Search results for: stock market decisions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5204

Search results for: stock market decisions

5024 The Impact of Trading Switch on Price and Liquidity

Authors: Bel Abed Ines Mariem

Abstract:

Different stock markets keep changing their exchange structure for the only purpose of improving the functioning of their markets. This paper investigates the effects of the transfer from one trading category to another in the Tunisian Stock Exchange on market price and liquidity. The sample consists of 40 securities transferred from call auction to continuous auction and conversely during the period between 2004 and 2013. The methodology used is the event study. Empirical results show an interesting phenomenon observed; stocks transferred to the call system have experienced an improvement on their price and liquidity especially for less liquid ones. However, price and liquidity for stocks transferred from call system to continuous system have decreased.

Keywords: microstructure, call auction, continuous auction, price, liquidity and event study

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5023 Portfolio Selection with Active Risk Monitoring

Authors: Marc S. Paolella, Pawel Polak

Abstract:

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

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5022 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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5021 Carbon Stock of the Moist Afromontane Forest in Gesha and Sayilem Districts in Kaffa Zone: An Implication for Climate Change Mitigation

Authors: Admassu Addi, Sebesebe Demissew, Teshome Soromessa, Zemede Asfaw

Abstract:

This study measures the carbon stock of the Moist Afromontane Gesha-Sayilem forest found in Gesha and Sayilem District in southwest Ethiopia. A stratified sampling method was used to identify the number of sampling point through the Global Positioning System. A total of 90 plots having nested plots to collect tree species and soil data were demarcated. The results revealed that the total carbon stock of the forest was 362.4 t/ha whereas the above ground carbon stock was 174.95t/ha, below ground litter, herbs, soil, and dead woods were 34.3,1.27, 0.68, 128 and 23.2 t/ha (up to 30 cm depth) respectively. The Gesha- Sayilem Forest is a reservoir of high carbon and thus acts as a great sink of the atmospheric carbon. Thus conservation of the forest through introduction REDD+ activities is considered an appropriate action for mitigating climate change.

Keywords: carbon sequestration, carbon stock, climate change, allometric, Ethiopia

Procedia PDF Downloads 128
5020 Detecting Financial Bubbles Using Gap between Common Stocks and Preferred Stocks

Authors: Changju Lee, Seungmo Ku, Sondo Kim, Woojin Chang

Abstract:

How to detecting financial bubble? Addressing this simple question has been the focus of a vast amount of empirical research spanning almost half a century. However, financial bubble is hard to observe and varying over the time; there needs to be more research on this area. In this paper, we used abnormal difference between common stocks price and those preferred stocks price to explain financial bubble. First, we proposed the ‘W-index’ which indicates spread between common stocks and those preferred stocks in stock market. Second, to prove that this ‘W-index’ is valid for measuring financial bubble, we showed that there is an inverse relationship between this ‘W-index’ and S&P500 rate of return. Specifically, our hypothesis is that when ‘W-index’ is comparably higher than other periods, financial bubbles are added up in stock market and vice versa; according to our hypothesis, if investors made long term investments when ‘W-index’ is high, they would have negative rate of return; however, if investors made long term investments when ‘W-index’ is low, they would have positive rate of return. By comparing correlation values and adjusted R-squared values of between W-index and S&P500 return, VIX index and S&P500 return, and TED index and S&P500 return, we showed only W-index has significant relationship between S&P500 rate of return. In addition, we figured out how long investors should hold their investment position regard the effect of financial bubble. Using this W-index, investors could measure financial bubble in the market and invest with low risk.

Keywords: financial bubble detection, future return, forecasting, pairs trading, preferred stocks

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5019 Markowitz and Implementation of a Multi-Objective Evolutionary Technique Applied to the Colombia Stock Exchange (2009-2015)

Authors: Feijoo E. Colomine Duran, Carlos E. Peñaloza Corredor

Abstract:

There modeling component selection financial investment (Portfolio) a variety of problems that can be addressed with optimization techniques under evolutionary schemes. For his feature, the problem of selection of investment components of a dichotomous relationship between two elements that are opposed: The Portfolio Performance and Risk presented by choosing it. This relationship was modeled by Markowitz through a media problem (Performance) - variance (risk), ie must Maximize Performance and Minimize Risk. This research included the study and implementation of multi-objective evolutionary techniques to solve these problems, taking as experimental framework financial market equities Colombia Stock Exchange between 2009-2015. Comparisons three multiobjective evolutionary algorithms, namely the Nondominated Sorting Genetic Algorithm II (NSGA-II), the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Indicator-Based Selection in Multiobjective Search (IBEA) were performed using two measures well known performance: The Hypervolume indicator and R_2 indicator, also it became a nonparametric statistical analysis and the Wilcoxon rank-sum test. The comparative analysis also includes an evaluation of the financial efficiency of the investment portfolio chosen by the implementation of various algorithms through the Sharpe ratio. It is shown that the portfolio provided by the implementation of the algorithms mentioned above is very well located between the different stock indices provided by the Colombia Stock Exchange.

Keywords: finance, optimization, portfolio, Markowitz, evolutionary algorithms

Procedia PDF Downloads 262
5018 Findings: Impact of a Sustained Health Promoting Workplace on Stock Price Performance and Beta; A Singapore Case

Authors: Wee Tong Liaw, Elaine Wong Yee Sing

Abstract:

The main objective and focus of this study are to establish the significance of a sustained health promoting workplace on stock and portfolio returns focusing on companies listed on the Singapore stock exchange, using a two-factor model comprising of the single factor CAPM and a 'health promoting workplace' factor. The 'health promoting workplace' factor represents the excess returns derived between two portfolios of component stocks that, when combined, would represent a top tier stock market index in Singapore, namely the STI index. The first portfolio represents companies that are independently assessed by the Singapore’s Health Award, SHA, to have a sustained and comprehensive health promoting workplace (SHA-STI portfolio) and the second portfolio represents companies that had not been independently assessed (Non-SHA STI portfolio). Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry-wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. When using a ten year holding period instead of a one year holding period, excess returns in the SHA-STI portfolio over Non-SHA STI portfolio were consistently being observed over all test periods, during 2001 to 2013. In addition, when applied to the SHA-STI portfolio, results from the Two Factor Model consistently revealed higher explanatory powers across all test periods for the portfolio as well as all the individual component stocks in SHA-STI portfolio, than the single factor CAPM model. However, with respect to attaining higher level of achievement in the Singapore Health Award, this study did not show any incentive for selecting listed companies that have achieved a higher level of award. Results from this study would give further insights to investors and fund managers alike who intend to consider health promoting workplace as a risk factor in their stock or portfolio selection process, in particular for investors who have a preference for STI’s component stocks and with a longer investment horizon. Key micro factors like management abilities, business development strategies and production capabilities that meet the needs of market would create the demand for a company’s product(s) or service(s) and consequently contribute to its top line and profitability. Thereafter, the existence of a sustainable health promoting workplace would be a key catalytic factor in sustaining a productive workforce needed to support the continued success of a profitable business.

Keywords: asset pricing model, company's performance, stock returns, financial risk factor, sustained health promoting workplace

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5017 Application of the Quantile Regression Approach to the Heterogeneity of the Fine Wine Prices

Authors: Charles-Olivier Amédée-Manesme, Benoit Faye, Eric Le Fur

Abstract:

In this paper, the heterogeneity of the Bordeaux Legends 50 wine market price segment is addressed. For this purpose, quantile regression is applied – with market segmentation based on wine bottle price quantile – and the hedonic price of wine attributes is computed for various price segments of the market. The approach is applied to a major privately held data set which consists of approximately 30,000 transactions over the 2003–2014 period. The findings suggest that the relative hedonic prices of several wine attributes differ significantly among deciles. In particular, the elasticity coefficient of the expert ratings shows strong variation among prices. If - as suggested in the literature - expert ratings have a positive influence on wine price on average, they have a clearly decreasing impact over the quantiles. Finally, the lower the wine price, the higher the potential for price appreciation over time. Other variables such as chateaux or vintage are also shown to vary across the distribution of wine prices. While enhancing our understanding of the complex market dynamics that underlie Bordeaux wines’ price, this research provides empirical evidence that the QR approach adequately captures heterogeneity among wine price ranges, which simultaneously applies to wine stock, vintage and auctions’ house.

