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Regulation - February 04, 2013

Informing the regulatory debate

By Frédéric Ducoulombier, Director of Executive Education, EDHEC-Risk Institute and Director, EDHEC Risk Institute–Asia

Frédéric Ducoulombier

In the wake of the global financial crisis, politicians have made strident calls to curb speculative activities and singled out short-selling and high-frequency trading as epitomes of socially useless practices that were increasing financial market volatility. Under pressure, regulators worldwide have imposed or are looking at introducing new restrictions on trading. What can be learnt from research?

Securities and markets regulators around the world introduced bans on short-selling at different stages of development of the recent crisis, purportedly to halt price falls, reduce volatility and, in the words of former chairman of the Securities and Exchange Commission Christopher Cox, “restore equilibrium to the markets.”

These hasty decisions were not only devoid of theoretical basis, but also flew in the face of empirical evidence. Academic studies, including work by EDHEC-Risk Institute researchers, had documented the positive contribution of short-sellers to market efficiency and shown that constraining short sales significantly reduced market quality – by reducing liquidity and increasing volatility – and could have unintended spillover effects.

In a series of articles published or forthcoming in leading academic journals, EDHEC Business School Professor Ekkehart Boehmer, who serves as the PhD in Finance Assistant Academic Director for Asia, and his co-authors have studied short-selling activities, looking at the type of information possessed by short-sellers1, at the impact between short-selling activities and abnormal returns2, and at the link between short-selling and the price discovery process3. They established that short-sellers are important contributors to efficient stock prices, that short interest contains valuable information for the market, that information is compounded faster and more efficiently into prices when short sellers are more active and that short-sellers change their trading around extreme return events in a way that aids price discovery.

Professor Boehmer and co-authors, and EDHEC Business School Professor Abraham Lioui, who serves as the PhD in Finance Assistant Academic Director for Europe, have also looked at the consequences of the short-selling bans imposed in the United States and around the world in 2008. The study led by Professor Boehmer4 concluded that stocks subject to the US ban suffered a severe degradation in market quality, as measured by spreads and price impacts (i.e. liquidity), and intraday volatility. The multi-country study by Professor Lioui5 focused on the impact of the 2008/2009 bans on leading market and financial indices in the US, France, the UK and Germany and found that these led to a systematic increase in the volatility of market indices and had an even stronger impact on financial indices. He did not observe a systematic effect on skewness, indicating that the ban did not reduce downward pressure in a significant manner. He also observed that kurtosis, a measure proxying extreme market movement, increased during the ban, although not in a statistically significant manner. It is on the basis of these studies that EDHEC-Risk Institute unequivocally condemned moves of the European financial market authorities in August 2011 to impose or extend short-selling bans.

The Institute6 had then denounced these decisions as a “political smokescreen” that was “likely to prove counterproductive, both directly by disrupting market functioning and degrading market quality at a most testing time, and indirectly by further fuelling defiance vis-à-vis sovereign states and the continued inability of their political institutions to address the causes of the current crisis.” The conclusions of Professors Boehmer and Lioui have since been confirmed by other academics as well as by researchers working for market authorities and supranational organisations. Mr. Cox admitted that the biggest mistake of his tenure had been to agree to the 2008 short-selling ban under intense political pressure. Such candid admission has yet to come from Europe where the crisis and regulatory pressure to constrain short-selling are still current.

High-frequency trading has been described by the United States Securities and Exchange Commission as “one of the most significant market structure developments in recent years”. It relies on computer algorithms to exploit tiny price differences by emitting and cancelling orders and moving in and out of markets in milliseconds, holding positions for seconds at most. High frequency traders have come to dominate transactions in developed markets and understandably generated considerable policy interest. Among others, they have been accused of taking unfair advantage of other market participants, of increasing market volatility and of providing “ghost” liquidity. While some market regulators are still debating whether high-frequency trading should be regulated, others have already drafted curbs on the activity or wish to impose specific (e.g. market making) obligations on firms engaging in the practice.

