从光大“乌龙指”事件看高频交易监管

随着电子化交易的发展,高频交易在证券市场中的运用越来越多。高频交易在增加流动性的同时,也因技术故障等问题造成证券市场价格剧烈动荡,这引发了人们的争论,即是否需要对高频交易进行限制。高频交易虽然带来了流动性,但是技术故障引发市场波动,量化交易的助涨助跌,更是会引发崩盘的系统性风险。因此,限制高频交易具有正当性。光大"乌龙指"事件,是我国首例因为技术故障引发的极端事件,应该借此机会反思,建立熔断机制、异常交易的处理规则和法律制度。     

Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures

The increasing volume of messages sent to the exchange by algorithmic traders stimulates a fierce debate among academics and practitioners on the impacts of high-frequency trading (HFT) on capital markets. By comparing a variety of regression models that associate various measures of market liquidity with measures of high-frequency activity on the same dataset, we find that for some models the increase in high-frequency activity improves market liquidity, but for others, we get the opposite effect. We indicate that this ambiguity does not depend only on the stock market or the data period, but also on the used HFT measure: the increase of high-frequency orders leads to lower market liquidity whereas the increase in high-frequency trades improves liquidity. We hypothesize that the observed decrease in market liquidity associated with an increasing level of high-frequency orders is caused by a rise in quote volatility.     

Multiple duration analyses of dynamic limit order placement strategies and aggressiveness in a low-latency market environment

This study examines dynamic order placement strategies in a low-latency environment together with limit orders' aggressiveness by a new approach which utilises survival analysis with a multiple-spell duration model. Two samples are considered, including the period immediately followed Australian Securities Exchange (ASX)’s migration to Integrated Trading System (ITS) and the period subsequent to the launch of ASX Trade. We find the evidence supporting both the ‘cost of immediacy hypothesis' and the ‘chasing hypothesis' as in Hasbrouck and Saar (2009). Furthermore, several distinctions in the results are found between the samples of ITS period and ASX Trade period as well as between the samples of small-cap stocks and large-cap stocks. The findings of this study are beneficial not only for high-frequency traders in forming dynamic order placement strategies in a low-latency stock market environment, but also for market regulators in helping their attempt to improve regulations for stock exchanges.     

Trading activity,dealer concentration and foreign exchange market quality

We study the relation between foreign exchange market quality and both trading activity and dealer concentration by considering two currency pairs with significant differences along both dimensions – the Euro–US dollar and Canadian dollar–US dollar. A variance ratio test reveals over-reaction in currency prices, but that this is smallest when trading activity is high and dealer concentration at its peak. A GARCH model shows that over-reaction declines as trading activity and dealer concentration increase, with the results being stronger for the Euro. Our results confirm that trading activity is an important determinant of market quality, but also point to a significant role for dealer concentration.     

The diversity of high-frequency traders

The regulatory debate concerning high-frequency trading (HFT) emphasizes the importance of distinguishing different HFT strategies and their influence on market quality. Using data from NASDAQ-OMX Stockholm, we compare market-making HFTs to opportunistic HFTs. We find that market makers constitute the lion's share of HFT trading volume (63–72%) and limit order traffic (81–86%). Furthermore, market makers have higher order-to-trade ratios and lower latency than opportunistic HFTs. In a natural experiment based on tick size changes, we find that the activity of market-making HFTs mitigates intraday price volatility.     

Time to Slow Down for High-Frequency Trading? Lessons from Artificial Markets

In this paper, we focus on the French cancel order tax implemented on 1 August 2012. We question the effectiveness of the modified tax with no exemptions and we analyze its impact on market quality, measured by liquidity, volatility and efficiency. Additionally, this paper raises the question whether this tax leads to a reduction of high-frequency trading (HFT) activities and a decline in trading volume. Based on our findings we report that introduction of cancel order tax only slightly reduces HFT activities, but it significantly affects market liquidity, increases market volatility and leads to deteriorating market efficiency. We conclude that it is difficult to dissuade investors from entering into unproductive trades and eliminate negative outputs of HFT (such as price manipulations) through tax, without altering the benefits of HFT like liquidity provision and efficient price discovery.     

