Portfolio Management Methods Research Articles

A Portfolio Management Method for Process Mining-Enabled Business Process Improvement Projects

AbstractProcess mining has received tremendous attention from research and industry, establishing itself as a highly sought-after technology. Despite the technological maturity of process mining solutions, which has been achieved through extensive investments in research and development, organizations still face the challenge of elusive value when systematically adopting process mining. The authors attribute this dilemma to a lack of support for scaling and managing process mining project portfolios. To address this practical need and research gap, the authors propose a method for managing portfolios of so-called process mining value cases, which are defined as process mining-enabled business process improvement projects, towards an evolutionary roadmap (mapper). The method is designed to support organizations identify portfolios of process mining projects that generate value by improving business processes. The method was developed through a combination of design science research and situational method engineering and comprises five activities that each outline techniques, roles, and tools: strategize, identify, select, implement, and monitor. The method has been instantiated as a software prototype and iteratively evaluated for applicability and real-world fidelity by involving an expert panel of academics and practitioners. The usefulness of the artifact was substantiated through a real-world case study in a naturalistic setting.

Curriculum learning empowered reinforcement learning for graph-based portfolio management: Performance optimization and comprehensive analysis

Portfolio management (PM) is a popular financial process that concerns the occasional reallocation of a particular quantity of capital into a portfolio of assets, with the main aim of maximizing profitability conditioned to a certain level of risk. Given the inherent dynamicity of stock exchanges and development for long-term performance, reinforcement learning (RL) has become a dominating solution for solving the problem of portfolio management in an automated and efficient manner. Nevertheless, the present RL-based PM methods just take into account the variations in prices of portfolio assets and the implications of price variations, while overlooking the significant relationships among different assets in the market, which are extremely valuable for managerial decisions. To close this gap, this paper introduces a novel deep model that combines two subnetworks; one to learn a temporal representation of historical prices using a refined temporal learner, while the other learns the relationships between different stocks in the market using a relation graph learner (RGL). Then, the above learners are integrated into the curriculum RL scheme for formulating the PM as a curriculum Markov Decision Process, in which an adaptive curriculum policy is presented to enable the agent to adaptively minimize risk value and maximize cumulative return. Proof-of-concept experiments are performed on data from three public stock indices (namely S&P500, NYSE, and NASDAQ), and the results demonstrate the efficiency of the proposed framework in improving the portfolio management performance over the competing RL solutions.

Implementation of value-oriented project portfolio management for the development of complex system

ObjectivesThe aim of the article is to set the problem of forming the optimal value-oriented portfolio of the development of a complex system, taking into account the mutual influence of the components of the portfolio on each other.Material and methodsThe research used: project portfolio management methods; systems theory and system analysis (for the formalization of value-oriented management processes); mathematical modeling tools (for the formation of basic models of portfolio management).ResultsThis article provides a basic methodological framework for portfolio management of organizational development. The conceptual framework for portfolio management has been formalized, where portfolio management processes are considered as a means of implementing strategic decisions.ConclusionsThe success of development portfolio management should not only be measured by the economic component, but also by the values that influence the sustainable development of the region. The current legal framework for the design and implementation of public projects in Ukraine is not up to date, as confirmed by the findings of international experts and domestic scientists.

CREDIT RISK MANAGEMENT OF “HALYK BANK” JSC: PROBLEMS AND SOLUTIONS

The purpose of the research work is to reveal the essence of the credit risk system, study the causes of its occurrence, and conduct a detailed analysis of the loan portfolio and credit risk management methods on the example of the commercial bank "Halyk Bank of the Republic of Kazakhstan" JSC. The authors analyze the loan portfolio of the bank using CAMELS, Z - score methods and build a regression analysis using R-studio, identify the main problems in credit risk management in a commercial bank and propose some solutions. In this article such problems in credit risk management as incomplete credit risk assessment, weak credit risk monitoring, insufficient collateral assessment, improper risk diversification, insufficient credit risk management policy are identified, and several solutions and methods for their improvement are proposed. The informational approach to solving the set goals is formed based on existing scientific research, published periodicals, scientific articles and financial statements of the bank, and its statistical data is used as material for writing a research paper.

