Research articles for the 2020-09-09

A Tale of Two Skewness: Professional Epidemic Experience, Probability Weighting, and Stock Price Crash Risk
Gu, Leilei,Ni, Xiaoran,Peng, Yuchao
Under probability weighting, entrepreneurs’ skewness preference, the tendency to seek right-skewed and avoid left-skewed risks, can affect the negative skewness of stock prices. Based on the evidence after the outbreak of Severe Acute Respiratory Syndrome (SARS), which is caused by the same family of viruses as COVID-19, we show that firms managed by CEOs who previously experienced the outbreak of SARS during their tenure of high executives have lower stock price crash risk measured by negative skewness. Among those firms, this effect especially matters for CEOs that actually experienced prominent operating distress or stock price crashes during the outbreak of SARS. In addition, firms managed by CEOs with professional epidemic experience tend to disclose bad news in a timelier manner, and have lower discretionary accruals. Our overall evidence indicates that entrepreneurs with imprinted professional epidemic experience may overweight the probability of extreme tail events. As a result, they intentionally avoid stock price crashes through preventing the formation and accumulation of bad news.

Achieving Broadened Accountability in Nonprofit Governance Through Social Competence Within a Community of Practice
Morrison, Joseph
The nonprofit sector is challenged by increasing public and stakeholder demands for a Broadened Accountability (BA). Strong expectations for performance accountability now accompany those for fiscal accountability. In response, better concepts of nonprofit accountability and associated practices to achieve it are being developed in the literature. However, knowledge of obstacles to achieving Broadened Accountability and possible paths towards overcoming them has lagged. This paper attempts to stimulate research and contribute to such knowledge by 1) elaborating on the assertion that a central difficulty is found in a pair of perceived governance dilemmas that can drive leaders into either/or choices between the two forms of accountability; 2) exploring the role that a Community of Practice (COP) can play in avoiding governance dilemmas; and 3) developing grounded concepts around how relational practices such as blended strategizing, facework, reflexive monitoring and skillful organizing contribute to the formation of a COP. The study’s ethnographic methods recorded and analyzed real-life interactions involving a board chair-chief executive officer pair. The paper presents detailed narrative description of these actions to convey its key contribution â€" a process model for overcoming obstacles to achieving BA â€" and to provide stimulus for new practice by leaders in governance situations.

Artificial Intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry
Nils Köbis,Luca Mossink

The release of openly available, robust natural language generation algorithms (NLG) has spurred much public attention and debate. One reason lies in the algorithms' purported ability to generate human-like text across various domains. Empirical evidence using incentivized tasks to assess whether people (a) can distinguish and (b) prefer algorithm-generated versus human-written text is lacking. We conducted two experiments assessing behavioral reactions to the state-of-the-art Natural Language Generation algorithm GPT-2 (Ntotal = 830). Using the identical starting lines of human poems, GPT-2 produced samples of poems. From these samples, either a random poem was chosen (Human-out-of-the-loop) or the best one was selected (Human-in-the-loop) and in turn matched with a human-written poem. In a new incentivized version of the Turing Test, participants failed to reliably detect the algorithmically-generated poems in the Human-in-the-loop treatment, yet succeeded in the Human-out-of-the-loop treatment. Further, people reveal a slight aversion to algorithm-generated poetry, independent on whether participants were informed about the algorithmic origin of the poem (Transparency) or not (Opacity). We discuss what these results convey about the performance of NLG algorithms to produce human-like text and propose methodologies to study such learning algorithms in human-agent experimental settings.

Bank Cleanups, Capitalization and Lending: Evidence from India
Chopra, Yakshup,Subramanian, Krishnamurthy,Tantri, Prasanna L.
We examine the Indian bank asset quality review, which doubled the declared loan delinquency rate. Relative economic stability during the exercise and the absence of a capital backstop together make it unique. We find that the expected reduction in information asymmetry does not automatically lead to the recapitalization of banks by markets. The consequent undercapitalization leads to underinvestment and risk-shifting through zombie lending. The impact flows to the real economy through borrowers, including shadow banks, and adversely impacts growth. These findings show that bank cleanup exercises not accompanied by policies aimed at recapitalization may be insufficient even during normal times.

