DYNAMIC STOCK RETURN–VOLUME RELATION: EVIDENCE FROM EMERGING ASIAN MARKETS

This paper empirically examines the dynamic stock return–volume relations for six emerging Asian markets: Indonesia, Malaysia, Singapore, South Korea, Taiwan, and Thailand. Evidence is found that trading volume Granger causes stock return in quantiles and the causal effects of volume are heterogeneous across quantiles. This shows that volume carries some information to the return and could be interpreted in light of theoretical models. In addition, we find that there is bi‐directional causality between stock return and trading volume in most of the markets. The finding indicates that those Asian emerging markets with different institutions and information flows than more mature markets have present similar causal effects on the stock return–volume relation. Furthermore, the cross‐country evidence shows that the US market helps to predict the returns of the emerging Asian markets.     

Incomplete Information, Trading Costs and Cross‐autocorrelations in Stock Returns

This paper provides an economic rationale for the cross‐autocorrelation patterns in stock returns in the context of a microstructure model in which investors have incomplete information. The paper shows that in a market in which investors are informed about only a sub‐set of stocks, the emergence of lead‐lag, cross‐autocorrelations is a function of the cost of trading in other stocks based on information about the sub‐set of stocks. If cross‐trading costs are high, informed investors will trade only in the sub‐set of stocks they are informed about; if cross‐trading costs are moderate, informed investors will randomize between trading and not trading in other stocks; and if cross‐trading costs are low, they will trade in all stocks. When informed investors trade only in a sub‐set of stocks, prices of stocks with more informed trading will adjust to common factor information faster than the prices of stocks with less informed trading giving rise to asymmetric lead‐lag cross‐autocorrelations. When informed investors trade in all stocks, asymmetric lead‐lag cross‐autocorrelations will disappear as a result of their cross‐market arbitrage trading. These results provide a number of testable implications for lead‐lag cross‐autocorrelation patterns. The data is consistent with the empirical predictions .
(J.E.L.G12, G14).     

Dynamic probability of informed trading and price movements: evidence from the CSI300 index futures market

This article first uses dynamic probability of informed trading (DPIN) for measuring the probability of informed trading in the CSI300 index futures market and proves its validity for predicting future price movements. Instead of using the original Lee–Ready algorithm, this study uses bulk volume classification (BVC) for classifying volume. BVC could effectively improve the predictive power of DPIN for future price movements. The relationship between DPIN and returns indicates that informed buying raises the futures price while informed selling moves the futures price downward. DPIN could effectively capture price information in the index future markets in China.     

Dynamic relationship between stock market trading volumes and investor fear gauges movements

This article applies multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) to investigate cross-correlation behaviours between two kinds of stock markets trading volumes and investor fear gauges covering the data of U.S. stock markets from 2 January 2004 to 31 July 2018. The empirical results show that the dynamic relationship between stock markets trading volume fluctuations and different kinds of investor fear gauges are multifractal and find that the dynamic relationship is strongly anti-persistent. Moreover, financial crisis in 2008 has a significant impact on the cross-correlated behaviour, suggesting that stock market trading volume fluctuations and investor fear gauges are more susceptible to each other during the financial crisis period. Through the rolling windows analysis, we also find that the stock markets trading volume fluctuations and different kinds of investor fear gauges are anti-persistent dynamic cross-correlated.     

The anatomy of returns from moving average trading rules in the Russian stock market

This paper examines the profitability of index trading strategies that are based on dual moving average crossover (DMAC) rules in the Russian stock market over the 2003–2012 period. It contributes to the existing technical analysis (TA) literature by comparing for the first time in emerging markets the relative performance of individual stocks’ trading portfolios with that of trading strategies for the index that consists of the same stocks (i.e., the most liquid stocks of the Moscow Exchange). The results show that the best trading strategies of the in-sample period can outperform buy-and-hold strategy during the subsequent out-of-sample period, although with low statistical significance. In addition, we document the benefits of using DMAC combinations that are much longer than those employed in previous TA literature. Moreover, the decomposition of the full-sample-period performance into separate bull- and bear-period performances shows that the outperformance of the best past index trading strategies over is mostly attributable to the fact that they managed to stay mostly out of the stock market during a dramatic crash caused by the global financial crisis.     

