Search results

This study aims to determine whether, by means of the application of genetic algorithms (GA) through the traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than those that would be obtained using technical analysis investment strategies following a traditional approach (TA) and the buy and hold (B&H) strategy.

The study was carried out based on the daily price records of the NASDAQ financial asset during 2013–2017. TA approach was carried out under graphical analysis applying the standard MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic operators (i.e. crossover and mutation) were adopted as based on the chromosome customization and fitness evaluation. The chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome. For each chromosome, buy and sell indexes of the strategy were considered. Fitness evaluation served to defining the evaluation strategy of the chromosomes in the population according to the fitness function using the returns gained in each chromosome.

The paper provides empirical-theoretical insights about the effectiveness of GA to overcome the investment strategies based on MACD and B&H by achieving 5 and 11% higher returns per year, respectively. GA-based approach was additionally capable of improving the return-to-risk ratio of the investment.

Limitations deal with the fact that the study was carried out on US markets conditions and data which hamper its application in some extend to markets with not as much development.

The findings suggest that not only skilled but also amateur investors may opt for investment strategies based on GA aiming at refining profitable financial signals to their advantage.

This paper looks at machine learning as an up-to-date tool with great potential for increasing effectiveness in profits when applied into TA investment approaches using MACD in well-developed stock markets.

This study aims to investigate Malaysian stock market efficiency from the view of Sharīʿah-compliant and conventional stocks based on the effectiveness of technical trading strategies.

This study uses unconventional trading strategies that mix buy recommendations of Bursa Malaysia analysts with sell signals generated from 10 selected technical trading strategies (simple moving average, moving average envelopes, Bollinger Bands, momentum, commodity channel index, relative strength index, stochastic, Williams percentage range, moving average convergence divergence oscillator and shooting star) that are detected using ChartNexus. The period from 1 January 2013 until 31 December 2015 produces a total sample consisting of 1,265 buy recommendations of 125 Sharīʿah-compliant stocks and 400 buy recommendations of conventional stocks. The study period is extended until 31 March 2016 to provide an ample time for detecting the sell signal especially for buy recommendations that are released towards the end of 2015.

The resulting Jensen’s alpha show 8 out of 10 strategies are effective in generating abnormal returns in Sharīʿah-compliant samples while only 3 out of 10 strategies are effective in conventional samples. Prominent effectiveness of technical trading strategies in Sharīʿah-compliant stocks implies clear inefficiency in that stock market segment as opposed to those of the conventional stocks.

The results based on unconventional trading strategies provide new insights of Malaysian stock market efficiency especially in Sharīʿah-compliant and conventional stocks. The paper provides more robust findings on market efficiency as firms’ equity level data were focussed together with analysts’ buy recommendations from Bursa Malaysia.

The authors test the weak-form efficiency in cryptocurrency markets using the most recent and comprehensive data as of 2021. The authors apply various technical indicators to take a long or short position on 99 cryptocurrencies and compare the 10-day returns based on the technical trading strategies to the simple buy-and-hold returns. The authors find that the trading strategies based on single indicators or the combination of two indicators do not generate higher returns than buy-and-hold returns among cryptos. These findings suggest that cryptocurrency markets are weak-form efficient in general.

The purpose of this paper is to introduce instruction of technical analysis on the undergraduate level that can coincide with traditional teachings of fundamental analysis.

Through examples using the latest in security analysis technology, this paper illustrates the importance of technical security analysis.

This research illustrates how technical analysis techniques may be used to make more significant investment decisions.

Kirkpatrick and Dahlquist define technical analysis as a security analysis discipline for forecasting future direction of prices through the study of past market data primarily price and volume This form of analysis has stood in direct contrast to the fundamental analysis approach whereby actual facts of the company its industry and sector may be ignored. Understanding this contrast, much of academia has chosen to continue to focus its finance curricula on fundamental analysis techniques. As more universities implement trading rooms to reflect that of industry, they must recognize that any large brokerage trading group or financial institution will typically have both a technical analysis and fundamental analysis team. Thus, the need to incorporate technical analysis into undergraduate finance curricula.

Established companies often engage with startups as a way to improve their innovation performance. While there has been extensive discussion on the reasons, modes, and expected outcomes of these initiatives, there is still a need to understand more about how corporate engagements with startups (CEwS) evolve and how they can enhance a company’s innovation capability. This study proposes a framework of engagement strategies, discussing their purposes and implications to understand the subject better.

This study involved managers from twelve large, established companies across various sectors. The authors used a multicase approach to analyze their experiences and offer a framework for corporate-startup engagement.

The framework for corporate-startup engagement consists of four main strategies: (1) innovative improvement, (2) R&D expansion, (3) more value to corporate venture capital and (4) ecosystem articulation. The authors found that ecosystem articulation, which combines the potentials of the other three strategies, is the most sophisticated approach.

This study offers a systematic view of the CEwS phenomenon, identifying the various modes of engagement, the reasons for adopting each one and potential ways to advance and improve them. For managers, the study reveals the CEwS as a lever to build innovation capabilities over time.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

This article aims to investigate the financial constraints and nonlinearity of farm size growth.

Farm size growth is measured with land, labor and output using data from the Farm Accountancy Data Network (FADN) for Hungary and Slovenia. A dynamic panel model is applied to assess financial constraints and nonlinearity of farm size growth.