A State-of-the-Art Review of Probabilistic Portfolio Management for Future Stock Markets

Portfolio management has long been one of the most significant challenges in large- and small-scale investments alike. The primary objective of portfolio management is to make investments with the most favorable rate of return and the lowest amount of risk. On the other hand, time series prediction has garnered significant attention in recent years for predicting the trend of stock prices in the future. The combination of these two approaches, i.e., predicting the future stock price and adopting portfolio management methods in the forecasted time series, has turned out to be a novel research line in the past few years. That is, to have a better understanding of the future, various researchers have attempted to predict the future behavior of stocks and subsequently implement portfolio management techniques on them. However, due to the uncertainty in predicting the future, the reliability of these methodologies is in question, and it is unclear to what extent their results can be relied upon. Therefore, probabilistic approaches have also entered the research arena, and attempts have been made to incorporate uncertainty into future forecasting and portfolio management. This issue has led to the development of probabilistic portfolio management for future data. This review paper begins with a discussion of various time-series prediction methods for stock market data. Next, a classification and evaluation of portfolio management approaches are provided. Afterwards, the Monte Carlo sampling method is discussed as the most prevalent technique for probabilistic analysis of stock market data. The probabilistic portfolio management method is applied to future Shanghai Stock Exchange data in the form of a case study to measure the applicability of this method to real-world projects. The results of this research can serve as a benchmark example for the analysis of other stock market data.

Multivariate Profile Monitoring Method

Several authors refer to product portfolio management as an essential process because it may be used as a corporate management tool. However, the product portfolio management methods which are often adopted have limitations that prevent its use in practice, mainly due to the high dimensionality of selecting an optimal portfolio. Moreover, the large amount of available data is a relevant issue for practical applications. Thus, the contribution of this article is to propose a method for the product life cycle to monitor time-series behaviour patterns. The goal is to identify changes that may indicate that the product portfolio needs to be revised. The proposed method uses a multivariate regression model to relate financial variables associated with the products portfolio, the performance of products against competition, and even macroeconomic data. The objective is, through profile monitoring, to identify the specific time for the product portfolio review decision-making. We adopted three tools to develop a method – principal component analysis, multivariate regression model, and profile monitoring with Hotelling T 2 Control chart. A Monte Carlo simulation validated the approach. The results showed false alarm rate and average time to signal to be similar to previous studies. Finally, the application of the model is illustrated in a real case, using data provided by a company’s portfolio of agricultural equipment.

Information technology for choosing the project portfolio management approach and the optimal level of maturity of an organization

The choice of a project portfolio management approach has a significant impact on the effectiveness of the organization. However, each organization that carries out project activities must not only choose a project portfolio management approach, but also the degree to which its capabilities are used. This degree determines an organization's level of maturity in project portfolio management. There are many models of maturity known. The use of such models often involves a long study and costs organizations a lot of money. The paper is aimed at creating an information technology for choosing a project portfolio management approach and the optimal level of maturity of the organization in the field of project portfolio management. This information technology is created and presented in the form of IDEF0 diagram. Using information about the organization and the environment, experts can investigate the application of different alternative project portfolio management approaches. When performing this analysis, they use the Project Portfolio Management Approach Selection Method and the Organizational Maturity Level Selection Method for Portfolio Management. Using the first of these methods, experts can select the most appropriate approach based on two criteria: the risks from non-performance or imperfect performance of the processes of the generalized portfolio management process table and the cost of performing the approach processes. The second method is used to assess an organization's level of maturity in portfolio management and select the optimal level of maturity. Information technology is based on two developed applications. The first solution is designed to select the project portfolio management approach. The second application solves the problem of choosing the level of maturity of the organization in the field of portfolio management Projects. The applications have an intuitive interface. Both applications have been tested and are ready for use. Information technology is intended for use by project portfolio managers.

Parameter uncertainty in policy planning models: Using portfolio management methods to choose optimal policies under world market volatility

Even accurate and precisely specified models with excellent underlying data quality can be inhibited by parameter uncertainty that reflects uncertain factors. This paper suggests adopting portfolio management methods from finance in policy planning models as a practical tool for explicitly reckoning the parameter uncertainty when defining optimal policy. We demonstrate the approach in an economywide model that aims to find an optimal pro-poor agricultural value chain in Senegal under the world market uncertainty. We show that prioritizing the rice sector is the most effective policy in terms of expected policy return, but this policy is also associated with the highest risk, increasing poverty under unfavorable yet realistic scenarios. However, like diversified portfolios in finance, balancing rice promotion with support for other sectors can reduce risk at the cost of reduced expected policy return. The suggested methodology allows for explicit risk-based decision-making and can be used in policy prioritization models that cannot define robust optimal policy under standard parameter sensitivity analysis tests.

