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Franziska Schulz

Personal Details

First Name:Franziska
Middle Name:
Last Name:Schulz
Suffix:
RePEc Short-ID:psc549
[This author has chosen not to make the email address public]
Terminal Degree:2017 Center for Applied Statistics and Econometrics (CASE); Humboldt-Universität Berlin (from RePEc Genealogy)

Affiliation

(33%) Institut für Statistik und Ökonometrie (ISÖ)
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://ise.wiwi.hu-berlin.de/
RePEc:edi:ishubde (more details at EDIRC)

(34%) Center for Applied Statistics and Econometrics (CASE)
Humboldt-Universität Berlin

Berlin, Germany
http://www.case.hu-berlin.de/
RePEc:edi:cahubde (more details at EDIRC)

(33%) Sonderforschungsbereich 649: Ökonomisches Risiko
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://sfb649.wiwi.hu-berlin.de/
RePEc:edi:sohubde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. López Cabrera, Brenda & Schulz, Franziska, 2016. "Time-adaptive probabilistic forecasts of electricity spot prices with application to risk management," SFB 649 Discussion Papers 2016-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  2. López Cabrera, Brenda & Schulz, Franziska, 2014. "Forecasting generalized quantiles of electricity demand: A functional data approach," SFB 649 Discussion Papers 2014-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  3. López Cabrera, Brenda & Schulz, Franziska, 2014. "Forecasting generalized quantiles of electricity demand: A functional data approach," SFB 649 Discussion Papers 2014-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  4. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  5. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    repec:hum:wpaper:sfb649dp2016-035 is not listed on IDEAS

Articles

  1. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
  2. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. López Cabrera, Brenda & Schulz, Franziska, 2014. "Forecasting generalized quantiles of electricity demand: A functional data approach," SFB 649 Discussion Papers 2014-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Burdejová, Petra & Härdle, Wolfgang Karl, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers 2017-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Luke Durell & J. Thad Scott & Douglas Nychka & Amanda S. Hering, 2023. "Functional forecasting of dissolved oxygen in high‐frequency vertical lake profiles," Environmetrics, John Wiley & Sons, Ltd., vol. 34(4), June.
    4. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," LSE Research Online Documents on Economics 120774, London School of Economics and Political Science, LSE Library.
    5. van der Meer, D.W. & Shepero, M. & Svensson, A. & Widén, J. & Munkhammar, J., 2018. "Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes," Applied Energy, Elsevier, vol. 213(C), pages 195-207.
    6. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    7. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," Applied Energy, Elsevier, vol. 301(C).
    8. Fabio Bellini & Bernhard Klar & Alfred Müller, 2018. "Expectiles, Omega Ratios and Stochastic Ordering," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 855-873, September.
    9. Qinyu Wu & Fan Yang & Ping Zhang, 2023. "Conditional generalized quantiles based on expected utility model and equivalent characterization of properties," Papers 2301.12420, arXiv.org.
    10. López Cabrera, Brenda & Schulz, Franziska, 2016. "Time-adaptive probabilistic forecasts of electricity spot prices with application to risk management," SFB 649 Discussion Papers 2016-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Chao, Shih-Kang & Härdle, Wolfgang Karl & Huang, Chen, 2016. "Multivariate factorisable sparse asymmetric least squares regression," SFB 649 Discussion Papers 2016-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
    13. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102, arXiv.org.
    14. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
    15. Tran, Ngoc Mai & Osipenko, Maria & Härdle, Wolfgang Karl, 2014. "Principal component analysis in an asymmetric norm," SFB 649 Discussion Papers 2014-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Shirun Shen & Huiya Zhou & Kejun He & Lan Zhou, 2024. "Principal Component Analysis of Two-dimensional Functional Data with Serial Correlation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(3), pages 601-620, September.
    17. Kei Hirose & Keigo Wada & Maiya Hori & Rin-ichiro Taniguchi, 2020. "Event Effects Estimation on Electricity Demand Forecasting," Energies, MDPI, vol. 13(21), pages 1-20, November.

