scholarly journals Forward-Looking Volatility Estimation for Risk-Managed Investment Strategies during the COVID-19 Crisis

Risks ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 33
Author(s):  
Luca Di Persio ◽  
Matteo Garbelli ◽  
Kai Wallbaum
Keyword(s):  
Developed Countries ◽  
Investment Strategies ◽  
Economic Returns ◽  
Control Solution ◽  
Volatility Estimation ◽  
Risk Return ◽  
Time Period ◽  
Long Time ◽  
The Impact ◽  
Forward Looking

Under the impact of both increasing credit pressure and low economic returns characterizing developed countries, investment levels have decreased over recent years. Moreover, the recent turbulence caused by the COVID-19 crisis has accelerated the latter process. Within this scenario, we consider the so-called Volatility Target (VolTarget) strategy. In particular, we focus our attention on estimating volatility levels of a risky asset to perform a VolTarget simulation over two different time horizons. We first consider a 20 year period, from January 2000 to January 2020, then we analyse the last 12 months to emphasize the effects related to the COVID-19 virus’s diffusion. We propose a hybrid algorithm based on the composition of a GARCH model with a Neural Network (NN) approach. Let us underline that, as an alternative to standard allocation methods based on realized and backward oriented volatilities, we exploited an innovative forward-looking estimation process exploiting a Machine Learning (ML) solution. Our solution provides a more accurate volatility estimation, allowing us to derive an effective investor risk-return profile during market crisis periods. Moreover, we show that, via a forward-looking VolTarget strategy while using an ML-based prediction as the input, the average outcome for an investment in a drawdown plan is more sustainable while representing an efficient risk-control solution for long time period investments.

scholarly journals Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Ulrik B. Pedersen ◽  
Dimitrios-Alexios Karagiannis-Voules ◽  
Nicholas Midzi ◽  
Tkafira Mduluza ◽  
Samson Mukaratirwa ◽  
...  
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Predictive Accuracy ◽  
Weather Data ◽  
Geostatistical Model ◽  
Prevalence Data ◽  
Time Period ◽  
Long Time ◽  
Potential Risk Factors ◽  
The Impact

Temperature, precipitation and humidity are known to be important factors for the development of schistosome parasites as well as their intermediate snail hosts. Climate therefore plays an important role in determining the geographical distribution of schistosomiasis and it is expected that climate change will alter distribution and transmission patterns. Reliable predictions of distribution changes and likely transmission scenarios are key to efficient schistosomiasis intervention-planning. However, it is often difficult to assess the direction and magnitude of the impact on schistosomiasis induced by climate change, as well as the temporal transferability and predictive accuracy of the models, as prevalence data is often only available from one point in time. We evaluated potential climate-induced changes on the geographical distribution of schistosomiasis in Zimbabwe using prevalence data from two points in time, 29 years apart; to our knowledge, this is the first study investigating this over such a long time period. We applied historical weather data and matched prevalence data of two schistosome species (<em>Schistosoma haematobium</em> and <em>S. mansoni</em>). For each time period studied, a Bayesian geostatistical model was fitted to a range of climatic, environmental and other potential risk factors to identify significant predictors that could help us to obtain spatially explicit schistosomiasis risk estimates for Zimbabwe. The observed general downward trend in schistosomiasis prevalence for Zimbabwe from 1981 and the period preceding a survey and control campaign in 2010 parallels a shift towards a drier and warmer climate. However, a statistically significant relationship between climate change and the change in prevalence could not be established.

scholarly journals The changes of the agribusiness impact on the competitive environment of agricultural enterprises

2012 ◽  
Vol 48 (No. 10) ◽  
pp. 449-455 ◽  
Author(s):  
V. Bečvářová
Keyword(s):  
Market Power ◽  
Food Chain ◽  
Research Output ◽  
Developed Countries ◽  
Food Distribution ◽  
Agricultural Enterprises ◽  
Positive Effects ◽  
Regulatory Policies ◽  
Long Time ◽  
The Impact