Retail Trading in Options and the Rise of the Big Three Wholesalers

We document a rapid increase in retail trading in options in the United States. Facilitated by payment for order flow (PFOF) from wholesalers executing retail orders, retail trading recently reached over 60% of total market volume. Nearly 90% of PFOF comes from three wholesalers. Exploiting new flags in transaction-level data, we isolate wholesaler trades and build a novel measure of retail options trading. Our measure comoves with equity-based retail activity proxies and drops significantly during U.S. brokerage platform outages and trading restrictions. Retail investors prefer cheaper, weekly options with average bid-ask spread of 12.6%, and lose money on average.     

What does PIN identify? Evidence from the T-bill market

The probability of informed trading (PIN) measure has been increasingly used in empirical research in finance. However, there is a growing debate as to whether PIN measures information-based or liquidity-based trading. We contribute to the discussion by estimating PIN using transaction data for one-month T-bills. Our PIN estimates exceed those reported for equities, despite it being unlikely that the probability of informed trading is higher in T-bills than equities. We conclude that PIN identifies trading clusters and that the source of the clustering depends on the economics of the market. The economics of the T-bill market suggest discretionary liquidity traders are the likely source of the clustering.     

Public information releases, private information arrival and volatility in the foreign exchange market

This paper estimates the impact of market activity and news on the volatility of returns in the exchange market for Japanese Yen and US dollars. We examine the effects of news on volatility before, during and after news arrival, using three categories of news. Market activity is proxied by quote arrival, separated into a predictable seasonal component and an unexpected component. Results indicate that both components of market activity, as well as news releases, affect volatility levels. We conclude that both private information and news effects are important determinants of exchange rate volatility. Our finding that unexpected quote arrival positively impacts foreign exchange rate volatility is consistent with the interpretation that unexpected quote arrival serves as a measure of informed trading. Corroborating this interpretation is regression analysis, which indicates that spreads increase in the surprise component of the quote arrival rate, but not in the expected component. The estimated impact of a unit increase in unexpected quote arrival and the range of values observed for this variable imply an important volatility conditioning role for informed trading.     

Applying developed‐country regulation in emerging markets: an analysis of Thai insider trading

This paper undertakes an out‐of‐sample test of developed‐country insider trading regulation in an emerging market environment (Thailand), where severe information asymmetry, lax enforcement and poor pricing efficiency are endemic. Thai insider trading regulation, which mimics developed market rules, fails on all three measures of success. Insiders trade with impunity during a regulated trading ban. Their trading performance outperforms other investors at all times, and they continue to exploit their privileged position with respect to information flow. Our study suggests it is inappropriate for emerging market regulators to adopt developed market regulation without first considering the unique characteristics of their own environment.     

Hawkes model for price and trades high-frequency dynamics

We introduce a multivariate Hawkes process that accounts for the dynamics of market prices through the impact of market order arrivals at microstructural level. Our model is a point process mainly characterized by four kernels associated with, respectively, the trade arrival self-excitation, the price changes mean reversion, the impact of trade arrivals on price variations and the feedback of price changes on trading activity. It allows one to account for both stylized facts of market price microstructure (including random time arrival of price moves, discrete price grid, high-frequency mean reversion, correlation functions behaviour at various time scales) and the stylized facts of market impact (mainly the concave-square-root-like/relaxation characteristic shape of the market impact of a meta-order). Moreover, it allows one to estimate the entire market impact profile from anonymous market data. We show that these kernels can be empirically estimated from the empirical conditional mean intensities. We provide numerical examples, application to real data and comparisons to former approaches.     

How does the market variance risk premium vary over time? Evidence from S&P 500 variance swap investment returns

We explore whether the market variance risk premium (VRP) can be predicted. We measure VRP by distinguishing the investment horizon from the variance swap’s maturity. We extract VRP from actual S&P 500 variance swap quotes and we test four classes of predictive models. We find that the best performing model is the one that conditions on trading activity. This relation is also economically significant. Volatility trading strategies which condition on trading activity outperform popular benchmark strategies, even once we consider transaction costs. Our finding implies that broker dealers command a greater VRP to continue holding short positions in index options in the case where trading conditions deteriorate.     