EDHEC-Risk Institute Professor Jakša Cvitanic has approached high-frequency trading from a simulation angle in early work with United States Commodity Futures Trading Commission Chief Economist Doctor Andrei Kirilenko. Work by Professor Boehmer and his co-authors provide the most comprehensive international evidence to date on the impact of the rise of automated trading. Using intraday data that cover 42 exchanges and an average of more than 25,000 different common stocks, a first paper7 shows that, on average, greater algorithmic trading intensity improves liquidity and informational efficiency, but increases short-term volatility. The volatility increase is robust to a range of different volatility measures and it is not due to more “good” volatility that would arise from faster price discovery. The paper also finds that, in contrast to the average effect, more algorithmic trading reduces liquidity in small stocks; has little effect on the liquidity of low-priced or high-volatility stocks; and leads to greater increases in volatility in these stocks. Finally, during days when market making is difficult, algorithmic trading provides less liquidity, improves efficiency more, and increases volatility more than on other days. The paper controls for the direction of causality to show that algorithmic traders add liquidity and short-term volatility to the market.

The second article8 looks at an important follow-up question – whether this elevated short-term volatility can impact the ability of firms to raise new equity capital. Some traders, especially liquidity providers, dislike volatility because it increases the adverse selection risk associated with limit order strategies, the typical way of supplying liquidity. If the elevated volatility and the potentially associated reduction in liquidity persist over time, they can discourage long-term investors and hinder a firm’s ability to raise new capital. Professor Boehmer’s empirical results point towards the ability of higher algorithmic trading activity to reduce the proceeds from new equity issues, but more importantly, the links such trading activity has with increased levels of share repurchases; altogether, an economically substantial decline in net equity is documented. These effects are concentrated in firms that are among the smallest or the most volatile third of firms in a given market.

While supportive of prior findings that attribute liquidity- and efficiency-enhancing effects to algorithmic and high-frequency trading, the findings of Professor Boehmer complement these with evidence that algorithmic trading liquidity provision does not apply to all firms and not necessarily on days when market making is unusually costly. For the smallest third of firms and on days when market making is costly, algorithmic traders appear to trade according to strategies that do not primarily focus on market making. Algorithmic trading also systematically increases volatility, which imposes costs on other market participants. In evaluating the costs and benefits of algorithmic trading in markets dominated by high frequency trading, regulators should take into account this new evidence. The findings also suggest that the activity can potentially affect the more fundamental functions of capital markets; future research should specifically verify and measure the potential indirect impact of high frequency trading on capital formation to further inform the regulatory debate.



Footnotes

  1. Which shorts are informed? Ekkehart Boehmer, Charles Jones and Xiaoyan Zhang. Journal of Finance 63, 2008, 491-528. (Lead Article and Finalist, 2008 Smith Breeden Prize (runner up).)
  2. The good news in short interest. Ekkehart Boehmer, Brad Jordan and Zsuzsa Huszar. Journal of Financial Economics 96, 2010, 80-97. (Fama/DFA Prize for the best paper in the Journal of Financial Economics.)
  3. Short selling and the price discovery process. Ekkehart Boehmer and Juan Wu. EDHEC-Risk Institute Working Paper, May 2010. Forthcoming in Review of Financial Studies.
  4. Shackling Short Sellers: The 2008 Shorting Ban. Ekkehart Boehmer, Charles Jones and Xiaoyan Zhang, EDHEC-Risk Institute Working Paper, September 2009.
  5. Spillover Effects of Counter-Cyclical Market Regulation: Evidence from the 2008 Ban on Short Sales. Abraham Lioui. Journal of Alternative Investments 13, 2011, 53-66.
  6. EDHEC-Risk Institute denounces short selling bans. EDHEC-Risk Institute Press Release, 12 August 2011.
  7. International Evidence on Algorithmic Trading. Ekkehart Boehmer, Kingsley Fong, and Juan Wu, AFA 2013 San Diego Meetings Paper.
  8. Algorithmic Trading and Changes in Firms’ Equity Capital. Ekkehart Boehmer, Kingsley, and Juan Wu, Working Paper, 12 November 2012.