Browsing by Subject "Banking"

Sort by: Order: Results:

Now showing items 1-4 of 4
  • Hatwágner, Miklós F.; Vastag, Gyula; Niskanen, Vesa A.; Kóczy, László T. (Springer Verlag, 2019)
    Studies in Computational Intelligence
    Fuzzy Cognitive Map (FCMs) is an appropriate tool to describe, qualitatively analyze or simulate the behavior of complex systems. FCMs are bipolar fuzzy graphs: their building blocks are the concepts and the arcs. Concepts represent the most important components of the system, the weighted arcs define the strength and direction of cause-effect relationships among them. FCMs are created by experts in several cases. Despite the best intention the models may contain subjective information even if it was created by multiple experts. An inaccurate model may lead to misleading results, therefore it should be further analyzed before usage. Our method is able to automatically modify the connection weights and to test the effect of these changes. This way the hidden behavior of the model and the most influencing concepts can be mapped. Using the results the experts may modify the original model in order to achieve their goal. In this paper the internal operation of a department of a bank is modeled by FCM. The authors show how the modification of the connection weights affect the operation of the institute. This way it is easier to understand the working of the bank, and the most threatening dangers of the system getting into an unstable (chaotic or cyclic state) can be identified and timely preparations become possible. © Springer Nature Switzerland AG 2019.
  • Lappi, Pauli (2017)
    We study non-compliance in an emissions trading system in which firms may bank and borrow permits. We find a condition involving auditing probability that characterizes compliance and allows us to analyze the time paths of actual emissions, reported emissions and violations. We find two interesting time instants. At the first time instant, reported emissions begin to be lower than the actual emissions, and at the second time instant, the reported emissions become zero and the actual emissions become constant. The results indicate, among other things, that a given penalty scheme may fail to induce compliance over the whole planning interval, even though it achieves compliance over the initial stage.
  • Hatwagner, M.F.; Vastag, G.; Niskanen, V.A.; Kóczy, L.T. (Springer, 2018)
    Lecture Notes in Computer Science
    Fuzzy Cognitive Maps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs is mostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model ‘sensitivity’ to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and Bacterial Evolutionary Algorithm is a novelty of the approach. © Springer International Publishing AG, part of Springer Nature 2018.
  • Jakonen, Oskari (Helsingin yliopisto, 2020)
    This paper constructs and analyses a variation on a DSGE model with a shadow banking system integrated in the financial sector by Falk Mazelis. Shadow banking is fundamentally described as credit intermediation outside the regular banking system and the description is specified in this paper during the process of historical review of the Chinese financial sector. Excess credit in the shadow banking sector and theoretical studies of banks’ and shadow banks different reaction to monetary policy shocks are the main motives behind this study. The Mazelis model builds upon a Gertler-Karadi DSGE model of financial intermediation with unconventional monetary policy. After mapping previous literature on banking, shadow banking and DSGE modelling the detailed model of Mazelis is adjusted by altering the monetary policy rule and four model parameters towards Chinese economical characteristics. The adjustments are and argued with data, previous literature, and theoretical arguments motivated by the historical review. The main objective of this approach is, trough the variation, to capture the effect of Chinese economical characteristics towards an economy with modelled shadow banking sector. The implications of the original model are considered as a foundation for the altered model. In the original model after tightening monetary policy, regular banks reduce the amount of loans on their balance sheet while shadow banks increase lending. This reduces the real effects of the shock, but at the same time shadow banks amplify the reaction of key variables to real shocks and can make the financial sector and the whole economy more unstable. The analysis of the altered model provides suggestions that the implemented Chinese characteristics make the economy slightly more vulnerable to a monetary policy tightening reducing capital and consumption. In addition, simulated shocks to productivity and monetary policy amplify the reactions of the financial sector in bank and shadow bank loan supply suggesting that the altered model can make the economy all the more unstable. The DSGE framework used in this paper does not try to model Chinese economy, but rather provides hints of economic elements in it and highlights specific aspects of it.