School of Business, East China University of Science and Technology, Shanghai, China.
PLoS One. 2011;6(9):e24391. doi: 10.1371/journal.pone.0024391. Epub 2011 Sep 14.
We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions, and (iii) real traders to random strategies with respect to timing that share otherwise all other characteristics. We find in general that more trading results in smaller net return due to trading frictions, with the exception that the net return is independent of the trading frequency for A-share individual traders. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by traders. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.
我们提出了一组新的经验事实，用于量化金融市场的结构。关键思想是研究投资策略和价格的组合结构，以便对金融和经济市场有一个定性的新的理解水平。我们研究了中国深圳证券交易所 2003 年全年的详细订单流。这个巨大的数据集使我们能够比较（i）一个封闭的国内市场（A 股）和一个国际市场（B 股），（ii）个人和机构，以及（iii）实际交易员相对于其他所有特征相同的随机策略的交易时机。我们发现，由于交易摩擦，更多的交易通常会导致净回报降低，但 A 股个人交易员的交易频率与净回报无关。我们发现了具有非平凡指数的定量幂律，这些定律量化了策略使用的频率和持有期对性能的恶化。随机策略的表现明显优于实际策略，无论是对于赢家还是输家。存在令人惊讶的大的套利机会，尤其是使用零智能策略时。这是这些金融市场可能存在低效的一个诊断。
