Search results for: building stock decarbonization

Authors: Zain Ul Abideen

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The study examines the potentially dark and bright parts of behavioral biases in investors’ investment decisions in the Pakistani equity market. These biases, directly and indirectly, play a comprehensive role in controlling and deciding the investor’s investment decisions. Stock market anomalies are used as a mediator, while financial literacy is used as a moderator to check the mentioned relationship. The sample consisted of investors who have trading experience of more than two years in the stock market. The result indicates that calendar anomalies do not mediate between overconfidence bias and investment decisions. However, the study investigates the mediating role of fundamental and technical anomalies between overconfidence bias and investment decisions. Furthermore, calendar anomalies play a significant role between the disposition effect and investment decisions. Calendar anomalies also mediate between herding bias and investment decisions. Financial literacy significantly moderates between behavioral biases and stock market anomalies. This research would be beneficial for individual and professional investors in their investment decisions. They should be financially literate, consequently less biased and have no market anomalies. Investors in emerging and developed economies can make optimal decisions in their respective stock markets.

Keywords: behavioral biases, financial literacy, stock market anomalies, investment decision

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Authors: Rosyidah, Permata Wulandari

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We investigate the price effect of addition and deletions from the Indonesia Sharia Stock Index (ISSI) and Jakarta Islamic Index (JII). Using event study methodology, we measure abnormal returns for firms over the period June 2019 - to December 2021. Through the sample of 107 additions and 95 deletions, we find evidence to support the theory of Muslim country investment behavior. We find that additions to the Islamic index led to a significant positive stock market reaction and deletions to the Islamic index led to a negative stock market reaction on Jakarta Islamic Index (JII) and there is no significant reaction of addition and deletion on Indonesia Sharia Stock Index (ISSI).

Keywords: abnormal return, abnormal volume, event study, index changes, sharia index

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Authors: Mohammad Azam

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The purpose of this study is to investigate risk and real excess portfolio returns using inflation adjusted risk-free rates, a measuring technique that focuses on the momentum augmented Fama-French six-factor model and use monthly data from 1994 to 2022. With the exception of profitability, the data show that market, size, value, momentum, and investment factors are all strongly associated to excess portfolio stock returns using ordinary lease square regression technique. According to the Gibbons, Ross, and Shanken test, the momentum augmented Fama-French six-factor model outperforms the market. This technique discovery may be utilised by academics and professionals to acquire an in-depth knowledge of the Pakistan Stock Exchange across a broad stock pattern for investing decisions and portfolio construction.

Keywords: real excess portfolio returns, momentum augmented fama & french five-factor model, GRS-test, pakistan stock exchange

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Authors: Yathreb Sabsaby

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Energy efficiency retrofitting of existing buildings was long ignored by public authorities who favored energy efficiency policies in new buildings, which are easier to implement. Indeed, retrofitting is more complex and difficult to organize because of the extreme diversity in existing buildings, administrative situations and occupation. Energy efficiency retrofitting of existing buildings has now become indispensable in all economies—even emerging countries—given the constraints imposed by energy security and climate change, and because it represents considerable potential energy savings. Addressing energy efficiency in the existing building stock has been acknowledged as one of the most critical yet challenging aspects of reducing our environmental footprint on the ecosystem. Tripoli, Lebanon chosen as case study area is a typical Mediterranean metropolis in the North Lebanon, where multifamily residential buildings are all around the city. This generally implies that the density of energy demand is extremely high, even the renewable energy facilities are involved, they can just play as a minor energy provider at the current technology level in the single family house. It seems only the low energy design for buildings can be made possible, not the zero energy certainly in developing country. This study reviews the latest research and experience and provides recommendations for deep energy retrofits that aim to save more than 50% of the energy used in a typical Tripoli apartment building.

Keywords: energy-efficiency, existing building, multifamily residential building, retrofit

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

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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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Authors: Saleem Abuleil, Khalid S. Alsamara

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Events represent a significant source of information on the web; they deliver information about events that occurred around the world in all kind of subjects and areas. These events can be collected and organized to provide valuable and useful information for decision makers, researchers, as well as any person seeking knowledge. In this paper, we discuss an ongoing research to target stock markets domain to observe and record changes (events) when they happen, collect them, understand the meaning of each one of them, and organize the information along with meaning in a well-structured format. By using Semantic Role Labeling (SRL) technique, we identified four factors for each event in this paper: verb of action and three roles associated with it, entity name, attribute, and attribute value. We have generated a set of rules and techniques to support our approach to analyze and understand the meaning of the events taking place in stock markets.