Keywords: hedonics, market segmentation, quantile regression, heterogeneity, wine economics

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5016 Understanding the Nature of Capital Allocation Problem in Corporate Finance

Authors: Meltem Gurunlu

Abstract:

One of the central problems in corporate finance is the allocation of funds. This usually takes two forms: allocation of funds across firms in an economy or allocation of funds across projects or business units within a firm. The first one is typically related to the external markets (the bond market, the stock market, banks and finance companies) whereas the second form of the capital allocation is related to the internal capital markets in which corporate headquarters allocate capital to their business units. (within-group transfers, within-group credit markets, and within-group equity market). The main aim of this study is to investigate the nature of capital allocation dynamics by comparing the relevant studies carried out on external and internal capital markets with paying special significance to the business groups.

Keywords: internal capital markets, external capital markets, capital structure, capital allocation, business groups, corporate finance

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5015 Quantifying Uncertainties in an Archetype-Based Building Stock Energy Model by Use of Individual Building Models

Authors: Morten Brøgger, Kim Wittchen

Abstract:

Focus on reducing energy consumption in existing buildings at large scale, e.g. in cities or countries, has been increasing in recent years. In order to reduce energy consumption in existing buildings, political incentive schemes are put in place and large scale investments are made by utility companies. Prioritising these investments requires a comprehensive overview of the energy consumption in the existing building stock, as well as potential energy-savings. However, a building stock comprises thousands of buildings with different characteristics making it difficult to model energy consumption accurately. Moreover, the complexity of the building stock makes it difficult to convey model results to policymakers and other stakeholders. In order to manage the complexity of the building stock, building archetypes are often employed in building stock energy models (BSEMs). Building archetypes are formed by segmenting the building stock according to specific characteristics. Segmenting the building stock according to building type and building age is common, among other things because this information is often easily available. This segmentation makes it easy to convey results to non-experts. However, using a single archetypical building to represent all buildings in a segment of the building stock is associated with loss of detail. Thermal characteristics are aggregated while other characteristics, which could affect the energy efficiency of a building, are disregarded. Thus, using a simplified representation of the building stock could come at the expense of the accuracy of the model. The present study evaluates the accuracy of a conventional archetype-based BSEM that segments the building stock according to building type- and age. The accuracy is evaluated in terms of the archetypes’ ability to accurately emulate the average energy demands of the corresponding buildings they were meant to represent. This is done for the buildings’ energy demands as a whole as well as for relevant sub-demands. Both are evaluated in relation to the type- and the age of the building. This should provide researchers, who use archetypes in BSEMs, with an indication of the expected accuracy of the conventional archetype model, as well as the accuracy lost in specific parts of the calculation, due to use of the archetype method.

Keywords: building stock energy modelling, energy-savings, archetype

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5014 Electricity Market Categorization for Smart Grid Market Testing

Authors: Rebeca Ramirez Acosta, Sebastian Lenhoff

Abstract:

Decision makers worldwide need to determine if the implementation of a new market mechanism will contribute to the sustainability and resilience of the power system. Due to smart grid technologies, new products in the distribution and transmission system can be traded; however, the impact of changing a market rule will differ between several regions. To test systematically those impacts, a market categorization has been compiled and organized in a smart grid market testing toolbox. This toolbox maps all actual energy products and sets the basis for running a co-simulation test with the new rule to be implemented. It will help to measure the impact of the new rule, based on the sustainable and resilience indicators.

Keywords: co-simulation, electricity market, smart grid market, market testing

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5013 Lexicon-Based Sentiment Analysis for Stock Movement Prediction

Authors: Zane Turner, Kevin Labille, Susan Gauch

Abstract:

Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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5012 Lexicon-Based Sentiment Analysis for Stock Movement Prediction

Authors: Zane Turner, Kevin Labille, Susan Gauch

Abstract:

Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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5011 Optimization of Black-Litterman Model for Portfolio Assets Allocation

Authors: A. Hidalgo, A. Desportes, E. Bonin, A. Kadaoui, T. Bouaricha

Abstract:

Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation.