Big Data, Artificial Intelligence and Machine Learning: A Transformative Symbiosis in Favour of Financial Technology
Stasinakis, Charalampos,Sermpinis, Georgios
The financial technology revolution is a reality, as the financial world is gradually transforming into a digital domain of high-volume information and high-speed data transformation and processing. The more this transformation takes place, the more consumer and investor behaviour shifts towards a pro-technology attitude of financial services offered by market participants, financial institutions and financial technology companies. This new norm is confirming that information technology is driving innovation for financial technology. In this framework, the value of big data, artificial intelligence and machine learning techniques becomes apparent. The aim of this chapter is multi-fold. Firstly, a multidimensional descriptive analysis is shown to familiarise the reader with the extent of penetration of the above in the financial technology road-map. A short non-technical overview of the methods is then presented. Next, the impact of data analytics and relevant techniques on the evolution of financial technology is explained and discussed along with their applications’ landscape. The chapter also presents a glimpse of the shifting paradigm these techniques bring forward for several fintech related professions, while artificial intelligence and machine learning techniques are tied with the future challenges of AI ethics, regulation technology and the smart data utilisation.

Combined Framing Effects of Emotion and Visual Exemplar on Attitudes and Behavioral Intentions Toward Carbon Pricing
Dobson, David
Carbon pricing is believed to be one of the most effective ways to curb carbon emissions. However, societal acceptance of carbon pricing has been lukewarm, as it imposes fees on consumers. This study investigated the role of combining emotional responses in gain/loss framing with visual imagery in generating a desired attitude and behavioral intention toward carbon pricing. The study tested the effects of message framing in a 2x2 (emotion: hope vs. fear; visual: present vs. absent) between-subjects experiment and showed that fear arousal in the loss-framed message was more persuasive than hope arousal in the gain-framed message. The mediation role of message evaluative processing on fear response was significant. This research offers important theoretical contributions by examining the role of emotions and visual imagery in carbon pricing persuasion. It also poses helpful message framing guidance for public policy decision-making on communicating carbon pricing.

Dynamic Capabilities in Microfinance Innovation: A Case Study of the Grameen Foundation
Kayongo, Sarah,Mathiassen, Lars
The purpose of this research is to understand how microfinance organizations innovate their products, services, and processes to improve financial inclusion. The approach used is a retrospective, longitudinal, qualitative case study of how Grameen Foundation, a global non-government organization that partners with various microfinance institutions to provide micro loans and savings innovated. Data was obtained using semi structured interviews and publicly available material. Applying Dynamic Capability Theory highlighted the unique ways in which Grameen Foundation innovated through the three concepts of (1) sensing, (2) seizing, and (3) transforming. Our findings offer five insights that characterize how Grameen Foundation innovated its products, services and processes to improve financial inclusion by: 1) sensing country-specific needs; 2) seizing opportunities to use existing technology; 3) funding projects that created financial linkages through multi-sectorial partnerships; 4) adopting a business model that enabled innovation transfer and scaling; and, 5) strengthening how program performance was measured, monitored and evaluated to sustain the scaling of outcomes. While single case studies suffer from limited generalizability, this study may help microfinance practitioners assess the transferability of the findings to other contexts where changes will likely produce different outcomes for microfinance institutions and their beneficiaries. Future studies will benefit from applying other methods and theories that focus on innovation with built-in resiliency and capabilities to withstand the everchanging economic environments in which microfinance institutions operate.

Fairness principles for insurance contracts in the presence of default risk
Delia Coculescu,Freddy Delbaen

We use the theory of cooperative games for the design of fair insurance contracts. An insurance contract needs to specify the premium to be paid and a possible participation in the benefit (or surplus) of the company. It results from the analysis that when a contract is exposed to the default risk of the insurance company, ex-ante equilibrium considerations require a certain participation in the benefit of the company to be specified in the contracts. The fair benefit participation of agents appears as an outcome of a game involving the residual risks induced by the default possibility and using fuzzy coalitions.

High-Resolution Poverty Maps in Sub-Saharan Africa
Kamwoo Lee,Jeanine Braithwaite

Up-to-date poverty maps are an important tool for policymakers, but until now, have been prohibitively expensive to produce. We propose a generalizable prediction methodology to produce poverty maps at the village level using geospatial data and machine learning algorithms. We tested the proposed method for 25 Sub-Saharan African countries and validated them against survey data. The proposed method can increase the validity of both single country and cross-country estimations leading to higher precision in poverty maps of the 25 countries than previously available. More importantly, our cross-country estimation enables the creation of poverty maps when it is not practical or cost-effective to field new national household surveys, as is the case with many Sub-Saharan African countries and other low- and middle-income countries.

