nep-cmp New Economics Papers
on Computational Economics
Issue of 2014‒05‒09
twenty papers chosen by
Stan Miles
Thompson Rivers University

  1. Fiscal and Monetary Policies in Complex Evolving Economies By Giovanni Dosi; Giorgio Fagiolo; Mauro Napoletano; Andrea Roventini
  2. Exact simulation of Hawkes process with exponentially decaying intensity By Angelos Dassios; Hongbiao Zhao
  3. Modeling consumer opinions towards dynamic pricing: An agent-based approach By Anna Kowalska-Pyzalska; Katarzyna Maciejowska; Katarzyna Sznajd-Weron; Rafal Weron
  4. Spatial interactions in agent-based modeling By Marcel Ausloos; Herbert Dawid; Ugo Merlone
  5. Rock around the Clock: An Agent-Based Model of Low-and High-Frequency Trading By Sandrine Jacob Leal; Mauro Napoletano; Andrea Roventini; Giorgio Fagiolo
  6. Learning about learning in games through experimental control of strategic interdependence By Jason Shachat; J. Todd Swarthout
  7. Alternative Agricultural Price Distortions for CGE Analysis, 2007 and 2011 By Jensen, Hans Grinsted; Kym Anderson
  8. Lookahead Strategies for Sequential Monte Carlo By Ming Lin; Rong Chen; Jun S. Liu
  9. Optimal Step-wise Parameter Optimization of a FOREX Trading Strategy By Alberto De Santis; Umberto Dellepiane; Stefano Lucidi; Stefania Renzi
  10. Financial Symmetry and Moods in the Market By Roberto Savona; Maxence Soumare; Jørgen Vitting Andersen
  11. Calculating the Funding Valuation Adjustment (FVA) of Value-at-Risk (VAR) based Initial Margin By Andrew Green; Chris Kenyon
  12. Numerical Simulations of Competition in Quantities By Devon Gorry; John Gilbert
  13. Nonlinear Valuation under Collateral, Credit Risk and Funding Costs: A Numerical Case Study Extending Black-Scholes By Damiano Brigo; Qing Liu; Andrea Pallavicini; David Sloth
  14. Greenhouse Gas and Cyclical Growth By Lance Taylor; Duncan Foley
  15. Fiscal consolidation in times of crisis: is the sooner really the better? By Christophe Blot; Marion Cochard; Jérôme Creel; Bruno Ducoudre; Danielle Schweisguth; Xavier Timbeau
  16. Facilitation and Internalization Optimal Strategy in a Multilateral Trading Context By Qinghua Li
  17. Impulse Control of a Diffusion with a Change Point By Lokman A. Abbas-Turki; Ioannis Karatzas; Qinghua Li
  18. Market Coupling as the Universal Algorithm to Assess Zonal Divisions By Grzegorz Orynczak; Marcin Jakubek; Karol Wawrzyniak; Michal Klos
  19. On Generating Monte Carlo Samples of Continuous Diffusion Bridges By Ming Lin; Rong Chen; Per Mykland
  20. The Zero Lower Bound: Frequency, Duration, and Numerical Convergence By Alexander W. Richter; Nathaniel A. Throckmorton

  1. By: Giovanni Dosi; Giorgio Fagiolo; Mauro Napoletano; Andrea Roventini
    Abstract: In this paper we explore the effects of alternative combinations of fiscal and monetary policies under different income distribution regimes. In particular, we aim at evaluating fiscal rules in economies subject to banking crises and deep recessions. We do so using an agent-based model populated by heterogeneous capital- and consumption-good firms, heterogeneous banks, workers/consumers, a Central Bank and a Government. We show that the model is able to reproduce a wide array of macro and micro empirical regularities, including stylised facts concerning nancial dynamics and banking crises. Simulation results suggest that the most appropriate policy mix to stabilise the economy requires unconstrained counter-cyclical fiscal policies, where automatic stabilisers are free to dampen business cycles fluctuations, and a monetary policy targeting also employment. Instead, "discipline-guided" fiscal rules such as the Stability and Growth Pact or the Fiscal Compact in the Eurozone always depress the economy, without improving public finances, even when escape clauses in case of recessions are considered. Consequently, austerity policies appear to be in general self-defeating. Furthermore, we show that the negative effects of austere fiscal rules are magnied by conservative monetary policies focused on inflation stabilisation only. Finally, the effects of monetary and fiscal policies become sharper as the level of income inequality increases.
