answering a query is within a constant factor of the minimum space needed to represent I_{[a_l;a_r]}, assuming that the size of internal memory is (|S| log n)^{delta} blocks, for some constant delta > 0. The space usage of the data structure is O(n log |S|) bits in the worst case, and we further show how to bound the size of the data structure in terms of the 0-th order entropy of x. We show how to support updates achieving various time-space trade-offs. We also consider an approximate version of the basic secondary indexing problem where a query reports a superset of I_{[a_l;a_r]} containing each element not in I_{[a_l;a_r]} with probability at most epsilon, where epsilon > 0 is the false positive probability. For this problem the amount of data that needs to be read by the query algorithm is reduced to O(|I_{[a_l;a_r]}| log(1/epsilon)) bits.Comment: 16 page

Optimal composition of hybrid/blended real estate portfolios

Purpose: The purpose of this paper is to establish an optimum mix of liquid, publicly traded assets that may be added to a real estate portfolio, such as those held by open-ended funds, to provide the liquidity required by institutional investors such as UK defined contribution pension funds. This is with the objective of securing liquidity while not unduly compromising the risk-return characteristics of the underlying asset class. This paper considers the best mix of liquid assets at different thresholds for a liquid asset allocation, with the performance then evaluated against that of a direct real estate benchmark index. Design/Methodology/Approach: The authors employ a mean-tracking error optimisation approach in determining the optimal combination of liquid assets that can be added to a real estate fund portfolio. The returns of the optimised portfolios are compared to the returns for portfolios that employ the use of either cash or listed real estate alone as a liquidity buffer. Multivariate Generalised Autoregressive models are used along with rolling correlations and tracking errors to gauge the effectiveness of the various portfolios in tracking the performance of the benchmark index. Findings: The results indicate that applying formal optimisation techniques leads to a considerable improvement in the ability of the returns from blended real estate portfolios to track the underlying real estate market. This is the case at a number of different thresholds for the liquid asset allocation and in cases where a minimum return requirement is imposed. Practical Implications: The results suggest that real estate fund managers can realise the liquidity benefits of incorporating publicly traded assets into their portfolios without sacrificing the ability to deliver real estate-like returns. However, in order to do so, a wider range of liquid assets must be considered, not just cash. Originality/value: Despite their importance in the real estate investment industry, comparatively few studies have examined the structure and operation of open-ended real estate funds. To the authors’ knowledge, this is the first study to analyse the optimal composition of liquid assets within blended or hybrid real estate portfolios

Distributed model predictive control of steam/water loop in large scale ships

In modern steam power plants, the ever-increasing complexity requires great reliability and flexibility of the control system. Hence, in this paper, the feasibility of a distributed model predictive control (DiMPC) strategy with an extended prediction self-adaptive control (EPSAC) framework is studied, in which the multiple controllers allow each sub-loop to have its own requirement flexibility. Meanwhile, the model predictive control can guarantee a good performance for the system with constraints. The performance is compared against a decentralized model predictive control (DeMPC) and a centralized model predictive control (CMPC). In order to improve the computing speed, a multiple objective model predictive control (MOMPC) is proposed. For the stability of the control system, the convergence of the DiMPC is discussed. Simulation tests are performed on the five different sub-loops of steam/water loop. The results indicate that the DiMPC may achieve similar performance as CMPC while outperforming the DeMPC method

Identifying, measuring and management risks in Russian secondary stock markets

: This paper outlines the changes and challenges of Emerging Russian Stock Market and investment strategy of portfolio management for the period 1996-1998 . It also taste the West models of optimization of portfolio risks and investment decisions for Russia. The major purpose of this article was to enhance the understanding of the participants in securities markets and enhance the performance of its stock and Emerging securities. This article will review the trends in the markets and help focus on the corporate risks and management and a detailed and developed conception of the mechanism of the initial public offerings and public placement of securities the global stock markets such as the U.S., Western Europe and emerging markets. It also outlined the regulatory structure and investor?s risk management tools required by western investors. In light of the recent ?financial crisis? in Russia and other major markets such as Asia, these tools will be increasing important. During much of the past decade the Russian Securities market has been developing into a number of areas including federal securities (GKO-OFZ), sub-federal (oblast) and municipal issues, corporate securities, Ag Bonds, futures, forward contracts and currency instruments. This article is developing in all those areasm .These will be increasing important in light of the new banking environment and securities laws and regulations. In 1997 Russia has joined the league of the few emerging markets that have market capitalizations of over $100 Billion. As of June 30, 1997 the capitalization is$104 Billion and has a YTD of 134 %. The recent ?Asian induced? corrections in the markets have reduced this by 20-40% according to private estimates. Nevertheless, it remains one of the most vibrant emerging securities markets in the world. The training focused on a number of issues related to emerging market securities including privatization, auctions, IPO?s and new products in the securities markets.