The market extension generally affects growth performance positively by allowing an expansion of markets, by increasing outside competition as well as by more rapid diffusion of new products, processes and research output between national economies. The positive effects of considerable market on productivity are indubitable. However, two other weighty phenomena of the process are necessary to investigate, effects of regulatory policy and market power exhibits. Agriculture as a sector belongs to those, where the support policies exist for a long time. Nevertheless, the last decades have witnessed considerable changes in this sector among most of developed countries and their agricultural/regulatory policies. It has been perceived, that the agriculture for 21st&nbsp;century cannot be separated from the other components of agri-food sector. The economic importance of the processing and finalization stages (i.e. food industry and food distribution) has increased over time. There are concerned inter-relationships between the market structures development and the crucial factors of the interconnected markets developments in the framework of production verticals of agricultural commodities. Reflecting the steadily more sophisticated supply side behaviour, solution is based upon the demand oriented approach explaining changes of the position of agriculture within the agri-food chain. Conflict of interest between the regulatory/agricultural policy and the market power of input supply and output processing firms and retail notably has increased dramatically. Economic manifestation of the increasing market power on the demand side as well as the impact of market interrelationships and change of policy regulation efficiency within commodity chains are characterised there.&nbsp; The position of agriculture within the agri-food chain has changed and the influence of farmers has decreased. Success of agricultural enterprises in achieving their operational goals is still more influenced by improvements in productivity and by competitiveness of other &ldquo;links&rdquo; of the agri-food chain.

scholarly journals The Impact of Economic Freedom on Economic Growth? New European Dynamic Panel Evidence

2020 ◽  
Vol 13 (2) ◽  
pp. 26
Author(s):  
Ivana Brkić ◽  
Nikola Gradojević ◽  
Svetlana Ignjatijević
Keyword(s):  
Economic Growth ◽  
Economic Freedom ◽  
Negative Impact ◽  
Developed Countries ◽  
Dynamic Panel ◽  
Heritage Foundation ◽  
Eu Membership ◽  
Time Period ◽  
European Economies ◽  
The Impact

This paper analyzes the impact of economic freedom along with traditional economic factors on economic growth for a panel of European countries. The growth of the gross domestic product was observed over a twenty-year time period on a sample of 43 developing and developed countries. Based on a robust dynamic panel setting, we conclude that increases in economic freedom as expressed by the Index of Economic Freedom/Heritage Foundation (but not its levels) are related to economic growth. The EU membership status either had no effect or it curbed the effect of the economic freedom on growth. We also find that the subprime economic crisis of 2008–2009 exerted a negative impact on the growth of European economies.

scholarly journals Long time frames to detect the impact of changing COVID-19 measures, Canada, March to July 2020

2021 ◽  
Vol 26 (40) ◽  
Author(s):  
Jessica E Stockdale ◽  
Renny Doig ◽  
Joosung Min ◽  
Nicola Mulberry ◽  
Liangliang Wang ◽  
...  
Keyword(s):  
Population Level ◽  
Time Frame ◽  
Control Measures ◽  
Type Model ◽  
Time Period ◽  
Long Time ◽  
The Mean ◽  
Reported Data ◽  
Time Frames ◽  
The Impact

Background Many countries have implemented population-wide interventions to control COVID-19, with varying extent and success. Many jurisdictions have moved to relax measures, while others have intensified efforts to reduce transmission. Aim We aimed to determine the time frame between a population-level change in COVID-19 measures and its impact on the number of cases. Methods We examined how long it takes for there to be a substantial difference between the number of cases that occur following a change in COVID-19 physical distancing measures and those that would have occurred at baseline. We then examined how long it takes to observe this difference, given delays and noise in reported cases. We used a susceptible-exposed-infectious-removed (SEIR)-type model and publicly available data from British Columbia, Canada, collected between March and July 2020. Results It takes 10 days or more before we expect a substantial difference in the number of cases following a change in COVID-19 control measures, but 20–26 days to detect the impact of the change in reported data. The time frames are longer for smaller changes in control measures and are impacted by testing and reporting processes, with delays reaching ≥ 30 days. Conclusion The time until a change in control measures has an observed impact is longer than the mean incubation period of COVID-19 and the commonly used 14-day time period. Policymakers and practitioners should consider this when assessing the impact of policy changes. Rapid, consistent and real-time COVID-19 surveillance is important to minimise these time frames.

