Top PDF FINANCIAL TRANSACTION TAXATION IN AGENT-BASED SIMULATION

FINANCIAL TRANSACTION TAXATION IN AGENT-BASED SIMULATION

FINANCIAL TRANSACTION TAXATION IN AGENT-BASED SIMULATION

The models of Lux (1998) and Lux and Marchesi (1999) also focus on the case of a limited number of agents. Within this approach, an agent may either be an optimistic or a pessimistic technical trader or fundamental trader. The probability that agents switch from having an optimistic technical attitude to a pessimistic one (and vice versa) depends on the majority opinion among the technical traders and the current price trend. For instance, if the majority of technical traders are optimistic and if prices are increasing, the probability that pessimistic technical traders turn into optimistic technical traders is relatively high. The probability that technical traders (either being optimistic or pessimistic) switch to fundamental trading (and vice versa) depends on the relative profi tability of the rules. However, a comparison of the performance of the trading rules is modeled in an asymmetric manner. Although the attractiveness of technical analysis depends on realized profi ts, the popularity of fundamental analysis is a result of expected future profi t opportunities. This class of models is quite effective at replicating several universal features of asset price dynamics.
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Financial fragility in a basic agent-based model

Financial fragility in a basic agent-based model

Agent-based simulation models constitute a further development of the possibilities offered by computing machines, in that aggregate equations no longer constitute the point of departure. Rather, the idea is to describe the behaviour of single components of a system – e.g. economic agents in an economic system – and reconstruct the aggregate behaviour by simulating their interactions. In this way, agent-based computer modelling develops features that are in many respects intermediate between those of verbal descriptions and those of equations-based models (Gilbert and Terna 2000).
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Financial Regulation in an Agent Based Macroeconomic Model

Financial Regulation in an Agent Based Macroeconomic Model

Starting from the agent-based decentralized matching macroeconomic model pro- posed in Riccetti et al. (2012), we explore the effects of banking regulation on macroe- conomic dynamics. In particular, we study the overall credit exposure and the lend- ing concentration towards a single counterparty, finding that the portfolio composition seems to be more relevant than the overall exposure for banking stability, even if both features are very important. We show that a too tight regulation is dangerous because it reduces credit availability. Instead, on one hand, too loose constraints could help banks to make money and to increase their net worth, thus making the constraints not binding. However, on the other hand, if bank profits are tied to higher payout ratio (as it really happened along the deregulation phase of the last 20 years), then the financial fragility increases causing a weaker economic environment (e.g., higher mean unem- ployment rate), a more volatile business cycle, and a higher probability of triggering financial crises. Accordingly, simulation results support the introduction of the Capital Conservation Buffer (Basel 3 reform).
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Agent–Based Keynesian Macroeconomics   An Evolutionary Model Embedded in an Agent–Based Computer Simulation

Agent–Based Keynesian Macroeconomics An Evolutionary Model Embedded in an Agent–Based Computer Simulation

Before discussing a suitable solution to this practical problem, we want to look to some stylized facts: Figure 2.5 shows the growth rates of private households interest–bearing financial assets in Germany in the years 1951 to 1998. In the present model, the accumulation of household savings can be achieved exclusively through financial assets—real savings are not considered. By consequence, we can compare the data in figure 2.5 with savings behavior on Agent Island. In addition, the nominal government bond interest rate is illustrated. The interesting facts displayed in this figure are that in the early years of the development of the German economy after World War II, (i) the growth rates of financial assets were substantial higher than the interest rates, and (ii) over the years they were falling towards the level of nominal interest rates. 30 years later in the beginning 1980s, both values settled around the same range. Since this time the average growth rate of financial assets became relatively stable and coincided with the average nominal interest rates. Against the background of the present study the interpretation of these facts are straightforward: (i) If nothing else but the complete interest earnings are saved every year by households, the growth rate of their financial assets coincides with the nominal interest rates. (ii) If, in addition, positive (or negative) savings are conducted out of other income sources, the growth rates of financial assets lies somewhat above (or below) the nominal interest rate. (iii) The crucial point is that reinvested interest earnings are withdrawn from the ‘income circuit’ (Reich, 1998). If they are withdrawn in such a way, the dynamics of inflation rates is not affected by those reinvested interest incomes (Reich, 1998). The reinvestment of interest incomes characterizes the mechanism of a savings book, which is a quite popular form of savings among German households—especially during that time. Consequently, the above mentioned ‘vicious circle’ cannot occur on Agent Island provided that interest incomes are reinvested by household agents in each period (like in a savings book). Conversely, this can produce deflationary effects, and it can result in exponentially growing financial assets (as identified in reality as well).
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A Study on Agent Based Modelling for Traffic          Simulation

