[Форекс] The Cost of Technical Trading Rules in the Forex Market.pdf
(
595 KB
)
Pobierz
olsv14mt.dvi
The Cost of Technical Trading Rules in the Forex Market:
A Utility-based Evaluation
Hans Dewachter and Marco Lyrio
ERIM R
EPORT
S
ERIES
R
ESEARCH IN
M
ANAGEMENT
ERIM Report Series reference number
ERS-2003-052-F&A
Publication status / version
May 2003
Number of pages
31
Email address corresponding author
hdewachter@fbk.eur.nl
Address
Erasmus Research Institute of Management (ERIM)
Rotterdam School of Management / Faculteit Bedrijfskunde
Rotterdam School of Economics / Faculteit Economische
Wetenschappen
Erasmus Universiteit Rotterdam
PoBox 1738
3000 DR Rotterdam, The Netherlands
Phone:
# 31-(0) 10-408 1182
Fax:
# 31-(0) 10-408 9640
Email:
info@erim.eur.nl
Internet:
www.erim.eur.nl
Bibliographic data and classifications of all the ERIM reports are also available on the ERIM website:
www.erim.eur.nl
E
RASMUS
R
ESEARCH
I
NSTITUTE OF
M
ANAGEMENT
REPORT SERIES
RESEARCH IN MANAGEMENT
B
IBLIOGRAPHIC DATA AND CLASSIFICATIONS
Abstract
We compute the opportunity cost for rational risk averse agents of using technical trading rules in
the foreign exchange rate market. Our purpose is to investigate whether these rules can be
interpreted as near-rational investment strategies for rational investors. We analyze four di.erent
exchange rates and find that the opportunity cost of using chartist rules tends to be prohibitively
high. We also present a method to decompose this opportunity cost into parts related to investor’s
irrationality and misallocation of wealth. The results show that irrationality of chartist beliefs is an
important component of the total opportunity cost of using technical trading rules.
5001-6182
Library of Congress
Classification
(LCC)
Business
5601-5689
4001-4280.7
Accountancy, Bookkeeping
Finance Management, Business Finance, Corporation Finance
HG 4638
Technical analysis securities
Journal of Economic
Literature
(JEL)
M
Business Administration and Business Economics
M 41
G 3
Accounting
Corporate Finance and Governance
F 31
G 15
Foreign Exchange
International Financial Markets
European Business Schools
Library Group
(EBSLG)
85 A
Business General
225 A
220 A
Accounting General
Financial Management
220 T
Quantitative methods for financial methods
Gemeenschappelijke Onderwerpsontsluiting (GOO)
85.00
Bedrijfskunde, Organisatiekunde: algemeen
85.25
85.30
Accounting
Financieel management, financiering
Keywords GOO
85.33 Beleggingen
Bedrijfskunde / Bedrijfseconomie
Accountancy, financieel management, bedrijfsfinanciering, besliskunde
Effectenhandel, Beleggingen, wisselkoersen, Rationaliteit
Free keywords
technical trading rule, exchange rate
Classification GOO
The Cost of Technical Trading Rules in the Forex Market:
A Utility-based Evaluation
and Marco Lyrio
a
a
CES, Catholic University of Leuven
b
RIFM and ERIM, Erasmus University Rotterdam
Hans Dewachter
a,b∗
May 2003
Abstract
We compute the opportunity cost for rational risk averse agents of using technical trading
rules in the foreign exchange rate market. Our purpose is to investigate whether these rules
can be interpreted as near-rational investment strategies for rational investors. We analyze
four different exchange rates and
fi
nd that the opportunity cost of using chartist rules tends
to be prohibitively high. We also present a method to decompose this opportunity cost
into parts related to investor’s irrationality and misallocation of wealth. The results show
that irrationality of chartist beliefs is an important component of the total opportunity
cost of using technical trading rules.
Keywords: technical trading rule, exchange rate.
J.E.L.: F31, G15.
Corresponding author. Address: Center for Economic Studies, Catholic University of Leuven, Naamses-
traat 69, 3000 Leuven, Belgium. Tel: (+)32(0)16-326859, e-mail: hans.dewachter@econ.kuleuven.ac.be. We are
grateful for
fi
nancial support from the FWO-Vlaanderen (Project No.:G.0332.01). The latest version of this pa-
per can be downloaded from http://www.econ.kuleuven.ac.be/ew/academic/intecon/Dewachter/default.htm.
The authors are responsible for remaining errors.
∗
1In odu ion
Despite the numerous studies reporting the pervasive use of technical trading rules and their
pro
fi
tability,
1
there is still a considerable amount of scepticism in the academic literature
regarding their true value. Critics of chartist rules often point to the seemingly suboptimal
nature of the portfolio composition implied by these rules (e.g. Skouras, 2001). After all,
investment strategies based on technical trading rules (i) restrict the information set to a
narrow group of pre-de
fi
ned information variables, (ii) assume a positive relation of the signal
with future expected excess returns
2
, and (iii) imply a bang-bang type of investment strategy,
i.e. a strategy where all wealth is invested either short or long. Each of these assumptions
goes against the standard rational investor paradigm. The
fi
rst two assumptions possibly go
against the rationality of expectations formation, while the third is in general at odds with
the assumption of risk aversion.
