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The Effect Of Past Price Patterns and Price Memory In Asset Markets: A Behavioral Hypothesis Test With Brazilian Young Investors Bernardo Fonseca Nunes.

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Presentation on theme: "The Effect Of Past Price Patterns and Price Memory In Asset Markets: A Behavioral Hypothesis Test With Brazilian Young Investors Bernardo Fonseca Nunes."— Presentation transcript:

1 The Effect Of Past Price Patterns and Price Memory In Asset Markets: A Behavioral Hypothesis Test With Brazilian Young Investors Bernardo Fonseca Nunes Post Graduation Program in Economics (PPGE) UFRGS - Brazil

2 Brazilian Stock Market Ibovespa Source:

3 Goals This work analyzes the power of Behavioral Finance to explain technical analysis use in buy-hold-sell decisions in financial asset management. Technical analysis is a financial markets technique that claims the ability to forecast the future direction of asset prices through the study of past market data, primarily price and volume. This method to evaluate stocks and bonds in capital markets is not predicted in conventional financial theories because other hypothesis conventionally assumed as Random Walk Hypothesis (MALKIEL, 1973) and Rational Expectations (MUTH, 1961), do not allow neither systematic deviations from fundamental prices nor any kind of price forecast using past trends or public information. Explore information Explore behavior Better “Model” Traditional Managers Behavioral Managers Quantitative Managers Fuller (2007, p.7) Sources of profitable strategies

4 Methodology This paper shows the results of an experiment performed in a sample of undergraduate Brazilian economics students with low experience in investment decisions. This sample was selected to reflect a relevant current part of Brazilian Stock Exchange (BOVESPA) which has presented, in 2007, a strong growth of participants with ages between 11 (eleven) and (30) thirty years old. Usually, technical analysis is the first step of young investors’ learning process. We replicate the first experimental treatment presented in Mussweiller and Schneller (2003), testing the salience effect promoted by extreme recent prices in individual asset pricing decisions. Technical Analysis example Mussweiller & Schneller (2003)

5 Methodology Behavioral finance identifies cognitive biases which have explanatory power about the observation of technical analysis as a decision tool for asset management. Hardcore research program do not accept technical analysis as an useful way to determine buy-hold-sell decisions and calls it pseudo-science. Behavioral finance and experimental economics allow us to understand the use of technical analysis by professional traders and individual investors through representativeness, confirmatory bias, selective thinking, self deception and communal reinforcement. Elster (1990), Kahneman & Miller (1986) and Mussweiller (2003): Human judgment is comparative in nature. Agents tend to make decisions comparing the situation with the most extreme recent events (Kahneman, 1999).

6 Experimental treatment Test the price chart pattern influence in individual asset pricing process. One session with undergraduate students from PUCRS/Brazil in Economics and Psychology class. Ages between 15 to 30 years old. Experience in investing or contact with financial affairs (Mean; SD) = (3,32; 6,21). Material: a stock buy-hold-sell recommendation distributed among participants in AD and BC information sets. Situation: a friend is planning to invest in 2 (two) possible stocks of the consume sector. Before him makes the decision, he asked an opinion from you about your expected target price in the next twelve months. You will receive information about the companies business and their past performance in the last twelve months. Information set A: Company 1 and salient high chart. Information set B: Company 1 and salient low chart. Information set C: Company 2 and salient high chart. Information set D: Company 2 and salient low chart.

7 Results Paired t test Difference between two groups means P-value = 0,0439, reject the null hypothesis with 95% confidence. HighLow Mean144,07135,77 SD19,8825,56 N47 P-value = 0,0820, reject the null hypothesis with 90% confidence.

8 Bernardo Fonseca Nunes MSN: bernardofn@hotmail.combernardofn@hotmail.com +55 (51) 3346 4164 Escola de Investidores –Porto Alegre – RS / Brazil Felipe Neri, nº 414, room 302 www.escoladeinvestidores.com.br Contact


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