A Study on Agent Based Modelling for Traffic Simulation

Abstract— Computer simulations allow one to understand interactions of physical particles and make sense of astronomical observations. Today, Offices, administrations, financial trading, economic exchange, the control of infrastructure networks, and a large share of our communication would not be conceivable without the use of computers anymore. With the statistical analysis of data and data-driven efforts to reveal the prototype of transport traffic model, we focused the prospects of computer simulation and the features of agent-based modelling and multi-agent simulation (MAS). Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterize transport systems. Traffic simulation can be implemented using agent-based modelling (ABM), which enables dynamic objects such as vehicles to be modelled individually and have control over their behaviour. In doing so, we studied and presented various issues agent-based simulation, and provide a way to do them right from a scientific perspective. This paper focuses on the use of traffic simulation in helping traffic engineers to reduce congestion. It aims to help in developing a unique traffic simulation system that can be used to study traffic theory and access network infrastructure and control changes.
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Financial transactions taxation in the European Union and Croatia

Financial transactions taxation in the European Union and Croatia

326 to facilitate harmonisation of the application of the FTT, other forms of taxation of financial transactions would not be permitted. However, countries would be able to set their own rates, higher than the minimum, letting them provide addi- tional sources of revenue. Accordingly, only transactions among financial institu- tions of the participating countries would be taxed. The proposal is based on the triple-A approach, meaning it refers to All markets, All instruments and All actors. According to European Commission (2013b) the following would be considered financial institutions: investment companies, organised markets, credit institu- tions, insurance and reinsurance companies, investment funds and investment fund management companies, pensions funds and pensions funds management companies, holding companies, leasing companies, special purpose companies and other institutions as defined by statute. As well as these, other companies that undertake certain financial activities that exceed 50% of their annual income would also be considered financial institutions.
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Limited financial market participation:
a transaction cost-based explanation

Limited financial market participation: a transaction cost-based explanation

For the estimation of such cost bounds, I extend Luttmer (1999) and determine the lower bounds as the minimal costs that rationalize non-participation, i.e. as those costs exactly equal to the utility gains from trade. However, unlike Luttmer, whose work is based on aggregate information, I use individual level data, which allow to distinguish between actual participants and non-participants to financial markets, instead of simply characterizing traders and non-traders in the time period under scrutiny. As a consequence, the nature of the costs I focus upon is substantially different from the nature of the costs in Luttmer’s analysis. In fact, the frictions he considers are the costs that the representative agent must pay to trade and modify her consumption in the current period and in one or at most few subsequent periods. Instead, by distinguishing between participants and non-participants, this paper focuses on the costs any individual faces in order to actually participate to financial markets. In addition, because of the use of aggregate data, the validity of Luttmer’s results is limited and his analysis applies strictly only to an agent who happens to consume US per-capita consumption because, in the presence of fixed costs, the conditions upon which aggregation results are based do not hold. For this reason, the use of micro data is particularly desirable in a framework where fixed costs play a role. The use of individual-level data brings about several other advantages. First, it allows to verify whether there are important cost differences when trading different portfolios, - at least to the extent that the data permit to distinguish between different assets. Second, it allows to take into account the effects that individual specific factors have on utility reducing the scope for unobserved heterogeneity and, consequently, the potential for bias. Last, given the availability of some panel dimension in the data I use, it is possible to account for differences in the covariance between individual consumption growth and asset returns.
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Agent-based Model Construction in Financial
Economic System