我国证券市场正反馈交易的实证检验

正反馈交易是投资者依据证券t-1期收益高低决定其第t期买卖行为的一种交易策略,这种交易策略广泛存在于世界各国的证券市场中,使证券市场表现出超常的波动性。本文使用上证指数和深证指数对我国证券市场的正反馈交易进行了实证研究,结果显示我国证券市场同样存在显著的正反馈交易现象,这种现象降低了市场的稳定性。     

Is the corn futures market noisier? The impact of high frequency quoting

ABSTRACT

The paper pioneers research on high frequency (HF) quoting noise in electronically traded agricultural futures markets. HF quoting – quickly cancelling posted limit orders and replacing them with new ones – emerges as a strategy for liquidity-providing traders. HF quoting can generate noise in price quotes which adds uncertainty to order execution and impairs the informational value of bid and ask prices. It can also lead to the perception that markets cannot be trusted for commercial transactions. Using intraday Best Bid Offer data for 2008–2013 and wavelet-based measures of volatility, we investigate the excess variance and co-movement discrepancies in the bid and ask prices. We find excess HF quoting variance exists. It is the highest at 250-ms scale – 90% higher than the variance implied by a random walk – but declines quickly to 7% at the 32 s scale. But its economic magnitude is negligibly small. Bid and ask price co-movements show a low degree of discrepancy with average correlations at 0.67 at 250 ms and reaching 0.95 at 8 s. All measures indicate that HF quoting noise has declined through the period. Overall, HF quoting has not caused excess variance during the transition to electronic trading in the liquid corn futures market.     

The revenue potential of a financial transaction tax for US financial markets

This paper estimates the revenue potential of a financial transaction tax (FTT) for US financial markets. We focus on analyzing the revenue potential of the Inclusive Prosperity Act that was introduced in the US House of Representatives in 2012 and the US Senate in 2015. The tax rates stipulated in this Act include 0.5% (50 basis points (bps)) for all stock transactions, 0.1% (10 bps) for all bond transactions and 0.005% (0.5 bps) on the notional value of all derivative trades. We examine three sets of evidence to generate potential revenue estimates: 1) the levels of transaction costs in US financial markets over time and within the range of financial market segments; 2) the extent of trading elasticities under various trading conditions; and 3) the current level of trading activity in US financial markets. Based on this evidence, we conclude that a US FTT operating at the tax rates stated above would generate about $220 billion per year, equal to about 1.2% of the current US GDP.     

Price Limits, Information Acquisition, and Bid–ask Spreads: Theory and Evidence

A number of futures markets use price limits which, in effect, preclude trade from occurring at prices outside certain exogenous bounds. Noting that such markets are characterized by heterogeneously informed traders, whereas previous work on price limits assumes symmetrically informed traders, we examine the effects of price limits in a setting where market participants are asymmetrically informed. We find that imposing price limits generally lowers the quality of information acquired in equilibrium, but lowers bid–ask spreads as well. Thus, depending on the relative weights placed by society on liquidity versus price efficiency, there may exist a set of price limits that are most efficient in achieving a trade-off between liquidity and informational efficiency. We perform empirical tests of some implications of the model using cross-sectional data on price limits. We find that price limits are strongly negatively related to both price volatility and trading volume. Though other explanations for our empirical findings cannot be ruled out, these results are not inconsistent with the model's implication that price limits should be tighter for contracts which offer greater profit potential for informed traders.     

Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.     

On the Use of the Moving Average Trading Rule to Test for Weak Form Efficiency in Capital Markets

The examination for the possible existence of predictive power in the moving average trading rule has been used extensively to test the hypothesis of weak form market efficiency in capital markets. This work focuses mainly on the study of the variation of the moving average (MA) trading rule performance as a function of the length of the longer MA. Empirical analysis of daily data from NYSE and the Athens Stock Exchange reveal high variability of the performance of the MA trading rule as a function of the MA length and on some occasions the series of successive trading rule total returns is non‐stationary. These findings have direct implications in weak form market efficiency testing. Indeed, given this high variability of the performance of the MA trading rule, by just finding out that trading rules with some specific combinations of MA lengths can or cannot beat the market, as is the case in most of the published work thus far, is not enough evidence for or against the existence of weak form market efficiency. Results also show that on average in about three out of four cases trading rule signals are false, a fact that leaves a lot of space for improved trading rule performance if trading rule signals are combined with other information (e.g. filters, or volume of trade). Finally, some evidence of enhanced trading rule performance for the shorter MA lengths was found. This enhanced performance is partly attributed to the higher probability that a trading rule signal is not a whipsaw, as well as to the larger number of days out‐of‐the‐market which are associated with shorter MA lengths.     

Overconfidence and Bubbles in Experimental Asset Markets

This paper investigates the relationship between market overconfidence and occurrence of stock-price bubbles. Sixty participants traded stocks in 10 experimental asset markets. Markets were constructed on the basis of subjects' overconfidence: The most overconfident subjects form high overconfidence markets and the least overconfident subjects low overconfidence markets. Prices in low overconfidence markets tend to track the fundamental asset value more accurately than prices in high overconfidence markets and are significantly lower and less volatile. Additionally, we observe significantly higher bubble measures and trading volume in high overconfidence markets. Two possible explanations for these differences are analyzed: While price expectations are significantly higher in high overconfidence markets, no differences in the average degree of risk aversion were detected.     