Modern methods of data mining: Applicability in the securities market

Subject. The article addresses data mining methods, their applicability in the securities market. Objectives. The aim is to identify the specifics of using modern data mining methods in the stock market, outline basic tenets for building a combined data mining model. Methods. The study rests on logical and systems approaches, general scientific methods of analysis and synthesis, and comparative analysis. Results. Based on the analysis of existing works and models, the paper unveils the specifics of using modern methods of data mining in the stock market, defines the main postulates for building a data mining model. The findings can be used by financial market participants, State authorities, and research and educational organizations. Conclusions. Today, data mining methods are an alternative to the traditional portfolio analysis and management methods, being a logical continuation of them due to the ability to work with a large amount of diverse information and use approaches that overcome the shortcomings and limitations of other methods. To build a model of data mining to evaluate assets and portfolio management in the securities market, it is necessary to combine several methods of different models, combine the fundamental and technical analysis, and create systems for identifying asset volatility.

Multiagent-based deep reinforcement learning for risk-shifting portfolio management

The growing popularity of quantitative trading in pursuit of a systematic and algorithmic approach to investment has drawn considerable attention among traders and investment firms. Consequently, an effective computational method for evaluating potential risk factors and returns is crucial for the development of algorithmic trading strategies. In traditional finance and financial engineering research, statistical approaches have been widely applied to quantitative analysis. Meanwhile, investor demand for quantitative hedge funds has surged worldwide. In the current study, the multiperiod portfolio selection problem was considered in terms of the realistic transaction cost model, which is a major concern for quantitative hedge fund managers. We developed a dedicated multiagent-based deep reinforcement learning framework with a two-level nested agent structure to determine effective portfolio management methods with different objectives. In addition, we proposed a specially-designed reward function for investment performance evaluation and a novel policy network structure for trading decision-making. To efficiently identify specific asset attributes in a portfolio, each agent is equipped with a refined deep policy network and a special training method that enables the proposed reinforcement learning agent to learn risk transfer behaviors. The results revealed the effectiveness of our proposed framework, which outperformed several established or representative portfolio selection strategies.

CHANGE-МЕНЕДЖМЕНТ И AGILE-МЕТОДЫ В РАЗВИТИИ МОТИВАЦИОННОЙ ПОЛИТИКИ КОМПАНИИ

The introduction of flexible project methods, or agile transformation, is perceived by many as a magic pill that will instantly solve most of the existing problems. But in practice, it turns out that it is not as easy to effectively carry out agile transformation as it seemed: some approaches do not work partially or at all, employees (from an ordinary manager to a top) desperately resist innovations, and more time is spent on the transition to flexible project management than we would like. The modern economic reality is changing rapidly, and customer expectations are changing no less quickly. The speed of change encourages companies to invest heavily in digital and agile transformations that allow them to scale and bring the benefits of agile teams to the level of the entire enterprise. However, few people achieve the desired results. To fully implement digital or agile transformation, commercial and technology teams must achieve and maintain consistency. Full company-wide consistency is the most important condition for competitiveness in the modern economy. The difficulty of combining agile teams into an agile company lies in the emerging gap between the teams that perform the work and the teams that distribute the funding. To bridge this gap, managers need the opportunity to: - increase visibility – visually present the work in backlogs (for plans) and demonstrations (for new solutions); - understand the workflow – analyze step-by-step results in order to assess progress in achieving the final results; - optimize investments – change the strategy or persistently follow the plan, redistributing funds to maximize the acceleration of value delivery. In an effort to achieve and maintain consistency, companies often find that traditional methods of portfolio management are ineffective. Instead, many implement Lean Portfolio Management methods to ensure consistency throughout the organization. The Lean Portfolio Management (LPM) methodology describes the principles of lean management that top management applies to align strategy with execution. Portfolio management teams study the company's strategies and allocate budget funds for the implementation of this strategy.

