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Coherent Preferences and Price Reference Point Jumps in Stock Market (Poster Presentation)

From the viewpoint of rational decision making framework, individuals always trade stocks accordingly to the underlying fundamental value that can be derived by available information. According to such framework, stock returns follow a Brownian motion, implying random walks or no preferences. Contrary to those, empiric tests in judgment and decision making processes have exposed many violations of rational decision making theory. In fact, individuals are sensitive to gains and losses defined relatively to a reference point in behavioral economics and finance literature and this sensitiveness can show asymmetries between the negative and the positive sides of the utility function. However, it is a challenge to find the right way to determine individual preferences and beliefs outside laboratory and examine individual trading behaviors in stock market using high frequency trading data. In this paper, by analyzing the microstructure of an ETF price-volume distribution, we assume that boundedly-rational traders tend to engage in a price reversal process in narrow framing, which brings the stock price back to a level which is considered to be a reference point concerning to a behavioral assessment value. We assume also that individuals prefer to trade mostly at such point, and that they adapt to any prospect or outcome by assigning decision weights in the allocation of final trading wealth over a price range. We measure individual decision weights directly by using collective cumulative trading volume distribution over a price range and select the maximum volume price as the price reference point. We propose the hypothesis that individuals demonstrate coherent preferences in intraday trading in stock markets and we test such hypothesis by using a set of explicit models of non-linear coherent preferences against a large number of price-volume distributions, each of which is generated from an ETF intraday tick-by- tick high frequency trading data from the Chinese stock market. We confirmed the hypothesis as 82.42 percent of total price-volume distributions in our tests shows significantly coherent preferences. In addition, they update the reference point that jumps from time to time in intraday trading because a considerable number of price-volume distributions exhibit two maximum volume prices (11.92% of total distributions), generating a price mean return. Finally, we extend the models of coherent preferences to an explicit S-shaped value functions in prospect theory, suggesting potential applications in behavioral finance.

Market Microstructure, Coherent Preferences, Price-Volume Distribution, Narrow Framing, Reference Point, Jump, Decision Weight, Prospect Theory

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