Keywords: natuaral language processing, Arabic language, event extraction and understanding, sematic role labeling, stock market

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Authors: Amir Razmjou, Elika Karbassi Yazdi

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Several direct lithium extraction (DLE) technologies have been developed for Li extraction from different brines. Although laboratory studies showed that they can technically recover Li to 90%, challenges still remain in developing a sustainable process that can serve as a foundation for the lithium dependent low-carbon economy. There is a continuing quest for DLE technologies that do not need extensive pre-treatments, fewer materials, and have simplified extraction processes with high Li selectivity. Here, an overview of DLE technologies will be provided with an emphasis on the basic principles of the materials’ design for the development of membranes with nanochannels and nanopores with Li ion selectivity. We have used a variety of building blocks such as nano-clay, organic frameworks, Graphene/oxide, MXene, etc., to fabricate the membranes. Molecular dynamic simulation (MD) and density functional theory (DFT) were used to reveal new mechanisms by which high Li selectivity was obtained.

Keywords: lithium recovery, membrane, lithium selectivity, decarbonization

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Lindrianasari Stefanie, Aminah Khairudin

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This study aims to provide empirical evidence regarding the ability of Price to Earnings Ratio and PEG Ratio in predicting future stock returns issuers. The samples used in this study are stocks that go into LQ45. The main contribution is to assign empirical evidence if the PEG Ratio can provide optimum return compared to Price to Earnings Ratio. This study used a sample of the entire company into the group LQ45 with the period of observation. The data used is limited to the financial statements of a company incorporated in LQ45 period July 2013-July 2014, using the financial statements and the position of the company's closing stock price at the end of 2010 as a reference benchmark for the growth of the company's stock price compared to the closing price of 2013. This study found that the method of PEG Ratio can outperform the method of PE ratio in predicting future returns on the stock portfolio of LQ45.

Keywords: price to earnings growth, price to earnings ratio, future returns, stock price

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Authors: Konstantinos Pikos, Dimitrios Kaimaris

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Although designing building blocks is a procedure used by many planners around the world, there isn’t an automated tool that will help planners and designers achieve their goals with lesser effort. The difficulty of the subject lies in the repeating process of manually drawing lines, while not only it is mandatory to maintain the desirable offset but to also achieve a lesser impact to the existing building stock. In this paper, using Geographical Information Systems (GIS) and the Python programming language, an automated tool integrated into ArcGIS PRO, is being presented. Despite its simplistic enviroment and the lack of specialized building legislation due to the complex state of the field, a planner who is aware of such technical information can use the tool to draw an initial approach of the final building blocks in an area with pre-existing buildings in an attempt to organize the usually sprawling suburbs of a city or any continuously developing area. The tool uses ESRI’s ArcPy library to handle the spatial data, while interactions with the user is made throught Tkinter. The main process consists of a modification of building edgescoordinates, using NumPy library, in an effort to draw the line of best fit, so the user can get the optimal results per block’s side. Finally, after the tool runs successfully, a table of primary planning information is shown, such as the area of the building block and its coverage rate. Regardless of the primary stage of the tool’s development, it is a solid base where potential planners with programming skills could invest, so they can make the tool adapt to their individual needs. An example of the entire procedure in a test area is provided, highlighting both the strengths and weaknesses of the final results.

Keywords: arcPy, GIS, python, building blocks

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Authors: Nikolaos Konstantopoulos, Aristeidis Samitas, Vasileiou Evangelos

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The purpose of this study is to examine if the financial trends influence not only the stock markets’ returns, but also their anomalies. We choose to study the day of the week effect (DOW) for the Greek stock market during the Euro period (2002-12), because during the specific period there are not significant structural changes and there are long term financial trends. Moreover, in order to avoid possible methodological counterarguments that usually arise in the literature, we apply several linear (OLS) and nonlinear (GARCH family) models to our sample until we reach to the conclusion that the TGARCH model fits better to our sample than any other. Our results suggest that in the Greek stock market there is a long term predisposition for positive/negative returns depending on the weekday. However, the statistical significance is influenced from the financial trend. This influence may be the reason why there are conflict findings in the literature through the time. Finally, we combine the DOW’s empirical findings from 1985-2012 and we may assume that in the Greek case there is a tendency for long lived turn of the week effect.

