Brown’s Weighted Exponential Moving Average Implementation in Forex Forecasting

In 2016, a time series forecasting technique which combined the weighting factor calculation formula found in weighted moving average with Brown’s double exponential smoothing procedures had been introduced. The technique is known as Brown’s weighted exponential moving average (B-WEMA), as a new variant of double exponential smoothing method which does the exponential filter processes twice. In this research, we will try to implement the new method to forecast some foreign exchange, or known as forex data, including EUR/USD, AUD/USD, GBP/USD, USD/JPY, and EUR/JPY data. The time series data forecasting results using B-WEMA then be compared with other conventional and hybrid moving average methods, such as weighted moving average (WMA), exponential moving average (EMA), and Brown’s double exponential smoothing (B-DES). The comparison results show that B-WEMA has a better accuracy level than other forecasting methods used in this research

Big 5 ASEAN capital markets forecasting using WEMA method

ASEAN through ASEAN Economics Community (AEC) 2020 treaty has proposed financial integration via capital markets integration in order to aim comprehensive ASEAN economic integration. Therefore, the need to have a proper prediction of ASEAN capital market becomes a major issue. In this study, we took big 5 ASEAN capital markets, i.e. Straits Times Index (STI), Kuala Lumpur Stock Exchange (KLSE), Stock Exchange of Thailand (SET), Jakarta Stock Exchange (JKSE), and Philippine Stock Exchange (PSE) to be forecasted using WEMA method. Weighted Exponential Moving Average (WEMA) is a new hybrid moving average method which combines the weighting factor calculation in Weighted Moving Average (WMA) with the procedure of Exponential Moving Average (EMA). WEMA has successfully been implemented and used to forecaste discrete time series data, but never being used to forecast ASEAN capital markets. In this study, we took further action by implementing the WEMA method with brute force approach for scaling factor tuning on big 5 ASEAN capital markets. From the experimental results, we found that WEMA has successfully forecasted all those exchanges. By looking at the forecast error measurement, it gives the best performance on PSE and worst performance on SET dataset among all datasets being considered in this study

WEMA versus B-WEMA Methods in Forex Forecasting

Weighted Exponential Moving Average (WEMA) method is a new hybrid moving average method which combines the weighting factor calculation found in Weighted Moving Average method with Exponential Moving Average method. It had been proven on previous study that the method can give a better accuracy and robustness levels compared to other conventional moving average methods. Another study which combined the Weighted Moving Average method with Brown's Double Exponential Smoothing method had also been done. The proposed method is known as Brown's Weighted Exponential Moving Average (B-WEMA) method and had been proven to excel other conventional moving average methods in terms of the accuracy and robustness levels. In this study, we will try to compare WEMA and B-WEMA forecasting methods in time series analysis, especially in forecasting. We will implement both methods to forecast three major foreign exchange (forex) data transactions and compare the performance of both methods by using Mean Square Error and Mean Absolute Percentage Error criteria. From the experiments taken, it can be concluded that WEMA and B-WEMA have quite the same accuracy and robustness levels due to their slightly same MSE and MAPE values

Stochastic calculus and derivatives pricing in the Nigerian stock market

Led by the Central Bank of Nigeria (CBN) and the Nigerian Stock Exchange (NSE), policy makers, investors and other stakeholders in the Nigerian Stock Market consider the introduction of derivative products in Nigerian capital markets essential for their investment and risk management needs. This research foregrounds these interests through detailed theoretical and empirical review of derivative pricing models. The specific objectives of the research include: 1) To explore the key stochastic calculus models used in pricing and trading financial derivatives (e.g. the Black-Scholes model and its extensions); 2) To examine the investment objectives fulfilled by derivatives; 3) To investigate the links between the stylized facts in the Nigerian Stock Market (NSM), the risk management techniques to be adopted, and the workings of the pricing models; and 4) To apply the research results to the NSM, by comparing the investment performance of selected derivative pricing models under different market scenarios, represented by the stylized facts of the underlying assets and market characteristics of the NSM. The foundational concepts that underpin the research include: stochastic calculus models of derivative pricing, especially the Black-Scholes (1973) model; its extensions; the practitioners’ Ad-Hoc Black Scholes models, which directly support proposed derivative products in the NSM; and Random Matric Theory (RMT). RMT correlates market data from the NSM and Johannesburg Stock Exchange (JSE) and facilitates possible simulation of non-existing derivative prices in the NSM, from those in the JSE. Furthermore, the research explores in detail the workings of different derivative pricing models, for example various structures for the Ad-Hoc Black Scholes models, using selected underlying asset prices, to determine the applicability of the models in the NSM. The key research findings include: 1) ways to estimate the parameters of the stochastic calculus models; 2) exploring the benefits of introducing pioneer derivative products in the NSM, including risk hedging, arbitrage, and price speculation; 3) using NSM stylized facts to calibrate selected derivative pricing models; and 4) explaining how the results could be used in future experimental modelling to compare the investment performance of selected models. By way of contributions to knowledge, this is the first study known to the researcher that provides in-depth review of the theoretical and empirical underpinnings of derivative pricing possible in the NSM. This forms the basis for the Black Scholes approach to asset pricing of European option contract, which is the kind of call/put option contract that is being adopted in the NSM. The research provides the initial foundations for effective derivatives trading in the NSM. By explaining the heuristics for developing derivative products in the NSM from JSE information, the research will support future work in this important area of study

