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Sand in the Wheels or Wheels in the Sand? Tobin Taxes and Market Crashes

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  • Hynek Lavicka
  • Tomas Lichard
  • Jan Novotny

Abstract

The recent crisis revived interest in financial transaction taxes (FTTs) as a means to offset negative risk externalities. However, up-to-date academic research does not provide sufficient insights into the effects of transaction taxes on financial markets as the literature has here-to-fore been focused too narrowly on Gaussian variance as a measure of volatility. In this paper, we argue that it is imperative to understand the relationship between price jumps, Gaussian variance, and FTTs. While Gaussian variance is not necessarily a problem in itself, the non-normality of return distribution caused by price jumps affects not only the performance of many risk-hedging algorithms but directly influences the frequency of catastrophic market events. To study the aforementioned relationship, we use an agent-based model of financial markets. Its results show that FTTs may increase the variance while decreasing the impact of price jumps. This result implies that regulators may face a trade-off between overall variance and price jumps when designing optimal tax. However, the results are not robust to the size of the artificial market as non-linearities emerge when the size of the market is increased.

Suggested Citation

  • Hynek Lavicka & Tomas Lichard & Jan Novotny, 2014. "Sand in the Wheels or Wheels in the Sand? Tobin Taxes and Market Crashes," CERGE-EI Working Papers wp511, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Handle: RePEc:cer:papers:wp511
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    References listed on IDEAS

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    Cited by:

    1. Sandrine Jacob Leal & Mauro Napoletano, 2016. "Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High- Frequency Trading," Sciences Po publications 2016-12, Sciences Po.

    More about this item

    Keywords

    price jumps; financial transaction taxes; agent-based modeling; Monte Carlo; volatility;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies

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