Portfolio-based Planning: State of the Art, Common Practice and Open Challenges

In recent years the field of automated planning has significantly advanced and several powerful domain-independent planners have been developed. However, none of these systems clearly outperforms all the others in every known benchmark domain. This observation motivated the idea of configuring and exploiting a portfolio of planners to perform better than any individual planner: some recent planning systems based on this idea achieved significantly good results in experimental analysis and International Planning Competitions. Such results let us suppose that future challenges of the Automated Planning community will converge on designing different approaches for combining existing planning algorithms. This paper reviews existing techniques and provides an exhaustive guide to portfolio-based planning. In addition, the paper outlines open issues of existing approaches and highlights possible future evolution of these techniques

Portfolio management with cryptocurrencies: the role of estimation risk

This paper contributes to the literature on cryptocurrencies, portfolio management and estimation risk by comparing the performance of naïve diversification, Markowitz diversification and the advanced Black–Litterman model with VBCs that controls for estimation errors in a portfolio of cryptocurrencies. We show that the advanced Black–Litterman model with VBCs yields superior out-of-sample risk-adjusted returns as well as lower risks. Our results are robust to the inclusion of transaction costs and short-selling, indicating that sophisticated portfolio techniques that control for estimation errors are preferred when managing cryptocurrency portfolios

Challenges of Portfolio-based Planning

In the recent years the field of automated planing has significantly advanced and several powerful domain-independent planners have been developed. However, none of these systems clearly outperforms all the others in every known benchmark domain. This observation motivated the idea of configuring and exploiting a portfolio of planners to achieve better performances than any individual planner: some recent planning systems based on this idea obtained significantly good results in experimental analysis and International Planning Competitions. Such results lead us to think that future challenges for the automated planning community will converge on designing different approaches for combining existing planning algorithms. This paper focuses on the challenges and open issues of existing approaches and highlights the possible future evolution of these techniques. In addition the paper introduces algorithm portfolios, reviews existing techniques, and describes the decisions that have to be taken during the configuration

A comparative analysis of resampling efficiency and Black-Litterman portfolio optimization

openIt is common knowledge that the traditional Mean-Variance (MV) approach presents several non-negligible criticalities such as unintuitive and highly concentrated portfolios, input sensitivity, and estimation error maximization. Black-Litterman (BL) model and Resampled Efficiency (RE) techniques are advanced methods that help to generate better allocations than the traditional “a la Markowitz” method. On the one hand, the Black-Litterman model represents a well-known approach that overcomes this issue by assuming partial information on the expected returns. By blending a reference market distribution with subjective views on the market, the approach yields optimal portfolios that smoothly reflect those views. On the other, portfolio resampling, following a heuristic approach allows the portfolio manager to visualize the estimation error in traditional portfolio optimization methods. Starting from a thorough review of the literature about traditional portfolio theory and a discussion of its limitations, the two approaches: BL and RE are introduced. The core of this work will focus on the implementation of the Black-Litterman model together with resampling techniques for portfolio allocations, carrying out an empirical examination of the usefulness of those technologies in reducing estimation errors

Implementing the Black-Litterman Model with Resampling: A Typical Investment Portfolio with Hedge Funds

Asset allocation decision is ranked as the most important investment decision an investor should make. Researchers have developed many optimization tools to find the best allocation for investors. Our paper will focus on implementing Black-Litterman model together with resampling techniques for portfolio allocations. In our paper, we are going to empirically test the usefulness of those techniques. The results from our research proved that Black-Litterman model and Resampling techniques are advanced methods, which help to generate better allocations than the traditional Markowitz method does. As focusing on typical Canadian investors, our reference portfolio is consisted of S&P TSX, S&P 500, DEX Universe Bond Index, T-Bills and various Canadian hedge funds indices. Using new data sets, we will test whether the results presented in Kooli and Selam’s 2010 paper will still hold. Lastly, further thoughts of our research will be discussed

