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This paper used a discrete time microstructure model studying the hidden excess demand and market liquidity of financial market which are two unobservable state variables. Based on the model, the estimates of the two immeasurable state variables may be obtained using the Kalman filter and the maximum likelihood method. Contrast to conventional financial model, we apply the excess demand to determi...Show More
Asset allocation is an important decision problem in financial planning. In this paper, we study the multistage dynamic asset allocation problem which an investor is allowed to reallocate its wealth among a set of assets over finite discrete decision points, in which the stochastic return rates of the assets follow a Markov chain with nonstationary transition probabilities. The objective is to max...Show More
Dynamic construction of optimal portfolio is investigated. Multiple assets are allocated and rebalanced periodically based on different principles. We develop several dynamic allocation strategies to maximize long-term portfolio value based on Kelly's approach related to mutual information. We show that the resulting asset allocation strategy outperforms the traditional approaches and produces an ...Show More
This paper derives the optimal consumption and portfolio choice pattern over the life-cycle for households facing uninsurable labor income risk, ruin risk, stochastic capital markets, and uncertain lifetime. Our model posits a dynamic utility maximized with CRRA and Epstein-Zin preferences that has access to liquid stocks, bonds, and illiquid life annuities. The empirical results of this research ...Show More
Optimal asset allocation deals with how to divide the investor's wealth across some asset-classes in order to maximize the investor's gain. We consider the optimal asset allocation in a multi-period investment settings: optimal dynamic asset allocation provides the (optimal) re-balancing policy to accomplish some investment's criteria. Given a sequence of target sets, which represent the portfolio...Show More
A power supplier in a pool-based market needs to allocate his generation capacities to participate in contract and spot markets. In this paper, the optimal portfolio selection theory is introduced for this purpose. A model applying this theory is proposed to solve the supplier asset allocation problem. Real market data are used in a numerical study to test the proposed model. The results show that...Show More
A portfolio is an useful method to calculate the rate of expected earnings and risks based on changes in stock prices. However, past methods such as the fundamental analysis, the technical analysis and etc. are not proposed as a decision support system available for real investments. On the other hand, speaking about the asset allocation, those methods determine asset allocation ratio using genera...Show More
Efficiency improvement is the core element in state-owned assets management of colleges and universities. Internet thinking and technology create favorable conditions for efficiency improvement of assets management. In this study, state-owned assets data of colleges and universities were analyzed and typical problems against efficiency improvement of asset management was analyzed. Finally, strateg...Show More
This paper presents a development of the assets management system that purposely aspires to assist the Department of Highways (DOH), Ministry of Transportation, Thailand in managing their assets. Currently, the DOH has over hundred billions Thai Baht or approximately three billions USD in assets under management, which require a constant maintenance. The study initially focuses on an assessment of...Show More
Financial market microstructure model is a phenomenon model which describes financial markets based the microstructure theory. The initial values of the unknown parameters and/or states of the model have a great impact on the model identification, so an estimation method which combines genetic algorithm, Kalman filter and maximum likelihood method is presented to estimate the unknown parameters an...Show More
Chinese enterprises have been conducting low-end processing for foreign brands. In recent years, they want to get rid of this high-pay low-income pattern and develop towards the high-end of the value chain. Most of them are transforming to service-focused enterprises that aim to provide customers with customized service. In service-focused enterprises, the human asset - like industry experts, tech...Show More
Motivated by the Navy's interest in decision support tools that augment planning activities within a maritime operations center (MOC), we have developed a multilevel resource allocation model that is capable of interacting with human planners to dynamically allocate hierarchically-organized assets to process interdependent tasks in order to accomplish mission objectives. The planning problem is fo...Show More
Institutional investors manage their strategic mix of asset classes over time to achieve favorable returns in spite of uncertainties. A fundamental issue in this context is to maintain risk under control while achieving the desired return targets. When the asset mix is to be re-balanced many times over the investment horizon, the decision maker faces a rather difficult constrained dynamic optimiza...Show More
This study proposes a new method for optimizing household financial asset allocation (FAA) and developing scientific risk control strategies by integrating Internet of Things (IoT) data and clustering algorithms. IoT technology is utilized to collect real-time data, including macroeconomic indicators, market dynamics, and investor behavior. The data comes from national statistical offices, financi...Show More
The objective of this paper is to survey the literature from theoretical and the practical perspective of asset allocation and portfolio construction, and the ideal means of performing this mission is through portfolio management process. The efficient financial markets and behavioral finance are two different bases in which investors can evaluate best approach for asset allocation and security se...Show More
In this paper, asset-liability management model of China insurance companies is brought forward. Model's objective function is to maximize risk adjusted income, which not only considers the absolute income of insurance and investment business, but also the cost of risk capital occupied. In developing model's constraints, the business and regulatory characteristic of China insurance companies is co...Show More
In this paper, the duration gap and immunity conditions are used to control the interest rate risk and protect the equity rights. By using the time structure matching of assets-liabilities to control the time structure risk, the optimal model of assets and liabilities portfolio is established. The contributions of this paper lie on two aspects: firstly, it controls the liquidity risk through the t...Show More
We discuss an optimal asset allocation problem in a wide class of discrete-time regime-switching models including the hidden Markovian regime-switching (HMRS) model, the interactive hidden Markovian regime-switching (IHMRS) model and the self-exciting threshold autoregressive (SETAR) model. In the optimal asset allocation problem, the object of the investor is to select an optimal portfolio strate...Show More
Asset management is a crucial component of the asset management system in universities. However, there exists an issue with portfolio optimization not being optimal. Various reasons have led to problems such as low efficiency, high costs, and poor procurement outcomes in traditional management methods for university assets. To address this, a multi-objective genetic algorithm is proposed for multi...Show More
Asset allocation, diversification of investments across various asset classes, presents significant challenges in accurately forecasting expected returns and adapting to dynamic market conditions. This research explores a novel approach, “Opportunistic Balancing and Strategic Insights through Deep Reinforcement Learning in Asset Allocation,” by leveraging Deep Reinforcement Learning (DRL) to optim...Show More
We study the use of PPO (Proximal Policy Optimization) algorithm for trading ETFs belonging to different asset classes. The studied asset classes include common stocks, bonds, REIT (Real Estate Investment Trust), gold, and future contracts on agricultural commodities. When properly training the PPO agent with the proposed ratio allocation strategy, the agent outperforms the static, periodical reba...Show More
In the power industry deregulation era, an power supplier needs to optimal allocate its generation capacities for participating in different markets in order to maximize the return while control the risk of receiving the minimum profit below a certain level. This paper, based on a thorough analysis on the asset allocation problem of power suppliers, performs such an optimization using the proposed...Show More

