Application of the scrum framework in non-software project management

Scrum is an agile project management approach that has been widely practiced in the software development projects. It has proven to increase quality, productivity, customer satisfaction, transparency and team morale among other benefits from its implementation. The concept of scrum is based on the concepts of incremental innovation strategies, lean manufacturing, kaizen, iterative development and so on and is usually contrasted with the linear development models such as the waterfall method in the software industry. The traditional approaches to project management such as the waterfall method imply intensive upfront planning and approval of the entire project. These sort of approaches work well in the well-defined stable environments where all the specifications of the project are known in the beginning. However, in the uncertain environments when a project requires continuous development and incorporation of new requirements, they do not tend to work well. The scrum framework was inspiraed by Nonaka’s article about new product developement and was later adopted by software development practitioners. This research explores conditions for and benefits of the application of scrum framework beyond software development projects. There are currently a few case studies on the scrum implementation in non-software projects, but there is a noticeable trend of it in the scrum practitioners’ community. The research is based on the real-life context multiple case study analysis of three different non-software projects. The results of the research showed that in order to succeed within scrum projects need to satisfy certain conditions – necessary and sufficient. Among them the key factors are uncertainty of the project environment, not well defined outcomes, commitment of the scrum teams and management support. The top advantages of scrum implementation identified in the present research include improved transparency, accountability, team morale, communications, cooperation and collaboration. Further researches are advised to be carried out in order to validate these findings on a larger sample and to focus on more specific areas of scrum project management implementation.

Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

Meditationes sancti evangelii 88

Arkit: A-B4.

Computational Market Dynamics of Virtual Economies

The last two decades have provided a vast opportunity to live and explore the compulsive imaginary world or virtual world through massively multiplayer online role-playing games (MMORPGs). MMORPG gives a wide range of opportunities to its users to participate with multi-players on the same platform, to communicate and to do real time actions. There is a virtual economy in these games which is largely player-driven. In-game currency provides its users to build up their Avatars, to buy or sell the necessary goods to play, survive in the games and so on. As a part of virtual economies generated through EVE Online, this thesis mainly focuses on how the prices of the minerals in EVE Online behave by applying the Jabłonska- Capasso-Morale (JCM) mathematical simulation model. It is to verify up to what degree the model can reproduce the virtual economy behavior. The model is applied to buy and sell prices of two minerals namely, isogen and morphite. The simulation results demonstrate that JCM model ts reasonably well to the mineral prices, which lets us conclude that virtual economies behave similarly to the real ones.

Animal Spirits in Financial Markets: Agent-Based Model

In this work an agent based model (ABM) was proposed using the main idea from the Jabłonska-Capasso-Morale (JCM) model and maximized greediness concept. Using a multi-agents simulator, the power of the ABM was assessed by using the historical prices of silver metal dating from the 01.03.2000 to 01.03.2013. The model results, analysed in two different situations, with and without maximized greediness, have proven that the ABM is capable of explaining the silver price dynamics even in utmost events. The ABM without maximal greediness explained the prices with more irrationalities whereas the ABM with maximal greediness tracked the price movements with more rational decisions. In the comparison test, the model without maximal greediness stood as the best to capture the silver market dynamics. Therefore, the proposed ABM confirms the suggested reasons for financial crises or markets failure. It reveals that an economic or financial collapse may be stimulated by irrational and rational decisions, yet irrationalities may dominate the market.