How Do Investors React to Investment-Opportunity Shock? Evidence from the COVID-19 Pandemic and Taiwan Bio-Tech Firms
Chen, Yue-Rong,Li, Mei-Xuan,Wang, Yanzhi
While the stock market crashed in the first quarter after the outbreak of COVID-19, this paper finds that bio-tech firms and their investors could take advantage of the COVID-19 investment opportunity and earn positive abnormal returns. Bio-tech firms earn abnormal returns of 1.63% per dayâ€"which can be translated into average capital gains of about 86.7 million NT dollars per dayâ€" around the event day on which the WHO declared COVID-19 a global emergency. Positive returns continue after the event day. Moreover, small firms and firms that enjoy greater patent originality and receiving government R&D subsidies earn higher abnormal returns.

How Important is Social Trust During the COVID-19 Crisis Period? Evidence from the Fed Announcements
Mazumder, Sharif
During the COVID-19 crisis period, firms headquartered in high social trust US states perform better than their counterparts from the low social trust states. Stock returns over the crisis period are 3 to 4 percentage points higher, on average, if social trust increases by one standard deviation. The association is stronger for firms of more affected industries (COVID-19 industries). More specifically, a one standard deviation increase of social trust associates with a 6.45% increase of 𝐶𝐴ð'… if firms belong to the COVID-19 industries. Next, I analyze the stock market reactions to the Fed’s announcements on March 23, 2020. The results show that firms headquartered in the high trust states benefit less from the announcements because these firms can access to other external financings cheaply. The average three-day announcement 𝐶𝐴ð'… and 𝐵𝐻𝐴ð'… (FF 3-factor adjusted) are higher by 2.5% and 2.6%, respectively, if firms headquartered in low trust states.

Information Chasing versus Adverse Selection in Over-the-Counter Markets
Wang, Chaojun,Zou, Junyuan
Contrary to the prediction of the classic adverse selection theory, informed speculators receive better pricing relative to uninformed liquidity traders in over-the-counter financial markets. Dealers compete for information by chasing informed orders so as to better position their future price quotes. On a multi-dealer platform, dealers' incentive of information chasing exactly offsets their fear of adverse selection. Through information chasing, dealers transform adverse selection by the informed into winner's curse when bidding for the uninformed. As a result, the adverse selection cost is entirely passed on to liquidity traders. Price dispersion and bid-ask spread endogenously arise from winner's curse. Both price dispersion and price efficiency increase with the mass of liquidity traders. As long as speculators have slightly correlated signals, they trade with the same dealer in equilibrium, giving rise to an information monopolist despite direct competition among the dealers. Post-trade transparency reduces information chasing incentive and thus price efficiency.

Inter-organisational patent opposition network: How companies form adversarial relationships
Tomomi Kito,Nagi Moriya,Junichi Yamanoi

Much of the research on networks using patent data focuses on citations and the collaboration networks of inventors, hence regarding patents as a positive sign of invention. However, patenting is, most importantly, a strategic action used by companies to compete with each other. This study sheds light on inter-organisational adversarial relationships in patenting for the first time. We constructed and analysed the network of companies connected via patent opposition relationships that occurred between 1980 and 2018. A majority of the companies are directly or indirectly connected to each other and hence form the largest connected component. We found that in the network, many companies disapprove patents in various industrial sectors as well as those owned by foreign companies. The network exhibits heavy-tailed, power-law-like degree distribution and assortative mixing, making it an unusual type of topology. We further investigated the dynamics of the formation of this network by conducting a temporal network motif analysis, with patent co-ownership among the companies considered. By regarding opposition as a negative relationship and patent co-ownership as a positive relationship, we analysed where collaboration may occur in the opposition network and how such positive relationships would interact with negative relationships. The results identified the structurally imbalanced triadic motifs and the temporal patterns of the occurrence of triads formed by a mixture of positive and negative relationships. Our findings suggest that the mechanisms of the emergence of the inter-organisational adversarial relationships may differ from those of other types of negative relationships hence necessitating further research.