Private information and its origins in an electronic foreign exchange market

We study the risk of informed trading in an electronic foreign exchange market and test whether informed trading is driven by marketwide private information. Our framework is based on a structural microstructure trade model that measures the market makers' beliefs directly. Evidence of high concentration of informed trades is found to be inversely related to the overall 24-hour trading activity, i.e., early morning and late afternoon GMT rounds of trading involve the highest risk of informed trading. We structurally identify that the trades due to region-specific private information are dominant and explain between 5 and 25% of the variation in currency returns. In contrast, marketwide private information explains only about 1–5% of the variation in returns.     

Intraday trade in dealership markets

We develop and test a structural asymmetric information transaction model to characterize the price impact of information when markets are thin. Since orders are accepted individually, the model allows for transaction costs and brokerage fees. Equilibrium demands mixed entry strategies on the part of potentially informed traders. Estimation of the structural parameters is performed using a maximum likelihood procedure on NYSE data. The structural model is rejected primarily because the nonlinear restrictions do not allow for sufficient correlation between price movements and pricing errors. This leads to unreasonably low estimates of the probability of informed trade relative to an unrestricted alternative. The price impact of information is found to be positive and significant, but economically small. This is because although the amount of private information is substantial, the quality of the information signals is poor, particularly in the middle of the trading day. Informed agents do not trade small quantities, which suggests that their ability to divide orders is limited by transaction costs.     

Effects of electronic trading on the Hang Seng Index futures market

This investigation of the switch from open-outcry trading to electronic trading on the Hang Seng Index (HSI) futures contract reveals that the bid–ask spread narrows and the futures price plays more of a role in information transmission. Factors, such as anonymity in trading and fast order execution in electronic trading, attract informed traders to the futures market, enhancing the information flow. Our results provide support for the worldwide trend of transforming open-outcry markets into electronic trading platforms.     

PERIODIC,COMPLETE‐PARTICIPATION TRADE IN THE LAGOS‐ROCHETEAU MODEL

This paper contributes to a recent policy discussion regarding the costs and benefits of setting up a centralized electronic trading platform to replace over‐the‐counter (OTC) markets. We modify the Lagos and Rocheteau (2009, henceforth LR) asset trading model by replacing their investor‐dealer random matching and bilateral trade with a centralized competitive market that opens periodically. This arrangement preserves the main tension and trade‐off in LR. We then analyse and quantify when to introduce a centralized market and how frequently it should open in order to make it as efficiently as the decentralized OTC market in LR.     

Market concentration and competition in OECD mobile telecommunications markets

This study analyses the progress of market concentration in OECD member states’ mobile telecommunications markets and evaluates the relationship between market concentration and performance. Using annual panel data from 24 OECD member states for the 1998–2011 period, the study estimates regression equations for market concentration, mobile prices and profits. The empirical results indicate that the more concentrated the mobile market, the higher the prices and profits, providing support for the market power hypothesis. If this hypothesis holds, then market concentration can be a useful indicator of market performance. On the other hand, the applicability of the hypothesis is unclear for the second half of the sample period. The results provide evidence that regulatory policies influence the structure and performance of mobile markets.     

The Effect of Confidence in Valuation Estimates on Arbitrager Behavior and Market Prices

The authors develop a complete framework for optimizing trading decisions that incorporates investors' confidence in their valuation estimates. Quantified estimates of arbitragers' uncertainty about their appraisals of asset values are shown to be extractable from market prices alone. An empirical investigation over the 1977–2015 interval indicated that confidence levels exhibit persistence subject to mean reversion, with a positive relationship found with the magnitude of existing mispricings. Higher returns are discovered to long (short) arbitrage of an asset, whose intrinsic value is higher (lower) than the market price, after rises in uncertainty among informed investors.     

Marketmaking in the Laboratory: Does Competition Matter?

This paper is the first experimental study of the effects of competition and adverse selection on the performance of market maker (MM-) markets. Information distribution may is either symmetric or heterogeneous. MM-markets are either monopolistic (the specialist markets), or competitive (the multi MM-market). Welfare comparisons are with respect to a continuous double auction (DA-) market. Informed subjects receive an imperfect signal of the true state of the world. We find three main results. First, competition among market makers significantly reduces the bid-ask spread, and increases transaction volume. Second, competition among market makers induces competitive undercutting, yielding net trading losses for market makers as a group in most periods. Third, from the perspective of uninformed traders, a competing MM-regime is optimal, since it minimizes their expected trading losses.     

INFORMATION AND PRICE DISPERSION: THEORY AND EVIDENCE

Limited information is the key element generating price dispersion in models of homogeneous-goods markets. We show that the global relationship between information and price dispersion is an inverse-U shape. We test this mechanism for the retail gasoline market using a new measure of information based on commuter data from Austria. Commuters sample gasoline prices on their commuting route, providing us with spatial variation in the share of informed consumers. Our empirical estimates are in line with the theoretical predictions. We also quantify how information affects average prices paid and the distribution of surplus in the gasoline market.