    Date: 2014–02–14
    URL: http://d.repec.org/n?u=RePEc:thk:rnotes:40&r=cmp
  2. By: Angelos Dassios; Hongbiao Zhao
    Abstract: We introduce a numerically efficient simulation algorithm for Hawkes process with exponentially decaying intensity, a special case of general Hawkes process that is most widely implemented in practice. This computational method is able to exactly generate the point process and intensity process, by sampling interarrivaltimes directly via the underlying analytic distribution functions without numerical inverse, and hence avoids simulating intensity paths and introducing discretisation bias. Moreover, it is flexible to generate points with either stationary or non-stationary intensity, starting from any arbitrary time with any arbitrary initial intensity. It is also straightforward to implement, and can easily extend to multi-dimensional versions, for further applications in modelling contagion risk or clustering arrival of events in finance, insurance, economics and many other fields. Simulation algorithms for one dimension and multi-dimension are represented, with numerical examples of univariate and bivariate processes provided as illustrations.
    Keywords: Contagion risk; Stochastic intensity model; Self-exciting point process; Hawkes process; Hawkes process with exponentially decaying intensity; Exact simulation; Monte Carlo simulation.
    URL: http://d.repec.org/n?u=RePEc:wyi:journl:002211&r=cmp
  3. By: Anna Kowalska-Pyzalska; Katarzyna Maciejowska; Katarzyna Sznajd-Weron; Rafal Weron
    Abstract: Using an agent-based modeling approach we show how personal attributes, like conformity or indifference, impact opinions of individual electricity consumers regarding innovative dynamic tariff programs. We also examine the influence of advertising, discomfort of usage and the expectations of financial savings on opinion dynamics. Our main finding is that currently the adoption, understood as a positive opinion or attitude toward the innovation, of dynamic electricity tariffs is virtually impossible due to the high level of indifference in today’s societies. However, if in the future the indifference level is reduced, e.g., through educational programs that would make the customers more engaged in the topic, factors like tariff pricing schemes and intensity of advertising will became the focal point.
    Keywords: Dynamic pricing; Demand response; Opinion formation; Agent-based model
    JEL: C63 O33 Q48 Q55
    Date: 2014–04–30
    URL: http://d.repec.org/n?u=RePEc:wuu:wpaper:hsc1406&r=cmp
  4. By: Marcel Ausloos (Liege & Amsterdam); Herbert Dawid (Bielefeld); Ugo Merlone (Torino)
    Abstract: Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.
    Date: 2014–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1405.0733&r=cmp
  5. By: Sandrine Jacob Leal; Mauro Napoletano; Andrea Roventini; Giorgio Fagiolo
    Abstract: We build an agent-based model to study how the interplay between low- and high- frequency trading affects asset price dynamics. Our main goal is to investigate whether high-frequency trading exacerbates market volatility and generates ash crashes. In the model, low-frequency agents adopt trading rules based on chrono- logical time and can switch between fundamentalist and chartist strategies. On the contrary, high-frequency traders activation is event-driven and depends on price fluctuations. High-frequency traders use directional strategies to exploit market in- formation produced by low-frequency traders. Monte-Carlo simulations reveal that the model replicates the main stylized facts of financial markets. Furthermore, we find that the presence of high-frequency trading increases market volatility and plays a fundamental role in the generation of flash crashes. The emergence of flash crashes is explained by two salient characteristics of high-frequency traders, i.e., their ability to i) generate high bid-ask spreads and ii) synchronize on the sell side of the limit order book. Finally, we find that higher rates of order cancellation by high-frequency traders increase the incidence of flash crashes but reduce their duration.
