EVOLUTION OF CANADIAN EQUITY MARKETS

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1 EVOLUTION OF CANADIAN EQUITY MARKETS This paper is the first in a series aimed at examining the long-term impact of changes in Canada s equity market structure. Our hope is that this series can help inform discussions on how to improve market quality going forward. To that end, we very much welcome constructive feedback or dialogue with all interested stakeholders. PART 1: HAVE SPREADS REALLY NARROWED? The dynamics of trading equities in Canada have undergone a dramatic shift in the past fifteen years. While volume traded has increased and quoted spreads have narrowed, we believe that the marketplace has changed in some undesirable ways - among the most concerning, an approximate doubling of short-term intraday volatility resulting in higher implicit execution costs for investors. Our study shows that the apparent benefits of higher volume and narrower spreads have come at the expense of increased relative intraday trading volatility. We believe this volatility constitutes a substantial hidden cost for natural investors and raises serious questions about the true costs and benefits of narrowed spreads. Figure 1: Volume/Spreads/Intraday Volatility 20 Day Moving Average A: Total Canadian Volume (Millions) B: Spreads (Bps) C: Intraday 5 Minute Bar Volatility (% of Day's Trading Range) 7% 5% 3% Stephen Bain, CFA Managing Director, Head - Canadian Electronic Trading (416) stephen.bain@rbccm.com Shary Mudassir, CFA, CAIA Associate - Global Algorithmic Trading (416) shary.mudassir@rbccm.com

2 MARKETPLACE EVOLUTION Our study was based on tick-level data on over 400 Canadian symbols dating back to representing the bulk of weight in the S&P/TSX Composite over the entire study period. Since 1996 these stocks have gone through three distinct trading regimes: eighths trading prevailed until mid-1996, nickel trading until 2001, and ultimately decimalization. We are also mindful of the role that maker-taker and fragmentation have played in the evolution of our market structure. In the U.S., maker-taker was originally offered by Island ECN as early as By early 2002 both Arca and NASDAQ began the practice of rebating passive liquidity. Canada s first foray into maker-taker in mid-2000 was value-based and offered free trading to liquidity providers. Following a brief pilot on NASDAQ and Amex interlisted names, in mid-2006 TSX migrated to a full volume based maker-taker model. Fragmentation in the U.S. had its birth in Reg ATS in 1998 and was cemented by Reg NMS which took effect in We believe this fragmentation and proliferation of maker-taker had a significant impact on Canadian interlisted issues well in advance of events in Canada. In short, the fact that many stocks in our sample were interlisted also means they were de-facto highly fragmented (and rebated) years in advance of fragmentation in Canada. Figure 2: The Canadian Marketplace Supporters of the aforementioned changes cite increased volume traded and narrower spreads as irrefutable evidence of how our market structure has improved. Many also claim that today s markets have reduced volatility by absorbing short-term supply/demand imbalances. But is this claim really valid? How does trading volatility relate to claims of more liquidity and narrower spreads? Our study offers answers to these questions. 2

3 HAS DAILY VOLATILITY COME DOWN? In our study we examine multiple measures of daily volatility - all to the same conclusion (see Figure 3). We find no evidence of a permanent decline in daily volatility from 1996 to present. Also, we would point out that the explosion of volatility during the 2008 Financial Crisis was not tempered by today s market structure nor the HFT strategies that came (coincidentally) with it. What seems clear is that daily volatility is dominated by macro factors with extreme price movements tightly linked to the return volatility needed to restore supply/demand imbalances. Figure 3: Daily Volatility Charts B,C,D are Based on Study Sample Set A. CBOE S&P500 Volatility Index (VIX) B. Median Daily High Low Difference (bps) C. Median 30 Day Rolling Log Return Standard Deviation D. Median Close to Close Absolute Returns (%) 2.5% 4% 2.0% 3% 1.5% 2% 1.0% 1% Why have we focused on daily volatility? It remains critical to establish the highly correlated nature of the various daily volatility measures as they provide valuable context to the analysis of intraday trading. In particular, these measures are critical to normalizing the analysis of trading volatility over the timeframe of our study. Again, proponents of modern market structure argue that the current marketplace attracts more liquidity with narrower spreads. If so, we would expect to find evidence in the form of less intraday price volatility and less deviation from short-term equilibrium prices. As we will show in the next section, we find this not to be the case. 3