Keywords: Black-Litterman, Markowitz, market data, portfolio manager opinion

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5010 Corporate Voluntary Greenhouse Gas Emission Reporting in United Kingdom: Insights from Institutional and Upper Echelons Theories

Authors: Lyton Chithambo

Abstract:

This paper reports the results of an investigation into the extent to which various stakeholder pressures influence voluntary disclosure of greenhouse-gas (GHG) emissions in the United Kingdom (UK). The study, which is grounded on institutional theory, also borrows from the insights of upper echelons theory and examines whether specific managerial (chief executive officer) characteristics explain and moderates various stakeholder pressures in explaining GHG voluntary disclosure. Data were obtained from the 2011 annual and sustainability reports of a sample of 216 UK companies on the FTSE350 index listed on the London Stock Exchange. Generally the results suggest that there is no substantial shareholder and employee pressure on a firm to disclose GHG information but there is significant positive pressure from the market status of a firm with those firms with more market share disclosing more GHG information. Consistent with the predictions of institutional theory, we found evidence that coercive pressure i.e. regulatory pressure and mimetic pressures emanating in some industries notably industrials and consumer services have a significant positive influence on firms’ GHG disclosure decisions. Besides, creditor pressure also had a significant negative relationship with GHG disclosure. While CEO age had a direct negative effect on GHG voluntary disclosure, its moderation effect on stakeholder pressure influence on GHG disclosure was only significant on regulatory pressure. The results have important implications for both policy makers and company boards strategizing to reign in their GHG emissions.

Keywords: greenhouse gases, voluntary disclosure, upper echelons theory, institution theory

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5009 Challenges of Carbon Trading Schemes in Africa

Authors: Bengan Simbarashe Manwere

Abstract:

The entire African continent, comprising 55 countries, holds a 2% share of the global carbon market. The World Bank attributes the continent’s insignificant share and participation in the carbon market to the limited access to electricity. Approximately 800 million people spread across 47 African countries generate as much power as Spain, with a population of 45million. Only South Africa and North Africa have carbon-reduction investment opportunities on the continent and dominate the 2% market share of the global carbon market. On the back of the 2015 Paris Agreement, South Africa signed into law the Carbon Tax Act 15 of 2019 and the Customs and Excise Amendment Act 13 of 2019 (Gazette No. 4280) on 1 June 2019. By these laws, South Africa was ushered into the league of active global carbon market players. By increasing the cost of production by the rate of R120/tCO2e, the tax intentionally compels the internalization of pollution as a cost of production and, relatedly, stimulate investment in clean technologies. The first phase covered the 1 June 2019 – 31 December 2022 period during which the tax was meant to escalate at CPI + 2% for Scope 1 emitters. However, in the second phase, which stretches from 2023 to 2030, the tax will escalate at the inflation rate only as measured by the consumer price index (CPI). The Carbon Tax Act provides for carbon allowances as mitigation strategies to limit agents’ carbon tax liability by up to 95% for fugitive and process emissions. Although the June 2019 Carbon Tax Act explicitly makes provision for a carbon trading scheme (CTS), the carbon trading regulations thereof were only finalised in December 2020. This points to a delay in the establishment of a carbon trading scheme (CTS). Relatedly, emitters in South Africa are not able to benefit from the 95% reduction in effective carbon tax rate from R120/tCO2e to R6/tCO2e as the Johannesburg Stock Exchange (JSE) has not yet finalized the establishment of the market for trading carbon credits. Whereas most carbon trading schemes have been designed and constructed from the beginning as new tailor-made systems in countries the likes of France, Australia, Romania which treat carbon as a financial product, South Africa intends, on the contrary, to leverage existing trading infrastructure of the Johannesburg Stock Exchange (JSE) and the Clearing and Settlement platforms of Strate, among others, in the interest of the Paris Agreement timelines. Therefore the carbon trading scheme will not be constructed from scratch. At the same time, carbon will be treated as a commodity in order to align with the existing institutional and infrastructural capacity. This explains why the Carbon Tax Act is silent about the involvement of the Financial Sector Conduct Authority (FSCA).For South Africa, there is need to establish they equilibrium stability of the CTS. This is important as South Africa is an innovator in carbon trading and the successful trading of carbon credits on the JSE will lead to imitation by early adopters first, followed by the middle majority thereafter.

Keywords: carbon trading scheme (CTS), Johannesburg stock exchange (JSE), carbon tax act 15 of 2019, South Africa

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5008 Analyzing Medical Workflows Using Market Basket Analysis

Authors: Mohit Kumar, Mayur Betharia

Abstract:

Healthcare domain, with the emergence of Electronic Medical Record (EMR), collects a lot of data which have been attracting Data Mining expert’s interest. In the past, doctors have relied on their intuition while making critical clinical decisions. This paper presents the means to analyze the Medical workflows to get business insights out of huge dumped medical databases. Market Basket Analysis (MBA) which is a special data mining technique, has been widely used in marketing and e-commerce field to discover the association between products bought together by customers. It helps businesses in increasing their sales by analyzing the purchasing behavior of customers and pitching the right customer with the right product. This paper is an attempt to demonstrate Market Basket Analysis applications in healthcare. In particular, it discusses the Market Basket Analysis Algorithm ‘Apriori’ applications within healthcare in major areas such as analyzing the workflow of diagnostic procedures, Up-selling and Cross-selling of Healthcare Systems, designing healthcare systems more user-friendly. In the paper, we have demonstrated the MBA applications using Angiography Systems, but can be extrapolated to other modalities as well.