Optimal Portfolio Construction for Oil-Based Sovereign Wealth Funds

Chapter 1 of this dissertation delves into the economic challenges faced by oil-exporting countries that rely heavily on a single income source, with a particular focus on Saudi Arabia as a case study. The primary objective is to examine the efforts of Saudi Arabia\u27s sovereign wealth fund in diversifying revenue streams and mitigating risks associated with an excessive dependence on oil. To achieve this, the study proposes an adaptation of the subset-optimization algorithm within the mean-variance model, aiming to enhance portfolio construction in sovereign wealth funds. Chapter 2 of the dissertation conducts a comparative analysis between portfolios constructed using the subset-optimization algorithm and a benchmark portfolio that does not employ the algorithm. The findings show that the subset-optimized portfolios outperform the benchmark across various performance metrics. Notably, these portfolios exhibit higher Sharpe ratios, greater investor utility, and lower volatility compared to the benchmark. Additionally, the use of the algorithm leads to reduced exposure to oil beta across different subset sizes. Notably, as the subset size decreases, the portfolio\u27s volatility also decreases, suggesting the algorithm\u27s effectiveness in diversification. In Chapter 3, the research explores advanced estimation strategies for portfolio construction, considering two distinct cases. The first case incorporates a four-factor model, including the Carhart four-factor model, along with an additional factor specifically related to oil. The second case uses the Bayesian-shrinkage estimator for estimating the variance–covariance matrix and incorporates an informative prior within a Bayesian framework to estimate expected returns. Comparisons among the different models and inputs demonstrate that these advanced estimation techniques lead to improved portfolio performance. Specifically, the Sharpe ratio and investor utility are enhanced, indicating the contribution of these cutting-edge techniques to the creation of more effective and efficient portfolios. Overall, the findings highlight the algorithm\u27s potential to enhance risk-adjusted returns, reduce exposure to specific market factors such as oil, and ultimately contribute to the overall enhancement of portfolio management

Video sebagai E-portfolio Mahasiswauntuk Meningkatkan Keterampilan Mahasiswa

      The development of science and technology information in the era of globalization  so advanced. This phenomenon results in a change in all aspects of life, including one of them is the educational aspect. The use of technology in education is done in order to improve the efficiency and effectiveness of the learning process. However, the growing use of technology is not widely used lecturers to change the way student assessment. Student assessment is focussed on learning outcomes not only of the process of change as a result of the student\u27s ability to learn. the use of portfolios also require adequate storage space and requires no small cost. Therefore we need a valuation technique that directs faculty to assess student skills or psychomotor aspects. By using the technique of portfolio assessment with the use of the video as a result be able to answer all the problems that exist. This journal will discuss how assessment techniques, portfolio assessment, the transition of the portfolio into an e-portfolio, the use of video as a medium of e--portfolio also discusses the problems encountered in the portfolio assessment. Besides, there are advantages and disadvantages of the use  of video  as a medium  of e--portfolio.   In the implementation  of this journal featuring two case studies of e--portfolio with student video uploaded on YouTube and shown in the playlist in Magics Channel owned Perguruan Tinggi Raharj

Brass Bands In and Out of Context – An exploration and critical reflection of my recent creative practice, focussing on atypical works for the traditional brass band

This critical commentary presents a brief historical context of the traditional brass band and my personal connection to it as a performer and composer, exploring the implications of this upon my own artistic practice. The complementary writing that follows examines a selection of works from my recent creative output that challenge the traditional brass band paradigm, as demonstrated in the accompanying portfolio of original compositions. Each chapter is dedicated to a subdivision within the portfolio, focussing on specific compositional elements that reflect atypical brass band styles, including the application of electronics, the use of advanced idiomatic techniques and writing for multiple layered ensembles, with differentiation. Concluding with reflections on my compositional practice and work within education, the ensuing discourse investigates the impact legacy of the work itself, with anthropological observations