Agent-based Model Construction in Financial Economic System

The paper gives picture of enrichment to economic and financial system analysis using agent-based models as a form of advanced study for financial economic post-statistical-data and micro-simulation analysis. The paper reports the construction of artificial stock market that emerges the similar statistical facts with real data in Indonesian stock market. We use the individual but dominant data, i.e.: PT TELKOM in hourly interval. The artificial stock market shows standard statistical facts, e.g.: volatility clustering, the excess kurtosis of the distribution of return, and the scaling properties with its breakdown in the crossover of Levy distribution to the Gaussian one. From this point, the artificial stock market will always be evaluated in order to have comprehension about market process in Indonesian stock market generally.
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Financial sector taxation: Financial activities tax or financial transaction tax?

Financial sector taxation: Financial activities tax or financial transaction tax?

Other possible variant of FTT represents a nar- row based FTT. Under that model, only stock and bond transactions would be covered into the tax base. In this case, it is easy to defi ne tax base for the transactions, for the asset price is determined by the market at the time when the transaction is executed. To sum up, broad based FTT does not seem to be an appropriate candidate on taxing the fi nancial sector on EU level due to the complicated deter- mination of the tax base in case of derivates, which could be solved by setting a actual price of the deri- vate as the tax base, but would lead to the signifi cant decrease of the tax base as was already mentioned above, which is in contradiction with the consider- ation, that FTT should be mainly the tool for raising the revenue.
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Environment for agent based model in mobile database 
		transaction: a review

Environment for agent based model in mobile database transaction: a review

A database which store locations of users will often change due to the user's location varies at times. According to [16], the database is structured to local databases and distributed at different BSs. It consists of temporal and non-temporal data objects. The difference between both is that temporal data objects are used to record object status in the external environment. The timestamp is associated with each temporal data object to trace the data object life. The timestamp is given when a transaction is initiated and set upon it if the transaction is successfully committed before its deadline.
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A beginner's guide to systems simulation in immunology

A beginner's guide to systems simulation in immunology

7. Decide on the most appropriate simulation approach. This decision is made based on the characteristics of the problems, the research questions to be addressed, the scope, the level of aggregation and the experimental data avail- able. Some of the most common approaches used in immunology are agent-based modelling and simulation, discrete-event modelling and simulation, cellular au- tomata and system dynamics. Cellular automata is used for problems involving autonomous individual interactions within a neighbourhood placed in a lattice and emergent behaviour. Agent-based simulation is suitable for problems involv- ing autonomous individual behaviour, elements spacial localization, memory and emergence. Discrete-event simulation tackles problems that are process-oriented, which have passive individual entities and chronological sequence of events. Fur- thermore, each event occurs at an instant in time and marks a change of state in the system. It can be used for any experiment where there is no need for contin- uous time. SD defines a system at a high level of aggregation and, therefore, it should be used when the research question involves patterns of behaviours and feed-back interactions between the aggregates. This approach is very useful to simulate dynamics of populations and interactions between different populations overtime. For example, interactions between tumours and populations of effector cells, populations of viruses and T cells, etc.
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Transfer Pricing: The Nigerian Perspective

Transfer Pricing: The Nigerian Perspective

given to a connected taxable person as stipulated under Section 7(8) of the Income Tax (Transfer Pricing) Regulations 2012 include: (a) the connected taxable person has failed to materially comply with a fundamental term of the Advance Pricing Agreement; (b) there has been a material breach of one or more of the critical assumptions underlying the Advance Pricing Agreement; (c) there is a change in the tax law that is materially relevant to the Advance Pricing Agreement; or (d) the Advance Pricing Agreement was entered into based on a misrepresentation, mistake or omission by the connected taxable person.
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Performance of Time-Bound Negotiation in Agent-Based Manufacturing Control

Performance of Time-Bound Negotiation in Agent-Based Manufacturing Control

In a typical MAS shop floor control application, software agents represent various entities in the system (tasks, sub- tasks, machines, people, etc.) and they jointly determine the allocation and routing of tasks among machines through a negotiation process. This often involves an auction/bidding scheme with valuation criteria such as production cost and expected finishing time. The main emphasis of research in this area has been on the design of such negotiation schemes for coping with challenging operating conditions under various system configurations. Many of these schemes are based on the contract net protocol (CNP) [15] which was originally proposed for cooperative problem solving in a distributed processing environment [16].
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DESIGN OF BRANCHLESS BANKING INFORMATION SYSTEM USING USSD TECHNOLOGY: CASE STUDY IN PT BANK RAKYAT INDONESIA (BRI PERSERO) TBK.