scholarly journals Upravljanje globalnim brendom s osvrtom na efekt zemlje porijekla

2017 ◽  
Vol 5 (2) ◽  
Author(s):  
Aleksandra Krajnović ◽  
Ivan Jadreško ◽  
Jurica Bosna
Keyword(s):  
Developing Countries ◽  
Economies Of Scale ◽  
Brand Management ◽  
Country Of Origin ◽  
Developed Countries ◽  
International Expansion ◽  
Long Time ◽  
Geographical Expansion ◽  
The Impact ◽  
Cover Up

Geographical expansion is inevitable destiny of brands because it determines the growth of the brand and its ability to innovate and maintain competitive advantage in terms of economies of scale and productivity. Therefore, brand managers are trying to find out new ways and approaches in a manner to achive international expansion. The effect that has been studied for a long time in relation with brands is the effect of the country of origin. Purpose of this paper is to find out the impact of the country of origin on the contemporary brand management. Goal of the paper is to point out the end of country of origin trend in developed countries and development of this effect in developing countries. More and more companies are currently trying to cover up the country of origin of the product while brend with its image represents more important and familiar information. Generally, the effect of country of origin becomes less important while the country of the brand has a growing importance.

scholarly journals Spatial evaluation of volcanic ash forecasts using satellite observations

2015 ◽  
Vol 15 (17) ◽  
pp. 24727-24749 ◽  
Author(s):  
N. J. Harvey ◽  
H. F. Dacre
Keyword(s):  
Volcanic Ash ◽  
Pearson Correlation ◽  
Skill Score ◽  
Near Miss ◽  
Model Parameters ◽  
Time Period ◽  
Long Time ◽  
The Impact ◽  
Success Index ◽  
Ash Transport

Abstract. The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD) models. In this paper an objective metric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The metric is based on the fractions skill score (FSS). This measure of skill provides more information than traditional point-by-point metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale over which skill is being assessed. The FSS determines the scale over which a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700 km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

scholarly journals Winner Strategies in Crisis

2021 ◽  
Vol 92 ◽  
pp. 03015
Author(s):  
Laura Langenstein ◽  
Martin Užík ◽  
Roman Warias
Keyword(s):  
Business Model ◽  
Value Added ◽  
Investment Strategies ◽  
Performance Impact ◽  
Time Period ◽  
Markowitz Portfolio ◽  
Long Time ◽  
Investment Portfolios ◽  
Pe Ratio ◽  
Better Than

Research background: Since the publication of Markowitz’ Portfolio Selection Theory, researchers and practitioners have been searching for the optimal structure of investment portfolios. An unlimited number of portfolio-based investment strategies have been created since 1952. However, none of these strategies seem to continuously generate overperformance over a long time period. This may also be due to the strong dynamics of economic development and other external factors. Purpose of the article: The aim of this article is to analyze which strategies are successful in generating winning portfolios in times of crisis. Three types of crises are considered: first, the bursting of the dot-com bubble in 2001, second, the financial crisis of 2008, and finally, the performance impact of the corona crisis. Methods: The data of the S&P 500 and STOXX Europe 600 companies are analyzed. The first step is the statistical review of the performance of companies in different periods with the focus on the analysis of the crisis years. Subsequently, the formation of portfolios is carried out according to known key figures such as high-low PE ratio, high-low market-to-book ratio, and others. In the form of a regression analysis, selected fundamental data are used to statistically check their relevance for performance. Findings & Value added: The results shows that all crises have similarities in certain factors. However, they also show that companies with a digital business model are able to manage crises better than those without a digital business model.

scholarly journals The Impact Of Trading Volume On Portfolios Effective Time Formation/Holding Periods Based On Momentum Investment Strategies

2011 ◽  
Vol 10 (7) ◽  
pp. 1
Author(s):  
Tov Assogbavi ◽  
Martin Giguere ◽  
Komlan Sedzro
Keyword(s):  
Trading Volume ◽  
Selection Process ◽  
High Volume ◽  
Investment Strategies ◽  
Momentum Strategy ◽  
Holding Period ◽  
Effective Time ◽  
Price Momentum ◽  
Time Period ◽  
The Impact

