TY - JOUR A1 - Mihoci, Andrija T1 - Varga, Matija ; Varga, Vesna: Kontroling informacijskih sustava i financija energetskih tvrtki. Čakovec : Udruga financijsko-informatičkih stručnjaka Međimurja, 2015. - ISBN 978-953-57671-1-4 N2 - Knjiga sadržava osnovne pojmove kontrolinga (govori se o potrebi za kontrolingom), poglavlje o istinitosti informacija, poglavlje o informacijskim sustavima za potporu funkcije kontrolinga i interne revizije, poglavlje o informacijskim sustavima za potporu procesnom kontrolingu, poglavlje o značenju revizije informacijskih sustava, poglavlje o financijskom kontrolingu unutar energetskih tvrtki, poglavlje o uređajima mobilne tehnologije sa softverom za potporu kontrolingu itd. Knjiga govori o zadatcima uprave i suštini kontrolinga. T2 - Controlling information systems and finance energy companies KW - Controlling KW - Information Systems KW - Finance and Auditing KW - Energy Sector Y1 - 2015 UR - http://bib.irb.hr/prikazi-rad?rad=757306 ER - TY - JOUR A1 - Mihoci, Andrija T1 - Varga, Matija; Varga, Vesna: Vrijednosne informacije za kupce prirodnog plina. Čakovec : Udruga financijsko-informatičkih stručnjaka Međimurja, 2016. - ISBN 987-953-57671-2-1 N2 - Ovaj priručnik daje vrijednosne informacije kupcima prirodnoga plina. Priručnik je rezultat višemjesečnoga rada autora. Namijenjen je prije svega svim potrošačima prirodnoga plina kao energenta. Također, priručnik može biti teorijska podloga koja se može primijeniti na uvodnim satima seminara, ali i kod prikaza područja u kojima se spominje opskrba i prodaja prirodnoga plina. Također, može poslužiti u strukovnim školama kao dopunska literatura studentima veleučilišta i visokih škola na kolegijima s područja poslovanja u unutarnjoj trgovini, poslovnog upravljanja u trgovini, usluga u trgovini, trgovina i trgovinske politike, međunarodnog i domaćeg tržišta roba i usluga, ali i nastavnicima te predavačima. Sveučilišni fakulteti mogu se također koristiti ovim priručnikom kao dopunskom literaturom iz navedenih područja. Također, njime se mogu koristiti čitatelji željni stjecanja novih znanja iz trgovine i trgovačkog poslovanja. Čitatelji mogu u njemu pronaći vrijedne informacije o tržištu plina i opskrbi potrošača. Osim toga, može poslužiti kao dodatna literatura u nastavi ekonomske skupine predmeta. Budući studenti i nastavnici ekonomije mogu je primijeniti u različitim područjima prirodnih, tehničkih i društvenih znanosti. KW - Information Science KW - Mining, Petroleum and Geological Engineering KW - Economics Y1 - 2016 UR - https://bib.irb.hr/prikazi-rad?&rad=806210 ER - TY - JOUR A1 - Mihoci, Andrija T1 - Varga, Matija: Informatičke tehnologije u primjeni: kroz različita područja. Čakovec : Udruga financijsko-informatičkih stručnjaka Međimurja, 2013. - ISBN 978-953-57672-0-6 N2 - Ova višenamjenska knjiga donosi brojne primjere primjene informatičke tehnologije. Ta je primjena u svakom poglavlju prikazana u konkretnim i zasebnim područjima. Pomoću primjenskih alata otvorenog koda prikazani su i zadaci temeljeni na primjerima iz najnovije literature. Također, u knjizi su prikazani brojni web alati i njihova primjena. T2 - Information Technology and its Applications: through the different Areas KW - Information Technology KW - Cloud Computing KW - SWOT Analysis KW - Relational Databases Y1 - 2013 UR - http://bib.irb.hr/prikazi-rad?lang=en&rad=631178 ER - TY - THES A1 - Mihoci, Andrija T1 - Structural Adaptive Models in Financial Econometrics N2 - Modern methods in statistics and econometrics successfully deal with stylized facts observed on financial markets. The presented techniques aim to understand the dynamics of financial market data more accurate than traditional approaches. Economic and financial benefits are achievable. The results are here evaluated in practical examples that mainly focus on forecasting of financial data. Our applications include: (i) modelling and forecasting of liquidity supply, (ii) localizing multiplicative error models and (iii) providing evidence for the empirical pricing kernel paradox across countries. KW - Statistics and Econometrics KW - Financial Marktes KW - Dynamics KW - Forecasting KW - Financial Data KW - Applications Y1 - 2012 UR - http://edoc.hu-berlin.de/docviews/abstract.php?lang=ger&id=39635 PB - Humboldt-Universität CY - Berlin ER - TY - GEN A1 - Härdle, Wolfgang Karl A1 - Hautsch, Nikolaus A1 - Mihoci, Andrija T1 - Local Adaptive Multiplicative Error Models for High-Frequency Forecasts T2 - Journal of Applied Econometrics N2 - We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analysing 1-minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis. KW - Multiplicative Error Model KW - Local Adaptive Modelling KW - High-Frequency Processes KW - Trading Volume KW - Forecasting Y1 - 2015 UR - http://onlinelibrary.wiley.com/doi/10.1002/jae.2376/abstract U6 - https://doi.org/10.1002/jae.2376 SN - 1099-1255 VL - 30 IS - 4 SP - 529 EP - 550 ER - TY - RPRT A1 - Zharova, Alona A1 - Mihoci, Andrija A1 - Härdle, Wolfgang Karl T1 - Academic Ranking Scales in Economics: Prediction and Imputation N2 - Publications are a vital element of any scientist’s career. It is not only the number of media outlets but aslo the quality of published research that enters decisions on jobs, salary, tenure, etc. Academic ranking scales in economics and other disciplines are, therefore, widely used in classification, judgment and scientific depth of individual research. These ranking systems are competing, allow for different disciplinary gravity and sometimes give orthogonal results. Here a statistical analysis of the interconnection between Handelsblatt (HB), Research Papers in Economics (RePEc, here RP) and Google Scholar (GS) systems is presented. Quantile regression allows us to successfully predict missing ranking data and to obtain a so-called HB Common Score and to carry out a cross-rankings analysis. Based on the merged ranking data from different data providers, we discuss the ranking systems dependence, analyze the age effect and study the relationship between the research expertise areas and the ranking performance. KW - Scientometrics KW - Ranking KW - Quantile Regression KW - Handelsblatt KW - RePEc KW - Google Scholar Y1 - 2016 UR - https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2016-021.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Xu, Xiu A1 - Mihoci, Andrija A1 - Härdle, Wolfgang Karl T1 - lCARE - localizing Conditional AutoRegressive Expectiles N2 - We account for time-varying parameters in the conditional expectile based value at risk (EVaR) model. EVaR appears more sensitive to the magnitude of portfolio losses compared to the quantile-based Value at Risk (QVaR), nevertheless, by fitting the models over relatively long ad-hoc fixed time intervals, research ignores the potential time-varying parameter properties. Our work focuses on this issue by exploiting the local parametric approach in quantifying tail risk dynamics. By achieving a balance between parameter variability and modelling bias, one can safely fit a parametric expectile model over a stable interval of homogeneity. Empirical evidence at three stock markets from 2005- 2014 shows that the parameter homogeneity interval lengths account for approximately 1-6 months of daily observations. Our method outperforms models with one-year fixed intervals, as well as quantile based candidates while employing a time invariant portfolio protection (TIPP) strategy for the DAX portfolio. The tail risk measure implied by our model finally provides valuable insights for asset allocation and portfolio insurance. KW - Expectiles KW - Tail Risk KW - Local Parametric Approach KW - Risk Management Y1 - 2015 UR - https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2015-052.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Gschöpf, Philipp A1 - Härdle, Wolfgang Karl A1 - Mihoci, Andrija T1 - TERES - Tail Event Risk Expectile based Shortfall N2 - A flexible framework for the analysis of tail events is proposed. The framework contains tail moment measures that allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture distributions. Empirical results from the US, German and UK stock markets, as well as for the selected currencies indicate that ES can be successfully estimated on a daily basis using a one-year time horizon across different risk levels. KW - Expected Shortfall KW - Expectiles KW - Tail Risk KW - Risk Management KW - Tail Events KW - Tail Moments Y1 - 2015 UR - https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2015-047.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Härdle, Wolfgang Karl A1 - Mihoci, Andrija A1 - Hian-Ann Ting, Christopher T1 - Adaptive Order Flow Forecasting with Multiplicative Error Models N2 - A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading volumes and the order flow dynamics. Analysing order flow series and its information content of mini Nikkei 225 index futures traded at the Osaka Securities Exchange in 2012 and 2013, a data-driven optimal length of local windows up to approximately 1-2 hours is reasonable to capture parameter variations and is suitable for short-term prediction. Our proposed trading strategies achieve statistical arbitrage opportunities and are therefore beneficial for quantitative finance practice. KW - Multiplicative Error Models KW - Trading Volume KW - Order Flow KW - Forecasting Y1 - 2014 UR - https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2014-035.