    Date: 2014–01–31
    URL: http://d.repec.org/n?u=RePEc:thk:rnotes:37&r=cmp
  6. By: Jason Shachat; J. Todd Swarthout
    Abstract: We report results from an experiment in which humans repeatedly play one of two games against a computer program that follows either a reinforcement or an experience weighted attraction learning algorithm. Our experiment shows these learning algorithms detect exploitable opportunities more sensitively than humans. Also, learning algorithms respond to detected payoff-increasing opportunities systematically; however, the responses are too weak to improve the algorithms' payoffs. Human play against various decision maker types doesn't vary significantly. These factors lead to a strong linear relationship between the humans' and algorithms' action choice proportions that is suggestive of the algorithms' best response correspondences.
    Keywords: Learning, Repeated games, Experiments, Simulation
    JEL: C72 C92 C81
    Date: 2013–10–14
    URL: http://d.repec.org/n?u=RePEc:wyi:wpaper:002031&r=cmp
  7. By: Jensen, Hans Grinsted; Kym Anderson
    Abstract: A recent World Bank research project has generated an annual time series of distortions to agricultural incentives over the past half century for 82 countries, the majority of which are low-and middle-income countries. In this memorandum, the current GTAP version 8 Data Base may be modified to incorporate this dataset, using an Altertax simulation. The files required for this Altertax simulation, including parameter files and shock files are generated by the DAItoGTAP.tab file which will accommodate any level of aggregation of the GTAP database. In this memorandum the data files required to modify the GTAP v8.1 database can be downloaded. Data required to modify the GTAP v9 database will be available at a later date when v9 is released.
    Date: 2014
    URL: http://d.repec.org/n?u=RePEc:gta:resmem:4364&r=cmp
  8. By: Ming Lin; Rong Chen; Jun S. Liu
    Abstract: Based on the principles of importance sampling and resampling, sequential Monte Carlo (SMC) encompasses a large set of powerful techniques dealing with complex stochastic dynamic systems. Many of these systems possess strong memory, with which future information can help sharpen the inference about the current state. By providing theoretical justification of several existing algorithms and introducing several new ones, we study systematically how to construct effient SMC algorithms to take advantage of the "future" information without creating a substantially high computational burden. The main idea is to allow for lookahead in the Monte Carlo process so that future information can be utilized in weighting and generating Monte Carlo samples, or resampling from samples of the current state.
    Keywords: Sequential Monte Carlo; Lookahead weighting; Lookahead sampling; Pilot lookahead; Multilevel; Adaptive lookahead.
    Date: 2013–10–14
    URL: http://d.repec.org/n?u=RePEc:wyi:journl:002173&r=cmp
  9. By: Alberto De Santis (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Umberto Dellepiane (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Stefano Lucidi (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza"); Stefania Renzi (Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza")
    Abstract: The goal of trading simply consists in gaining profit by buying/selling a security: the difference between the entry and the exit price in a position determines the profit or loss of that trade. A trading strategy is used to identify proper conditions to trade a security. The role of optimization consists in finding the best conditions to start a trading maximizing the profit. In this general scenario, the strategy is trained on a chosen batch of data (training set) and applied on the next batch of data (trading set). Given a strategy, there are different issues to deal with, to obtain the best performances from the optimization. First of all, among all the parameters that define the strategy, it is important to identify and select the most relevant ones that become the optimization problem variables. In this way the problem complexity is reduced and the overfitting on the training set is avoided. Once the variables are chosen, the focus is on the time period used for the training and the trading sets. Accordingly, for any parameter, a proper box constraint is fixed taking into account the frequency of the given trading strategy (time scale, reactivity, etc.). Since the objective function is not defined in closed form but through an algorithm, the problem lies within the framework of black-box optimization.