This paper analyzes momentum investment strategies based on past market data to evaluate the impact of trading volume on price momentum for the Canadian Stock Market. Utilizing variant models of Jegadeesh and Titman (1993) and Lee and Swaminathan (2000), we evaluate the effective time formation/holding periods of portfolios using both past price and trading volume. The findings suggest that taking high trading volume into consideration in momentum investment strategies on the TSX between 1996 to 2004 generally outperformed a strictly price-based momentum strategy for both winners (t= 2.118, p< .05) and losers (t= 2.174, p< .05). The most effective time period for a winning-high-volume portfolio was nine months of formation, starting in April and a 3-month holding period. The holding period is shorter by six months compared to what is suggested by Assogbavi, et al. (2008). In addition, high-volume portfolios consistently bettered low-volume portfolios for both winners (t= 4.121, p< .001) and losers (t= 3.956, p< .001). For investors who base their portfolio construction on momentum investment strategies, these findings suggest that it would be wise to incorporate past trading volume in their selection process.

scholarly journals Long time frames to detect the impact of changing COVID-19 control measures

2020 ◽  
Author(s):  
Jessica E Stockdale ◽  
Renny Doig ◽  
Joosung Min ◽  
Nicola Mulberry ◽  
Liangliang Wang ◽  
...  
Keyword(s):  
Population Level ◽  
Time Frame ◽  
Control Measures ◽  
Policy Makers ◽  
Time Period ◽  
Reporting Process ◽  
Long Time ◽  
The Mean ◽  
Time Frames ◽  
The Impact

AbstractBackgroundMany countries have implemented population-wide interventions such as physical distancing measures, in efforts to control COVID-19. The extent and success of such measures has varied. Many jurisdictions with declines in reported COVID-19 cases are moving to relax measures, while others are continuing to intensify efforts to reduce transmission.AimWe aim to determine the time frame between a change in COVID-19 measures at the population level and the observable impact of such a change on cases.MethodsWe examine how long it takes for there to be a substantial difference between the cases that occur following a change in control measures and those that would have occurred at baseline. We then examine how long it takes to detect a difference, given delays and noise in reported cases. We use changes in population-level (e.g., distancing) control measures informed by data and estimates from British Columbia, Canada.ResultsWe find that the time frames are long: it takes three weeks or more before we might expect a substantial difference in cases given a change in population-level COVID-19 control, and it takes slightly longer to detect the impacts of the change. The time frames are shorter (11-15 days) for dramatic changes in control, and they are impacted by noise and delays in the testing and reporting process, with delays reaching up to 25-40 days.ConclusionThe time until a change in broad control measures has an observed impact is longer than is typically understood, and is longer than the mean incubation period (time between exposure than onset) and the often used 14 day time period. Policy makers and public health planners should consider this when assessing the impact of policy change, and efforts should be made to develop rapid, consistent real-time COVID-19 surveillance.

Corporate Social Responsibility Measures: A Brief Review

2021 ◽  
pp. 227853372199220
Author(s):  
Akanksha Shukla ◽  
Geetika ◽  
Nimesh Shukla
Keyword(s):  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Developed Countries ◽  
Financial Measures ◽  
Time Period ◽  
And Performance ◽  
Corporate Social ◽  
The Impact

Studies are being conducted to measure the impact of corporate social responsibility (CSR) on different dimensions of performance of the firm. Therefore, it becomes imperative to measure CSR activities undertaken by the firms. The measures used to assess CSR range from quantitative to perceptual; hence, the study proposes to present an analytical profile of various methods used to measure CSR. The article reviews studies that span over the time period from the 1980s to 2016 to determine the relationship between CSR and performance of the firm. Various measures of CSR used in studies are broadly categorized as rating-based measures, financial measures, perceptual measures, and disclosure-based measures. The study revealed that perceptual and rating-based measures are the most commonly used measures. Also, it has been found that the operationalization of CSR using these two measures has been used in the studies that are conducted mainly in developed countries. However, disclosure of CSR and expenditure made on social responsibility can be more comprehensive measures as they are more objective in nature and are not influenced by the biases. Also, expenditure on CSR can be a useful measure while conducting a cost-benefit analysis of CSR activities performed by the organizations.

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