4 HAVE INTRADAY TRADING RANGES COME DOWN? Figure 4 compares intraday trading ranges (five, ten and fifteen minute high-low range) relative to same day trading ranges (high-low) for all the stocks in our study. What we have found is, relative to its daily trading range, the median stock in our sample has experienced a 70 to 100% increase in intraday price range volatility - nearly double pre-2000 levels. Figure 4: Median Intraday Trading Ranges Given as a percent of Day s Trading Range 16% 12% Five Minute Ten Minute 8% Fifteen Minute 4% Note: See Appendix - Sample Calculation I for a more detailed description of our calculation methodology. HAS THE DISTRIBUTION OF VOLUME AROUND SHORT-TERM EQUILIBRIUM PRICES IMPROVED? While price range volatility has increased, we also feel it is important to examine the distribution of trading prices relative to short-term equilibrium. Figure 5 shows that absolute deviation relative to short-term VWAP has actually increased even more precipitously. For the median stock in our study the increase in price deviation relative to VWAP ranged from 80 to 200% - more than double pre-2000 levels. Figure 5: Median Volume Weighted Absolute Deviation from Interval VWAP Given as a percent of Day s Trading Range 4% 3% Five Minute Ten Minute 2% Fifteen Minute 1% Note: See Appendix - Sample Calculation II for a more detailed description of our calculation methodology. 4

5 GLOBAL ALGORITHMIC TRADING To gain further insight on the impact to our sample set Figure 6 presents a histogram of the distribution for four date ranges covering eighths trading, nickel trading, decimalization and finally market fragmentation and proliferation of maker-taker. For the identified time periods we can see that that the distributions for more recent periods exhibit a higher mean and more positive skew (See Appendix for stats). Figure 6: Distribution of Price Deviations from 15 Minute Bar VWAP 30% Percent of Sample 20% 10% Apr Jan (Nickels) Jan Apr (Eighths) Jan Nov (Decimalization) Nov Dec (Market Fragmentation) 0% 0% 5% 10% 15% Percent of Day's Trading Range We expect some readers may be interested in the above analysis for non-block trading only. We found the ex-block data to yield a similar overall conclusion: an approximate doubling of trading volatility and deviation from interval VWAP over pre-2000 levels. OBSERVATIONS Our study (representing roughly 90% of Canada s main equity benchmark) establishes that intraday trading volatility relative to daily volatility has approximately doubled from pre-2000 levels. We are unaware of any similar length longitudinal study of intraday trading activity in Canada s equity markets and believe our findings should be of significant interest to lawmakers and regulators - both in Canada and other jurisdictions. Our initial interpretation of these findings is that efforts by Canadian and U.S. regulators to foster better liquidity (narrower spreads) in equity markets by offering various incentives has given rise to undesirable behaviors manifested in the form of increased intraday price volatility. Our findings stand in direct support of anecdotal observations of many market participants alleging latency arbitrage and statistical front-running. The trading volatility we have documented can be characterized as the new spread - and more importantly, as a substantial hidden cost for natural investors. In today s environment, any desire to transact in sizes much larger than a board lot and/or over time can result in rapid decay of benefits realized from narrower nominal spreads. We would highlight that our study supports the notion that increased trading volatility in equity markets is not restricted to discrete events such as that experienced during The Flash Crash, Knight Capital Group s systems failure or the myriad of mini flash crashes documented by pundits such as Nanex. In our view, these are more extreme cases of the same type of volatility we have documented in our study - magnified by failures of technology. 5

