Andrija Mihoci

Personal Details

First Name:	Andrija
Middle Name:
Last Name:	Mihoci
Suffix:
RePEc Short-ID:	pmi550
	[This author has chosen not to make the email address public]
	http://www.b-tu.de/fg-oekonometrie/
	Brandenburg University of Technology Chair of Economic Statistics and Econometrics Erich-Weinert-Str. 1 03046 Cottbus
	+49 (0) 355 69 38 20
Terminal Degree:	2012 Institut für Statistik und Ökonometrie (ISÖ); Wirtschaftswissenschaftliche Fakultät; Humboldt-Universität Berlin (from RePEc Genealogy)

Affiliation

(80%) Institut Wirtschaftswissenschaften
Brandenburgische Technische Universität Cottbus

Cottbus, Germany
http://www.tu-cottbus.de/fakultaet3/de/fakultaet/institute/wirtschaftswissen-schaften.html
RePEc:edi:iwcotde (more details at EDIRC)

(10%) 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)

(10%) Sonderforschungsbereich 649: Ökonomisches Risiko
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

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

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. Gschöpf, Philipp & Härdle, Wolfgang Karl & Mihoci, Andrija, 2015. "TERES: Tail event risk expectile based shortfall," SFB 649 Discussion Papers 2015-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

   Cited by:

   1. Andrew J. Patton & Johanna F. Ziegel & Rui Chen, 2017. "Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk)," Papers 1707.05108, arXiv.org.
      • Patton, Andrew J. & Ziegel, Johanna F. & Chen, Rui, 2019. "Dynamic semiparametric models for expected shortfall (and Value-at-Risk)," Journal of Econometrics, Elsevier, vol. 211(2), pages 388-413.
   2. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.

2. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2015. "lCARE: Localizing conditional autoregressive expectiles," SFB 649 Discussion Papers 2015-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
   4. 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.
   5. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

3. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2015. "lCARE: Localizing conditional autoregressive expectiles," SFB 649 Discussion Papers 2015-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Zhang, Yue-Jun & Ma, Shu-Jiao, 2019. "How to effectively estimate the time-varying risk spillover between crude oil and stock markets? Evidence from the expectile perspective," Energy Economics, Elsevier, vol. 84(C).
   4. 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.
   5. Härdle, Wolfgang Karl & Ling, Chengxiu, 2018. "How Sensitive are Tail-related Risk Measures in a Contamination Neighbourhood?," IRTG 1792 Discussion Papers 2018-010, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

4. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.

5. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.

6. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Local adaptive multiplicative error models for high-frequency forecasts," SFB 649 Discussion Papers 2012-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
      • Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 157-177.
   4. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
   5. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   6. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
   7. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
   8. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
   9. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
   10. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
   11. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
   12. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
   13. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
   14. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
   15. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
       • Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2015. "lCARE: Localizing conditional autoregressive expectiles," SFB 649 Discussion Papers 2015-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   16. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
       • Chen, Ying & Chua, Wee Song & Härdle, Wolfgang Karl, 2016. "Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics," SFB 649 Discussion Papers 2016-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   17. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   18. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
       • Massimiliano Caporin & Eduardo Rossi & Paolo Santucci De Magistris, 2014. "Chasing Volatility. A Persistent Multiplicative Error Model With Jumps," "Marco Fanno" Working Papers 0186, Dipartimento di Scienze Economiche "Marco Fanno".

7. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Local adaptive multiplicative error models for high-frequency forecasts," SFB 649 Discussion Papers 2012-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.

   Cited by:

