Jeff Gruenewald, Brent R. Klein, Grant Drawve, Brent L. Smith and Katie Ratcliff
The purpose of this paper is to provide a metric for validating the Nationwide Suspicious Activity Reporting (SAR) Initiative’s (NSI) sixteen-category instrument, which is…
Abstract
Purpose
The purpose of this paper is to provide a metric for validating the Nationwide Suspicious Activity Reporting (SAR) Initiative’s (NSI) sixteen-category instrument, which is designed to guide law enforcement in the collection and analysis of suspicious behaviors preceding serious crimes, including terrorist attacks.
Design/methodology/approach
Data on suspicious preoperational activities and terrorism incident outcomes in the USA between 1972 and 2013 come from the American Terrorism Study (ATS). Using a mixed-method approach, the authors conduct descriptive and multivariate analyses to examine the frequencies of the least and most prevalent suspicious activities (or SAR indicators) and how they predict the likelihood of terrorism prevention. In addition, the authors contextualize how configurations of SAR indicators are associated with the successful thwarting of terrorism incidents by law enforcement using an analytical method known as conjunctive analysis of case configurations (CACC).
Findings
The study reveals several key findings. First, certain behaviors categorized as suspicious, such as making threats, occur more frequently than others. Second, making threats, conducting surveillance and terrorist recruitment/financing predict law enforcement interdiction in terrorism plots, while misrepresentation (or the manufacturing and use of false documents) is more associated with terrorist success. Third, prevalent SAR indicators operate differently in the context of various combinations of suspicious activities to shape the likelihood for law enforcement interdiction.
Research limitations/implications
The current study’s findings may not be generalizable to other forms of violent extremism and terrorism outside of the USA.
Practical implications
This study illuminates opportunities for the NSI to provide law enforcement with the necessary tools to reduce terrorism risk and prevent future attacks.
Originality/value
To our knowledge, no scholarly work to date has assessed how observable behavioral indicators of suspicious preoperational activities affect the outcomes of terrorist plots.
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Noel Scott, Brent Moyle, Ana Cláudia Campos, Liubov Skavronskaya and Biqiang Liu
Shuifeng Hong, Yimin Luo, Mengya Li and Duoping Yang
This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk…
Abstract
Purpose
This paper aims to empirically investigate time–frequency linkages between Euramerican mature and Asian emerging crude oil futures markets in terms of correlation and risk spillovers.
Design/methodology/approach
With daily data, the authors first undertake the MODWT method to decompose yield series into four different timescales, and then use the R-Vine Copula-CoVaR to analyze correlation and risk spillovers between Euramerican mature and Asian emerging crude oil futures markets.
Findings
The empirical results are as follows: (a) short-term trading is the primary driver of price volatility in crude oil futures markets. (b) The crude oil futures markets exhibit certain regional aggregation characteristics, with the Indian crude oil futures market playing an important role in connecting Euramerican mature and Asian emerging crude oil futures markets. What’s more, Oman crude oil serves as a bridge to link Asian emerging crude oil futures markets. (c) There are significant tail correlations among different futures markets, making them susceptible to “same fall but different rise” scenarios. The volatility behavior of the Indian and Euramerican markets is highly correlated in extreme incidents. (d) Those markets exhibit asymmetric bidirectional risk spillovers. Specifically, the Euramerican mature crude oil futures markets demonstrate significant risk spillovers in the extreme short term, with a relatively larger spillover effect observed on the Indian crude oil futures market. Compared with India and Japan in Asian emerging crude oil futures markets, China's crude oil futures market places more emphasis on changes in market fundamentals and prefers to hold long-term positions rather than short-term technical factors.
Originality/value
The MODWT model is utilized to capture the multiscale coordinated motion characteristics of the data in the time–frequency perspective. What’s more, compared to traditional methods, the R-Vine Copula model exhibits greater flexibility and higher measurement accuracy, enabling it to more accurately capture correlation structures among multiple markets. The proposed methodology can provide evidence for whether crude oil futures markets exhibit integration characteristics and can deepen our understanding of connections among crude oil futures prices.
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Idris A. Adediran, Raymond Swaray, Aminat O. Orekoya and Balikis A. Kabir
This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.
Abstract
Purpose
This study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.
Design/methodology/approach
The study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.