In this paper, we assess the value of technical trading rules for rational risk averse investors.
The main motivation being that even if technical trading rules turn out to be suboptimal
rules, the observed practice of using these rules could still be near rational for a large class
of risk averse agents. More speci
fi
cally, if the cost (as measured, for instance, by certainty
equivalents) for risk averse agents of using technical trading rules is low, one may argue that
following these (irrational) rules of thumb may come close to the optimal trading strategy
and could, therefore, be rationalized in terms of information cost type of arguments.
The opportunity cost associated with the use of technical trading rules for risk averse
agents can be decomposed in two components: the
fi
rst component relates to the potential
error in the assumed relation between the chartist signal and the expected future return (ex-
pectational error); the second component originates from the suboptimality of the investment
strategy (allocation error). We present a simple method to compute each of these components.
The method involves the introduction of a hypothetical risk neutral agent. Risk neutral liq-
uidity constrained agents have in common with technical traders that investment strategies
will be typically bang-bang solutions, i.e. either invest all wealth in the long or in the short
side. In fact, as argued by Skouras (2001), as long as the chartist signal is one-to-one with
the expected future excess return, chartist trading strategies are equivalent to those of a ra-
tional risk neutral liquidity constrained agent. In this case, chartist rules are, therefore, also
rational. Differences in the trading positions of a risk neutral and a technical trader isolate,
therefore, the costs associated with expectational errors in the relation between the technical
trading signal and the expected return. The second cost component -associated with the
misallocation of wealth- can be recovered by contrasting the portfolio positions of risk averse
and risk neutral agents. Since both agents have identical expectations, the difference in their
trading positions can be linked to the costs of risk averse agents investing according to bang-
bang investment strategies. Combining these cost components results in a total opportunity
1
See, among others, Gençay (1999); LeBaron (1992, 1999, 2000); Neely et al (1997); and Taylor (1980).
2
We assume here a standardized rule where a positive (negative) technical trading signal corresponds to a
long (short) investment position.
2
cost for a rational risk averse agent of using technical trading rules. We use this technique
to identify possible classes of risk averse agents for which these opportunity costs are limited.
In this case, one could perhaps rationalize the use of trading rules in terms of near-rational
behavior.
Computing the costs of chartist trading rules implies both the identi
fi
cation of technical
trading signals and the design of a statistical model to relate the conditional moments of the
excess returns to the technical trading signal. In this paper, we restrict the analysis to the
class of moving average signals, or rules. We select this class as it constitutes the most widely
used class of technical trading rules in the foreign exchange market. These rules have also
been shown to be robust in their pro
fi
t generating capacities. We also opt for a relatively
simple model relating return moments to the trading signal. While more advanced techniques
such as the nonparametric regression technique of Brandt (1999), or nonlinear models such as
neural nets (Gençay, 1999) or Markov switching models (e.g. Dewachter, 2001) could be used,
we try to strike a balance between generality and computational costs. We, therefore, use a
regression approach to estimate possible time-varying parameters of a Taylor expansion of the
relation between return moments and trading signals. This approach is sufficiently
fl
exible
to allow for nonlinearities in the signal-return moment relation while at the same time it is
computationally tractable so as to allow for continuous updating of the parameters.
The remainder of the paper is organized in three main sections. In section 2, we discuss
the proposed decomposition of the costs associated with the use of technical trading rules.
The empirical results are presented in section 3. In this section, we
fi
rst analyze the statistical
models relating trading signals to return moments. We do
fi
nd evidence of a nonlinear relation
both for the expected return and for the conditional variance. Using these models to construct
the optimal portfolio rule for classes of risk averse agents, we subsequently analyze the value
of technical trading signals and the costs associated with following technical trading rule
strategies. We summarize the main
fi
ndings of the paper in the concluding section.
2 The opportunity cost of technical trading rules
Technical trading rules are typically rules of thumb that relate a certain information variable,
the technical trading signal, to a trading position. Denoting the time t technical trading signal
by z
t
, the technical trading rule speci
fi
es a mapping from the signal z
t
to an advised trading
position ω
CH
(z
t
) . A typical feature is the discontinuity in the mapping ω
CH
(z
t
).Weassume
that the trading signal has been standardized such that the trading rule, i.e. the mapping
from the signal to the trading position, can be described by:
b if z
t
> 0
ω
CH
(z
t
)=
0 if z
t
=0
(1)
−b if z
t
< 0
3
Plik z chomika:
Emas18
Inne pliki z tego folderu:
Dennis Relative Strength Index Futures Trading System.pdf
(2642 KB)
Effective Short Selling- Profiting in Bull and Bear Markets.pdf
(2966 KB)
Forex Hosting Metatrader 24 hours with VPS.pdf
(7567 KB)
day trading - complete ebook for trading stock futures forex options more than 100 ebooks must have for trader.rar
(161214 KB)
2 Forex Trading Strategy - Learn How To Day Tradeswing Trade Major Currency Pairs.pdf
(48576 KB)
Inne foldery tego chomika:
ebooki giełda, forex
FOREX_1
FOREX_3
FOREX_4
Zgłoś jeśli
naruszono regulamin