Results show that, except for land in Slovenia and output in Hungary, liquidity constraints are less important for farm size growth than endogenous factors based on farm size growth expectations and steady farm size restructuring. Smaller farms are growing faster than larger ones. The hypothesis that a higher level of subsidies would increase farm size is not supported for Hungary. When farms reach a certain size, the land area of the largest farms increases. Farm debts in Hungary are linked with land growth and in Slovenia with output growth.

Further research on the impact of liquidity constraints and subsidies can be conducted at a disaggregate farm-type level to examine whether there is variability in the underlying interlinkages at the farm-type specialization level.

The implication that farm size growth is dependent on initial size and that smaller farms are growing faster than bigger ones indicates that it is not necessary to favor the fastest growing smaller farms thus supports the application of a non-discriminatory farm size policy for observing farm size structural changes.

The dynamic panel econometric model that incorporates cash flow as a measure of financial constraints provides insight into farm size growth in cross-country comparison in relation to potential farm liquidity constraints, farm debt and the nonlinearity of farm size, which information is of relevance to policy makers and practitioners.

Within the growing study of transnational entrepreneurial practice, existing conceptualisation of diaspora entrepreneurship has often lacked engagement with the particularities of the diaspora condition. This paper seeks to advance theoretical understanding and empirical study of diaspora entrepreneurship through identifying the processes that generate diaspora entrepreneurship across economic, social and political spheres.

To analyse the relationship between the development of venture activity and diaspora (re)production, in depth, qualitative biographical analysis was undertaken with UK-based diaspora entrepreneurs embedded within the particular contexts of the Sri Lankan Tamil and Kurdish diasporas. Skilled and active diaspora entrepreneurs were purposively selected from these extreme case contexts to explore their entrepreneurial agency within and across the business, social and political realms.

Results identified key dimensions shaping the development of diaspora entrepreneurship. These comprised the role of diaspora context in shaping opportunity frameworks and the mobilisation of available resources, and how venture activity served to sustain collective diaspora identity and address diaspora interests. These findings are used to produce an analytical model of the generation of diaspora entrepreneurship to serve as a basis for discussing how heterogeneous and hybrid entrepreneurial strategies emerge from and shape the evolving diaspora context.

By placing the reproduction of social collectivity centre-stage, this paper identifies the particularities of diaspora entrepreneurship as a form of transnational entrepreneurship. This recognizes the significance of a contextualised understanding of entrepreneurial diversity within wider processes of diaspora development, which has important implications for policy and practice development in homeland and settlement areas.

In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study.

It can be seen that support vector machine (SVM) is used with particle swarm optimization (PSO) where PSO is used as a fast and accurate classification to search the problem-solving space and finally the results are compared with the neural network performance.

Based on the result, the authors can say that both new models are trustworthy in 6 days, however, SVM-PSO is better than basic research. The hit rate of SVM-PSO is 77.5%, but the hit rate of neural networks (basic research) is 74.2.

In this research, two approaches (raw-based and signal-based) have been developed to generate input data for the model: raw-based and signal-based. For comparison, the hit rate is considered the percentage of correct predictions for 16 days.

Building on the institutional theory perspective on corporate governance change and based on interviews with investor relations (IR) managers in large Japanese companies, this study aims to examine Japanese IR managers’ perceptions of the influence of foreign shareholders on Japan’s corporate governance reform and stakeholder-based system. The paper examines tensions, conflicts and collaborations among different stakeholders involved in corporate governance changes in Japan, especially in the areas of firm ownership, employment relations and boards of directors. The paper explains why convergence does not happen in some large Japanese companies by investigating Japanese managers’ responses to and perceptions of foreign shareholders in multiple corporate contexts.

The author conducted in-depth interviews with ten IR managers at large, listed Japanese companies in Kyoto and Tokyo and two managers at foreign investment banks in Tokyo, between 2018 and 2021.

This paper explores five themes that emerged from my interviews: Chief executive officers’ (CEOs’) mixed perceptions of foreign investors, the effectiveness of CEO compensation and outside directors, managers’ reluctance to accept stock price-driven business strategies, foreign investors’ engagement vs investments in index funds and gender patterns, including the effectiveness of token female outside directors. The Japanese companies the author looked at incorporated foreign shareholders as consultants and adopted a few major shareholder-based customs, such as CEOs communicating with investors, having outside directors, increasing CEO compensation and slimming down unprofitable parts of the business via restructuring and downsizing. Simultaneously, they resisted a few major shareholder-based practices. Foreign shareholders’ pressure revealed tensions and contradictions between the Japanese stakeholder system and shareholder primacy-based customs.

This paper is one of the few qualitative studies that explores Japanese IR managers’ responses to and perceptions of foreign shareholders in corporate governance reform, with a particular focus on ownership, employment relations and board members. This paper provides examples of tension, conflict and cooperation between Japanese managers and foreign investors, as seen through the eyes of Japanese IR managers. Examining changes in Japan’s stakeholder-based system of corporate governance reform enables us to better understand the processes by which, with vigorous pressure from government and foreign shareholders, a non-western country like Japan may adopt shareholder-based customs and how such a change may also lead to institutional changes.