  2. López Cabrera, Brenda & Schulz, Franziska, 2014. "Forecasting generalized quantiles of electricity demand: A functional data approach," SFB 649 Discussion Papers 2014-030, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Burdejová, Petra & Härdle, Wolfgang Karl, 2017. "Dynamic semi-parametric factor model for functional expectiles," SFB 649 Discussion Papers 2017-027, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Luke Durell & J. Thad Scott & Douglas Nychka & Amanda S. Hering, 2023. "Functional forecasting of dissolved oxygen in high‐frequency vertical lake profiles," Environmetrics, John Wiley & Sons, Ltd., vol. 34(4), June.
    4. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," LSE Research Online Documents on Economics 120774, London School of Economics and Political Science, LSE Library.
    5. van der Meer, D.W. & Shepero, M. & Svensson, A. & Widén, J. & Munkhammar, J., 2018. "Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes," Applied Energy, Elsevier, vol. 213(C), pages 195-207.
    6. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    7. Xu, Xiuqin & Chen, Ying & Goude, Yannig & Yao, Qiwei, 2021. "Day-ahead probabilistic forecasting for French half-hourly electricity loads and quantiles for curve-to-curve regression," Applied Energy, Elsevier, vol. 301(C).
    8. Fabio Bellini & Bernhard Klar & Alfred Müller, 2018. "Expectiles, Omega Ratios and Stochastic Ordering," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 855-873, September.
    9. Qinyu Wu & Fan Yang & Ping Zhang, 2023. "Conditional generalized quantiles based on expected utility model and equivalent characterization of properties," Papers 2301.12420, arXiv.org.
    10. López Cabrera, Brenda & Schulz, Franziska, 2016. "Time-adaptive probabilistic forecasts of electricity spot prices with application to risk management," SFB 649 Discussion Papers 2016-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Chao, Shih-Kang & Härdle, Wolfgang Karl & Huang, Chen, 2016. "Multivariate factorisable sparse asymmetric least squares regression," SFB 649 Discussion Papers 2016-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    12. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
    13. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102, arXiv.org.
    14. Li, Z. & Hurn, A.S. & Clements, A.E., 2017. "Forecasting quantiles of day-ahead electricity load," Energy Economics, Elsevier, vol. 67(C), pages 60-71.
    15. Tran, Ngoc Mai & Osipenko, Maria & Härdle, Wolfgang Karl, 2014. "Principal component analysis in an asymmetric norm," SFB 649 Discussion Papers 2014-001, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    16. Shirun Shen & Huiya Zhou & Kejun He & Lan Zhou, 2024. "Principal Component Analysis of Two-dimensional Functional Data with Serial Correlation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(3), pages 601-620, September.
    17. Kei Hirose & Keigo Wada & Maiya Hori & Rin-ichiro Taniguchi, 2020. "Event Effects Estimation on Electricity Demand Forecasting," Energies, MDPI, vol. 13(21), pages 1-20, November.