   1. Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," BOFIT Discussion Papers 12/2015, Bank of Finland Institute for Emerging Economies (BOFIT).
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2015. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," SFB 649 Discussion Papers 2015-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
   2. Klochkov, Yegor & Härdle, Wolfgang Karl & Xu, Xiu, 2019. "Localizing Multivariate CAViaR," IRTG 1792 Discussion Papers 2019-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   3. Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the Term Structure of Option Implied Volatility: The Power of an Adaptive Method," IRTG 1792 Discussion Papers 2018-046, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
      • Chen, Ying & Han, Qian & Niu, Linlin, 2018. "Forecasting the term structure of option implied volatility: The power of an adaptive method," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 157-177.
   4. Caporin, Massimiliano & Rossi, Eduardo & Santucci de Magistris, Paolo, 2017. "Chasing volatility," Journal of Econometrics, Elsevier, vol. 198(1), pages 122-145.
   5. Khowaja, Kainat & Saef, Danial & Sizov, Sergej & Härdle, Wolfgang Karl, 2020. "Data Analytics Driven Controlling: bridging statistical modeling and managerial intuition," IRTG 1792 Discussion Papers 2020-026, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
   6. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
   7. Shen, Zhiwei, 2016. "Adaptive local parametric estimation of crop yields: implication for crop insurance ratemaking," 156th Seminar, October 4, 2016, Wageningen, The Netherlands 249984, European Association of Agricultural Economists.
   8. Tapia, Sebastian & Kristjanpoller, Werner, 2022. "Framework based on multiplicative error and residual analysis to forecast bitcoin intraday-volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
   9. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
   10. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
   11. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
   12. Niels Gillmann & Ostap Okhrin, 2023. "Adaptive local VAR for dynamic economic policy uncertainty spillover," Papers 2302.02808, arXiv.org.
   13. Yoontae Jeon & Thomas H. McCurdy, 2017. "Time-Varying Window Length for Correlation Forecasts," Econometrics, MDPI, vol. 5(4), pages 1-29, December.
   14. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
   15. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
       • Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2015. "lCARE: Localizing conditional autoregressive expectiles," SFB 649 Discussion Papers 2015-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   16. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
       • Chen, Ying & Chua, Wee Song & Härdle, Wolfgang Karl, 2016. "Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics," SFB 649 Discussion Papers 2016-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   17. Härdle, Wolfgang Karl & Mihoci, Andrija & Ting, Christopher Hian-Ann, 2014. "Adaptive order flow forecasting with multiplicative error models," SFB 649 Discussion Papers 2014-035, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   18. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Chasing volatility - A persistent multiplicative error model with jumps," CREATES Research Papers 2014-29, Department of Economics and Business Economics, Aarhus University.
       • Massimiliano Caporin & Eduardo Rossi & Paolo Santucci De Magistris, 2014. "Chasing Volatility. A Persistent Multiplicative Error Model With Jumps," "Marco Fanno" Working Papers 0186, Dipartimento di Scienze Economiche "Marco Fanno".

8. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," SFB 649 Discussion Papers 2009-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).

   Cited by:

   1. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
   2. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
      • Hautsch, Nikolaus & Huang, Ruihong, 2012. "The market impact of a limit order," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 501-522.
      • Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," SFB 649 Discussion Papers 2009-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   3. Härdle, Wolfgang Karl & Majer, Piotr, 2012. "Yield curve modeling and forecasting using semiparametric factor dynamics," SFB 649 Discussion Papers 2012-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   4. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
   5. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
      • Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity and volatility in the U.S. treasury market," Staff Reports 590, Federal Reserve Bank of New York.
   6. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
   7. Geir H. Bjønnes & Carol L. Osler & Dagfinn Rime, 2021. "Price discovery in two‐tier markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3109-3133, April.
   8. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   9. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.
   10. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
   11. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
       • Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378, April.
   12. Siikanen, Milla & Kanniainen, Juho & Luoma, Arto, 2017. "What drives the sensitivity of limit order books to company announcement arrivals?," Economics Letters, Elsevier, vol. 159(C), pages 65-68.
   13. Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
   14. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
   15. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
   16. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
       • Chen, Ying & Chua, Wee Song & Härdle, Wolfgang Karl, 2016. "Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics," SFB 649 Discussion Papers 2016-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   17. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   18. Choros-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "CDO surfaces dynamics," SFB 649 Discussion Papers 2013-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   19. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.

9. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," SFB 649 Discussion Papers 2009-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).

   Cited by:

   1. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
      • Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
   2. Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," CFS Working Paper Series 2009/23, Center for Financial Studies (CFS).
      • Hautsch, Nikolaus & Huang, Ruihong, 2012. "The market impact of a limit order," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 501-522.
      • Hautsch, Nikolaus & Huang, Ruihong, 2009. "The market impact of a limit order," SFB 649 Discussion Papers 2009-051, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   3. Härdle, Wolfgang Karl & Majer, Piotr, 2012. "Yield curve modeling and forecasting using semiparametric factor dynamics," SFB 649 Discussion Papers 2012-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   4. Andrija Mihoci & Christopher Hian-Ann Ting & Meng-Jou Lu & Kainat Khowaja, 2022. "Adaptive order flow forecasting with multiplicative error models," Digital Finance, Springer, vol. 4(1), pages 89-108, March.
   5. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
      • Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity and volatility in the U.S. treasury market," Staff Reports 590, Federal Reserve Bank of New York.
   6. Meihui Guo & Yi-Ting Guo & Chi-Jeng Wang & Liang-Ching Lin, 2015. "Assessing influential trade effects via high-frequency market reactions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(7), pages 1458-1471, July.
   7. Geir H. Bjønnes & Carol L. Osler & Dagfinn Rime, 2021. "Price discovery in two‐tier markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3109-3133, April.
   8. Hautsch, Nikolaus & Huang, Ruihong, 2011. "Limit order flow, market impact and optimal order sizes: Evidence from NASDAQ TotalView-ITCH data," SFB 649 Discussion Papers 2011-056, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   9. Hai-Chuan Xu & Wei Chen & Xiong Xiong & Wei Zhang & Wei-Xing Zhou & H Eugene Stanley, 2016. "Limit-order book resiliency after effective market orders: Spread, depth and intensity," Papers 1602.00731, arXiv.org, revised Feb 2017.
   10. Christos Kollias & Stephanos Papadamou & Costas Siriopoulos, 2013. "European Markets’ Reactions to Exogenous Shocks: A High Frequency Data Analysis of the 2005 London Bombings," IJFS, MDPI, vol. 1(4), pages 1-14, November.
   11. Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378.
       • Brownlees, Christian T. & Gallo, Giampiero M., 2011. "Shrinkage estimation of semiparametric multiplicative error models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 365-378, April.
   12. Siikanen, Milla & Kanniainen, Juho & Luoma, Arto, 2017. "What drives the sensitivity of limit order books to company announcement arrivals?," Economics Letters, Elsevier, vol. 159(C), pages 65-68.
   13. Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
   14. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
   15. Kyle Bechler & Michael Ludkovski, 2017. "Order Flows and Limit Order Book Resiliency on the Meso-Scale," Papers 1708.02715, arXiv.org.
   16. Ying Chen & Wee Song Chua & Wolfgang Karl Härdle, 2019. "Forecasting limit order book liquidity supply–demand curves with functional autoregressive dynamics," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1473-1489, September.
       • Chen, Ying & Chua, Wee Song & Härdle, Wolfgang Karl, 2016. "Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics," SFB 649 Discussion Papers 2016-025, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   17. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   18. Choros-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2013. "CDO surfaces dynamics," SFB 649 Discussion Papers 2013-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   19. Choroś-Tomczyk, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2016. "A semiparametric factor model for CDO surfaces dynamics," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 151-163.

Articles

1. Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2018. "lCARE - localizing conditional autoregressive expectiles," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 198-220.
   • Xu, Xiu & Mihoci, Andrija & Härdle, Wolfgang Karl, 2015. "lCARE: Localizing conditional autoregressive expectiles," SFB 649 Discussion Papers 2015-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   See citations under working paper version above.
2. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Local adaptive multiplicative error models for high-frequency forecasts," SFB 649 Discussion Papers 2012-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   See citations under working paper version above.
3. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," CFS Working Paper Series 2009/18, Center for Financial Studies (CFS).
   • Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2009. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," SFB 649 Discussion Papers 2009-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
   See citations under working paper version above.Sorry, no citations of articles recorded.

Chapters

1. Andrija Mihoci, 2017. "Modelling Limit Order Book Volume Covariance Structures," Chapters, in: Tsukasa Hokimoto (ed.), Advances in Statistical Methodologies and Their Application to Real Problems, IntechOpen.

   Cited by:

   1. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

More information

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Statistics

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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 6 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-FOR: Forecasting (3) 2009-09-26 2012-05-08 2014-09-25
2. NEP-MST: Market Microstructure (3) 2009-09-26 2012-05-08 2014-09-25
3. NEP-ECM: Econometrics (2) 2012-05-08 2015-12-08
4. NEP-ETS: Econometric Time Series (2) 2012-05-08 2015-12-08
5. NEP-RMG: Risk Management (2) 2015-09-26 2015-12-08
6. NEP-EDU: Education (1) 2016-06-04
7. NEP-ORE: Operations Research (1) 2014-09-25
8. NEP-SOG: Sociology of Economics (1) 2016-06-04

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