Details

Autor(en) / Beteiligte

• Papaioannou, Panagiotis
• Dionysopoulos, Thomas
• Russo, Lucia
• Giannino, Francesco
• Janetzko, Dietmar
• Siettos, Constantinos

Titel

S&P500 Forecasting and trading using convolution analysis of major asset classes

Ist Teil von

• Procedia computer science, 2017, Vol.113, p.484-489

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2017

Link zum Volltext

Quelle

Elsevier ScienceDirect Journals Complete

Beschreibungen/Notizen

• By monitoring the time evolution of the most liquid Futures contracts traded globally as acquired using the Bloomberg API from 03 January 2000 until 15 December 2014 we were able to forecast the S&P 500 index beating the “Buy and Hold” trading strategy. The proposed approach is a trend following trading strategy based on convolution computations of 42 of the most liquid Futures contracts of four basic financial asset classes, namely, equities, bonds, commodities and foreign exchange. Simulations provide empirical evidence of directional predictability of the S&P500 Index, thus enhancing the financial assets’ forecasting toolkit of quantitative trading academics and professionals.