Title Calibration of bollinger bands parameters for trading strategy development in the Baltic Stock Market /
Translation of Title Bolingerio juostų metodo parametrų kalibravimas sudarant prekybos Baltijos šalių akcijomis strategiją.
Authors Kabasinskas, Audrius ; Macys, Ugnius
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Is Part of Inžinerinė ekonomika = Engineering economics.. Kaunas : Technologija. 2010, vol. 21, iss. 3, p. 244-254.. ISSN 1392-2785. eISSN 2029-5839
Keywords [eng] bollinger bands ; trading bands ; short term ; investment ; portfolio optimization ; parameter calibration ; Baltic stock market ; standard deviation ; moving average ; technical analysis
Abstract [eng] In recent decades there was a robust boom in investment sector in Lithuania, as more people chose to invest money in investment funds rather than keep money in the closet. The Baltic States Market turnover has increased from 721 MEUR in 2000 to 978 MEUR in 2008 (with peak 2603 MEUR in 2005). When difficult period appeared in global markets, a lot of attention was dedicated towards the managing of investments. Investment management firms in Lithuania gain significance in personal as well as in business section increasingly; even though these firms are considerably young (the first one in Lithuania was established in year 2000). Successful investment begins with the financial analysis of stock, asset or index, which you are going to invest. Professionals can be divided into two groups as far as this point is concerned: supporters of fundamental analysis and the supporters of technical analysis. Fundamental analysts try to determine a company’s value by looking at the balance sheet, cash flow statement and income statement. Technicians, on the other hand, assume that all these fundamentals are accounted for in the stock’s price and analyses charts of price movements and various indicators derived from the price and volume. Technical analysis suffered major criticism when Fama (1965) presented his efficient-market hypothesis (EMH), which states that past prices cannot be used to profitably predict future prices. However, many researches showed that EMH is not adequate in many aspects. With this background the “Quantitative Behavioral Finance” theory was introduced (see recent works of Gunduz Caginalp, Vernon Smith, David Porter, Don Balenovich, Vladimira Ilieva, Ahmet Duran, and Ray Sturm). This theory includes some topics of classical theories, but mainly it is based on behavioral analysis of market agents and helps to understand behavioral biases in conjunction with valuation. [...].
Published Kaunas : Technologija
Type Journal article
Language English
Publication date 2010
CC license CC license description