Проектное управление инфраструктурой сети оператора связи в условиях трансформации состояния внешней среды

The analysis revealed trends in the development of the telecommunications market associated with an increase in the involvement of information services in various technological processes, a continuous change in the regulatory framework that regulates the functioning of telecom operators, the complication of organizational processes and the use of a wide variety of equipment and information systems in the operation of communication networks. As a result, information uncertainty is generated among decision-makers in the process of operating and developing the network infrastructure of a telecom operator. To eliminate the uncertainty, a methodology is proposed for managing the network infrastructure of a telecom operator in the context of the transformation of the state of the external environment. Within the framework of the methodology, the management of the network infrastructure is based on the representation of each control action as a separate project, and the sequence of the provided control actions in the form of a portfolio of projects. At the stage of monitoring the state of the network, the indicators of economic efficiency and reliability of the telecommunication system and its individual elements are assessed. The parameters of the external environment that surrounds the network infrastructure are also subject to control. If the indicators deviate from the permissible values, a control cycle is launched, during which the state of the elements of the network infrastructure and sections of the coverage area is analyzed. Based on the results of the analysis, the network elements are grouped by types, control actions that must be provided to maintain the operational characteristics of the network infrastructure. Then the formation of projects of control actions is carried out, which are added to the portfolio of corrective actions provided. As a result, project portfolio management methods become applicable to such management influences. The application of these methods allows solving the problems of workforce management and resources management when providing control actions to network infrastructure. The use of the methodology opens up opportunities for the development of OSS / BSS systems in the field of improving the solution of the resources managing problems of a telecom operator by organizing the planning of measures to provide control actions on the network infrastructure.

ADAPTIVE PORTFOLIO MANAGEMENT OF ENERGY SAVING PROJECTS AT A METALLURGICAL ENTERPRISE

Today, the problem of creating and implementing methodological foundations for managing portfolios of energy saving projects at metallurgical enterprises is urgent, taking into account strategic goals, limited resources and risks. The solution to this problem is complicated by the fact that it is necessary to take into account the many interrelated flows of energy resources, requirements, goals and strategies of behavior of individual subdivisions of metallurgical enterprises, as well as the dynamics of production processes, etc. The subject of the article is adaptive methods of portfolio management of energy saving projects at metallurgical enterprises. The purpose of this work is to create methods for the formation and adaptive management of the project portfolio, taking into account the strategic goals of the metallurgical enterprise for energy saving and energy efficiency. The following tasks are solved: analysis and comparison of traditional and adaptive project management processes; description of the main provisions of the methodology of predictive adaptation in the management of the portfolio of energy-saving projects of the metallurgical enterprise; detailed consideration of the stages of formation and implementation of the portfolio of energy saving projects of the metallurgical enterprise; consideration of the results of the assessment of the importance of the criteria in substantiating the priorities of the energy strategy of the enterprise; discussion of the results of the formation of the energy saving program at PJSC Dneprospetsstal. Research methods: portfolio management methods, forecasting methods, expert-analytical methods, risk management methods. The following results were obtained: The substantiation of expediency of use of adaptive management of energy saving projects at the metallurgical enterprise is carried out. The stages of strategic planning for energy saving and energy efficiency, the stages of formation and implementation of the portfolio of energy saving projects of the metallurgical enterprise are described. The results of the formation of the energy saving program at PJSC Dneprospetsstal were considered. Conclusions: Building a management system for energy saving projects and programs at metallurgical enterprises requires solving the problem of predictive analysis of energy consumption and fuel and energy balance with subsequent implementation of adaptive mechanisms for planning, monitoring and change management, which allows more efficient formation and implementation of energy saving projects and projects. to promote the increase of energy efficiency and competitiveness of the enterprises of the metallurgical industry of Ukraine.

Deep reinforcement learning for portfolio management of markets with a dynamic number of assets

This work proposes a novel portfolio management method using deep reinforcement learning on markets with a dynamic number of assets. This problem is especially important in cryptocurrency markets, which already support the trading of hundreds of assets with new ones being added every month. A novel neural network architecture is proposed, which is trained using deep reinforcement learning. Our architecture considers all assets in the market, and automatically adapts when new ones are suddenly introduced, making our method more general and sample-efficient than previous methods. Further, transaction cost minimization is considered when formulating the problem. For this purpose, a novel algorithm to compute optimal transactions given a desired portfolio is integrated into the architecture. The proposed method was tested on a dataset of one of the largest cryptocurrency markets in the world, outperforming state-of-the-art methods, achieving average daily returns of over 24%.