Understanding Customer Switching Behaviour in the Retail Banking Sector: The Case of Nigeria and the Gambia

This thesis examines customer switching behaviour in Nigeria and Gambia, focusing on the retail banking sector. The study’s key objective is to provide new knowledge on customer banking behaviour in the retail banking sector. The study is grounded in Bansal et al.’s (2005) push-pull-mooring model. A qualitative method was employed in the data collection, incorporating a triangulation approach, whereby direct observations were combined with thematic interviews and focus group discussions. The intention behind this method was to increase the validity of the research results. Ultimately, the study findings indicate significant factors and subfactors influencing customer switching behaviour in the retail banking sector. The results are categorised as push, pull, or mooring factors. It identifies seven push factors with thirteen subfactors, four pull factors with ten subfactors, and six mooring factors with three subfactors. The study’s significant contribution to existing knowledge of services marketing is the identification of new and emerging constructs, thus extending the existing knowledge in the literature. The study’s findings support numerous results of prior relevant research, while some findings disagree with those of previous research. Furthermore, the new constructs that emerge from this research are highly relevant to today’s consumers. For example, factors like banking products, perceived knowledge of banking products, perceived relative security of banking products, satisfaction with the current bank, emotions (e.g., regret or anger), liquidity challenges, bank staff career development prospects, and ethical banking issues are the study’s unique contributions to the push factors and subfactors. In addition, the emerging pull factors and subfactors include technological advancement, coronavirus pandemic-induced switching, a bank’s physical appearance, positive banking expectations, a bank’s relative proximity, expected switching benefits, perceived usefulness of a bank’s digital platforms, perceived ease of banking transactions, personalised banking offerings, and repositioning banking business models. Lastly, the new mooring factors and subfactors identified in this study are inertia, changes in customer needs or tastes, involuntary switching, and bank responsiveness. Consequently, the author has developed a framework/model based on the findings of this study. The new framework/model presented comprehensive results with practical implications and a valuable contribution to the current knowledge of customer switching behaviour

Plant Biodiversity and Genetic Resources

The papers included in this Special Issue address a variety of important aspects of plant biodiversity and genetic resources, including definitions, descriptions, and illustrations of different components and their value for food and nutrition security, breeding, and environmental services. Furthermore, comprehensive information is provided regarding conservation approaches and techniques for plant genetic resources, policy aspects, and results of biological, genetic, morphological, economic, social, and breeding-related research activities. The complexity and vulnerability of (plant) biodiversity and its inherent genetic resources, as an integral part of the contextual ecosystem and the human web of life, are clearly demonstrated in this Special Issue, and for several encountered problems and constraints, possible approaches or solutions are presented to overcome these

Financialisation, Capital Accumulation and Economic Development : A Theoretical and Empirical Investigation of the Nigerian Economy

The primary focus of this study is to highlight those unobtrusive, yet fundamental, factors undermining economic development in Nigeria. To begin with, it posits that the decelerating pace of capital accumulation in Nigeria, which naturally occasions rising unemployment and poverty levels, and widening inequality gap, is the result of the ‘low possibility’ of capitalist enterprises in the country of earning an adequate rate of profit from their productive processes. In turn, the ‘low possibility’ is argued to be the result of the uneven development inherent in the modern capitalist structure, the high cost of capital and of production peculiar to Nigeria, and the ineffective demand for goods made in Nigeria: these elements are viewed as been precipitated by the contradictions of the contemporary political-economic arrangement that organises the Social Structures of Accumulation. For Nigeria to ‘develop’, it is contended that the unobtrusive elements inherent in the contradiction of the political-economic economic that undermine the capitalists’ ability to earn a commensurate rate of profit in the country needs to be fully addressed first. Furthermore, this study suggests that it is crucial the country embraces knowledge-based industrialisation if it is to achieve some form of ‘competitive advantage’ in the global market, which could enable its productive processes extract a commensurate level of profit from the market. To facilitate the knowledge-based industrialisation, the state should, not only create a conducive environment for industrial development but also play the lead role in transforming the peripheral and oil dependent economy to a knowledge-based economy by coordinating business organisations and investing in high-risk innovations