Fast Distributed Near-Optimum Assignment of Assets to Tasks

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The Computer Journal
Year: 2010 | Volume: 53, Issue: 9 | Journal Article |
Cited by: Papers (8)
We investigate the assignment of assets to tasks where each asset can potentially execute any of the tasks, but assets execute tasks with a probabilistic outcome of success. There is a cost associated with each possible assignment of an asset to a task, and if a task is not executed, there is also a cost associated with the non-execution of the task. Thus, any assignment of assets to tasks will re...Show More

Fast Distributed Near-Optimum Assignment of Assets to Tasks

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Year: 2010 | Volume: 53, Issue: 9 | Journal Article |
The construction of an investment portfolio with tradable assets is one of the most studied problems in Finance and is done correctly through an optimal asset allocation. This research attempts to construct an efficient portfolio using an artificial intelligence approach using Particle Swarm Optimization (PSO) technique and the use of the genetic algorithm (GA) to find the best parameters setting ...Show More
Portfolio optimization is one of the most intriguing topics in the field of finance. The purpose is to maximize return while minimizing risk. In this paper, we investigate the experimental performance of the classical Markowitz portfolio optimization with and without rebalancing based on the minimum risk in terms of portfolio return, portfolio risk, and Sharpe ratio, and compare the results to the...Show More