Examples of Right-Time Decisions From High Frequency Data

Operative Use of Eddy Covariance Measurements: Are High Frequency Data Indispensable?

This paper introduces a framework for analysis of cross-sectional dependence in the idiosyncratic volatilities of assets using high frequency data. We rst consider the estimation of standard measures of dependence in the idiosyncratic volatilities such as covariances and correlations. Next, we study an idiosyncratic volatility factor model, in which we decompose the co-movements in idiosyncratic volatilities into two parts: those related to factors such as the market volatility, and the residual co-movements. When using high frequency data, naive estimators of all of the above measures are biased due to the estimation errors in idiosyncratic volatility. We provide bias-corrected estimators and establish their asymptotic properties. We apply our estimators to high-frequency data on 27 individual stocks from nine dierent sectors, and document strong cross-sectional dependence in their idiosyncratic volatilities. We also nd that on average 74% of this dependence can be explained by the market volatility.

Information Quality for Effective Asset Management: A literature review

Dynamic Copula Models and High Frequency Data

This research aims to describe the management and maintenance of assets and facilities, as well as the supporting and inhibiting factors in the management of advice and facilities in MTsN 1 Jombang. This research includes qualitative case studies. Data is collected through observation methods, question answers, and documentation. The results of this research show that: 1) The management of assets and stocks in MTsN 1 Jombang covers the stages of planning, procurement, inventory, use, disposal, and storage. 2) In terms of its maintenance, it involves the resources that exist in the school, not only the wakamad, but all of them play a role in safeguarding the means and facilities that it owns. 3) As to the inhibitory factor of its own resources, such as no care for the facilities and facilities of the madrasah, the supporting factor of the SDM is the main factor in supporting the success of the programmes that have been held by the madrasah.

Owing to enormous advances in data acquisition and processing technology the study of high (or ultra) frequency data has become an important area of econometrics. At least three avenues of econometric methods have been followed to analyze high frequency financial data: Models in tick time ignoring the time dimension of sampling, duration models specifying the time span between transactions and, finally, fixed time interval techniques. Starting from the strong assumption that quotes are irregularly generated from an underlying exogeneous arrival process, fixed interval models promise feasibility of familiar time series techniques. Moreover, fixed interval analysis is a natural means to investigate multivariate dynamics. In particular, models of price discovery are implemented in this venue of high frequency econometrics. Recently, a sound statistical theory of ‘realized volatility’ has been developed. In this framework high frequency log price changes are seen as a means to observe volatility at some lower frequency.

This study is conducted to check the co-movement between the equity markets of BRICS countries that is Brazil, Russia, India and China with Pakistan. These countries are selected because they are world emerging markets. Co-movement is checked through co-integration analysis. Ten years monthly stock indices are taken for analysis that is from July 2006 to June 2016. No cointegration is found between Pakistani equity market and the BRICS countries. So, this favours the international portfolio investors. Furthermore, Brazilian market is found to be the most attractive market for the portfolio investors in order to maximize their wealth by minimizing their risk levels. The future research can be extended by using high frequency data in order to check the comovement and cointegration.

Market microstructure theory highlights two important empirical predictions about how financial asset prices evolve over time, which are: (1) trades convey information that contributes to security price movements; and (2) intensified trading activity increases price volatility. This thesis provides three essays that develop new empirical models for high frequency returns, volatility, trading volumes and trade durations in order to test these two empirical predictions. Our newly proposed models show strong support for these theoretically implied predictions and provide additional insights into the interdependence amongst returns, volatility, volumes, and trade durations.

Asset Management (AM) is promising for value creation from assets in the long term. A major concern to this end relates with the capabilities to achieve effective AM decision-making at every organisational level, i.e. operational, tactical, and strategical. Therefore, the goal of this research, grounded on a systematic literature review, is to identify which are the main sources of uncertainty that may influence the achievement of AM system related objectives and, as such, should be taken into consideration in a risk-informed decision-making process. Taking the manufacturing sector as a reference, the risk sources addressed by the extant literature are identified and mapped against a reference classification scheme. As a result, the research offers a comprehensive framework where risk sources, affecting the AM decision-making process, are systematically mapped. Information management is found to be the main risk source when making asset-related decisions.

사회기반시설이 노후화됨에 따라 현행 시설물 유지관리를 넘어 예산을 절약하고 시설물의 가치를 높이기 위해 공공시설에 자산관리를 도입해야 한다는 요구가 증대되고 있다. 공공시설 자산관리는 이러한 요구에 대응하기 위한 새로운 시설물 유지보수 개념으로 기존의 시설물 유지관리업무를 통해 축적된 데이터를 분석하고 생애주기분석, 리스크관리 등의 의사결정 방법을 활용하여 최적화된 유지관리계획을 수립하고 실행하는 것이다. 자산관리의 정보화 방안을 도출하기 위해 자산관리 업무를 조사하고, 뉴질랜드의 IIMM의 내용과 미국의 FHWA의 업무정의 그리고 국내의 대표적 유지관리시스템을 분석하였다. 또한 현행 시설물 유지관리 조직간의 역할을 조사하고, 자산관리 조직과 업무간의 관계를 분석하였다. 마지막으로 자산관리에 필요한 정보와 기존 유지관리시스템이 포함하고 있는 정보를 자산관리 업무와 비교분석하였다. 본 논문에서는 공공시설 자산관리 정보화 방안으로 첫째, 시설물 유지관리시스템에 있는 기능을 중복해서 개발하지 않고 자산관리 핵심업무만을 구현하며 둘째, 시스템의 구조를 계층으로 분할하고 셋째, 자산관리시스템과 기존 시설물 유지관리시스템들간을 연동하여 정보를 공유하는 방안을 제시하였다. With the social infrastructure being deteriorated, there is a growing need to introduce the asset management to social infrastructure management in order to increase their value and save budget. Social infrastructure asset management is a new concept of facility management in response to these demands. It is defined as a procedure for collecting and analysing facility maintenance data and for making and practicing an economically optimized management plan. Detailed survey work of asset management business is analyzed in order to derive a strategy for asset management information. The contents of IIMM of New Zealand and the asset management definition of the FHWA of the United States, and representative facility management systems of Korea are analysed. The role between organizations and the relationship between business and organization were analyzed. Information required for asset management and for existing facility management systems is compared with business of asset management. In this thesis, three development strategies are suggested. The first one is to develop core business of asset management while excluding duplicated development. The second one is to divide system's structure into three layers. And the last one is to share information by interfacing asset management systems with existing facility management systems.