Findings
The study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.
Originality/value
The study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.
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This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes.
Abstract
Purpose
This study aims to uncover the main predictors of financial distress in the Gulf Cooperation Council (GCC) countries using a wide range of global factors and asset classes.
Design/methodology/approach
This study uses novel approaches that take into account extreme events as well as the nonlinear behavior of time series over various time intervals (i.e. short, medium and long term) and during boom and bust episodes. This study primarily uses the conditional value at risk (CoVaR), the quantile multivariate causality test and the partial wavelet coherence method. The data collection period ranges from March 2014 to September 2022.
Findings
US T-bills and gold are the primary factors that can increase financial stability in the GCC region, according to VaRs and CoVaRs. More proof of the predictive value of the oil, gold and wheat markets, as well as geopolitical tensions, uncertainty over US policy and volatility in the oil and US equities markets, is provided by the multivariate causality test. When low extreme quantiles or cross extreme quantiles are taken into account, these results are substantial and sturdy. Lastly, after adjusting for the effect of crude oil prices, this study’s wavelet coherence results indicate diminished long-run connections between the GCC stock market and the chosen global determinants.
Research limitations/implications
Despite the implications of the author’s research for decision makers, there are some limitations mainly related to the selection of Morgan Stanley Capital International (MSCI) GCC ex-Saudi Arabia. Considering the economic importance of the Kingdom of Saudi Arabia (KSA) in the region, the author believes that it would be better to include this country in the data to obtain more robust results. In addition, there is evidence in the literature of the existence of heterogeneous responses to global shocks; some markets are more vulnerable than others. This is another limitation of this study, as this study considers the GCC as a bloc rather than each country individually. These limitations could open up further research opportunities.
Originality/value
These findings are important for investors seeking to manage their portfolios under extreme market conditions. They are also important for government policies aimed at mitigating the impact of external shocks.
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Aleksan Shanoyan, R. Brent Ross, Hamish R. Gow and H. Christopher Peterson
The purpose of this paper is to assess the role of a third-party market facilitation strategy in creating sustainable market linkages and revitalizing an important agri-food…
Abstract
Purpose
The purpose of this paper is to assess the role of a third-party market facilitation strategy in creating sustainable market linkages and revitalizing an important agri-food sector in a developing country setting. More specifically, this study evaluates a third-party facilitator’s ability to assist producers and processors in developing internal private enforcement mechanisms through stimulating investments in relationship-specific assets.
Design/methodology/approach
This paper uses mixed methods approach. The research is grounded by a case study of the USDA Marketing Assistance Program (MAP) in the Armenian dairy industry. Qualitative evidence from the case study is combined with data from a survey of 745 Armenian dairy farmers to examine the impact of participation in the USDA MAP-facilitated marketing channel on farm-level investments.
Findings
The main results indicate that over the four-year period of the USDA MAP facilitation of dairy supply chain, farms linked to the formal milk marketing channel have invested in approximately twice as many assets specific to milk production compared to farms in the informal channel. This finding supports the hypothesis that third-party market facilitation strategy pursued by the USDA MAP has stimulated investments in private enforcement capital between dairy producers and processors and implies that an external third-party market facilitator can play an important role in enhancing performance of supply chain linkages.
Originality/value
These findings and the lessons from the case of USDA MAP contribute to better understanding of third-party market linkage facilitation strategies and will be useful for the development community and agribusiness decision makers.
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Taicir Mezghani and Mouna Boujelbène
This study aims to investigate the transmission of shock between the oil market and the Islamic and conventional stock markets of the Gulf Cooperation Council (GCC) countries…
Abstract
Purpose
This study aims to investigate the transmission of shock between the oil market and the Islamic and conventional stock markets of the Gulf Cooperation Council (GCC) countries during the oil shocks of 2008 and 2014.
Design/methodology/approach
This study uses two models. First, the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic model has been used to capture the fundamental contagion effects between the oil market and the Islamic and conventional stock markets during the tranquil and turmoil-crisis periods of 2008-2014. Second, the filter of Kalman has been used to capture the effects of pure contagion between the oil market and the GCC Islamic and conventional stock markets. The authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices.