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Härdle, Wolfgang Karl A1 - Hautsch, Nikolaus A1 - Mihoci, Andrija T1 - Local Adaptive Multiplicative Error Models for High-Frequency Forecasts N2 - We propose a local adaptive multiplicative error model (MEM) accommodating time varyingparameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time. Analyzing one-minute cumulative trading volumes of five large NASDAQ stocks in 2008, we show that local windows of approximately 3 to 4 hours are reasonable to capture parameter variations while balancing modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM where local estimation windows are fixed on an ad hoc basis. KW - Multiplicative Error Model KW - Local Adaptive Modelling KW - High-Frequency Processes KW - Trading Volume KW - Forecasting Y1 - 2012 UR - https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2012-031.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Härdle, Wolfgang Karl A1 - Hautsch, Nikolaus A1 - Mihoci, Andrija T1 - Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics N2 - We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are modelled using a vector autoregressive model. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model’s forecasting power can be used to improve optimal order execution strategies. KW - Limit Order Book KW - Liquidity Risk KW - Semiparametric Modelling KW - Factor Structure KW - Prediction Y1 - 2009 UR - http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2009-044.pdf PB - SFB 649 CY - Berlin ER - TY - RPRT A1 - Härdle, Wolfgang Karl A1 - Hautsch, Nikolaus A1 - Mihoci, Andrija T1 - Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics N2 - We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are modelled using a vector autoregressive model. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model’s forecasting power can be used to improve optimal order execution strategies. KW - Limit Order Book KW - Liquidity Risk KW - Semiparametric Model KW - Factor Structure KW - Prediction Y1 - 2009 UR - https://www.ifk-cfs.de/fileadmin/downloads/publications/wp/09_18.pdf PB - Center for Financial Studies (CFS) CY - Frankfurt ER - TY - CHAP A1 - Härdle, Wolfgang Karl A1 - Mihoci, Andrija A1 - Hian-Ann Ting, Christopher T1 - Adaptive Order Flow Forecasting with Multiplicative Error Models T2 - Book of abstracts of the ISCCRO - international statistical conference in Croatia N2 - A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading volumes and the order flow dynamics. Analysing order flow series and its information content of mini Nikkei 225 index futures traded at the Osaka Securities Exchange in 2012 and 2013, a data-driven optimal length of local windows up to approximately 1-2 hours is reasonable to capture parameter variations and is suitable for short-term prediction. Our proposed trading strategies achieve statistical arbitrage opportunities and are therefore beneficial for quantitative finance practice. KW - Forecasting KW - Multiplicative Error Models KW - Order Flow KW - Trading Volume Y1 - 2016 UR - http://www.hsd-stat.hr/en/isccro_en/publications/ N1 - ISSN 1849-9864 PB - Croatian Statistical Association CY - Zagreb ER - TY - GEN A1 - Härdle, Wolfgang Karl A1 - Hautsch, Nikolaus A1 - Mihoci, Andrija T1 - Modelling and Forecasting Liquidity Supply Using Semiparametric Factor Dynamics T2 - Journal of Empirical Finance N2 - We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are modelled jointly with best bid and best ask quotes using a vector error correction specification. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. We find spill-over effects between both sides of the market and provide evidence for short-term quote predictability. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model's forecasting power can be used to improve optimal order execution strategies. KW - Limit Order Book KW - Liquidity Risk KW - Semiparametric Modelling KW - Factor Structure KW - Prediction Y1 - 2012 U6 - https://doi.org/10.1016/j.jempfin.2012.04.002 SN - 0927-5398 VL - 19 IS - 4 SP - 610 EP - 625 ER - TY - CHAP A1 - Klinke, Sigbert A1 - Mihoci, Andrija A1 - Härdle, Wolfgang Karl T1 - Exploratory Factor Analysis in Mplus, R and SPSS T2 - 8th International Conference on Teaching Statistics, Ljubljana, 2010 N2 - In teaching, factor analysis and principal component analysis are often used together, although they are quite different