Are price limits on futures markets that cool? evidence from the brazilian merchantile & futures exchange

This paper investigates the impact of price limits on the Brazil- ian future markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. Our main finding is that price limits drive back prices as they approach the lower limit. There is a strong cool-off effect of the lower limit on the conditional mean, whereas the upper limit seems to entail a weak magnet effect on the conditional variance. We then build a trading strategy that accounts for the cool-off effect so as to demonstrate that the latter has not only statistical, but also economic signifi- cance. The resulting Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider.

Are price limits on futures markets that cool?: evidence from the Brazilian Mercantile and Futures Exchange

This paper investigates the impact of price limits on the Brazilian futures markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the S˜ao Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. The results indicate that the conditional mean features a floor cool-off effect, whereas the conditional variance significantly increases as the price approaches the upper limit. We then build a trading strategy that accounts for the cool-off effect in the conditional mean so as to demonstrate that the latter has not only statistical, but also economic significance. The in-sample Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider, whereas out-of-sample results evince similar performances.

Using consumer search cost and loyalty to explain dispersion in banking fees

Pode-se observar uma considerável dispersão entre os preços que diferentes bancos comerciais no Brasil cobram por um mesmo pacote homogêneo de serviços— dispersão esta que é sustentada ao longo do tempo. Em uma tentativa de replicar esta observação empírica, foi desenvolvido um simples modelo que lança mão do arcabouço da literatura de custos de procura (search costs) e que baseia-se também na lealdade por parte dos consumidores. Em seguida, dados de preços referentes ao setor bancário brasileiro são aplicados ao modelo desenvolvido e alguns exercícios empíricos são então realizados. Esses exercícios permitem que: (i) os custos de procura incorridos pelos consumidores sejam estimados, ao fixar-se os valores dos demais parâmetros e (ii) as correspondentes perdas de peso-morto que surgem como consequência dos custos de procura incorridos pelos consumidores sejam também estimadas. Quando apenas 80% da população é livre para buscar por bancos que cobrem menores tarifas, à taxa de juros mensal de 0,5%, o valor estimado do custo de procura médio incorrido pelos consumidores chega a 1805,80 BRL, sendo a correspondente perda de peso-morto média na ordem de 233,71 BRL por consumidor.