    Keywords: Global Optimization, Black-Box, Forex Trading, Algorithmic Trading, Modelling Procedure
    Date: 2014
    URL: http://d.repec.org/n?u=RePEc:aeg:report:2014-06&r=cmp
  10. By: Roberto Savona (Department of Economics and Management - Università degli studi di Brescia); Maxence Soumare (Laboratoire Jean-Alexandre Dieudonné - Université de Nice-Sophia Antipolis); Jørgen Vitting Andersen (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne)
    Abstract: This paper introduces a theoretical framework for collective decision making to describe fluctuations and transitions in financial markets. Investors are assumed to be boundedly rational, using a limited set of information including past price history and expectation on future dividends. Investment strategies are dynamically changed based on realized returns within a game theoretical scheme with Nash equilibria. In such a setting, markets behave as complex systems whose payoff reflect an intrinsic financial symmetry that guarantees equilibrium in price dynamics (fundamentalist state) until the symmetry is broken leading to bubble or anti-bubble scenarios (speculative state). We model such two-phase transition in a micro-to-macro scheme through a Ginzburg-Landau-based power expansion leading to a market temperature parameter which modulates the state transitions in the market. Via simulation we prove that complex market dynamics can be phenomenologically explained by the number of traders, the strategies used by agents and the past price history, all included in our market temperature parameter.
    Keywords: Agent-based modelling; Game theory; Ginzburg-Landau theory; financial symmetry
    Date: 2014–03
    URL: http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-00983008&r=cmp
  11. By: Andrew Green; Chris Kenyon
    Abstract: Central counterparties (CCPs) require initial margin (IM) to be posted for derivative portfolios cleared through them. Additionally, the Basel Committee on Banking Supervision has proposed in BCBS-261 that all significant OTC derivatives trading must also post IM by 2019. IM is typically calculated using Value-at-Risk (VAR) or Conditional Value-at-Risk (CVAR, aka Expected Shortfall), based on historical simulation. As previously noted (Green2013a), (Green2013b) IM requirements give rise to a need for unsecured funding similar to FVA on unsecured derivatives. The IM cost to the derivatives originator requires an integral of the funding cost over the funding profile which depends on VAR- or CVAR-based calculation. VAR, here, involves running a historical simulation Monte Carlo inside a risk-neutral Monte Carlo simulation. Brute force calculation is computationally unfeasible. This paper presents a computationally efficient method of calculating IM costs for any derivative portfolio: Longstaff-Schwartz Augmented Compression, (LSAC). Essentially, Longstaff-Schwartz is used with an augmented state space to retain accuracy for VAR-relevant changes to the state variables. This method allows rapid calculation of IM costs both for portfolios, and on an incremental basis. LSAC can be applied wherever historic simulation VAR is required such as lifetime cost of market risk regulatory capital using internal models. We present example costs for IM under BCBS-261 for interest rate swap portfolios of up to 10000 swaps and 30 year maturity showing significant IM FVA costs and two orders of magnitude speedup compared to direct calculation.
    Date: 2014–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1405.0508&r=cmp
  12. By: Devon Gorry (Department of Economics and Finance, Utah State University); John Gilbert (Department of Economics and Finance, Utah State University)
    Abstract: We present a series of numerical simulation models built in Excel that can be used to explore the properties of various models of strategic competition in quantities and their economic implications. The resources incorporate both tabular and graphical data presentation formats and are built in such a way that they provide instant or 'live' feedback on the consequences of changes in the economic system. We discuss the theory behind the models, how they can be implemented as numerical simulations in Excel, and ways in which the simulations can be used to enhance student understanding of the material. The tools are all available through RePEc and on the website Economic Models in Excel (https://sites.google.com/site/economicm odelsinexcel/io).