Is Mandatory Risk Reporting Informative? Evidence from US REITS Using Machine Learning for Text Analysis
Koelbl, Marina,Schuierer, Ralf,Steininger, Bertram I.
The typical SEC’s reaction to a crisis is strengthening disclosure requirements mandating firms to inform investors about their assessment of future contingencies. This should enable investors to monitor risks a firm is facing. However lengthy and complex disclosures â€" mostly for dozens or hundreds of firms in an investor’s portfolio â€" can hardly be processed by a human. Additionally, it is unclear if investors follow regulatory requirements or disclosures are merely boilerplates giving the investor a limited view. The reported risk factors can be property-specific or market-wide such as the recent financial crisis or the current coronavirus. It would be informative for investors to see the firm’s risk assessment regarding these kinds of risks. To cope with the flood of information, we propose to use an unsupervised machine learning algorithm to identify and quantify the risk factor topics discussed in the SEC’s 10-K filing. We apply this algorithm (Structural Topic Model, STM) to the Item 1A and Item 7A of the US REITs’ 10-K’s filings between 2005 and 2019. Our results suggest, that STM is advantageous over the traditional methods since it finds clearer and consequently more meaningful risk factor topics beyond the investment foci of REITs. Furthermore, we investigate whether and how the identified topics affect the risk perception of investors after the filing date. We find all three kinds of topics: uninformative topics with no impact (null argument), increasing risk perception topics (divergence argument), and decreasing risk perception topics (convergence argument) â€" the majority. Overall, our results suggest that REIT managers use risk disclosures to reveal previously unknown information that has not yet been incorporated into market prices in the short run; but they diminish in the long run.

Law-invariant functionals that collapse to the mean
Fabio Bellini,Pablo Koch-Medina,Cosimo Munari,Gregor Svindland

We discuss when law-invariant convex functionals "collapse to the mean". More precisely, we show that, in a large class of spaces of random variables and under mild semicontinuity assumptions, the expectation functional is, up to an affine transformation, the only law-invariant convex functional that is linear along the direction of a nonconstant random variable with nonzero expectation. This extends results obtained in the literature in a bounded setting and under additional assumptions on the functionals. We illustrate the implications of our general results for pricing rules and risk measures.

Level Up: The Success Factors in Advancing African-American Women Into the C-Suite in Corporate America
Bishop, Jennifer
Research shows that African-American women represent a small number of C-Suite positions in US Fortune 500 and Fortune 1000 corporations. It appears that cracks are beginning to form in the glass ceiling. However, for African-American women, a barrier called the “Black Ceiling,” remains in place. Black women, who have made it, often are ending up in support positions, rather than the operational roles leading to CEO positions (McGirt, E. 2017). Research shows that having women on a company’s board of directors is associated with better financial performance, a better gender mix among senior managers and a link to greater financial results. According to Catalyst (2019), women made up 58% of all employees in the financial services industry between the years of 2007 and 2015. During that same period, women represented 48% of first/mid-level managers and 29% of executive/senior-level managers. Women of color, however, represented only 16.8% of first/mid-level managers and 4.8% of executive/senior-level managers. This research will examine how African-American women’s careers, in Mid-level and Senior-level management, have currently advanced in the financial services industry. What factors are helping African-American women experience career advancements/promotions, and, with minimal support, what would position them to be in the succession pipeline leading to the C-Suite level in the banking industry?

Multi-utility representations of incomplete preferences induced by set-valued risk measures
Cosimo Munari

We establish a variety of numerical representations of preference relations induced by set-valued risk measures. Because of the general incompleteness of such preferences, we have to deal with multi-utility representations. We look for representations that are both parsimonious (the family of representing functionals is indexed by a tractable set of parameters) and well behaved (the representing functionals satisfy nice regularity properties with respect to the structure of the underlying space of alternatives). The key to our results is a general dual representation of set-valued risk measures that unifies the existing dual representations in the literature and highlights their link with duality results for scalar risk measures.

Pathway to Personal Financial Success
Tyler, Jeffrey,Servi, Jim
Individuals armed with solid financial knowledge and commitment to prudent financial goals likely will achieve a higher level of wealth and ultimately financial wellness than those who do not. There are, however, potential landmines along the road to financial wellness. Two of the biggest negative behaviors that can get individuals off track are procrastination and impulsive purchasing. Our research will show how self-regulation can temper the negative effects of procrastination and impulsivity, when supported through the intervention of social support which can serve to strengthen positive financial habits.

