Computational Economics
http://lists.repec.org/mailman/listinfo/nep-cmp
Computational Economics2014-07-05Stan MilesA Comparison of Programming Languages in Economics
http://d.repec.org/n?u=RePEc:nbr:nberwo:20263&r=cmp
We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++11, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration with grid search, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and comment on the strength and weakness of each language.S. Borağan Aruoba, Jesús Fernández-Villaverde2014-06Rock around the Clock: An Agent-Based Model of Low- and High-Frequency Trading
http://d.repec.org/n?u=RePEc:gre:wpaper:2014-21&r=cmp
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 flash crashes. In the model, low-frequency agents adopt trading rules based on chronological 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.Sandrine Jacob Leal, Mauro Napoletano, Andrea Roventini, Giorgio Fagiolo2014-06Agent-based models, Limit order book, High-frequency trading, Low-frequency trading, Flash crashes, Market volatilitySimulation of Congestion Management and Security Constraints in the Nordic Electricity Market
http://d.repec.org/n?u=RePEc:hhs:nhhfms:2014_030&r=cmp
Presently in the Nordic day-ahead market, zonal pricing or market splitting is used for relieving congestion between a predetermined set of price areas. Constraints internal to the price areas are resolved by counter trading or redispatching in the regulation market. In a model of the Nordic electricity market we consider an hourly case from winter 2010 and present analyses of the effects of different congestion management methods on prices, quantities, surpluses and network utilization. We also study the effects of two different ways of taking into account security constraints.Bjørndal, Endre, Bjørndal, Mette, Gribkovskaia, Victoria2014-06-26Congestion management; Zonal pricing; Dayahead market simulationStock Market Prediction from WSJ: Text Mining via Sparse Matrix Factorization
http://d.repec.org/n?u=RePEc:arx:papers:1406.7330&r=cmp
We revisit the problem of predicting directional movements of stock prices based on news articles: here our algorithm uses daily articles from The Wall Street Journal to predict the closing stock prices on the same day. We propose a unified latent space model to characterize the "co-movements" between stock prices and news articles. Unlike many existing approaches, our new model is able to simultaneously leverage the correlations: (a) among stock prices, (b) among news articles, and (c) between stock prices and news articles. Thus, our model is able to make daily predictions on more than 500 stocks (most of which are not even mentioned in any news article) while having low complexity. We carry out extensive backtesting on trading strategies based on our algorithm. The result shows that our model has substantially better accuracy rate (55.7%) compared to many widely used algorithms. The return (56%) and Sharpe ratio due to a trading strategy based on our model are also much higher than baseline indices.Felix Ming Fai Wong, Zhenming Liu, Mung Chiang2014-06Finding The Nearest Valid Covariance Matrix: A Fx Market Case
http://d.repec.org/n?u=RePEc:hig:wpaper:32/fe/2014&r=cmp
We consider the problem of finding a valid covariance matrix in the FX market given an initial non-PSD estimate of such a matrix. The standard no-arbitrage assumption implies additional linear constraints on such matrices, which automat-ically makes them singular. As a result, one cannot just take the given estimate plug it into the standard optimization problem and solve it by applying even the most advanced numerical techniques developed recently. The reason is that such a problem is not well-posed while the PSD-solution is not strictly feasible. In order to deal with this issue, we described a low-dimensional face of the PSD cone that contains the feasible set. After projecting the initial problem onto this face, we come out with a reduced problem, which turns out to be well posed and of a smaller scale. We show that after solving the reduced problem the solution to the initial problem can be uniquely recovered in one step. We run numerous numerical experiments to compare performance of different algorithms in solving the reduced problem and to demonstrate the advantages of dealing with the reduced problem as opposed to the original one. The smaller scale of the reduced problem implies that virtually any numerical method can be applied effectively to find its solution.Aleksei Minabutdinov, Ilia Manaev, Maxim Bouev2014covariance matrix, correlation matrix, foreign exchangeA range based Multi-Actor Multicriteria Analysis to incorporate uncertainty in stakeholder based evaluation processes
http://d.repec.org/n?u=RePEc:hal:wpaper:hal-01010513&r=cmp
Increasing concerns about environmental and social impacts have made multicriteria analysis (MCA) increasingly popular in decision making processes. The present paper proposes a new methodology which allows taking into account multicriteria aspects, stakeholder's preferences and long time horizon uncertainty. Relying on the MAMCA methodology developed by Macharis in 2000, we develop a new decision making support tool, the range based MAMCA. Within MAMCA, the different possible solutions or alternatives are evaluated on the objectives of the stakeholders. These evaluations can be however uncertain as there might be a lack of knowledge, lack of experience or future predications might be uncertain. By means of Monte Carlo Simulation a range based MAMCA approach is developed to generate several possible states of the world. While a classical MCA would have provided a single final ranking, encouraging the support of an alternative, which can either be the best or the worst one depending on its performance uncertainty in the long run. The range based MAMCA provides a wide range of possible rankings depending on the many possible states of the world. Thus, it provides scorings, rankings of alternatives and the probability they will occur. The new approach is described and shown by means of an illustrative case: the stakeholder support for different biofuel options.Gino Baudry, Cathy Macharis, Thomas Vallée2014-06-19Multi-criteria analysis; decision making; multi-actor multi criteria analysis; uncertainty; sustainable development; Monte Carlo Simulation.What happens if in the principal component analysis the Pearsonian is replaced by the Brownian coefficient of correlation?