DESIGN OF BRANCHLESS BANKING INFORMATION SYSTEM USING USSD TECHNOLOGY: CASE STUDY IN PT BANK RAKYAT INDONESIA (BRI PERSERO) TBK.

In 2016 there are some provinces that still have financial inclusion index below the national average such as West Sumatra province at 66.91%, Jambi at 66,91%, Central Borneoat 60,36%, North Borneoat 61,45% andSouth Borneo at 59,27%. Based on data obtained through the Central Bureau of Statistics (BPS), these provinces have percentage of the population who own or proficient to control the mobile phones above the national average and always increase each year in a varied number. In 2012 the national percentage is 47.99% and in 2015 increased to 56.92%. In 2015 percentage of West Sumatera Province is 57.04%, Jambi is 58.68%, Central Kalimantan is 63.29%, North Kalimantan is 67.48%, and South Kalimantan is 62.74%.These provinces have an index above the national average in the percentage of people who own or proficient to control the mobile phone but its financial inclusion index is still below the national average. In these provinces there is still considerable potential space for the banking industry to provide banking inclusion services. Performance expectation, business expectation and social factor have a significant positive effect on interest of information system utilization(Handayani, 2005).
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Agent based Simulation of Open Source Evolution

Agent based Simulation of Open Source Evolution

We used the NetLogo (2005) multi-agent simulation tool to develop our model. We selected NetLogo primarily because it is freely available on the web and well documented and supported. In this tool, agents move around a virtual world, interacting with it and with other agents. There is no centralised control or co-ordination of the agents' actions. Agents are responsible to maintaining their own state. The NetLogo virtual world consists of a grid of “patches”, each of which can have a state. Generally, agents have only local knowledge about their surroundings. Both agents and patches are active agents in the simulation, performing actions and asking other agents to perform other actions. Simulation proceeds by each agent and patch repeating its behaviour independently, often by following stochastic functions influenced by the agent's state and local environment. Agents perform their own actions asynchronously and as rapidly as they can. In an agent-based simulation, the overall behaviour of the system is an emergent property of the individual, independent interactions of the agents. This approach differs from the traditional modelling approach where the state of the system is captured in a single set of global state variables, such as stocks and flows.
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An Agent-based Simulation of the Effectiveness of Creative Leadership

An Agent-based Simulation of the Effectiveness of Creative Leadership

Agents evaluate the effectiveness of their actions according to how well they satisfy needs using a pre-defined equation referred to as a fitness function. The fitness of an action with respect to the need to attract mates is calculated as in (Gabora, 1995). The fitness function rewards actions that make use of trends detected by the symmetry and movement hidden nodes and used by knowledge-based operators to bias the generation of new ideas. It generates actions that are relatively realistic mating displays, and exhibits a cultural analog of epistasis. In biological epistasis, the fitness conferred by the allele at one gene depends on which allele is present at another gene. In this cognitive context, epistasis is present when the fitness contributed by movement of one limb depends on what other limbs are doing.
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Essays at the intersection of taxation and financial accounting

