scholarly journals Developing sustainable trading strategies using directional changes with high frequency data

2017 ◽  
Author(s):  
Ailun Ye ◽  
V. L. Raju Chinthalapati ◽  
Antoaneta Serguieva ◽  
Edward Tsang
Keyword(s):  
High Frequency ◽  
Trading Strategies ◽  
High Frequency Data ◽  
Frequency Data

scholarly journals Retornos Anormais no Ibovespa Utilizando Modelos para Dados de Alta Frequência

2012 ◽  
Vol 10 (2) ◽  
pp. 243
Author(s):  
Nelson Ferreira Fonseca ◽  
Wagner Moura Lamounier ◽  
Aureliano Angel Bressan
Keyword(s):  
High Frequency ◽  
Historical Data ◽  
Abnormal Returns ◽  
Equity Markets ◽  
Trading Strategies ◽  
High Frequency Data ◽  
Var Model ◽  
Frequency Data ◽  
Forecasting Models ◽  
Better Than

This article aims to identify profitable trading strategies based on the effects of leads and lags between the spot and futures equity markets in Brazil, using high frequency data. To achieve this objective and based on historical data of the Bovespa and the Bovespa Future indexes, four forecasting models have been built: ARIMA, ARFIMA, VAR, and VECM. The trading strategies tested were: net trading strategy, buy and hold strategy, and filter strategy – better than average predicted return. The period of analysis of this paper extends from August 1, 2006 to October 16, 2009. In this work, it was possible to obtain abnormal returns using trading strategies with the VAR model on the effects of leads and lags between the Bovespa index and Bovespa Future index.

Forecasting Exchange Rate Realized Volatility Through Decomposition Using High-Frequency Data

2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug
Keyword(s):  
Exchange Rate ◽  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Frequency Data
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