Keywords: day of the week effect, GARCH family models, Athens stock exchange, economic growth, crisis

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Eylem Güzel, Soner Güler, Mustafa Gülen

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Masonry is the oldest building materials since ancient times. Adobe, stone, brick are the most widespread materials used in the construction of masonry buildings. Masonry buildings compose of a large part of building stock especially in rural areas and underdeveloped regions of Turkey. The seismic performance of adobe masonry buildings is vulnerable against earthquake effects. In this study, after 2011 Van earthquake with magnitude 7.2 Mw, damages occurred in existing adobe masonry buildings in Van city is investigated. The observed damages and reasons of adobe masonry buildings in design and construction phase are specified and evaluated.

Keywords: adobe masonry buildings, earthquake effects, damages, seismic performance

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Authors: Rit M., Girard R., Villot J., Thorel M.

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In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Tchapo Tchaga Sophia, Cai Chun

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This study measures the efficiency level of corporate governance to improve the quality level of value relevance in the resolution of market value efficiency increase issues, transparency problems, risk frauds, agency problems, investors' confidence, and decision-making issues using IFRS and Corporate Governance Acts (CGA). The final sample of this study contains 3660 firms from ten countries' stock markets from 2010 to 2020. Based on the efficiency market theory and the positive accounting theory, this paper uses multiple econometrical methods (DID method, multivariate and univariate regression methods) and models (Ohlson model and compliance index model) regression to see the incidence results of corporate governance mechanisms on the value relevance level under the influence of IFRS and corporate governance regulations act framework in Africa's stock exchanges for non-financial firms. The results on value relevance show that the corporate governance system, strengthened by the adoption of IFRS and enforcement of new corporate governance regulations, produces better financial statement information when its compliance level is high. And that is both value-relevant and comparable to results in more developed markets. Similar positive and significant results were obtained when predicting future book value per share and earnings per share through the determination of stock price and stock return. The findings of this study have important implications for regulators, academics, investors, and other users regarding the effects of IFRS and the Corporate Governance Act (CGA) on the relationship between corporate governance and accounting information relevance in the African stock market. The contributions of this paper are also based on the uniqueness of the data used in this study. The unique data is from Africa, and not all existing findings provide evidence for Africa and of the DID method used to examine the relationship between corporate governance and value relevance on African stock exchanges.

Keywords: corporate governance value, market efficiency value, value relevance, African stock market, stock return-stock price

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Authors: Nidhal Mgadmi, Abdelhafidh Othmani

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This article examines the causal relationship between stock indices and cryptocurrencies during the current war between Russia and Ukraine. The econometric investigation runs from February 24, 2022, to April 12, 2023, focusing on seven stock market indices (S&P500, DAX, CAC40, Nikkei, TSX, MOEX, and PFTS) and seven cryptocurrencies (Bitcoin, Ethereum, Litcoin, Dash, Ripple, DigiByte and XEM). In this article, we try to understand how investors react to fluctuations in financial assets to seek safe havens in cryptocurrencies. We used dynamic causality to detect a possible causal relationship in the short term and seven models to estimate the long-term relationship between cryptocurrencies and financial assets. The causal relationship between financial market indexes and cryptocurrency coins in the short run indicates that three famous cryptocurrencies (BITCOIN, ETHEREUM, RIPPLE) and the two digital assets with minor popularity (XEM, Digibyte) are impacted by the German, Russian, and Ukrainian stock markets. In the long run, we found a positive and significate effect of the American, Canadian, French, and Ukrainian stock market indexes on Bitcoin. Thus, the stability of the traditional financial markets during the current war period can be explained on the one hand by investors’ fears of an unstable business climate, and on the other hand, by speculators’ sentiment towards new electronic products, which are perceived as hedging instruments and a safe haven in the face of the conflict between Ukraine and Russia.

Keywords: causality, stock indices, cryptocurrency, war, Russia, Ukraine

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Authors: Mohammad Irfan

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The purpose of this paper is to investigate the relationship among the key macroeconomic variables and Islamic stock market in India. This study is based on the time series data of financial years 2009-2015 to explore the consistency of relationship between macroeconomic variables and Shariah Indices. The ADF (Augmented Dickey–Fuller Test Statistic) and PP (Phillips–Perron Test Statistic) tests are employed to check stationarity of the data. The study depicts the long run relationship between Shariah indices and macroeconomic variables by using the Johansen Co-integration test. BSE Shariah and Nifty Shariah have uni-direct Granger causality. The outcome of VECM is significantly confirming the applicability of best fitted model. Thus, Islamic stock indices are proficiently working for the development of Indian economy. It suggests that by keeping eyes on Islamic stock market which will be more interactive in the future with other macroeconomic variables.