Keywords: data mining, market basket analysis, healthcare applications, knowledge discovery in healthcare databases, customer relationship management, healthcare systems

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5007 Price Setting and the Role of Accounting Information

Authors: Chris Durden, Peter Lane

Abstract:

Cost accounting information potentially plays an important role in price setting. According to prior research fixed and variable cost information often is a key influence on pricing decisions. The literature highlights the benefits of applying systematic costing systems for enhanced price setting processes. This paper explores how costing systems are used for pricing decisions in the tourism and hospitality industry relative to other sources of price setting information. Pricing based on full cost information was found to have relatively greater importance and short-term survival and customer oriented objectives were found to be the more important pricing objectives. This paper contributes to the literature by providing a recent analysis of accounting’s role in price setting within the tourism and hospitality industry.

Keywords: cost accounting systems, pricing decisions, cost-plus pricing, market pricing, tourism industry

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5006 Modeling Usage Patterns of Mobile App Service in App Market Using Hidden Markov Model

Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

Abstract:

Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

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5005 A Comparative Analysis of Global Minimum Variance and Naïve Portfolios: Performance across Stock Market Indices and Selected Economic Regimes Using Various Risk-Return Metrics

Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

Abstract:

This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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5004 Options Trading and Crash Risk

Authors: Cameron Truong, Mikhail Bhatia, Yangyang Chen, Viet Nga Cao

Abstract:

Using a sample of U.S. firms between 1996 and 2011, this paper documents a positive association between options trading volume and future stock price crash risk. This relation is evidently more pronounced among firms with higher information asymmetry, business uncertainty, and short-sale constraints. In a dichotomous cross-sectional setting, we also document that firms with options trading have higher future crash risk than firms without options trading. We further show in a difference-in-difference analysis that firms experience an increase in crash risk immediately after the listing of options. The results suggest that options traders are able of identifying bad news hoarding by management and choose to trade in a liquid options market in anticipation of future crashes.

Keywords: bad news hoarding, cross-sectional setting, options trading, stock price crash

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5003 Financial Policies in the Process of Global Crisis: Case Study Kosovo, Case Kosovo

Authors: Shpetim Rezniqi

Abstract:

Financial Policies in the process of global crisis the current crisis has swept the world with special emphasis, most developed countries, those countries which have most gross -product world and you have a high level of living.Even those who are not experts can describe the consequences of the crisis to see the reality that is seen, but how far will it go this crisis is impossible to predict. Even the biggest experts have conjecture and large divergence, but agree on one thing: - The devastating effects of this crisis will be more severe than ever before and can not be predicted.Long time, the world was dominated economic theory of free market laws. With the belief that the market is the regulator of all economic problems. The market, as river water will flow to find the best and will find the necessary solution best. Therefore much less state market barriers, less state intervention and market itself is an economic self-regulation. Free market economy became the model of global economic development and progress, it transcends national barriers and became the law of the development of the entire world economy. Globalization and global market freedom were principles of development and international cooperation. All international organizations like the World Bank, states powerful economic, development and cooperation principles laid free market economy and the elimination of state intervention. The less state intervention much more freedom of action was this market- leading international principle. We live in an era of financial tragic. Financial markets and banking in particular economies are in a state of thy good, US stock markets fell about 40%, in other words, this time, was one of the darkest moments 5 since 1920. Prior to her rank can only "collapse" of the stock of Wall Street in 1929, technological collapse of 2000, the crisis of 1973 after the Yom Kippur war, while the price of oil quadrupled and famous collapse of 1937 / '38, when Europe was beginning World war II In 2000, even though it seems like the end of the world was the corner, the world economy survived almost intact. Of course, that was small recessions in the United States, Europe, or Japan. Much more difficult the situation was at crisis 30s, or 70s, however, succeeded the world. Regarding the recent financial crisis, it has all the signs to be much sharper and with more consequences. The decline in stock prices is more a byproduct of what is really happening. Financial markets began dance of death with the credit crisis, which came as a result of the large increase in real estate prices and household debt. It is these last two phenomena can be matched very well with the gains of the '20s, a period during which people spent fists as if there was no tomorrow. All is not away from the mouth of the word recession, that fact no longer a sudden and abrupt. But as much as the financial markets melt, the greater is the risk of a problematic economy for years to come. Thus, for example, the banking crisis in Japan proved to be much more severe than initially expected, partly because the assets which were based more loans had, especially the land that falling in value. The price of land in Japan is about 15 years that continues to fall. (ADRI Nurellari-Published in the newspaper "Classifieds"). At this moment, it is still difficult to çmosh to what extent the crisis has affected the economy and what would be the consequences of the crisis. What we know is that many banks will need more time to reduce the award of credit, but banks have this primary function, this means huge loss.