Findings
The main findings of this investigation are: first, the estimation of the dynamic conditional correlation– generalized autoregressive conditionally heteroskedastic model for oil market and the Islamic and conventional stock markets proves that the Islamic and conventional stock markets and oil market displayed a significant increase in the dynamic correlation during the turmoil period, from mid-2008 and mid-2014. This proves the existence of contagion between the markets studied. Second, the authors analyze the dynamic correlation between forecasting errors of oil returns and stock returns of GCC Islamic and GCC conventional indices. They show a strong increase in the correlation coefficients between the oil market and the conventional GCC stock markets, and between the conventional and Islamic GCC stock markets during the oil crisis of 2014. However, there is no change in regime in the figure of the correlation coefficient between the oil market and the GCC Islamic stock markets during the 2008 financial crisis. This pure contagion is mainly attributed to the herding bias in 2014 oil crisis.
Originality/value
This study contributes to identifying the contribution of herding bias on the volatility transmission between the oil markets, and the GCC Islamic and conventional stock market, especially during two controversial shocks: the 2008 oil-price increase and the 2014 oil drop.
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Samah Hazgui, Saber Sebai and Walid Mensi
This paper aims to examine the frequency of co-movements and asymmetric dependencies between bitcoin (BTC), gold, Brent crude oil and the US economic policy uncertainty (EPU…
Abstract
Purpose
This paper aims to examine the frequency of co-movements and asymmetric dependencies between bitcoin (BTC), gold, Brent crude oil and the US economic policy uncertainty (EPU) index.
Design/methodology/approach
The authors use a wavelet approach and a quantile-on-quantile regression (QQR) method.
Findings
The results show a positive interdependence between BTC and commodity price returns at both medium and low frequencies over the sample period. In contrast, the dependence is negative between BTC and EPU index at both medium and low frequencies. Furthermore, the co-movements between markets are more pronounced during crises. The results show that strategic commodities and EPU index have the ability to predict BTC price returns at both medium- and long-terms. The QQR method reveals that higher gold returns tend to predict higher/lower BTC returns when the market is in a bullish/bearish state. Moreover, lower gold returns tend to predict lower (higher) BTC returns when the market is in a bearish (bullish) state (positive (negative) relationship). The lower Brent returns tend to predict higher/lower BTC returns when the market is in a bullish/bearish state. High Brent quantiles tend to predict the lower BTC returns in its extremely bearish states. Finally, higher and lower EPU changes tend to predict lower and higher BTC returns when the market is in a bearish/bullish state (negative relationship).
Originality/value
There is generally a lack of understanding of the linkages between BTC, gold, oil and uncertainty index across multiple frequencies. This is, as far as the authors know, the first attempt to apply both the wavelet approach and a QQR method to examine the multiscale linkages among markets under study. The findings should encourage the relevant policymakers to consider these co-movements which vary over time and in duration when setting up regulations that deem to enhance the market efficiency.
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Bruno Varella Miranda, Brent Ross, Jason Franken and Miguel Gómez
The purpose of this study is to disentangle the drivers of adoption of procurement strategies in situations where small agri-food firms deal with constrained organizational…
Abstract
Purpose
The purpose of this study is to disentangle the drivers of adoption of procurement strategies in situations where small agri-food firms deal with constrained organizational choices. More specifically, the authors investigate the role of transaction costs, capabilities and networks in the definition of feasible “make-or-buy” choices in emerging wine regions.
Design/methodology/approach
This article analyzes a unique dataset of small wineries from five US states: Illinois, Michigan, Missouri, New York and Vermont. The reported results derive from both a hurdle model (i.e. a probit model and a truncated regression model) and a tobit model.
Findings
The results suggest the importance of trust as a replacement for formal governance structures whenever small firms deal with highly constrained sets of organizational choices. On the other hand, the level of dependence on a limited mix of winegrape varieties and the perception that these varieties are fundamental in building legitimacy help to explain higher rates of vertical integration.
Originality/value
This study is important because it sheds light on organizational constraints that affect millions of farmers across the globe. The study of “make-or-buy” decisions in agri-food supply chains has mostly relied on the implicit assumption that all organizational choices are available to every firm. Nevertheless, limited capabilities and the participation in low-density networks may constrain the ability of a firm to adopt a governance mechanism. Stated organizational preferences and actual organizational choices may thus differ.