Research Report Influence of Vehicle Assistant System on Track keeping
Nedoma, P.; Herda, Z.; Plíhal, Jiří
2021 - English
Presented results describe different methods for the evaluation of car stability in lateral direction. Due to the significant differences between the tests, uniform methodology for recognizing the drives with ESC and without it was not determined. Two different methods for the drive on the circle and VDA were proposed instead. For evaluation criteria of vehicle stability with respect to base measured quantities, was used model with weight functions.
Keywords:
Electronic stability control; Vehicle Assistant System; Vehicle stability
Fulltext is available at external website.
Research Report Influence of Vehicle Assistant System on Track keeping
Presented results describe different methods for the evaluation of car stability in lateral direction. Due to the significant differences between the tests, uniform methodology for recognizing the ...
Ockham's Razor from a Fully Probabilistic Design Perspective
Hoffmann, A.; Quinn, Anthony
2021 - English
This research report investigates an approach to the design of an Ockham prior penalising parametric complexity in the Hierarchical Fully Probabilistic Design (HFPD) [1] setting. We identify a term which penalises the introduction of an additional parameter in the Wold decomposition. We also derive the objective Ockham Parameter Prior (OPI) in this context, based on earlier work [2], and we show that the two are, in fact, closely related. This confers validity on the HFPD Ockham term.
Keywords:
Ockham’s Razor; Hierarchical Fully Probabilistic Design; Parametric Inference; Fully Probabilistic Design
Fulltext is available at external website.
Ockham's Razor from a Fully Probabilistic Design Perspective
This research report investigates an approach to the design of an Ockham prior penalising parametric complexity in the Hierarchical Fully Probabilistic Design (HFPD) [1] setting. We identify a term ...
Institutions, Financial Development, and Small Business Survival: Evidence from European Emerging Economies
Iwasaki, I.; Kočenda, Evžen; Shida, Y.
2020 - English
In this paper, we traced the survival status of 94,401 small businesses in 17 European emerging markets from 2007–2017 and empirically examined the determinants of their survival, focusing on institutional quality and financial development. We found that institutional quality and level of financial development exhibit statistically significant and economically meaningful impacts on the survival probability of the SMEs being researched. The evidence holds even when we control for a set of firm-level characteristics such as ownership structure, financial performance, firm size, and age. The findings are also uniform across industries and country groups and robust beyond the difference in assumption of hazard distribution.
Keywords:
small business; survival analysis; European emerging markets
Fulltext is available at external website.
Institutions, Financial Development, and Small Business Survival: Evidence from European Emerging Economies
In this paper, we traced the survival status of 94,401 small businesses in 17 European emerging markets from 2007–2017 and empirically examined the determinants of their survival, focusing on ...
Financial Crime and Punishment: A Meta-Analysis
de Batz, L.; Kočenda, Evžen
2020 - English
We examine how the publication of intentional financial crimes committed by listed firms is interpreted by financial markets, using a systematic and quantitative review of existing empirical studies. Specifically, we conduct a meta-regression analysis and investigate the extent and nature of the impact that the publication of financial misconducts exerts on stock returns. We survey 111 studies, published between 1978 and 2020, with a total of 439 estimates from event studies. Our key finding is that the average abnormal returns calculated from this empirical literature are affected by a negative publication selection bias. Still, after controlling for this bias, our meta-analysis indicates that publications of financial crimes are followed by statistically significant negative abnormal returns, which suggests the existence of an informational effect. Finally, the MRA results demonstrate that crimes committed in common law countries, alleged crimes, and accounting crimes carry particularly weighty information for market participants. The results call for more transparency on side of enforcers along enforcement procedures, to foster timely and proportionate market reactions and support efficient markets.
Keywords:
Meta-Analysis; Event study; Financial Misconduct; Fraud; Financial Markets; Returns; Listed Companies; Information and Market Efficiency
Fulltext is available at external website.
Financial Crime and Punishment: A Meta-Analysis
We examine how the publication of intentional financial crimes committed by listed firms is interpreted by financial markets, using a systematic and quantitative review of existing empirical studies. ...
Selective Attention in Exchange Rate Forecasting
Kapounek, S.; Kučerová, Z.; Kočenda, Evžen
2020 - English
We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000 news articles relevant to the six most-traded foreign exchange currency pairs for the period of 1979–2016. We employ a dynamic model averaging approach to reduce model selection uncertainty and to identify time-varying probability to include regressors in our models. Our results show that smaller sizes models accounting for the presence of selective attention offer improved fitting and forecasting results. Specifically, we document a growing impact of foreign trade and monetary policy news on the euro/dollar exchange rate following the global financial crisis. Overall, our results point to the existence of selective attention in the case of most currency pairs.
Keywords:
exchange rate; selective attention; news; forecasting; dynamic model averaging
Fulltext is available at external website.
Selective Attention in Exchange Rate Forecasting
We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market ...
Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach
Švorc, Jan; Vomlel, Jiří
2020 - English
The objective of this paper is to explore the associations between the subjective well-being (SWB) and the subjective and objective measures of the individual material situation in the four post-communist countries of Central Europe (the Czech Republic, Hungary, Poland, and Slovakia). The material situation is measured by income, relative income compared to others, relative income compared to one’s own past, perceived economic strain, financial problems, material deprivation, and housing problems. Our analysis is based on empirical data from the third wave of European Quality of Life Study conducted in 2011. Bayesian networks as a graphical representation of the relations between SWB and the material situation have been constructed in five versions. The models have been assessed using the Bayesian Information Criterion (BIC) and SWB prediction accuracy, and compared\nwith Ordinal Logistic Regression (OLR). Expert knowledge, as well as three different algorithms (greedy, Gobnilp, and Tree-augmented Naive Bayes) were used for learning the network structures. Network parameters were learned using the EM algorithm. Parameters based on OLR were learned for a version of the expert model. The Gobnilp model, the Markov equivalent to the greedy model, is BIC optimal. The OLR predicts SWB slightly better than the other models. We conclude that the objective material conditions' influence on SWB is rather indirect, through the subjective situational assessment of various aspects related to the individual material conditions.
Keywords:
Subjective Well-Being; Income; Economic Strain; Material Deprivation; Bayesian Networks; Central Europe
Fulltext is available at external website.
Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach
The objective of this paper is to explore the associations between the subjective well-being (SWB) and the subjective and objective measures of the individual material situation in the four ...
ECB monetary policy and commodity prices
Aliyev, S.; Kočenda, Evžen
2020 - English
We analyze the impact of the ECB monetary policies on global aggregate and sectoral commodity prices using monthly data from January 2001 till August 2019. We employ a SVAR model and assess separately period of conventional monetary policy before global financial crisis (GFC) and unconventional monetary policy during post-crisis period. Our key results indicate that contractionary monetary policy shocks have positive effects on the aggregate and sectoral commodity prices during both conventional and unconvetional monetary policy periods. The effect is statistically significant for aggregate commodity prices during post-crisis period. In terms of sectoral impact, the effect is statistically significant for food prices in both periods and for fuel prices during post-crisis period; other commodities display positive but statistically insignificant responses. Further, we demonstrate that the impact of the ECB monetary policy on commodity prices increased remarkably after the GFC. Our results also suggest that the effect of the ECB monetary policy on commodity prices does not transmit directly through market demand and supply expectations channel, but rather through the exchange rate channel that influences the European market demand directly.
Keywords:
European Central Bank; commodity prices; monetary policy
Fulltext is available at external website.
ECB monetary policy and commodity prices
We analyze the impact of the ECB monetary policies on global aggregate and sectoral commodity prices using monthly data from January 2001 till August 2019. We employ a SVAR model and assess separately ...
Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy
Murray, Sean Ernest; Quinn, Anthony
2020 - English
This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid carcinoma. The work seeks to address some limitations of previous approaches [4] which involve generic, non-selective transfer of archival data. It is proposed that improvements in patient-specific inferences may be achieved via transferring external population knowledge selectively. This involves matching the patient to a similar sub-population based on available metadata, generating a Gaussian Mixture Model within the partitioned data, and optimally transferring a data predictive distribution from the sub-population to the specific patient. Additionally, a performance evaluation method is proposed and early-stage results presented.
Keywords:
Bayesian estimation; thyroid carcinoma; patient-specific inferences
Fulltext is available at external website.
Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy
This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid ...
Bayesian transfer learning between autoregressive inference tasks
Barber, Alec; Quinn, Anthony
2020 - English
Bayesian transfer learning typically relies on a complete stochastic dependence speci cation between source and target learners which allows the opportunity for Bayesian conditioning. We advocate that any requirement for the design or assumption of a full model between target and sources is a restrictive form of transfer learning.
Keywords:
autoregression; transfer learning; Fully Probabilistic Design; FPD; food-commodities price prediction
Fulltext is available at external website.
Bayesian transfer learning between autoregressive inference tasks
Bayesian transfer learning typically relies on a complete stochastic dependence speci cation between source and target learners which allows the opportunity for Bayesian conditioning. We advocate that ...
Two limited-memory optimization methods with minimum violation of the previous quasi-Newton equations
Vlček, Jan; Lukšan, Ladislav
2020 - English
Limited-memory variable metric methods based on the well-known BFGS update are widely used for large scale optimization. The block version of the BFGS update, derived by Schnabel (1983), Hu and Storey (1991) and Vlček and Lukšan (2019), satisfies the quasi-Newton equations with all used difference vectors and for quadratic objective functions gives the best improvement of convergence in some sense, but the corresponding direction vectors are not descent directions generally. To guarantee the descent property of direction vectors and simultaneously violate the quasi-Newton equations as little as possible in some sense, two methods based on the block BFGS update are proposed. They can be advantageously combined with methods based on vector corrections for conjugacy (Vlček and Lukšan, 2015). Global convergence of the proposed algorithm is established for convex and sufficiently smooth functions. Numerical experiments demonstrate the efficiency of the new methods.
Keywords:
unconstrained minimization; variable metric methods; limited-memory methods; variationally derived methods; global convergence; numerical results
Available in a digital repository NRGL
Two limited-memory optimization methods with minimum violation of the previous quasi-Newton equations
Limited-memory variable metric methods based on the well-known BFGS update are widely used for large scale optimization. The block version of the BFGS update, derived by Schnabel (1983), Hu and Storey ...
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