Keywords: Indian Shariah Indices, macroeconomic variables, co-integration, Granger causality, vector error correction model (VECM)

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Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke

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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.

Keywords: generalized autoregressive score model, South Africa, stock returns, time-varying

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Authors: Farid Habibi Tanha, Mojtaba Jahanbazi, Morteza Foroutan, Rasidah Mohd Rashid

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This paper depicts the effects of asymmetric information in determining capital inflows to be captured through stock market microstructure. The model can explain several stylized facts regarding the capital immobility. The first phase of the research involves in collecting and refining 150,000,000 daily data of 11 stock markets over a period of one decade in an effort to minimize the impact of survivorship bias. Three micro techniques were used to measure information asymmetries. The final phase analyzes the model through panel data approach. As a unique contribution, this research will provide valuable information regarding negative effects of information asymmetries in stock markets on attracting foreign investments. The results of this study can be directly considered by policy makers to monitor and control changes of capital flow in order to keep market conditions in a healthy manner, by preventing and managing possible shocks to avoid sudden reversals and market failures.

Keywords: asymmetric information, capital inflow, market microstructure, investment

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Authors: Atul K. Desai, Jigar K. Sevalia, Sandip A. Vasanwala

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When a building is located in an urban area, it is exposed to a wind of different characteristics then wind over an open terrain. This is development of turbulent wake region behind an upstream building. The interaction with upstream building can produce significant changes in the response of the tall building. Here, in this paper, an attempt has been made to study wind induced interference effects on tall building. In order to study wind induced interference effect (IF) on Tall Building, initially a tall building (which is termed as Principal Building now on wards) with square plan shape has been considered with different Height to Width Ratio and total drag force is obtained considering different terrain conditions as well as different incident wind direction. Then total drag force on Principal Building is obtained by considering adjacent building which is termed as Interfering Building now on wards with different terrain conditions and incident wind angle. To execute study, Computational Fluid Dynamics (CFD) Code namely Fluent and Gambit have been used.

Keywords: computational fluid dynamics, tall building, turbulent, wake region, wind

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Authors: Almoutassem Bellah Nasser

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This paper is aimed at calculating the intangible assets of Jordanian economy. This effort is a response to the demand from corporations for these services which reflects a perceived gap in internal and external financial reporting on intangible investments. The main conclusion of the paper is to suggest that the way forward to a standardized, more comparable approach to measuring intangible capital is to employ CIV method of valuation. Published macroeconomic data traditionally exclude most intangible investment from measured GDP. This situation is beginning to change as some attempts have been made to measure the amount of intangible assets. It was found that intangible assets account for $164.20 million in all the listed companies of Jordan. All this money does not appear on the balance sheets of these companies and hence requires special attention of policy makers for better utilization.

Keywords: intangible capital, stock prices, Amman Stock Exchange

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Authors: Olufemi Oyedele

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Building collapse (BC) in Nigeria is becoming a regular occurrence, each recording great casualties in the number of lives and materials lost. Building collapse is a situation where building which has been completed and occupied, completed but not occupied or under construction, collapses on its own due to action or inaction of man or due to natural event like earthquake, storm, flooding, tsunami or wildfire. It is different from building demolition. There are various causes of building collapse and each case requires expert judgment to decide the cause of its collapse. Rate of building collapse is a reflection of the level of organization and control of building activities and degree of sophistication of the construction professionals in a country. This study explored the use of case study by examining the causes of six (6) collapsed buildings (CB) across Nigeria. Samples of materials from the sites of the collapsed buildings were taken for testing and analysis, while critical observations were made at the sites to note the conditions of the ground (building base). The study found out that majority of the building collapses in Nigeria were due to poor workmanship, sub-standard building materials, followed by bad building base and poor design. The National Building Code 2006 is not effective due to lack of enforcement and the Physical Development Departments of states and Federal Capital Territory are just mere agents of corruption allowing all types of construction without building approvals.