  3. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Capitani, Daniel Henrique Dario & Gaio, Luiz Eduardo, 2023. "Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 11(2), April.
    2. Urom, Christian & Anochiwa, Lasbrey & Yuni, Denis & Idume, Gabriel, 2019. "Asymmetric linkages among precious metals, global equity and bond yields: The role of volatility and business cycle factors," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    3. Dutta, Anupam & Bouri, Elie & Rothovius, Timo & Uddin, Gazi Salah, 2023. "Climate risk and green investments: New evidence," Energy, Elsevier, vol. 265(C).
    4. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    5. Julyerme M. Tonin & Carlos M. R. Vieira & Rui M. de Sousa Fragoso & João G. Martines Filho, 2020. "Conditional correlation and volatility between spot and futures markets for soybean and corn," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 707-724, October.
    6. Vo, Long Hai & Le, Thai-Ha, 2021. "Eatery, energy, environment and economic system, 1970–2017: Understanding volatility spillover patterns in a global sample," Energy Economics, Elsevier, vol. 100(C).
    7. Anthony N. Rezitis & Gregor Kastner, 2021. "On the joint volatility dynamics in dairy markets," Papers 2104.12707, arXiv.org.
    8. Naeem, Muhammad Abubakr & Karim, Sitara & Hasan, Mudassar & Lucey, Brian M. & Kang, Sang Hoon, 2022. "Nexus between oil shocks and agriculture commodities: Evidence from time and frequency domain," Energy Economics, Elsevier, vol. 112(C).
    9. Cruz, Jose Cesar Jr. & Silveira, Rodrigo L. F. & Capitani, Daniel H. D. & Urso, Fabiana S. P. & Martines, Joao G. Filho, 2016. "The effect of Brazilian corn and soybean crop expansion on price and volatility transmission," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236127, Agricultural and Applied Economics Association.
    10. M. Thenmozhi & Shipra Maurya, 2020. "Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(2), pages 131-164, August.
    11. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    12. Vo, D.H. & Vu, T.N. & Vo, A.T. & McAleer, M.J., 2018. "Modelling the Relationship between Crude Oil and Agricultural Commodity Prices," Econometric Institute Research Papers EI2019-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    13. Casagranda, Yasmin Gomes & Casarotto, Eduardo Luis & Pereira, Gênesis Miguel & Amorin, Anderson Luís Walker & Schollkopf, Joana Cechele & Mores, Giana de Vargas, 2023. "Agricultural commodities price dependence on Brazilian financial market," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 14(01), January.
    14. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    15. Faruk Urak & Abdulbaki Bilgic & Gürkan Bozma & Wojciech J. Florkowski & Erkan Efekan, 2022. "Volatility in Live Calf, Live Sheep, and Feed Wheat Return Markets: A Threat to Food Price Stability in Turkey," Agriculture, MDPI, vol. 12(4), pages 1-24, April.
    16. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    17. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A. & Fijorek, Kamil, 2018. "What drives food price volatility? Evidence based on a generalized VAR approach applied to the food, financial and energy markets," Economics Discussion Papers 2018-55, Kiel Institute for the World Economy (IfW Kiel).
    18. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    19. Wei Su, Chi & Wang, Xiao-Qing & Tao, Ran & Oana-Ramona, Lobonţ, 2019. "Do oil prices drive agricultural commodity prices? Further evidence in a global bio-energy context," Energy, Elsevier, vol. 172(C), pages 691-701.
    20. Xianfang Su & Huiming Zhu & Xinxia Yang, 2019. "Heterogeneous Causal Relationships between Spot and Futures Oil Prices: Evidence from Quantile Causality Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    21. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    22. Rangga Handika & Rangga Handika & Sigit Triandaru, 2016. "Is the Best Generalized Autoregressive Conditional Heteroskedasticity(p,q) Value-at-risk Estimate also the Best in Reality? An Evidence from Australian Interconnected Power Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 6(4), pages 814-821.
    23. Guo, Jin & Tanaka, Tetsuji, 2022. "Energy security versus food security: An analysis of fuel ethanol- related markets using the spillover index and partial wavelet coherence approaches," Energy Economics, Elsevier, vol. 112(C).
    24. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed & Tayachi, Tahar, 2021. "Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 71-85.
    25. Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    26. Chishti, Muhammad Zubair & Khalid, Ali Awais & Sana, Moniba, 2023. "Conflict vs sustainability of global energy, agricultural and metal markets: A lesson from Ukraine-Russia war," Resources Policy, Elsevier, vol. 84(C).