6 GLOBAL ALGORITHMIC TRADING SO WHAT IS THE SOLUTION? We do not advocate turning the clock back to Rather, we believe market stakeholders should seek ways to retain the benefits technology has brought to our markets. At the same time, they should address the shortcomings we have helped document to restore the confidence of natural investors. As such, we would offer the following recommendations: 1. Natural investors have a part to play: We acknowledge that, while regulators and marketplaces need to examine their approach to fostering healthy markets, natural investors and their agents have work to do. In today s environment liquidity takers need to re-examine how they access liquidity. The careful management of limits is clearly the best defense against trading at undesirable prices - in particular for institutional investors. That said, the reality remains that retail investors often lack the insight to manage limit prices at such a granular level and are up against liquidity providers aware of the new spread. Ultimately, while investors and their agents have a role to play, regulators also need to show leadership. 2. Re-examine incentives, starting with maker-taker: We have made no secret in the past of our view that regulators should be examining maker-taker and this study supports that view. These incentives amount to an unnatural subpenny subsidy for liquidity provision. While examination of trading increments is a considerably more complex topic (as the recent SEC Decimalization Roundtable highlighted), moderating maker-taker is the low hanging fruit that regulators can turn to with the goal of curbing liquidity inducements in a controlled manner. However, as we have previously highlighted, marketplaces cannot do this in isolation - again, regulators must take the lead. 3. Reign in innovations lacking clear net benefits: Regulators should be looking at all marketplace functionality (existing and proposed) through the lens of net benefits to the health of our markets. On this point we believe regulators are becoming more sensitive to this message and understand that innovations aimed at encouraging liquidity provision may have gone too far. We would nevertheless underscore that the net-benefit analysis should be biased toward encouraging innovations to help restore the parity of investors and liquidity providers. 6

7 GLOBAL ALGORITHMIC TRADING APPENDIX SAMPLE CALCULATION I: COMPUTATION OF INTRADAY TRADING RANGES METRIC The following is a graphical representation of the computation that underpins our analysis of intraday trading ranges in Figure 4. D Max, D Min represent the daily high and low for the stock for the day. For each 15 minute bar we express the local high and low range (L Max i L Min i ) as a percentage of days trading range (D Max D min ). This measure is then averaged across the day for each stock in our sample set and then a median across the entire population is derived. Figure I: Intraday Trading Ranges Calculation Example (15 Minute Bar) March 5, SU.TO $35.30 D Max L Max Min i L i V i = D Max D Min $35.10 Max L i $34.90 Min L i $34.70 D Min 10:00 11:00 12:00 13:00 14:00 15:00 16:00 SAMPLE CALCULATION II: COMPUTATION OF DEVIATIONS FROM INTERVAL VWAP METRIC Figure II: Volume Weighted Deviations from Interval VWAP Example (15 Minute Bar) March 5, SU.TO $35.30 D Max Volume Weighted Absolute Deviation from Interval VWAP (see Below) V i = D Max D Min $35.10 Stock Price Interval VWAP $34.90 $34.70 D Min 10:00 11:00 12:00 13:00 14:00 15:00 16:00 Stock Price $35.00 Interval VWAP Volume Weighted Absolute Deviation from Interval VWAP $ :45 12:50 12:55 13:00 7

8 DISTRIBUTION STATS FOR FIGURE 6 Date Range Median Mean Standard Deviation Skewness Jan Apr % 3.83% 5.52% 3.51 Apr Jan % 3.67% 4.50% 3.93 Jan Nov % 4.07% 3.34% 4.05 Nov Dec % 4.47% 2.93% 4.87 Disclaimer: This communication is for informational purposes only. It is not intended as an offer or solicitation for the purchase or sale of any financial instrument. The information contained herein, while obtained from sources that we believe to be reliable, is not guaranteed as to accuracy or completeness, nor is it a complete statement of any financial products or markets referred to in such information or an official confirmation of terms. RBC Capital Markets is a registered trademark of Royal Bank of Canada. To the full extent permitted by law, neither RBC Capital Markets nor any of its businesses or representatives, accepts any liability whatsoever arising from the use of this communication. RBC Capital Markets is the global brand name for the capital markets business of Royal Bank of Canada and it s affiliates, including RBC Capital Markets Corporation (member FINRA,NYSE,SIPC); RBC Dominion Securities Inc. (member IIROC and CIPF) and Royal Bank of Canada Europe Limited ( RBCEL )(authorized and regulated by FSA). This material is not for distribution to retail clients, as defined under the rules of the FSA. RBCEL accepts responsibility for this report and its dissemination in the United Kingdom. Registered trademark of Royal Bank of Canada. Used under license. Copyright All rights reserved. 8