Keywords: building collapse, concrete tests, differential settlement, integrity test, quality control

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Authors: Sohanur Rahman, Elisabeth Sinnewe, Larelle (Ellie) Chapple, Sarah Osborne

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Greater political attention to global climate change exposes firms to a higher level of political uncertainty, which can lead to adverse capital market consequences. However, a higher level of discourse on environment-specific political risk (EPR) between management and investors can mitigate information asymmetry, followed by less stock price crash risk. This study examines whether EPR discourse in discourse in the earnings conference calls (ECC) reduces firm-level stock price crash risk in the US market. This research also explores if adverse disclosures via media channels further moderates the association between EPR on crash risk. Employing a dataset of 28,933 firm-year observations from 2002 to 2020, the empirical analysis reveals that EPR discourse in ECC reduces future stock price crash risk. However, adverse disclosures via media channels can offset the favourable effect of EPR discourse on crash risk. The results are robust to the potential endogeneity concern in a quasi-natural experiment setting.

Keywords: earnings conference calls, environment, environment-specific political risk discourse, environmental disclosures, information asymmetry, reputation risk, stock price crash risk

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Authors: Edson Vengesai

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Derivative products have become essential instruments in portfolio diversification, price discovery, and, most importantly, risk hedging. Derivatives are complex instruments; their valuation, volatility implications, and real impact on the underlying assets' behaviour are not well understood. Little is documented empirically, with conflicting conclusions on how these instruments affect firm risk exposures. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivative usage on the underlying stock price exposure and systematic risk. The paper uses data from South African listed firms. The study employs GARCH models to understand the effect of derivative uses on conditional stock volatility. The GMM models are used to estimate the effect of derivatives use on stocks' systematic risk as measured by Beta and on the total risk of stocks as measured by the standard deviation of returns. The results provide evidence on whether derivatives use is instrumental in reducing stock returns' systematic and total risk. The results are subjected to numerous controls for robustness, including financial leverage, firm size, growth opportunities, and macroeconomic effects.

Keywords: derivatives use, hedging, volatility, stock price exposure

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Authors: Yan Lyu, Yiqun Pan, Zhizhong Huang

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In the design stage of a new building, the energy model of this building is often required for the analysis of the performance on energy efficiency. In practice, a certain degree of geometric simplification should be done in the establishment of building energy models, since the detailed geometric features of a real building are hard to be described perfectly in most energy simulation engine, such as ESP-r, eQuest or EnergyPlus. Actually, the detailed description is not necessary when the result with extremely high accuracy is not demanded. Therefore, this paper analyzed the relationship between the error of the simulation result from building energy models and the geometric simplification of the models. Finally, the following two parameters are selected as the indices to characterize the geometric feature of in building energy simulation: the southward projected area and total side surface area of the building, Based on the parameterization method, the simplification from an arbitrary column building to a typical shape (a cuboid) building can be made for energy modeling. The result in this study indicates that this simplification would only lead to the error that is less than 7% for those buildings with the ratio of southward projection length to total perimeter of the bottom of 0.25~0.35, which can cover most situations.

Keywords: building energy model, simulation, geometric simplification, design, regression

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Authors: Mazarine Roquet, Pierre Dewallef

Abstract:

The building sector, both residential and tertiary, accounts for a significant share of greenhouse gas emissions. In Belgium, partly due to poor insulation of the building stock, but certainly because of the massive use of fossil fuels for heating buildings, this share reaches almost 30%. To reduce carbon emissions from urban building heating, district heating networks emerge as a promising solution as they offer various assets such as improving the load factor, integrating combined heat and power systems, and enabling energy source diversification, including renewable sources and waste heat recovery. However, mainly for sake of simple operation, most existing district heating networks still operate at high or medium temperatures ranging between 120°C and 60°C (the socalled second and third-generations district heating networks). Although these district heating networks offer energy savings in comparison with individual boilers, such temperature levels generally require the use of fossil fuels (mainly natural gas) with combined heat and power. The fourth-generation district heating networks improve the transport and energy conversion efficiency by decreasing the operating temperature between 50°C and 30°C. Yet, to decarbonise the building heating one must increase the waste heat recovery and use mainly wind, solar or geothermal sources for the remaining heat supply. Fifth-generation networks operating between 35°C and 15°C offer the possibility to decrease even more the transport losses, to increase the share of waste heat recovery and to use electricity from renewable resources through the use of heat pumps to generate low temperature heat. The main objective of this contribution is to exhibit on a real-life test case the benefits of replacing an existing third-generation network by a fifth-generation one and to decarbonise the heat supply of the building stock. The second objective of the study is to highlight the difficulties resulting from the use of a fifth-generation, low-temperature, district heating network. To do so, a simulation model of the district heating network including its regulation is implemented in the modelling language Modelica. This model is applied to the test case of the heating network on the University of Liège's Sart Tilman campus, consisting of around sixty buildings. This model is validated with monitoring data and then adapted for low-temperature networks. A comparison of primary energy consumptions as well as CO2 emissions is done between the two cases to underline the benefits in term of energy independency and GHG emissions. To highlight the complexity of operating a lowtemperature network, the difficulty of adapting the mass flow rate to the heat demand is considered. This shows the difficult balance between the thermal comfort and the electrical consumption of the circulation pumps. Several control strategies are considered and compared to the global energy savings. The developed model can be used to assess the potential for energy and CO2 emissions savings retrofitting an existing network or when designing a new one.

