nep-cmp New Economics Papers
on Computational Economics
Issue of 2016‒01‒18
seven papers chosen by
Stan Miles
Thompson Rivers University

  1. Extended Abstract: Neural Networks for Limit Order Books By Justin Sirignano
  2. From spanning trees to arborescences: new and extended cost sharing solutions By Eric Bahel; Christian Trudeau
  3. The economic impact of the Russian import ban: A CGE analysis By Kutlina-Dimitrova, Zornitsa
  4. A detailed heterogeneous agent model for a single asset financial market with trading via an order book By Roberto Mota Navarro; Hern\'an Larralde Ridaura
  5. Systemic Risk Management in Financial Networks with Credit Default Swaps By Matt V. Leduc; Sebastian Poledna; Stefan Thurner
  6. Computing semiparametric bounds on the expected payments of insurance instruments via column generation By Robert Howley; Robert Storer; Juan Vera; Luis F. Zuluaga
  7. Taming Macroeconomic Instability: Monetary and Macro Prudential Policy Interactions in an Agent-Based Model By Lilit Popoyan; Mauro Napoletano; Andrea Roventini

  1. By: Justin Sirignano
    Abstract: We design and test neural networks for modeling the dynamics of the limit order book. In addition to testing traditional neural networks originally designed for classification, we develop a new neural network architecture for modeling spatial distributions (i.e., distributions on $\mathbb{R}^d$) which takes advantage of local spatial structure. Model performance is tested on 140 S\&P 500 and NASDAQ-100 stocks. The neural networks are trained using information from deep into the limit order book (i.e., many levels beyond the best bid and best ask). Techniques from deep learning such as dropout are employed to improve performance. Due to the computational challenges associated with the large amount of data, the neural networks are trained using GPU clusters. The neural networks are shown to outperform simpler models such as the naive empirical model and logistic regression, and the new neural network for spatial distributions outperforms the standard neural network.
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1601.01987&r=cmp
  2. By: Eric Bahel (Department of Economics, Virginia Polytechnic Institute and State University); Christian Trudeau (Department of Economics, University of Windsor)
    Abstract: The paper examines minimal cost arborescence problems, which generalize the well-known minimal cost spanning tree (mcst) problems. We propose a new family of cost sharing methods that are easy to compute, as they closely relate to the network-building algorithm. These methods, called minimal incoming cost rules for arborescences (MICRAs), include as a particular case the extension of the folk solution introduced by Dutta and Mishra (2012). A simpler computational procedure thus obtains for this method. We also provide new axiomatizations of (a) the set of stable and symmetric MICRAs and (b) the folk solution. Finally, we closely examine two remarkable MICRAs. The first one relates to the cycle-complete rule for mcst problems introduced in Trudeau (2012). The second one contrasts with the folk rule by fully rewarding agents who help others connect to the source.
    Keywords: arborescence problems; stable allocations, minimal incoming cost rules, leftover cost matrix
    JEL: C71 D63
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:wis:wpaper:1601&r=cmp
  3. By: Kutlina-Dimitrova, Zornitsa (DG Trade)
    Abstract: The aim of this paper is to assess the economic impact of the Russian embargo from 7 August 2014 on certain agricultural food products from the EU, the USA, Norway, Canada and Australia. The effects of this economic sanction are analysed in the framework of a computable general equilibrium (CGE) model with a particular focus on bilateral and total exports, production and welfare. The detailed, based on real trade data, calibration of the model allows for an exact identification of the sectoral shares and prohibitive tariffs aggregated to match the CGE model’s sectoral level of aggregation. In addition, the paper carries on a validation exercise to compare the model’s predictions with real trade data developments. The modelling simulation results show that the impact of the ban on total exports of the EU, the USA, Norway, Canada and Australia are limited. Total extra-EU exports decline by merely 0.12%. Nevertheless at a disaggregate level there are sectors – ‘vegetables and fruits’, ‘other meat’ and ‘dairy products’ – which experience two digit percentage change declines.
    Keywords: International trade; Agri-food embargo; CGE modelling; Russia
    JEL: F13 F17 Q17
    Date: 2016–01–07
    URL: http://d.repec.org/n?u=RePEc:ris:dgtcen:2015_003&r=cmp
  4. By: Roberto Mota Navarro; Hern\'an Larralde Ridaura
    Abstract: We present an agent based model of a single asset financial market that is capable of replicating several non-trivial statistical properties observed in real financial markets, generically referred to as stylized facts. While previous models reported in the literature are also capable of replicating some of these statistical properties, in general, they tend to oversimplify either the trading mechanisms or the behavior of the agents. In our model, we strived to capture the most important characteristics of both aspects to create agents that employ strategies inspired on those used in real markets, and, at the same time, a more realistic trade mechanism based on a double auction order book. We study the role of the distinct types of trader on the return statistics: specifically, correlation properties (or lack thereof), volatilty clustering, heavy tails, and the degree to which the distribution can be described by a log-normal. Further, by introducing the practice of profit taking, our model is also capable of replicating the stylized fact related to an asymmetry in the distribution of losses and gains.
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1601.00229&r=cmp
  5. By: Matt V. Leduc; Sebastian Poledna; Stefan Thurner
    Abstract: We study insolvency cascades in an interbank system when banks are allowed to insure their loans with credit default swaps (CDS) sold by other banks. We show that, by properly shifting financial exposures from one institution to another, a CDS market can be designed to rewire the network of interbank exposures in a way that makes it more resilient to insolvency cascades. A regulator can use information about the topology of the interbank network to devise a systemic insurance surcharge that is added to the CDS spread. CDS contracts are thus effectively penalized according to how much they contribute to increasing systemic risk. CDS contracts that decrease systemic risk remain untaxed. We simulate this regulated CDS market using an agent-based model (CRISIS macro-financial model) and we demonstrate that it leads to an interbank system that is more resilient to insolvency cascades.
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1601.02156&r=cmp
  6. By: Robert Howley; Robert Storer; Juan Vera; Luis F. Zuluaga
    Abstract: It has been recently shown that numerical semiparametric bounds on the expected payoff of fi- nancial or actuarial instruments can be computed using semidefinite programming. However, this approach has practical limitations. Here we use column generation, a classical optimization technique, to address these limitations. From column generation, it follows that practical univari- ate semiparametric bounds can be found by solving a series of linear programs. In addition to moment information, the column generation approach allows the inclusion of extra information about the random variable; for instance, unimodality and continuity, as well as the construction of corresponding worst/best-case distributions in a simple way.
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1601.02149&r=cmp
  7. By: Lilit Popoyan; Mauro Napoletano; Andrea Roventini
    Abstract: We develop an agent-based model to study the macroeconomic impact of alternative macro prudential regulations and their possible interactions with different monetary policy rules. The aim is to shed light on the most appropriate policy mix to achieve the resilience of the banking sector and foster macroeconomic stability. Simulation results show that a triple-mandate Taylor rule, focused on output gap, inflation and credit growth, and a Basel III prudential regulation is the best policy mix to improve the stability of the banking sector and smooth output fluctuations. Moreover, we consider the different levers of Basel III and their combinations. We find that minimum capital requirements and counter-cyclical capital buffers allow to achieve results close to the Basel III first-best with a much more simplified regulatory framework. Finally, the components of Basel III are nonadditive: the inclusion of an additional lever does not always improve the performance of the macro prudential regulation.
    Keywords: macro prudential policy; Basel III regulation; financial stability; monetary policy; agent-based computational economics
    Date: 2015–12–16
    URL: http://d.repec.org/n?u=RePEc:ssa:lemwps:2015/33&r=cmp

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