Practical Applications of Adaptive Portfolios and the Power of Diversification

<h3>Practical Applications Summary</h3> In <b>Adaptive Portfolios and the Power of Diversification</b>, in the August 2019 edition of <b><i>The Journal of Investing</i>, Jürgen Vandenbroucke</b> of <b>KBC Asset Management NV</b> describes a discretionary method for portfolio management that addresses investor emotions at the individual, investment-product, and portfolio levels. By adding “a behavioral component to the prevailing risk-based paradigm,” he subscribes to the adaptive market hypothesis (Lo 2004), which concerns how individuals’ emotions may negate rational investment decision-making. Vandenbroucke highlights the common consequences of emotion-driven investing. He then proposes remedies in the areas of investor profiling, product positioning, and portfolio construction. He distinguishes between investor attitudes toward “risk,” as measured by the variance of returns, and “loss,” as measured in terms of an investment’s potential gain versus its potential losses. This amounts to operating beyond the confines of a classical mean–variance framework and considering the entire shape of the distribution of future returns (which may be non-normal). He differentiates among investment products along spectrums of mean versus variance and upside potential versus downside hazard. Finally, he shows how to weight selected investment products to align investors’ loss aversion with a balance between upside potential and downside risk in a portfolio. This weighting allows a portfolio to inhabit an investor’s “comfort zone” by adjusting its allocations as market conditions change. A customer-centered adaptive portfolio of this kind enhances diversification and can temper emotionally driven trading activity that would otherwise be a drag on performance. <b>TOPICS:</b>Wealth management, portfolio construction, statistical methods

Evaluation methods for portfolio management

AbstractWe distinguish the evaluation methods for two main kinds of investment strategies, namely, passive and active portfolio management. Passive portfolio management aims at tracking an underlying index as close as possible with the most important measure being the tracking error. To claim the tracking error not exceeding a certain threshold, we apply the concept of noninferiority test as opposed to the common malpractice of one‐sided test, which tries to accept the null hypothesis when there is insufficient evidence to reject it. In contrast, the normal one‐sided test should be adopted in active portfolio management, which requires another crucial statistic, the information ratio, of an active portfolio to exceed the underlying benchmark in a risk adjusted sense. The asymptotic variances of the tracking error and the difference between two information ratios are derived, which allow proper evaluation and comparison of strategies within the passive and active portfolio management frameworks.

Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States

Portfolio management (PM) is a fundamental financial planning task that aims to achieve investment goals such as maximal profits or minimal risks. Its decision process involves continuous derivation of valuable information from various data sources and sequential decision optimization, which is a prospective research direction for reinforcement learning (RL). In this paper, we propose SARL, a novel State-Augmented RL framework for PM. Our framework aims to address two unique challenges in financial PM: (1) data heterogeneity – the collected information for each asset is usually diverse, noisy and imbalanced (e.g., news articles); and (2) environment uncertainty – the financial market is versatile and non-stationary. To incorporate heterogeneous data and enhance robustness against environment uncertainty, our SARL augments the asset information with their price movement prediction as additional states, where the prediction can be solely based on financial data (e.g., asset prices) or derived from alternative sources such as news. Experiments on two real-world datasets, (i) Bitcoin market and (ii) HighTech stock market with 7-year Reuters news articles, validate the effectiveness of SARL over existing PM approaches, both in terms of accumulated profits and risk-adjusted profits. Moreover, extensive simulations are conducted to demonstrate the importance of our proposed state augmentation, providing new insights and boosting performance significantly over standard RL-based PM method and other baselines.