Problems of Economic Recovery Planning after the COVID-19 Pandemic
Prohorovs, Anatolijs
As a result of the COVID-19 pandemic, for the first time in contemporary history, countries have faced an extensive and multifaceted negative impact on the economy, affecting almost all areas of socio-economic activity around the world and, accordingly, the drafting of recovery plans.The drafting of state economic recovery plans to mitigate the consequences of the COVID-19 pandemic is one of the most important factors influencing both the speed of recovery and the further development of the economy.The preparation of medium-term, regularly drafted government plans differs significantly from the planning required for a more effective economic recovery from the consequences of COVID-19. Some of the main differences are in algorithms and procedures for preparing plans, the required speed of their drafting, a higher level of uncertainty in planning and, accordingly, higher requirements for the coordination and management of the implementation of the drafted plans. In addition, drafting national plans for economic recovery is closely linked to the further development of the economy. Since the problems of economic development differ in different countries, this aspect must also be taken into account when drafting plans for the recovery and further development of the economy. Based on this, the article discusses the specific features and problems that need to be taken into account when drafting national plans for economic recovery after the COVID-19 pandemic.

Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies
Alla A. Petukhina,Raphael C. G. Reule,Wolfgang Karl Härdle

This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market. We study trading quantitatives such as returns, traded volumes, volatility periodicity, and provide summary statistics of return correlations to CRIX (CRyptocurrency IndeX), as well as respective overall high-frequency based market statistics with respect to temporal aspects. Our results provide mandatory insight into a market, where the grand scale employment of automated trading algorithms and the extremely rapid execution of trades might seem to be a standard based on media reports. Our findings on intraday momentum of trading patterns lead to a new quantitative view on approaching the predictability of economic value in this new digital market.

Stale Information in the Spotlight: The Effects of Attention Shocks on Equity Markets
Chen, Siyu,Lu, Runjing
Using a novel natural experiment, we provide causal evidence on how asset prices are affected when the media draws investor attention to stale information. We find that shortly after the announcement of a high-profile financial analyst award, stocks with preexisting recommendations from analysts who receive heightened media exposure from winning the award experience higher abnormal returns than those recommended by analysts who barely lose the award. Attention trading rather than ability signaling drives the differences in the returns. Furthermore, the award changes brokerages’ resource allocation and analysts’ information production, thereby having long-lasting effects on equity markets.

SynthETIC: an individual insurance claim simulator with feature control
Benjamin Avanzi,Gregory Clive Taylor,Melantha Wang,Bernard Wong

A simulator of individual claim experience called SynthETIC is described. It is publicly available, open source and fills a gap in the non-life actuarial toolkit. It simulates, for each claim, occurrence, notification, the timing and magnitude of individual partial payments, and closure. Inflation, including (optionally) superimposed inflation, is incorporated in payments. Superimposed inflation may occur over calendar or accident periods. The claim data are summarized by accident and payment "periods" whose duration is an arbitrary choice (e.g. month, quarter, etc.) available to the user. The code is structured as eight modules (occurrence, notification, etc.), any one or more of which may be re-designed according to the user's requirements. The default version is parameterized so as to include a broad (though not numerically precise) resemblance to the major features of experience of a specific (but anonymous) Auto Bodily Injury portfolio. It thus reflects a number of desirable (but complicated) data features, but the general structure is suitable for most lines of business, with some amendment of modules. The structure of the simulator enables the inclusion of a number of important dependencies between the variables related to an individual claim, e.g. dependence of notification delay on claim size, of the size of a partial payment on the sizes of those preceding, etc. The user has full control of the mechanics of the evolution of an individual claim. As a result, the complexity of the data set generated (meaning the level of difficulty of analysis) may be dialled anywhere from extremely simple to extremely complex. The user may generate a collection of data sets that provide a spectrum of complexity, and the collection may be used to present a model under test with a steadily increasing challenge.