    27. Xian, Hui & Gregory, Colson & Michael, Wetzstein, 2015. "Impact of nonrenewable on renewable energy: The case of wood pellets," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196833, Southern Agricultural Economics Association.
    28. Zhengyi Dong, 2019. "Does the Development of Bioenergy Exacerbate the Price Increase of Maize?," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    29. Sima Siami-Namini, 2019. "Volatility Transmission Among Oil Price, Exchange Rate and Agricultural Commodities Prices," Applied Economics and Finance, Redfame publishing, vol. 6(4), pages 41-61, July.
    30. Chang, C-L. & McAleer, M.J. & Wang, Y-A., 2016. "Modelling Volatility Spillovers for Bio-ethanol, Sugarcane and Corn Spot and Futures Prices," Econometric Institute Research Papers EI2016-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    31. Chia-Lin Chang & Michael McAleer & Yu-Ann Wang, 2016. "Modelling volatility spillovers for bio-ethanol, sugarcane and corn," Documentos de Trabajo del ICAE 2016-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    32. Boroumand, Raphaël Homayoun & Porcher, Thomas, 2023. "Volatility contagion and connectedness between WTI and commodity markets," Finance Research Letters, Elsevier, vol. 58(PA).
    33. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    34. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    35. Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Uddin, Gazi Salah & Kang, Sang Hoon, 2019. "Can agricultural and precious metal commodities diversify and hedge extreme downside and upside oil market risk? An extreme quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 588-601.
    36. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    37. Hokey Min, 2022. "Examining the Impact of Energy Price Volatility on Commodity Prices from Energy Supply Chain Perspectives," Energies, MDPI, vol. 15(21), pages 1-16, October.
    38. Han, Liyan & Jin, Jiayu & Wu, Lei & Zeng, Hongchao, 2020. "The volatility linkage between energy and agricultural futures markets with external shocks," International Review of Financial Analysis, Elsevier, vol. 68(C).
    39. Ben Amar, Amine & Goutte, Stéphane & Isleimeyyeh, Mohammad, 2022. "Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 386-400.
    40. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    41. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    42. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    43. Athanasios Tsagkanos & Aarzoo Sharma & Bikramaditya Ghosh, 2022. "Green Bonds and Commodities: A New Asymmetric Sustainable Relationship," Sustainability, MDPI, vol. 14(11), pages 1-16, June.
    44. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2017. "Food versus Fuel: An Updated and Expanded Evidence," Working Papers IES 2017/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    45. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    46. Rehman, Mobeen Ur & Bouri, Elie & Eraslan, Veysel & Kumar, Satish, 2019. "Energy and non-energy commodities: An asymmetric approach towards portfolio diversification in the commodity market," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    47. Jihed Majdoub & Salim Ben Sassi & Azza Bejaoui, 2021. "Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 789-816, December.
    48. Mitra, Subrata Kumar & Bhatia, Vaneet & Jana, R.K. & Charan, Parikshit & Chattopadhyay, Manojit, 2018. "Changing value detrended cross correlation coefficient over time: Between crude oil and crop prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 671-678.
    49. Tule, Moses K. & Salisu, Afees A. & Chiemeke, Charles C., 2019. "Can agricultural commodity prices predict Nigeria's inflation?," Journal of Commodity Markets, Elsevier, vol. 16(C).
    50. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2022. "Oil and gold as a hedge and safe-haven for metals and agricultural commodities with portfolio implications," Energy Economics, Elsevier, vol. 105(C).
    51. Stewart, Shamar L. & Isengildina Massa, Olga, 2024. "Food & Oil Price Volatility Dynamics: Insights from a TVP-SVAR-DCC-MIDAS Model," 2024 Annual Meeting, July 28-30, New Orleans, LA 343936, Agricultural and Applied Economics Association.
    52. Gustafsson, Robert & Dutta, Anupam & Bouri, Elie, 2022. "Are energy metals hedges or safe havens for clean energy stock returns?," Energy, Elsevier, vol. 244(PA).
    53. Ting-Ting Sun & Chi-Wei Su & Ran Tao & Meng Qin, 2021. "Are Agricultural Commodity Prices on a Conventional Wisdom with Inflation?," SAGE Open, , vol. 11(3), pages 21582440211, August.
    54. Miroslava Ivanova & Lilko Dospatliev, 2023. "Effects of Diesel Price on Changes in Agricultural Commodity Prices in Bulgaria," Mathematics, MDPI, vol. 11(3), pages 1-22, January.
    55. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    56. Ding, Shusheng & Cui, Tianxiang & Zheng, Dandan & Du, Min, 2021. "The effects of commodity financialization on commodity market volatility," Resources Policy, Elsevier, vol. 73(C).
