گزینه های دیجیتالی و بهره وری در بازارهای سرمایه تجربی

In asset markets, extraordinary price run-ups (bubbles) followed by crashes back to levels closer to fundamental values have been shown to adversely affect the real economy, leading to inefficient resource allocation and underinvestment. Conversely, derivative markets contribute to price discovery and lead to informationally more efficient prices in the market for the underlying asset. We combine these observations and test experimentally whether digital options – a type of derivative that has recently been introduced to a wider audience via online prediction markets – can reduce price bubbles in a laboratory setting. We find that subjects do not use the derivative market to improve their expectations of future asset prices and analyze this result.

The research question underlying this article is motivated by three loosely related topics in financial economics. The first of them is the propensity of market prices to sometimes exhibit extraordinary run-ups (bubbles) followed by crashes back to levels closer to fundamental values. This phenomenon has been documented as early as after the disintegration of the tulip price bubble in the Netherlands in 1637 or the plunge in stock prices of the South Sea Company in the UK in 1720. In the last century, the Great Depression in the 1930s clearly demonstrated the danger that spillover effects from price bubbles in financial markets pose for the underlying real economy. The global financial crisis following the crash of a price bubble in U.S. real estate prices in 2007 forms another example that is and will continue to be subject to intense analysis in the coming years. Bubble-and-crash patterns in financial market prices are widely considered harmful to economic activity in general, since they cause a misallocation of available resources to non-optimal uses. As a case in point, Gan (2007) documents how the adverse liquidity shock experienced by Japanese banks in the early 1990s led to reduced lending, which in turn had significant repercussions on both the real investments and the performance of capital-deprived Japanese firms. His study showcases an indirect transmission channel from asset market bubbles to the real economy, underlining the possible efficiency gains to be had from a better understanding of the bubble phenomenon. The second strand of research impacting on our work saw its beginnings in the 1970s. Cox (1976) was one of the earliest articles to model the link between futures trading and the information processing taking place in the formation of spot market prices. Since then, an extensive branch of literature has been devoted to the connection between the trading of forwards, futures and options, and its impact on the informational efficiency of the market price of the underlying asset. Both theoretical and empirical studies have shown that derivative markets generally process information earlier and faster than spot markets and that the creation of a derivative market to accompany a spot market usually leads to higher price efficiency in the latter.1 One explanation for this effect is proposed by Figlewski and Webb (1993), who reason that options give traders who cannot or will not engage in short sales due to e.g. transaction costs, an opportunity to sell short indirectly. The final component motivating our research is the emergence of a new type of online marketplace permitting the trading in digital options. Prediction markets and online betting sites like betonmarkets.com, binarybet.com, intrade.com, ladbrokes.com, and mybet.com (among others) are relatively new ventures which allow investors to trade cash-or-nothing (digital) options on financial market prices. A cash-or-nothing option returns a fixed cash amount in the case that it expires in the money and nothing if it expires out of the money. These options are sometimes referred to as ‘binary bets’ in markets outside the lab and are being marketed as being easier to understand than conventional bets (cp. Oliver, 2007). The sites mentioned above have in common that there are low barriers to entry and that trades can be initiated with relatively small investment volumes and transaction costs. Our article brings together the above three pieces of motivation. It aims at providing evidence regarding the question of whether the adverse effects of price bubbles in financial markets can be reduced if markets are provided with the forward-looking price information from digital option markets. We attempt to uncover the effects of giving traders an opportunity to trade digital options under the controlled conditions of a laboratory experiment. The design we employ is a modification of the experimental double auction asset market introduced in Smith et al. (1988). The rest of this article is structured as follows: Section 1 discusses some background issues and develops our hypotheses. Section 2 then introduces our experimental design. Section 3 reports the results of our experiments and provides a brief comparison with previous results from the literature. Section 4 concludes the paper and proposes possible future research questions. An appendix is provided in Appendix A.

In this article, we report the results of double auction stock market experiments in line with Smith et al. (1988), augmented by the possibility of trade in an option market. Our hypothesis was that trading in the option market induces subjects to form expectations about future prices at an early point in the experiment and to use these expectations to derive a spot price expectation closer to fundamental value by backward induction. We find no support for our hypothesis, as the extent and form of the observed stock price bubbles are comparable to those of earlier baseline experiments documented in the literature. We analyze the trading behavior in the stock and option markets and report some preliminary attempts to explain this finding, which are grounded in the bounded rationality of traders. A trader classification as proposed in Haruvy and Noussair (2006) supports the conjecture that a majority of traders does not (sufficiently) condition on fundamental value in their trading decisions for the bubble-and-crash pattern to be attenuated. In line with findings by Haruvy et al. (2007), traders in our markets seem to converge to efficient prices only through a process of myopically adapting their expectations based on observed price patterns in the past. There is a disconnect between our results, which indicate no improvement in informational market efficiency in the presence of digital options, and many other studies that find increased efficiency in spot markets which are complemented by standard options and particularly futures. The reason may lie in the specific form of derivative employed. Future contracts (and standard option contracts, conditional on the future price) imply that buyers take possession of the stock, while sellers have to buy the stock before or at the maturity date, which provides the means for hedging and arbitrage. Due to their trinary payoff pattern, hedging with digital options is hardly feasible. There thus seems to be a trade-off in that digital options may attract more diverse market participants due to their simplicity, yet on the other hand do not provide information of the same quality as standard derivative contracts due to the less direct link between their price and that of the underlying asset.25 Furthermore, the discontinuous payoff structure also increases incentives to manipulate the price of the underlying asset around the maturity date where this is possible. Based on these two findings from our experiments, we caution against placing too much faith in the ability of prediction markets using this type of derivative to induce an increase in spot market price efficiency. This is particularly true in markets where participants have the ability to influence the value of the underlying to a significant degree (as is for example often the case in prediction markets within companies). It is an open – but interesting – question, whether standard options would perform better at increasing informational efficiency in the Smith et al. (1988) market design.