Keywords: building simulation, fifth-generation district heating network, low-temperature district heating network, urban building heating

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Authors: Domenico Palladino, Nicolandrea Calabrese, Francesca Caffari, Giulia Centi, Francesca Margiotta, Giovanni Murano, Laura Ronchetti, Paolo Signoretti, Lisa Volpe, Silvia Di Turi

Abstract:

The aim to achieve a fully decarbonized building stock by 2050 stands as one of the most challenging issues within the spectrum of energy and climate objectives. Numerous strategies are imperative, particularly emphasizing the reduction and optimization of energy demand. Ensuring the high energy performance of buildings emerges as a top priority, with measures aimed at cutting energy consumptions. Concurrently, it is imperative to decrease greenhouse gas emissions by using renewable energy sources for the on-site energy production, thereby striving for an energy balance leading towards zero-emission buildings. Italy's predominant building stock comprises ancient buildings, many of which hold historical significance and are subject to stringent preservation and conservation regulations. Attaining high levels of energy efficiency and reducing CO2 emissions in such buildings poses a considerable challenge, given their unique characteristics and the imperative to adhere to principles of conservation and restoration. Additionally, conducting a meticulous analysis of these buildings' current state is crucial for accurately quantifying their energy performance and predicting the potential impacts of proposed renovation strategies on energy consumption reduction. Within this framework, the paper presents a pilot case in Rome, outlining a methodological approach for the renovation of historic buildings towards achieving Zero Emission Building (ZEB) objective. The building has a mixed function with offices, a conference hall, and an exposition area. The building envelope is made of historical and precious materials used as cladding which must be preserved. A thorough understanding of the building's current condition serves as a prerequisite for analyzing its energy performance. This involves conducting comprehensive archival research, undertaking on-site diagnostic examinations to characterize the building envelope and its systems, and evaluating actual energy usage data derived from energy bills. Energy simulations and audit are the first step in the analysis with the assessment of the energy performance of the actual current state. Subsequently, different renovation scenarios are proposed, encompassing advanced building techniques, to pinpoint the key actions necessary for improving mechanical systems, automation and control systems, and the integration of renewable energy production. These scenarios entail different levels of renovation, ranging from meeting minimum energy performance goals to achieving the highest possible energy efficiency level. The proposed interventions are meticulously analyzed and compared to ascertain the feasibility of attaining the Zero Emission Building objective. In conclusion, the paper provides valuable insights that can be extrapolated to inform a broader approach towards energy-efficient refurbishment of historical buildings that may have limited potential for renovation in their building envelopes. By adopting a methodical and nuanced approach, it is possible to reconcile the imperative of preserving cultural heritage with the pressing need to transition towards a sustainable, low-carbon future.

Keywords: energy conservation and transition, energy efficiency in historical buildings, buildings energy performance, energy retrofitting, zero emission buildings, energy simulation

Procedia PDF Downloads 45

Authors: Erfan Memarian, Seyyed Fazayel Alizadeh

Abstract:

This study aims to evaluate the impacts of the oil and financial markets of the United States on Iran stock exchange and to develop an ARDL model to predict the short and long-term relationship between these markets. In this regard, all 713 weekly data between 28 July 1999 and 20 March 2013 were analyzed by using Microfit4.0 and Eviews7 econometric softwares. The independent variable of the study is the “Price and Yield Index (TEDPIX)” of Tehran Stock Exchange and the independent variables include S & P 500 Index, the US three-month treasury bill rate and West Texas Intermediate oil spot price index. The results show that the West Texas Intermediate oil spot price and the S&P 500 indices have significant positive relationships with Iran's TEDPIX. Also, there exists a significant negative relationship between Iran's TEDPIX and the US three-month Treasury bill rate.

Keywords: TEDPIX; Tehran Stock Exchange; S&P 500 index; USA three-month Treasury bill rate; West Texas Intermediate oil

Procedia PDF Downloads 311