The Fed Takes on Corporate Credit Risk: An Analysis of the Efficacy of the SMCCF
Gilchrist, Simon,Wei, Bin,Yue, Zhanwei,Zakrajsek, Egon
We evaluate the efficacy of the Secondary Market Corporate Credit Facility (SMCCF), a program designed to stabilize the corporate bond market in the wake of the COVID-19 shock. The Fed announced the SMCCF on March 23 and expanded the program on April 9. Regression discontinuity estimates imply that these announcements reduced credit spreads on bonds eligible for purchase 70 basis points. We refine this analysis by constructing a sample of bondsâ€"issued by the same set of companiesâ€"which differ in their SMCCF eligibility. A diff-in-diff analysis shows that both announcements had large effects on credit spreads, narrowing spreads 20 basis points on eligible bonds relative to their ineligible counterparts within the same set of issuers across the two announcement periods. TheMarch 23 announcement also reduced bid-ask spreads ten basis points within ten days of the announcement. By lowering credit spreads and improving liquidity, the April 9 announcement had an especially pronounced effect on “fallen angels.” The actual purchases lowered credit spreads by an additional five basis points and bid-ask spreads by two basis points. These results confirm that the SMCCF made it easier for companies to borrow in the corporate bond market.

The Impact of COVID-19 and Policy Responses on Australian Income Distribution and Poverty
Jinjing Li,Yogi Vidyattama,Hai Anh La,Riyana Miranti,Denisa M Sologon

This paper undertakes a near real-time analysis of the income distribution effects of the COVID-19 crisis in Australia to understand the ongoing changes in the income distribution as well as the impact of policy responses. By semi-parametrically combining incomplete observed data from three different sources, namely, the Monthly Longitudinal Labour Force Survey, the Survey of Income and Housing and the administrative payroll data, we estimate the impact of COVID-19 and the associated policy responses on the Australian income distribution between February and June 2020, covering the immediate periods before and after the initial outbreak. Our results suggest that despite the growth in unemployment, the Gini of the equalised disposable income inequality dropped by nearly 0.03 point since February. The reduction is because of the additional wage subsidies and welfare supports offered as part of the policy response, offsetting a potential surge in income inequality. Additionally, the poverty rate, which could have been doubled in the absence of the government response, also reduced by 3 to 4 percentage points. The result shows the effectiveness of temporary policy measures in maintaining both the living standards and the level of income inequality. However, the heavy reliance on the support measures raises the possibility that the changes in the income distribution may be reversed and even substantially worsened off should the measures be withdrawn.

Time-inconsistent Markovian control problems under model uncertainty with application to the mean-variance portfolio selection
Tomasz R. Bielecki,Tao Chen,Igor Cialenco

In this paper we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfect strategies with the adaptive robust stochastic to tackle the theoretical aspects of the considered stochastic control problem. Consequently, as an important application of the theoretical results, by applying a machine learning algorithm we solve numerically the mean-variance portfolio selection problem under the model uncertainty.

V-, U-, L-, or W-shaped recovery after COVID: Insights from an Agent Based Model
Dhruv Sharma,Jean-Philippe Bouchaud,Stanislao Gualdi,Marco Tarzia,Francesco Zamponi

We discuss the impact of a Covid-like shock on a simple toy economy, described by the Mark-0 Agent-Based Model that we developed and discussed in a series of previous papers. We consider a mixed supply and demand shock, and show that depending on the shock parameters (amplitude and duration), our toy economy can display V-shaped, U-shaped or W-shaped recoveries, and even an L-shaped output curve with permanent output loss. This is due to the existence of a self-sustained "bad" state of the economy. We then discuss two policies that attempt to moderate the impact of the shock: giving easy credit to firms, and the so-called helicopter money, i.e. injecting new money into the households savings. We find that both policies are effective if strong enough, and we highlight the potential danger of terminating these policies too early. While we only discuss a limited number of scenarios, our model is flexible and versatile enough to allow for a much wider exploration, thus serving as a useful tool for the qualitative understanding of post-Covid recovery. We provide an on-line version of the code at .

Warren Buffett: A Practical Understanding of Financial Literacy Extended to Managing Investments
Koch, Christian
2020 has been a time of unprecedented change. Financial markets and consumer confidence have collapsed. The unemployment rate has reached double digits; the United States appears headed into a recession. Financial planning is in more demand as individuals and financial markets react to the COVID-19 pandemic. The increased demand highlights financial literacy concerns around managing investments. Since investment financial decision making can be a complex web with multiple factors, industry practitioners take various approaches to it. Often, people involved in the market make irrational decisions that violate sound judgment and basic economic investment principles. Therefore, financial advisors need to become leaders in adopting new research into practice that can advance financial literacy knowledge. Warren Buffett offers unconventional success to the fundamental approach to managing investments. Despite his success and large following in the investment world, Buffett’s approaches have not been passed to Americans. In this article, we use a thematic qualitative study to analyze Buffett’s approaches to managing investments by examining 11 years of his comments via the Warren Buffett Archive. Our analysis yields eight critical findings that are well-suited for industry, practitioners, and investors to make better, more informed investing decisions; two findings are uncommon approaches to managing investments.