Liquidity and market efficiency: A large sample study

Chordia et al. (2008, hereafter CRS) examine short horizon return predictability from past order flows of large, actively traded NYSE firms across three tick size regimes and conclude that higher liquidity facilitates arbitrage trading which enhances market efficiency. We extend CRS to a comprehensive sample of all NYSE firms and examine the dynamics between liquidity and market efficiency during informational periods. Our results indicate that although all NYSE firms experience an overall improvement in market efficiency across periods of different tick size regimes, this improvement varies significantly across the portfolios of sample companies formed on the basis of trading frequency, market capitalization, and trading volume. After controlling for these factors, we further document a positive association between a continuous measure of liquidity and market efficiency, and show that this effect is amplified during periods that contain new information, as reflected in high adverse selection component of the bid-ask spread.     

Is market fragmentation harming market quality?

We examine how fragmentation is affecting market quality in US equity markets. We use newly available trade reporting facilities (TRFs) data to measure fragmentation, and we use a variety of empirical approaches to compare execution quality and efficiency of stocks with more and less fragmented trading. We find that fragmentation affects all stocks; more fragmented stocks have lower transactions costs and faster execution speeds; and fragmentation is associated with higher short-term volatility but greater market efficiency, in that prices are closer to being a random walk. Our results that fragmentation does not appear to harm market quality are consistent with US markets being a single virtual market with multiple points of entry.     

Does trading volume detect information content in earnings reconciliations of foreign firms?

Currently, foreign firms trading securities on U.S. markets provide periodically a quantitative reconciliation of selected financial data consistent with U.S. GAAP (hereafter referred to as reconciled information) in Form 20-F. The SEC is examining whether users believe that this reconciliation process provides additional information above that provided by the foreign GAAP earning announcement and whether this incremental information enhances usefulness for market participants. We examine whether the reconciliation affects a primary indicator of information usefulness: the trading volume of capital markets participants.We use a regression model to examine the relation between a measure of abnormal trading volume and four firm-specific variables in the firm's information environment: similarities of accounting systems, analyst following, difference between reconciled earnings and foreign GAAP earnings, and dispersion of analysts’ expectations. We find a significant relation between abnormal volume and the reconciled earnings number and between abnormal volume and the dispersion of analysts forecasts. Our findings suggest that market participants may use the 20-F reconciliation in trading decisions.     

Public information arrival: Price discovery and liquidity in electronic limit order markets

How information is translated into market prices is still an open question. This paper studies the impact of newswire messages on intraday price discovery, liquidity, and trading intensity in an electronic limit order market. We take an objective ex ante measure of the tone of a message to study the impacts of positive, negative, and neutral messages on price discovery and trading activity. As expected, we find higher adverse selection costs around the arrival of newswire messages. Negative messages are associated with higher adverse selection costs than positive or neutral messages. Liquidity increases around positive and neutral messages and decreases around negative messages. Available order book depth as well as the trading intensity increases around all news. Our results suggest that market participants possess different information gathering and processing capabilities and that negative news messages are particularly informative and induce stronger market reactions.     

The role of private information in return volatility,bid–ask spreads and price levels in the foreign exchange market

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.     

Semi‐transparency,dealership market,and foreign exchange market quality

This paper examines the effects of a semi-transparency event, the introduction of the electronic trading system (EBS), on the market quality of a typical dealership market – the FX market. We find that increasing transparency leads to smaller quote disagreement among dealers and higher trading volume, but the beneficial effects are bigger for uninformed dealers than informed dealers. We also find that information efficiency improves overall in the semi-transparent system; however, informed dealers are found to quote less aggressively in the more transparent market. We conclude that semi-transparency raises market quality in general, but that it is the uninformed dealers who benefit more from this increased quality.     

Does Algorithmic Trading Improve Liquidity?

Algorithmic trading (AT) has increased sharply over the past decade. Does it improve market quality, and should it be encouraged? We provide the first analysis of this question. The New York Stock Exchange automated quote dissemination in 2003, and we use this change in market structure that increases AT as an exogenous instrument to measure the causal effect of AT on liquidity. For large stocks in particular, AT narrows spreads, reduces adverse selection, and reduces trade‐related price discovery. The findings indicate that AT improves liquidity and enhances the informativeness of quotes.     

Public Information Arrival

We develop a measure of public information flow to financial markets and use it to document the patterns of information arrival, with an emphasis on the intraday flows. The measure is the number of news releases by Reuter's News Service per unit of time. We find that public information arrival is nonconstant, displaying seasonalities and distinct intraday patterns. Next we relate our measure of public information to aggregate measures of intraday market activity. Our results suggest a positive, moderate relationship between public information and trading volume, but an insignificant relationship with price volatility.