Humans base typical everyday decisions on rules of thumb or mental shortcuts known as cognitive heuristics, rather than on deep and exhaustive analytical processing [1]. Cognitive heuristics most probably do come into play when people are faced with complex, difficult, uncertain or fast-to-make decisions for which they have no solid knowledge nor a concrete algorithm to apply [2]. Regarding the stock market, this paper analyzes selling decisions which are merely dependent on the initial buying prices of stocks in order to get insights into the flexibility of risk tolerance. We focused merely on the role of share prices, refraining from all other information usually considered and related with shares such as the volatility or the trading volume of the shares [3] the quality of products or services provided by the associated company, the previous share price performance, the brand value [4] or fundamental economic data such as the credit rating [5] or the growth of the company under scrutiny [6]. What qualities does the mere price of shares provide beside the simple fact that such a share costs less? For instance, “penny stocks”, also known as “microcap equities”, refer to shares which trade for a low amount of money, typically smaller than € 1 or $ 1, or, as an alternative definition, to a market cap of low value, e.g., approximately $50 million [7] Penny stocks, which are by definition thinly traded companies within illiquid markets [8] are known to be usual suspects for stock swindlers and trading manipulators [9], as they are often difficult to observe and are infrequently quoted. It is also known that shares become more volatile when they are split-which holds true even if microstructure biases are carefully controlled [10]. On the other side, high-priced shares are mostly called “blue chips”, commonly associated with high-quality and endurable companies. They offer much less volatility, much higher stability and are not so susceptible to easy stock swindling due to their mere size of market capitalization.
 
Nevertheless, as there is no standardized or initially standardized price of stock shares, the mere price does not evidently reflect the quality of the regarding company. Although it is true that many penny stocks refer to financially stricken enterprises which have lost market value and might provide higher inherent risks, they can also refer to the simple fact that the stock is assigned to more shares, for instance by a recent capital increase with “thinning out” the value of single shares. Comparable with free-traded currencies, there is no standardized price at the beginning of the history of a monetary system which can be used as a benchmark. Consequently, the stability, reliability or transparency of a currency cannot clearly be derived from the mere price of the standard unit- this is particularly the case for non-experts who cannot assess or interpret fiscal information on companies adequately. In this paper, we tried to answer the question, to what extent the investors’ investment decision is influenced by the initial share price and how the readiness to take higher risks is affected by pure price information.
 

he stocks list contained 60 fictive stocks represented by non-sense trigrammic names (three-letter codes) comparable with typical ticker codes (e.g., SRX, WDJ, VQE). Non-sense codes were used to minimize associations with concrete companies and the referring profitability of these companies. The stocks differed in terms of their pre-set, initial buying price: 20 of them ranged between 1.00 and 9.99 (exactly 1.45 and 9.80; this range is called “low”), 20 of them ranged between 10.00 and 99.99 (exactly 11.50 and 98.40; “medium”), the residuary 20 ranged between 100.00 and 999.99 (exactly 150.65 and 980.15; “high”). In this study, we made a deliberate decision against a fictive share prices sample ranged below 1.00 because we do not expect laymen or newcomers in the stock market to gain their first experiences with penny stocks. Great care was taken to only use so-called “precise prices”, e.g. 14.18 instead of 14.00, to circumvent potential precision effects [13] for which precise prices are practically handled as being of lower value than comparable round prices. To minimize confounding effects of different price level distributions among the ranges, the mean buying prices for each range was approximately set to the median for the referring range and the distribution of all ranges was normal. When prices were normalized by the lower value of the range, e.g. 100 for range high, the means did not differ from the means of each other range, ascertained by a factorial ANOVA with the between-items factor range (low, medium, high), F (2,57)<1, p=.8159, n.s. The treatment consisted of two different instructions aiming to evoke different risk behavior. In both instructions, our participants were told that they had invested 70,000 Euros in stocks. For instruction “hard work” the participants were additionally told that they have achieved this money through hard work, for instruction “legacy” the story was respectively worded as that they have achieved this money by a legacy from a close relative who had appointed them as their exclusive heir due to deep friendship (Table 1).

 Citation: Carbon CC, Schwarz ME (2014) The Share Price Neglect: Inverse Exponential Relation between Initial Share Price and Risk Tolerance. Int J Sch Cogn Psychol 1: 102. doi: 10.4172/ijscp.1000102

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