Keywords: globalisation, finance, crisis, recomandation, bank, credits

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5002 Exposing Investor Sentiment In Stock Returns

Authors: Qiang Bu

Abstract:

This paper compares the explanatory power of sentiment level and sentiment shock. The preliminary test results show that sentiment shock plays a more significant role in explaining stocks returns, including the raw return and abnormal return. We also find that sentiment shock beta has a higher statistical significance than sentiment beta. These finding sheds new light on the relationship between investor sentiment and stock returns.

Keywords: sentiment level, sentiment shock, explanatory power, abnormal stock return, beta

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5001 A Historical Overview of the General Implementation of the European Union Market Abuse Directive in the United Kingdom before the Brexit and Its Future Implications

Authors: Howard Chitimira

Abstract:

The European Union (EU) was probably the first body to establish multinational anti-market abuse laws aimed at enhancing the detection and curbing of cross-border market abuse activities in its member states. Put differently, the EU Insider Dealing Directive was adopted in 1989 and was the first law that harmonised the insider trading ban among the EU member states. Thereafter, the European Union Directive on Insider Dealing and Market Manipulation (EU Market Abuse Directive) was adopted in a bid to improve and effectively discourage all the forms of market abuse in the EU’s securities and financial markets. However, the EU Market Abuse Directive had its own gaps and flaws. In light of this, the Market Abuse Regulation and the Criminal Sanctions for Market Abuse Directive were enacted to repeal and replace the EU Market Abuse Directive in 2016. The article examines the adequacy of the EU Market Abuse Directive and its implementation in the United Kingdom (UK) prior to the British exit (Brexit). This is done to investigate the possible implications of the Brexit referendum outcome of 23 June 2016 on the future regulation of market abuse in the UK.

Keywords: market abuse, insider trading, market manipulation, European Union, United Kingdom

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5000 Corporate Governance and Firms` Performance: Evidence from Quoted Firms on the Nigerian Stock Exchange

Authors: Ogunwole Cecilia Oluwakemi, Wahid Damilola Olanipekun, Omoyele Olufemi Samuel, Timothy Ayomitunde Aderemi

Abstract:

The issues relating to corporate governance in both locally and internationally managed firms cannot be overemphasized because the lack of efficient corporate governance could orchestrate serious problems in any organization. Against this backdrop, this study examines the nexus between corporate governance and performance of firms from 2012 to 2020, using the case study of the Nigerian stock exchange. Consequently, data was collected from forty (40) listed firms on the Nigerian Stock Exchange. The study employed a fixed effect technique of estimation to address the objective of the study. It was discovered from the study that the influence of corporate governance components such as gender diversity, board independence and managerial ownership led to a significant positive impact on the performance of the firms under the investigation. In view of the above finding, this study makes the following recommendations for the policymakers in Nigeria that anytime the goal of the policymakers is the improvement of performance of the listed firms in the Nigerian stock exchange, board independence and a balance in the inclusion of male and female among the board of directors should be encouraged in these firms.