methods. We first summarise the similarities and differences between both approaches. From submitted theses it appears that student have difficulties seeing the differences. Although books and online resources mention some of the differences they are incomplete. A view either oriented on the similarities or the differences is reflected in software implementations. We therefore look at the implementations of factor analysis in Mplus, R and SPSS and finish with some conclusions for the teaching of Multivariate Statistics. KW - Factor Analysis KW - Principal Components Analysis KW - Software KW - Multivariate Statistics Y1 - 2010 UR - http://icots.info/8/cd/pdfs/invited/ICOTS8_4F4_KLINKE.pdf SN - 978-90-77713-54-9 ER - TY - CHAP A1 - Mihoci, Andrija ED - Hokimoto, Tsukasa T1 - Modelling Limit Order Book Volume Covariance Structures T2 - Advances in Statistical Methodologies and Their Application to Real Problems N2 - Limit order volume data have been here analysed using key multivariate techniques: principal components, factor and discriminant analysis. The focus lies on understanding of the covariance structure of posted quantities of the asset to be potentially sold or bought at the market. Employing the methods to data of 20 blue chip companies traded at the NASDAQ stock market in June 2016, one observes that two principal components account for approximately 85–95% of order book variation. The most important factor related to order book data variation has furthermore been the demand side (variability). The order book data variation, moreover, successfully classifies stock price movements. Potential applications include improving order execution strategies, designing trading algorithms and understanding price formation. KW - Limit Order Book KW - Multivariate Techniques KW - Principal Components Analysis KW - Factor Analysis KW - Discriminant Analysis Y1 - 2017 SN - 978-953-51-3102-1 SN - 978-953-51-3101-4 SP - 187 EP - 199 PB - InTech CY - Rijeka ER - TY - GEN A1 - Xu, Xiu A1 - Mihoci, Andrija A1 - Härdle, Wolfgang Karl T1 - lCARE - localizing Conditional AutoRegressive Expectiles T2 - Journal of Empirical Finance N2 - We account for time-varying parameters in the conditional expectile-based value at risk (EVaR) model. The EVaR downside risk is more sensitive to the magnitude of portfolio losses compared to the quantile-based value at risk (QVaR). Rather than fitting the expectile models over ad-hoc fixed data windows, this study focuses on parameter instability of tail risk dynamics by utilizing a local parametric approach. Our framework yields a data-driven optimal interval length at each time point by a sequential test. Empirical evidence at three stock markets from 2005–2016 shows that the selected lengths account for approximately 4–6 months of daily observations. This method performs favourable compared to the models with one-year fixed intervals, as well as quantile based candidates while employing a time invariant portfolio protection (TIPP) strategy for the DAX, FTSE 100 and S&P 500 portfolios. The tail risk measure implied by our model finally provides valuable insights for asset allocation and portfolio insurance. KW - Expectile KW - Tail Risk KW - Local Parametric Approach KW - Risk Management Y1 - 2018 UR - https://www.sciencedirect.com/science/article/pii/S0927539818300446 U6 - https://doi.org/10.1016/j.jempfin.2018.06.006 SN - 0927-5398 VL - 48 SP - 198 EP - 220 ER - TY - GEN A1 - Khan, Naveed Ahmad A1 - Mihoci, Andrija A1 - Michalk, Silke A1 - Sarachuk, Kirill A1 - Javed, Hafiz Ali T1 - Employee Performance Measures appraised by Training and Labour Market: Evidence from the Banking Sector of Germany T2 - Administrative Science N2 - Our paper examines the impact of training outputs and employment factors on several facets of employee performance while supporting managerial decision-making in the banking sector. First, we introduce four performance measures in individual productivity assessment. Second, three identified groups of covariates are associated with these measures, namely, the training method success, delivery of knowledge, and labor market performance feedback. Based on our empirical results from Germany, we suggest that response-related decisions are accompanying bank employees’ profiles and appraisal. In particular, we form decision-making functions and finally show that the banking industry successfully balances between internal and external factors in optimizing employees’ performance. Y1 - 2022 UR - https://www.mdpi.com/2076-3387/12/4/143 U6 - https://doi.org/10.3390/admsci12040143 SN - 2076-3387 VL - 12 IS - 4 SP - 1 EP - 13 ER -