Vaasan yliopiston opinnäytteet

Kauppatieteellinen tiedekunta, 2012

Opinnäytteen kokoteksti
luettavissa vain
Tritonian työasemilla

Pentikäinen, Atte-Ville

Technical Analysis and Combined Signal Approach in Country-Specific ETF Markets

Ohjaaja/Valvoja (DI):
Janne Äijö
Kauppatieteiden maisteri
Laskentatoimi ja rahoitus
Rahoituksen linja
Master's Degree Programme in Finance
Tutkielman kieli:
According to the efficient market hypothesis, no fundamental or technical analysis strategy, formula, or system can earn a risk-adjusted rate of return that beats the market defined by a benchmark index. The technical approach to investment, on the other hand, is essentially a reflection of the idea that the systematic errors investors make due to behavioural biases are believed to be affecting the market prices and causing market inefficiencies. By studying the market itself, as opposed to its components, technical analysis attempts to exploit these inefficiencies and predict the future market movements.

The Combined Signal Approach rests on the notion that information related to future price movements is somewhat dispersed among many trading rules. The purpose of this thesis is to examine whether the ETF markets can be beaten with the use of combined signal strategies, and whether the combined signal strategies can produce more informative signals than single rule strategies.

Even though the results are suggesting that the markets cannot be beaten by a statistically significant margin with the tested rule combinations, the results are suggesting that the Combined Signal Approach in technical analysis can be utilized in ETF markets. There may not be a single strategy that can constantly outperform the market defined by a benchmark, since the actual models of technical analysis seem to differ across markets and through time, but with more informative signals the return possibilities are apparent. Monte Carlo simulation was used to determine the statistical significance of the results.
Technical analysis, exchange-traded funds, behavioural finance, market efficiency, Monte Carlo simulation, data mining
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