    Keywords: IO, Excel, teaching
    Date: 2014–05–05
    URL: http://d.repec.org/n?u=RePEc:uth:wpaper:201401&r=cmp
  13. By: Damiano Brigo; Qing Liu; Andrea Pallavicini; David Sloth
    Abstract: We develop an arbitrage-free framework for consistent valuation of derivative trades with collateralization, counterparty credit gap risk, and funding costs, following the approach first proposed by Pallavicini and co-authors in 2011. Based on the risk-neutral pricing principle, we derive a general pricing equation where Credit, Debit, Liquidity and Funding Valuation Adjustments (CVA, DVA, LVA and FVA) are introduced by simply modifying the payout cash-flows of the deal. Funding costs and specific close-out procedures at default break the bilateral nature of the deal price and render the valuation problem a non-linear and recursive one. CVA and FVA are in general not really additive adjustments, and the risk for double counting is concrete. We introduce a new adjustment, called a Non-linearity Valuation Adjustment (NVA), to address double-counting. The theoretical risk free rate disappears from our final equations. The framework can be tailored also to CCP trading under initial and variation margins, as explained in detail in Brigo and Pallavicini (2014). In particular, we allow for asymmetric collateral and funding rates, replacement close-out and re-hypothecation. The valuation equation takes the form of a backward stochastic differential equation or semi-linear partial differential equation, and can be cast as a set of iterative equations that can be solved by least-squares Monte Carlo. We propose such a simulation algorithm in a case study involving a generalization of the benchmark model of Black and Scholes for option pricing. Our numerical results confirm that funding risk has a non-trivial impact on the deal price, and that double counting matters too. We conclude the article with an analysis of large scale implications of non-linearity of the pricing equations.
    Date: 2014–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1404.7314&r=cmp
  14. By: Lance Taylor; Duncan Foley
    Abstract: A growth model incorporating dynamics of capital per capita, atmospheric CO2 concentration, and labor and energy productivity is described. In the “medium run” output and employment are determined by effective demand in contrast to most models of climate change. In a “long run” of several centuries the model converges to a stationary state with zero net emissions of CO2. Properties of dismal and non-dismal stationary states are explored, with a latter requiring a relatively high level of investment in mitigation of emissions. Without such investment under “business as usual” output dynamics are strongly cyclical in numerical simulations. There is strong output growth for about eight decades, then a climate crisis, and output crash.
    Date: 2014–02
    URL: http://d.repec.org/n?u=RePEc:thk:rnotes:38&r=cmp
  15. By: Christophe Blot (OFCE); Marion Cochard (OFCE); Jérôme Creel (OFCE); Bruno Ducoudre (OFCE); Danielle Schweisguth (OFCE); Xavier Timbeau (OFCE)
    Abstract: Recent evidence has renewed views on the size of fiscal multipliers. It is notably emphasized that fiscal multipliers are higher in times of crisis. Starting from this literature, we develop a simple and tractable model to deal with the fiscal strategy led by euro area countries. Constrained by fiscal rules and by speculative attacks in financial markets, euro area members have adopted restrictive fiscal policies despite strong negative output gaps. Based on the model, we present simulations to determine the path of public debt given the current expected consolidation. Our simulations suggest that despite strong austerity measures, not all countries would be able to reach the 60% debt-to-GDP. If fiscal multipliers vary along the business cycle, this would give a strong case for delaying austerity. This alternative scenario is considered. Our results show not only that delaying austerity would improve growth perspectives and would not be incompatible with public debt converging to 60% of GDP.
    Keywords: public debt; fiscal multipliers; debt
    Date: 2014–04
    URL: http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/2g7mhju69b94obeaqlen09s1au&r=cmp
  16. By: Qinghua Li
    Abstract: This paper studies four trading algorithms of a professional trader at a multilateral trading facility, observing a realistic two-sided limit order book whose dynamics are driven by the order book events. The identity of the trader can be either internalizing or regular, either a hedge fund or a brokery agency. The speed and cost of trading can be balanced by properly choosing active strategies on the displayed orders in the book and passive strategies on the hidden orders within the spread. We shall show that the price switching algorithms provide lower and upper bounds of the mixed trading algorithms. Especially, when the internalization premium is zero, an internalizing trader's optimal mixed trading strategy can be achieved among the set of price switching strategies. For both an internalizing trader and a regular trader, the optimal price switching strategy exists and is expressed in terms of the value function. A parallelizable algorithm to numerically compute the value function and optimal price switching strategy for the discretized state process is provided.