Keywords: corporate, governance, firms, performance, Nigeria, stock, exchange

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4999 Exploring Behavioural Biases among Indian Investors: A Qualitative Inquiry

Authors: Satish Kumar, Nisha Goyal

Abstract:

In the stock market, individual investors exhibit different kinds of behaviour. Traditional finance is built on the notion of 'homo economics', which states that humans always make perfectly rational choices to maximize their wealth and minimize risk. That is, traditional finance has concern for how investors should behave rather than how actual investors are behaving. Behavioural finance provides the explanation for this phenomenon. Although finance has been studied for thousands of years, behavioural finance is an emerging field that combines the behavioural or psychological aspects with conventional economic and financial theories to provide explanations on how emotions and cognitive factors influence investors’ behaviours. These emotions and cognitive factors are known as behavioural biases. Because of these biases, investors make irrational investment decisions. Besides, the emotional and cognitive factors, the social influence of media as well as friends, relatives and colleagues also affect investment decisions. Psychological factors influence individual investors’ investment decision making, but few studies have used qualitative methods to understand these factors. The aim of this study is to explore the behavioural factors or biases that affect individuals’ investment decision making. For the purpose of this exploratory study, an in-depth interview method was used because it provides much more exhaustive information and a relaxed atmosphere in which people feel more comfortable to provide information. Twenty investment advisors having a minimum 5 years’ experience in securities firms were interviewed. In this study, thematic content analysis was used to analyse interview transcripts. Thematic content analysis process involves analysis of transcripts, coding and identification of themes from data. Based on the analysis we categorized the statements of advisors into various themes. Past market returns and volatility; preference for safe returns; tendency to believe they are better than others; tendency to divide their money into different accounts/assets; tendency to hold on to loss-making assets; preference to invest in familiar securities; tendency to believe that past events were predictable; tendency to rely on the reference point; tendency to rely on other sources of information; tendency to have regret for making past decisions; tendency to have more sensitivity towards losses than gains; tendency to rely on own skills; tendency to buy rising stocks with the expectation that this rise will continue etc. are some of the major concerns showed by experts about investors. The findings of the study revealed 13 biases such as overconfidence bias, disposition effect, familiarity bias, framing effect, anchoring bias, availability bias, self-attribution bias, representativeness, mental accounting, hindsight bias, regret aversion, loss aversion and herding bias/media biases present in Indian investors. These biases have a negative connotation because they produce a distortion in the calculation of an outcome. These biases are classified under three categories such as cognitive errors, emotional biases and social interaction. The findings of this study may assist both financial service providers and researchers to understand the various psychological biases of individual investors in investment decision making. Additionally, individual investors will also be aware of the behavioural biases that will aid them to make sensible and efficient investment decisions.

Keywords: financial advisors, individual investors, investment decisions, psychological biases, qualitative thematic content analysis

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4998 Media Planning Decisions and Preferences through a Goal Programming Model: An Application to a Media Campaign for a Mature Product in Italy

Authors: Cinzia Colapinto, Davide La Torre

Abstract:

Goal Programming (GP) and its variants were applied to marketing and specific marketing issues, such as media scheduling problems in the last decades. The concept of satisfaction functions has been widely utilized in the GP model to explicitly integrate the Decision-Maker’s preferences. These preferences can be guided by the available information regarding the decision-making situation. A GP model with satisfaction functions for media planning decisions is proposed and then illustrated through a case study related to a marketing/media campaign in the Italian market.

Keywords: goal programming, satisfaction functions, media planning, tourism management

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4997 A Prediction Model Using the Price Cyclicality Function Optimized for Algorithmic Trading in Financial Market

Authors: Cristian Păuna

Abstract:

After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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4996 Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs

Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

Abstract:

Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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4995 Willingness of Muslim Owners/Managers of Smes to Seek Capital Market Financing

Authors: Bashir Tijjani Abubakar

Abstract:

Capital markets play a very important role in financing of private and public institutions in both developing and developed economies. Unfortunately, small and medium enterprises (SMEs) in those economies are yet to fully utilize the markets to finance their long financial needs. This study assesses the factors that influence the decisions of the Muslim Owners/Managers of SMEs in Nigeria and specifically in Kano to seek capital market financing. Logit regression model was used to assess the factors such as control of ownership, perception of the owners/managers on the interest rate charged by commercial banks, educational qualification, size, and age of the SMEs. The study reveals that all the factors have significant positive influence on the willingness of the SMEs Owners/Managers to seek capital market financing. The study recommends educating the Owners/Managers on the operations and products of the markets.

Keywords: capital markets, capital market financing, small and medium enterprise and willingness, size of an enterprise, age of an enterprise and control of ownership

Procedia PDF Downloads 247