The financial stress index: identification of systemic risk conditions

This paper develops a financial stress index for the United States, the Cleveland Financial Stress Index (CFSI), which provides a continuous signal of financial stress and broad coverage of the areas that could indicate it. The index is based on daily public-market data collected from four sectors of the fi nancial markets—the credit, foreign exchange, equity, and interbank markets. A dynamic weighting method is employed to capture changes in the relative importance of these four sectors as they occur. In addition, the design of the index allows the origin of the stress to be identified. We compare the CFSI to alternative indexes, using a detailed benchmarking methodology, and show how the CFSI can be applied to systemic stress monitoring and early warning system design. To that end, we investigate alternative stress-signaling thresholds and frequency regimes and then establish optimal frequencies for filtering out market noise and idiosyncratic episodes. Finally, we quantify a powerful CFSI-based rating system that assigns a probability of systemic stress to ranges of CFSI outcomes.Systemic risk ; Risk assessment

How prudent are rural households in developing transition economies:

Rural households in developing economies frequently use precautionary saving to cope with income risk. Such prudent behavior can be strengthened in transition economies where more risks are typically faced by households during and after reforms. This paper uses a rich panel of rural households in Zhejiang, China, to examine the correlation between income uncertainty and the target ratio of wealth to permanent income as suggested by the buffer-stock model. The empirical results suggest that Chinese rural households hold a significant level of wealth to mitigate the adverse impacts of income risk. Simulation results show that an increase in income risk leads to a sharp increase in household wealth and precautionary saving could drop substantially if income risk is eliminated. The high level of prudence of rural households under economic transition can help us better understand the developments in China, which will have policy implications for both developing and transition countries.buffer-stock model, Income risk, precautionary saving,

The school reentry decision on poor girls: structural estimation and policy analysis using PROGRESA database

In this paper I present a dynamic structural model of girls' schooling choices and estimate it using the Mexican PROGRESA database. This structural approach allows evaluating the efectiveness of several policies to increase school reentry rates for girls in low-income households. To increase school attendance among poor children in developing countries, policy makers have implemented conditional cash transfers programs. Although transfers have been successful in keeping girls at school, they do not increase school attendance among girls who have dropped out of school. Cash transfer programs may fail because most of these poor girls leave school to stay at home helping in housework, rather than working for a salary. Results suggest that effective policies to increase school reentry rates for poor girls are free access to community nurseries and kindergartens, and increasingg the availability of secondary schools.Policy evaluation, Dynamic discrete choice structural models, School choices for girls, School reentry, PROGRESA

Indexing Metric Spaces for Exact Similarity Search

With the continued digitalization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the data are often viewed as the main sources of challenges when attempting to enable value creation from big data: volume, velocity and variety. Many studies address volume or velocity, while much fewer studies concern the variety. Metric space is ideal for addressing variety because it can accommodate any type of data as long as its associated distance notion satisfies the triangle inequality. To accelerate search in metric space, a collection of indexing techniques for metric data have been proposed. However, existing surveys each offers only a narrow coverage, and no comprehensive empirical study of those techniques exists. We offer a survey of all the existing metric indexes that can support exact similarity search, by i) summarizing all the existing partitioning, pruning and validation techniques used for metric indexes, ii) providing the time and storage complexity analysis on the index construction, and iii) report on a comprehensive empirical comparison of their similarity query processing performance. Here, empirical comparisons are used to evaluate the index performance during search as it is hard to see the complexity analysis differences on the similarity query processing and the query performance depends on the pruning and validation abilities related to the data distribution. This article aims at revealing different strengths and weaknesses of different indexing techniques in order to offer guidance on selecting an appropriate indexing technique for a given setting, and directing the future research for metric indexes