    Date: 2014–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1404.7320&r=cmp
  17. By: Lokman A. Abbas-Turki; Ioannis Karatzas; Qinghua Li
    Abstract: This paper solves a Bayes sequential impulse control problem for a diffusion, whose drift has an unobservable parameter with a change point. The partially-observed problem is reformulated into one with full observations, via a change of probability measure which removes the drift. The optimal impulse controls can be expressed in terms of the solutions and the current values of a Markov process adapted to the observation filtration. We shall illustrate the application of our results using the Longstaff-Schwartz algorithm for multiple optimal stopping times in a geometric Brownian motion stock price model with drift uncertainty.
    Date: 2014–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1404.1761&r=cmp
  18. By: Grzegorz Orynczak; Marcin Jakubek; Karol Wawrzyniak; Michal Klos
    Abstract: Adopting a zonal structure of electricity market requires specification of zones' borders. In this paper we use social welfare as the measure to assess quality of various zonal divisions. The social welfare is calculated by Market Coupling algorithm. The analyzed divisions are found by the usage of extended Locational Marginal Prices (LMP) methodology presented in paper [1], which takes into account variable weather conditions. The offered method of assessment of a proposed division of market into zones is however not limited to LMP approach but can evaluate the social welfare of divisions obtained by any methodology.
    Date: 2014–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1405.0878&r=cmp
  19. By: Ming Lin; Rong Chen; Per Mykland
    Abstract: Diffusion processes are widely used in engineering, fiance, physics and other fields. Usually continuous time diffusion processes are only observable at discrete time points. For many applications, it is often useful to impute continuous time bridge samples that follow the diffusion dynamics and connect each pair of the consecutive observations. The Sequential Monte Carlo (SMC) method is a useful tool to generate the intermediate paths of the bridge. Often the paths are generated forward from the starting observation and forced in some ways to connect with the end observation. In this paper we propose a constrained SMC algorithm with an effective resampling scheme that is guided by backward pilots carrying the information of the end observation. This resampling scheme can be easily combined with any forward SMC sampler. Two synthetic examples are used to demonstrate the effectiveness of the resampling scheme.
    Keywords: Stochastic diffusion equation, Sequential Monte Carlo, Resampling, Priority score, Backward pilot.
    Date: 2013–10–14
    URL: http://d.repec.org/n?u=RePEc:wyi:journl:002113&r=cmp
  20. By: Alexander W. Richter; Nathaniel A. Throckmorton
    Abstract: When monetary policy faces a zero lower bound (ZLB) constraint on the nominal interest rate, a minimum state variable (MSV) solution may not exist even if the Taylor principle holds when the ZLB does not bind. This paper shows there is a clear tradeoff between the expected frequency and average duration of ZLB events along the boundary of the convergence region---the region of the parameter space where our policy function iteration algorithm converges to an MSV solution. We show this tradeoff with two alternative stochastic processes: one where monetary policy follows a 2-state Markov chain, which exogenously governs whether the ZLB binds, and the other where ZLB events are endogenous due to discount factor or technology shocks. We also show that small changes in the parameters of the stochastic processes cause meaningful differences in the decision rules and where the ZLB binds in the state space.
    Keywords: Monetary policy; zero lower bound; convergence; minimum state variable solution; policy function iteration
    JEL: E31 E42 E58
    Date: 2014–05
    URL: http://d.repec.org/n?u=RePEc:abn:wpaper:auwp2014-09&r=cmp

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