CONCEPTUAL MODEL OF PROJECT-ORIENTED MANAGEMENT OF EDUCATIONAL ACTIVITIES OF HIGHER EDUCATION INSTITUTIONS

The subject matter of the article is the methods, models and mechanisms of project-oriented management of the educational activities of higher education institutions. The goal of the work is to develop a conceptual model for managing the educational activities of higher education institutions on the basis of a project-oriented approach. The following tasks were solved in the article: analysis of the educational activity management model of higher education institutions, the study of modern methods of managing university educational projects portfolios, the development of a mechanism for the formation of a conceptual model of project-oriented management of educational activities of higher education institutions. The following methods are used – project and portfolio management methods, systems theory and systems analysis, risk management methods. The following results were obtained – the main stages of the life cycle, their products and the mission of the project "Introductory Campaign of Higher Education Institutions" were identified, the concept of "educational product", "product of an educational project", "educational project", "educational activity project" was defined, a model for determining introductory campaign project values and effectiveness, a conceptual model of project-oriented management of educational activities of higher education institutions has been developed taking into account the value of the project "Introductory Campaign of Higher Education Institutions". Conclusions: ensuring the effectiveness of the implementation of the project approach in the ongoing activities of higher education institutions should be based on a clear identification of the attributes of these projects, including products, values and effectiveness, which will allow not only to clearly understand the result of project activities, but also to control its receipt. The implementation of the concept of project-oriented institutions of higher education will increase the efficiency of the current activities of universities and their development by using the advantages of project management technologies. The definition "Mission of the project "Introductory Campaign of Higher Education Institutions" is proposed, which is understood as the achievement of the maximum possible enrollment of students in the current conditions on the educational services market. The value of the "Introductory Campaign of the Higher Education Institution" project has been established, which determines the usefulness of the project product for stakeholders. The proposed conceptual model of a project-oriented approach to the management of educational activities of higher education institutions will allow to extend the project approach to the development and functioning of various blocks of the university’s activities based on the introduced concept of "product portfolio of higher education institutions". Such an approach in the future will make it possible to clearly identify the totality of university projects as part of educational activities and turn its current activities into a portfolio of projects.

Identifying path of Global Financial Crisis Contagion Direction on Industries of Iran Stock Market

Simultaneous understanding of volatilities and changes in financial markets is very important to optimize the portfolio and risk management methods. The 2008 financial crisis led into devaluation of most assets, increased volatilities and endangered several institutional investors' survival. When the stock market' correlation is highly enhanced, risk and return management with the classic portfolio theory becomes severely challenging. In this study, to manage systematic and non-systematic risks by investors and policymakers in case of similar financial crises, the Effect of global financial crisis contagion is examined through the path of S&P500 global index, and DFM regional index of different industries of Iran Stock Market is examined using DFGM contagion test and stochastic Ornstein Uhlenbech process. The results show that Dubai Stock Market has an important role in crisis expansion into different sectors of Iran Stock Markets so that the fundamental contagion effects are channelled via this direction. Also, according to the results, the starting point of the global financial crisis contagion was the basic metals industry, and the contagin happened in metal ores and petroleum products sectors with different rates. Finally, the global financial crisis is spread into different industries of Iran Stock Market via financial links and not trough commercial ones. Identifying the direction of contagion of financial crisis provides an opportunity for investors to apply hedging and asset allocation strategies optimally.

ПРИМЕНЕНИЕ AGILE-МЕТОДОВ И LEAN PORTFOLIO MANAGEMENT (LPM) В МОТИВАЦИИ КОМАНДНОЙ РАБОТЫ КОМПАНИИ

The world is changing rapidly, and customer expectations are changing just as quickly. The speed of change encourages companies to invest heavily in digital and agile transformations that scale and bring the benefits of agile teams to the enterprise level. However, few people achieve the desired results. To fully implement digital or agile transformation, commercial and technology teams must achieve and maintain consistency. Full company-wide consistency is a critical condition for competitiveness in today's economy. The difficulty of combining agile teams into an agile company is the resulting gap between the teams that do the work and the teams that distribute the funding. To bridge this gap, managers need the ability to: - increase visibility-visually present work in backlogs (for plans) and demos (for new solutions); - understand the workflow – analyze step-by-step results to assess progress towards achieving the final results; - optimize investment-change strategy or persistently follow a plan, reallocating funds to maximize the delivery of value. In an effort to achieve and maintain consistency, companies often find that traditional portfolio management methods are ineffective. Instead, many implement Lean Portfolio Management techniques to ensure consistency across the organization. The Lean Portfolio Management (LPM) methodology describes the principles of lean management that top management applies to align strategy with execution. Portfolio management teams study the company's strategies and allocate budget funds to implement this strategy. Like any portfolio, an LPM investment portfolio can be creatively defined as well as actively managed throughout the investment lifecycle. LPM focuses on aligning agile development with business strategy and creating value for customers through product and solution development. LPM in combination with agile development methods allows you to increase the flexibility of your business.