Abstract—This paper analyzes the predictivity and return
performance of the Barmish-Iwarere feedback trading algo-
rithm described in [1]. In the first part of the paper, we study
the trade triggering algorithm using either an Ito process model,
or real data from indexes and ETFs. It is shown through
hypothesis testing that the trigger provides mixed results in
predicting the sign of the single trade, for both the Ito process
and real indexes. However, we show empirically that the trigger
is sufficiently good in identifying a trend, while it fails in
detecting side movements. In the second part of the paper,
we analyze the effect of controller parameters under various
market circumstances. The efficiency of a pre-optimization on
historical data appears controversial. Some modifications are
experimented, with the objective of improving the returns.
In particular, the trigger is modified to detect anomalous
falls during a rising trend using the estimated volatility. The
resulting system is then tested with other indexes, commodities
and interest rates.
Index Terms—Trading system; trigger; feedback controller;
long-short trades.
G. C. Calafiore, Professor, Dipartimento di Automatica e Informatica,
Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
giuseppe.calafiore@polito.it.
B. Monastero, PhD Student, Dipartimento di Automatica e Informatica,
Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
bruno.monastero@polito.it.
[PDF]
Cite:Giuseppe C. Calafiore and Bruno Monastero, "Triggering Long-Short Trades on Indexes," International Journal of Trade, Economics and Finance vol.1, no.3, pp. 289-296, 2010.