http://d.repec.org/n?u=RePEc:pra:mprapa:56861&r=cmp
The Brownian correlation has been recently introduced by Székely et al. (2007; 2009), which has an attractive property that when it is zero, it guarantees independence. This paper investigates into the effects and advantages, if any, of replacement of the Pearsonian coefficient of correlation (r) by the Brownian coefficient of correlation (say, ρ), other things remaining the same. Such a replacement and analysis of its effects have been made by the Host-Parasite Co-evolutionary algorithm of global optimization applied on six datasets.Mishra, Sudhanshu K2014-06-29Brownian correlation, Principal Component Analysis, Global Optimization, Host-Parasite Co-evolutionary algorithm, Iris Flower Dataset, 1985 Auto Imports Database, Levy distribution, outliersActive extension portfolio optimization with non-convex risk measures using metaheuristics
http://d.repec.org/n?u=RePEc:arx:papers:1406.7723&r=cmp
We consider the optimization of active extension portfolios. For this purpose, the optimization problem is rewritten as a stochastic programming model and solved using a clever multi-start local search heuristic, which turns out to provide stable solutions. The heuristic solutions are compared to optimization results of convex optimization solvers where applicable. Furthermore, the approach is applied to solve problems with non-convex risk measures, most notably to minimize Value-at-Risk. Numerical results using data from both the Dow Jones Industrial Average as well as the DAX 30 are shown.Ronald Hochreiter, Christoph Waldhauser2014-06World Input-Output Network
http://d.repec.org/n?u=RePEc:ial:wpaper:6/2014&r=cmp
Economic systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the multi-regional input-output (MRIO) tables at the global level. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods ows between industries, we study the network properties of the so-called world input-output network (WION) and document its evolution over time. We are able to quantify not only some global network properties such as assortativity, clustering coeficient, and degree and strength distributions, but also its subgraph structure and dynamics by using community detection techniques. Over time, we detect a marked increase in cross-country connectivity of the production system, only temporarily interrupted by the 2008-2009 crisis. Moreover, we find a growing input-output regional community in Europe led by Germany and the rise of China in the global production system. Finally, we use the network-based PageRank centrality and community coreness measure to identify the key industries and economies in the WION and the results are different from the one obtained by the traditional final-demand-weighted backward linkage measure.Federica Cerina, Zhen Zhu, Alessandro Chessa, Massimo Riccaboni2014-07Complex Networks; Input-Output; PageRank Centrality; Community DetectionIntraday Anomalies and Market Efficiency: A Trading Robot Analysis
http://d.repec.org/n?u=RePEc:diw:diwwpp:dp1377&r=cmp
One of the leading criticisms of the Efficient Market Hypothesis (EMH) is the presence of so-called "anomalies", i.e. empirical evidence of abnormal behaviour of asset prices which is inconsistent with market efficiency. However, most studies do not take into account transaction costs. Their existence implies that in fact traders might not be able to make abnormal profits. This paper examines whether or not anomalies such as intraday or time of the day effects give rise to exploitable profit opportunities by replicating the actions of traders. Specifically, the analysis is based on a trading robot which simulates their behaviour, and incorporates variable transaction costs (spreads). The results suggest that trading strategies aimed at exploiting daily patterns do not generate extra profits. Further, there are no significant differences between sub-periods (2005-2006 - "normal" , 2007- 2009 - "crisis" , 2010-2011 - "post-crisis).Guglielmo Maria Caporale, Luis Gil-Alana, Alex Plastun, Inna Makarenko2014Efficient Market Hypothesis, intraday patterns, time of the day anomaly, trading strategy