Purpose The asset management industry has experienced a major evolution in Morocco. Since the mid-1990s, it has contributed to the financing of public spending in the country. At this time, the industry began to play an important role in financing the Moroccan economy and has since experienced constant growth. Today, with 582 undertakings for collective investment in transferable securities managed, it is a real vehicle for collecting savings and boosting financial markets, according to the president of the Association of Management Companies and Investment Funds (ASFIM). The objective of this research is to analyse the behavioural biases impacting the decisions of asset managers affiliated with Moroccan banks. This study aims to highlight these biases in light of the existing literature in behavioural finance. Design/methodology/approach The study employs an empirical approach, conducting semi-structured interviews with 14 asset managers from 7 different Moroccan banks. The research focuses on three main behavioural finance models. The first is related to the models of KAHENMAN and TVERSKY. The second relates to the model of the economist SHILLER, and finally, a proposal is in line with the models of SHEFRIN and STATMAN. Findings The results provide evidence of the presence of specific psychological biases in the decision-making processes of asset managers when buying and selling on the Casablanca Stock Exchange. In particular, the study shows that their investment decisions were significantly affected by loss aversion and overconfidence. Originality/value This research contributes to the understanding of how behavioural biases influence asset management decisions in the Moroccan context. It adds to the limited literature on behavioural finance in emerging markets, particularly focusing on the asset management industry in Morocco.

Much attention has been made of optimising information modelling in the construction sector. Government bodies have mandated collaborative working environments as a means of enhancing the process of delivering assets that not only meet user expectations, but also reduce project costs and enhance timely completion. An impetus is being placed on the need to reduce total lifecycle costs – 33% by 2020 (Construction Leadership Council, 2013) – so, more emphasis needs to be placed on the acceptance and use of information for the ongoing operation and maintenance of our built assets. Central to this concept is breaking down the disparate silos that constrict the architecture, engineering, construction (AEC) and asset management (AM) industries. This research project attempts to explore the phenomenon of whole-lifecycle asset information management, from the perspective of those critical to the process, the asset managers. Using cases from the UK Higher Education (HE) sector, individuals at all levels of the organisational structure (i.e. managerial through to technician) were engaged and an understanding of the varying roles and responsibilities used as a starting point for discovery. A grounded theory approach is adopted, iteratively collating qualitative data from four universities, as well as concurrent thematic analysis of said data, finally validating the theoretical findings against a fifth university. Working a cross-section of universities through semi-structured interview sessions allowed for a fluid approach, capturing the true narrative of the individual whilst adapting one’s understanding of the overarching phenomenon. Findings highlighted: - The wasteful model of information management, as currently exists within HE AM departments; roles, timeliness, accuracy, duplication and missing information all contribute towards delays and costly resource demands. - Inefficient and ineffective handover from the capital AEC teams to the AM teams, at the point of practical completion; greater preparation was requested by means of pre-planned site visits at scheduled intervals. - AM subjects were generally unwilling to adapt to the increasing demands of digital technologies and visual displays; the process was therefore found to be superfluous activity. - AM subjects’ experiential knowledge was underutilised and not captured / incorporated within project development; cyclical lessons were not learned. This thesis contributes to knowledge by way of a theoretical framework, developed in response to the findings from the interviews. The PPTC Lifecycle Framework introduces the concept of ‘channels’ as an additional project dimension to the pre-existing ones of ‘people’, ‘process’, and ‘technologies’, linking each to key activities and their respective lifecycle stages. The framework highlights the necessity for a ‘softer landing’. It also provides the means for asset managers to be more inclusive in the end-to-end development of built assets, so that they can ensure the successful preparation of all asset management information for ongoing operation and maintenance.

<p dir="ltr">Smart technologies spilled over from Industry 4.0 has benefited many sectors in the built environment. Digitization of information and digitalization of processes facilitated many advances in whole life cycle asset management. During uncertain times, smart technologies increasingly enable asset managers to better manage their assets with a life cycle approach. This paper studies the technology trend in facilities asset management. Next, the importance of managing change and resilience planning in whole life cycle asset management is explained. Finally, strategies using smart technology to strengthen resilience and manage change is present.</p>

Abstract. Advancements in data collection and data processing techniques revolutionized access to higher frequency data. A large body of literature focusses on these higher frequency data in advanced economies. In contrast, small less-developed economies often lack adequate and reliable databases of high-frequency economic indicators. We construct a monthly GDP indicator, using a well-established statistical methodology. To monitor the quality of the indicator, we treat it as an in-sample forecast with respect to December observation of GDP for 2012 -2018. The results show that the constructed monthly GDP indicator is reliable and therefore its methodology applicable in many small developing countries. Keywords. Monthly GDP indicator, GDP. JEL. C51, E30, E32.

Investigating High Frequency Exchange Rate from the Brazilian Sisbex Market