Essays at the intersection of taxation and financial accounting

firms provide a reference in their CBCR to the list of subsidiaries and branches in the financial statement notes. In these cases, data was hand-collected from the relevant notes to the financial statements. 54 Geographic segment information was hand- collected from the segment reporting note in the financial statements. For the publicly- listed firms, data for the firm-level controls was obtained from Datastream, whereas for the unlisted entities, this data was hand-collected from annual reports. Information on carried forward tax losses was hand-collected from the financial statement notes for all firms as this data item is not available on Datastream. Finally, our sample size is relatively small and thus our empirical tests could be easily influenced by a few influential observations. To mitigate this risk, we winsorize all continuous variables at the 1 st and 99 th percentiles. Appendix C provides formal definitions for all variables. Panel A of Table 3.2 lists the EU banks, their country of residence, GSIB and listing status, and total assets (measured in Euros) as at 31 December 2016. The table reveals the dominance by a relatively small number of large firms. The 14 GSIBs account for approximately 57% of total assets. Furthermore, 48 or 68.6% of sample banks are publicly-listed. Panel B displays the sample split by country. The major EU countries France, Germany, Spain, and the UK, account for a relatively greater proportion of the 14 countries covered. Panel C shows the asset size by firm-type. The mean (median) total assets of the primary sample is €441,451m (€212,329m). Table 3.3 presents details on the EU insurance firms. Panel A shows that similar to EU banks, larger firms dominate the sample. The 13 firms with total assets greater than €100,000m account for approximately 86% of total assets. Panel B reveals that the sample selection process resulted in EU insurers from 9 of the 14 EU countries the banks are based in and that firms from France, Germany, and UK comprise the majority (77.1%) of total assets. Panel C shows that, on average, the insurers are smaller than the banks. The mean (median) total assets of the control sample is €166,279m (€63,612m).
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Agent-based Simulation of Electricity Markets -A Literature Review-

Agent-based Simulation of Electricity Markets -A Literature Review-

As the concept of agent-based simulation is applied to large scale simulation platforms models such as EMCAS, PowerACE or NEMSIM, the requirements on the data and agent architecture increase considerably, ranging from detailed electricity market and load data to future power plant options. Thereby it has to be stated that a common challenge to all agent- based simulations in electricity markets is the validation of simulation results. This is an important issue which needs more attention in the current research. In most of the reviewed papers the validation process is limited to a qualitative discussion. None of the reviewed papers applies a thorough validation procedure for a comparison of simulation results with real market data. However some papers, such as (Bower et al., 2001, Scheidt, 2002), show a graphical comparison of results and real world development. In order to gain more acceptance by the modelling community, it might be valuable to support the graphical comparison by statistical indicators. A first attempt is presented by Sensfuß and Genoese (Sensfuß, Genoese, 2006; Genoese et al., 2007) showing a promising approach which needs further refinement. Another issue is the validation of the behaviour of single agents which is a demanding task in itself. Thereby the analysis of agent decisions such as consumer contract choice or investment decisions may require considerable efforts to improve the empirical data basis.
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Financial-transaction tax: small is beautiful. Bruegel Policy Contribution 2010/02, February 2010

Financial-transaction tax: small is beautiful. Bruegel Policy Contribution 2010/02, February 2010

By contrast, what is fairly clear is that higher transaction costs will tend to reduce trading volume. Such a reduction in trading volume would also tend to go hand-in-hand with a reduction in market liquidity, which could be a major adverse consequence of a tax. What is less clear is how large this effect will be. Figure 8 shows the ratio of turnover to market capitalisation (a measure called ‘stock-market velocity’). It shows that coun- tries with significant transaction taxes do not have exceptionally low stock-market velocities. This certainly suggests that the financial-trans- action tax itself is not the dominant determinant of trading activity, with other factors driving major cross-country differences. Those factors would include other sources of transaction cost, the size and frequency of shocks to these markets and the ways in which these shocks are absorbed. 3.2.6 Increased cost of funding for the real
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Measuring the Impact of Financial Taxation on Capital

Measuring the Impact of Financial Taxation on Capital

In the international context, taxing financial services is mainly implemented via two practices: (i) a value-added tax on financial transactions or (ii) a specific tax on some financial services. In Chile, a specific tax is levied on financial services. This tax takes different rates depending on the type of financial service provided. Following Arellano and Corbo (2013), a specific financial transaction tax can be considered as an extension of a value-added tax on financial services. However, it is simpler to implement since it does not contain the main methodological problems of applying a value-added tax on financial transactions. This is the reason why Chile and other countries have opted to implement a specific financial transaction tax instead of a value-added tax.
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