واقع أمن وسرية المعلومات الإلكترونية في بنك فلسطين
Shehada, Feras ,بدر, محمد
Arabic Abstract: هدفت هذه الدراسة إلى تقييم واقع أمن وسرية المعلومات الإلكترونية في بنك فلسطين "دراسة حالة" من خلال التعرف على مدى توافر مقومات حماية البنية التحتية لأمن المعلومات ، ولتحقيق هدف الدراسة تم إعداد استبانة مكونة من ثلاث محاور (الحماية المادية - الحماية البرمجية - حماية الأفراد) لقياس متغيرات الدراسة , وزعت على العاملين في أقسام تكنولوجيا المعلومات في بنك فلسطين وقد شملت عينة الدارسة على (38) وزعت عليهم الاستبانة وتم استرداد (31) استبانة حيث بلغت نسبة الاسترداد81%) )، وقد توصلت الدراسة إلى نتائج مهمة تشير إلى أنه يتوفر لدى بنك فلسطين مقومات بنية تحتية مقبولة بمحاورها الثلاثة (المادية ,البرمجية، والأفراد ) بنسب متفاوتة , حيث كان المحور الأول (الحماية المادية) في المرتبة الأولى بنسبة (%92.69), أما المحور الثاني (الحماية البرمجية ) كان في المرتبة الثانية بنسبة (%88.77) , والمحور الأخير (حماية الأفراد) احتل المرتبة الثالثة بنسبة (%80.00) مما يدل على أن الآراء كانت في المحاور الثلاثة موافقة بدرجة كبيرة جداً, وأنه لا توجد فروق ذات دلالة إحصائية في استجابات أفراد العينة حول واقع إدارة أمن المعلومات في بنك فلسطين تُعزى للمتغيرات الديموغرافية (المؤهل العلمي، المستوى الوظيفي، والخبرة) باستثناء متغير الدورات التدريبية حيث أظهرت النتائج أنه يوجد فروق ذات دلالة إحصائية في استجابات أفراد العينة حول واقع إدارة أمن المعلومات في بنك فلسطين تُعزى لمتغير الدورات التدريبية. وانتهت الدراسة إلى مجموعة من التوصيات من أهمها ، قيام بنك فلسطين بتطوير سياسات أمن المعلومات الخاصة به، والعمل على نشرها و تطبيقها، والقيام بمراجعتها، لما لهذه السياسات من أثر في تحسين الإجراءات الأمنية , ضرورة حث المصارف الفلسطينية على الاستمرار بالاهتمام بالبنية التحتية لأمن المعلومات وتطويرها لتجاري المستحدثات التكنولوجية السريعة.English Abstract: This study aims at evaluating the reality of electronic information security in Bank of Palestine" Case Study ", through recognizing the availability of the elements to protect the infrastructure of information security. To achieve the objective of this study, a questionnaire was prepared and consisted at three axes (Physical protecting, programming protecting and protect the individuals) To measure study variables, It was distributed among the employees in the Departments of information technology in Bank of Palestine, The study sample included (38) employees, we regained( 31) questionnaire, recovery rate of (81%). The study reached important results that there is in Bank Of Palestine the elements of accepted infrastructure in its three axes the( Physical, programming and individuals) in a different ration, and there was no significant differences related to individuals responses about the real field of information security in the Bank Of Palestine, that refers to demographic variables (Qualification, the professional level, the Experience). and there are significant differences related to individuals responses about the real field of information security in the Bank Of Palestine that refers to variable (training courses).The study ends in some recommendations, The most important one is that Bank Of Palestine should improve their own information security policies and publish, apply, develop and review them. As these policies have significant effects in promoting the security procedures, Also, they are important to encourage the Palestinian banks to continue paying attention to the information security infrastructure and developing to keep pace with rapid technological innovations.