    57. Monika Roman & Aleksandra Górecka & Joanna Domagała, 2020. "The Linkages between Crude Oil and Food Prices," Energies, MDPI, vol. 13(24), pages 1-18, December.
    58. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    59. Cheng, Natalie Fang Ling & Hasanov, Akram Shavkatovich & Poon, Wai Ching & Bouri, Elie, 2023. "The US-China trade war and the volatility linkages between energy and agricultural commodities," Energy Economics, Elsevier, vol. 120(C).
    60. Taghizadeh-Hesary, Farhad & Rasoulinezhad, Ehsan & Yoshino, Naoyuki, 2019. "Energy and Food Security: Linkages through Price Volatility," Energy Policy, Elsevier, vol. 128(C), pages 796-806.
    61. Yousaf, Imran & Jareño, Francisco & Tolentino, Marta, 2023. "Connectedness between Defi assets and equity markets during COVID-19: A sector analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    62. Christina Anderl & Guglielmo Maria Caporale, 2024. "Global Food Prices and Inflation," CESifo Working Paper Series 10992, CESifo.
    63. Uçak, Harun & Yelgen, Esin & Arı, Yakup, 2022. "The Role of Energy on the Price Volatility of Fruits and Vegetables: Evidence from Turkey," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 11(1), April.
    64. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Adewuyi, Adeolu O. & Lee, Chien-Chiang, 2022. "Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Energy Economics, Elsevier, vol. 113(C).
    65. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    66. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    67. Siami-Namini, Sima & Hudson, Darren, 2017. "Volatility Spillover Between Oil Prices, Us Dollar Exchange Rates And International Agricultural Commodities Prices," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252845, Southern Agricultural Economics Association.
    68. Declerck, Francis & Hikouatcha, Prince & Tchoffo, Guillaume & Tédongap, Roméo, 2023. "Biofuel policies and their ripple effects: An analysis of vegetable oil price dynamics and global consumer responses," Energy Economics, Elsevier, vol. 128(C).
    69. Shokoohi, Zeinab & Saghaian, Sayed, 2022. "Nexus of energy and food nutrition prices in oil importing and exporting countries: A panel VAR model," Energy, Elsevier, vol. 255(C).
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    72. Menéndez-García, Luis Alfonso & García-Nieto, Paulino José & García-Gonzalo, Esperanza & Sánchez Lasheras, Fernando, 2024. "Time series analysis for COMEX platinum spot price forecasting using SVM, MARS, MLP, VARMA and ARIMA models: A case study," Resources Policy, Elsevier, vol. 95(C).
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    78. Wei, Yanfeng & Qiu, Feng & An, Henry & Zhang, Xindon & Li, Changhong & Guo, Xiaoying, 2024. "Exogenous oil supply shocks and global agricultural commodity prices: The role of biofuels," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 394-414.
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    81. Makkonen, Adam & Vallström, Daniel & Uddin, Gazi Salah & Rahman, Md Lutfur & Haddad, Michel Ferreira Cardia, 2021. "The effect of temperature anomaly and macroeconomic fundamentals on agricultural commodity futures returns," Energy Economics, Elsevier, vol. 100(C).
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    1. Capitani, Daniel Henrique Dario & Gaio, Luiz Eduardo, 2023. "Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 11(2), April.
    2. Urom, Christian & Anochiwa, Lasbrey & Yuni, Denis & Idume, Gabriel, 2019. "Asymmetric linkages among precious metals, global equity and bond yields: The role of volatility and business cycle factors," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    3. Dutta, Anupam & Bouri, Elie & Rothovius, Timo & Uddin, Gazi Salah, 2023. "Climate risk and green investments: New evidence," Energy, Elsevier, vol. 265(C).
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    88. Anthony N. Rezitis & Panagiotis Andrikopoulos & Theodoros Daglis, 2024. "Assessing the asymmetric volatility linkages of energy and agricultural commodity futures during low and high volatility regimes," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 451-483, March.
    89. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
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Articles

  1. Brenda López Cabrera & Franziska Schulz, 2017. "Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 127-136, January.
    See citations under working paper version above.
  2. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    See citations under working paper version above.Sorry, no citations of articles recorded.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (2) 2015-02-28 2016-10-02
  2. NEP-AGR: Agricultural Economics (1) 2013-09-24
  3. NEP-FOR: Forecasting (1) 2016-10-02
  4. NEP-RMG: Risk Management (1) 2016-10-02

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