This article makes use of the apparent indifference that the market has been devoting to the developments made on the fundamentals of quantitative finance, to introduce novel insight for better understanding market evolution. We show how these drops and crises emerge as a natural result of local economical principles ruling tradesbetween economical agents and present evidence that heavy-tails of the return distributions are bounded by constraints associated with the topology of agent relations . Finally, we discuss how these constraints may be helpful for properly evaluate model risk.
We consider the evolution of scale-free networks according to preferential attachment schemes and show the conditions for which the exponent characterizing the degree distribution is bounded by upper and lower values. Our framework is an agent model, presented in the context of economic networks of trades, which shows the emergence of critical behavior. Starting from a brief discussion about the main features of the evolving network of trades, we show that the logarithmic return distributions have bounded heavy-tails , and the corresponding bounding exponent values can be derived . Finally, we discuss these findings in the context of model risk.
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This article makes use of
We consider the evolution of scale-free networks according to preferential attachment schemes and show the conditions for which the exponent characterizing the degree distribution is bounded by upper and lower values. Our framework is an agent model, presented in the context of economic networks of trades, which shows the emergence of critical behavior. Starting from a brief discussion about the main features of the evolving network of trades, we show that
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apparent indifference that the market has been devoting to the developments made on the fundamentals of quantitative finance, to introduce novel insight for better understanding market evolution. We show how these drops and crises emerge as a natural result of local economical principles ruling tradesbetween economical agents and present evidence that
logarithmic return distributions have bounded
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of the return distributions are bounded by constraints associated with the topology of agent relations
, and the corresponding bounding exponent values can be derived
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how these constraints may be helpful for properly evaluate
these findings in the context of