Australian Quant Action

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1 AUSTRALIA Top 5 Resources stocks in the Macquarie Alpha model Code Company Name Analyst Rec. FMG Fortescue Metals Outperform BSL BlueScope Steel Outperform S32 South32 Ltd Outperform NST Nthn Star Resources Neutral OZL Oz Minerals Neutral Top 5 Industrials stocks in the Macquarie Alpha model Code Company Name Analyst Rec. QAN Qantas Airways Outperform ALL Aristocrat Leisure Outperform DOW Downer Edi Ltd Outperform AMP Amp Limited Neutral NAB Natl Australia Bk Outperform Making Performance Great Again Event 2017 has been more favourable for active equity managers, with correlations normalising, spreads becoming less extreme, and greater tailwinds from factor returns. Impact After peaking in mid-2016, correlations between stocks have reduced to normal levels. This environment should result in more opportunities for skilful bottom-up managers to identify outperforming vs underperforming stocks. Similar trends can be seen across global markets and in style correlations. Lower correlations mean more opportunities for stock-pickers Macquarie Alpha sector exposure March 2017 vs August 2016 High Alpha Sector Representation Pharmaceuticals, Biotechnology & Life Sciences Mar-17 Aug-16 Source: Macquarie Research, March 2017 Source: Macquarie Research, March 2017 This environment is favourable for the Macquarie alpha model and recent returns have been strong. Top ranking stocks in the Industrials space are QAN, ALL, DOW, AMP and NAB. Top ranking stocks in the Resources sector include FMG, BSL, S32, NST and OZL. 3 March 2017 Macquarie Securities (Australia) Limited At a sector level, make up a greater proportion of the earnings yield basket compared to mid last year. We see a lower representation when looking at book yield. The rotation is consistent with the forecast from our Rallying to Value note. have become less cheap, while more Real Estate stocks now have a cheap relative book multiple. The Resources and Financials trade is also clearly evident in Revisions and Momentum baskets. Outlook The February reporting season saw more positive than negative report-date reactions. Daily cross-sectional volatility through February was also much lower, which suggests that: (a) market expectations were more aligned with reported results; and (b) the volume of surprises was benign. QBE (QBE), AMP Limited (AMP), BlueScope Steel (BSL), and Coca-Cola Amatil (CCL) all announced buybacks. Our prior work shows that the average excess return of stocks post a buyback announcement is 3.4% over 12 months and 9.1% over 24 months. Please refer to page 10 for important disclosures and analyst certification, or on our website

2 Making Performance Great Again 2017 has been a more favourable environment for asset managers, with correlations normalising across the globe. Equity markets continue to be supported by a resilient US economic cycle, higher commodity prices, and optimism that the US government will stimulate further growth. We have seen this flow through to returns for our models. Figure 1 below shows that the hit rate of our 10 investment styles has returned to positive territory after an out of character negative year in 2016 (we measure the hit rate by looking at the monthly IC of our 10 investment styles for each year). Most equity managers will be exposed to these styles. Negative style returns can therefore be significant headwinds to fund performance. The only other year since 1980 where we saw a negative hit rate across the 10 styles was 2009, when the market reversed sharply post-gfc. Figure 1 Annual hit rate of Macquarie Style groups* much stronger in % 70% 2017 has seen a rebound in style returns 60% 50% 40% 30% 2009 and 2016 the only years where style hit rate was negative 20% *10 groups capture investment different investment styles and include: Value, Momentum, Analyst Sentiment, Profitability, Growth, Capital, Quality, Low Risk, Liquidity, and Technical Indicators Source: Macquarie Research, IBES, March 2017 Hit Rate of Investment styles (positive IC) We flagged in our : Rallying to Value report the struggle experienced by Momentum and Earnings Revisions in We also noted that there had never been two consecutive years in which return spreads were negative for these two factors. The figure below shows that it has been a strong start to the year for Momentum, and more recently, Earnings Revisions. Figure 2 Returns of core factors has been much stronger in % 8% Performance of core styles much stronger in % 4% 2% 0% -2% -4% -6% -8% -10% Feb (16) Mar April May June July Aug Sep Oct Nov Dec Jan Feb (17) Earnings Yield Book Yield Low Volatility 12m Momentum ROE Size Earnings Certainty EPS Revisions Alpha Returns are monthly Long-minus-Short Quintiles across the ASX200 Source: Macquarie Research, IBES, March March

3 02-Jan 04-Jan 06-Jan 08-Jan 10-Jan 12-Jan 14-Jan 16-Jan 18-Jan 20-Jan 22-Jan 24-Jan 26-Jan 28-Jan 30-Jan 01-Feb 03-Feb 05-Feb 07-Feb 09-Feb 11-Feb 13-Feb 15-Feb 17-Feb 19-Feb 21-Feb 23-Feb 25-Feb 27-Feb Cumulative Returns (ASX200 Long - Short Quintile) Cumulative Returns (ASX200 Long - Short Quintile) Log Returns Value s Great Rotation Value s performance has also held up in the year-to-date, despite not being as dominant as it was in The rally continues to be the 5 th largest in the past three decades as we show below. Consistent with prior rallies, the magnitude of performance has diminished as the rally plays out. Returns to value are typically strongest at the start of a rally, as there is distress risk which comes out of the value basket. Figure 3 Comparison of Value Rallies (Book Yield Long-Short Quintile) Comparison of Value Rallies Apr-00 - Sep-04 Mar-09 - Aug-10 Aug-87 - Mar-89 Jul-91 - Mar-97 Feb-16 - Feb Source: Macquarie Research, IBES, March 2017 Months This is especially true for book multiple factors as we show above. At the end of a low-growth cycle, stocks with high book yields are best positioned to leverage potential expansions in economic activity. They re fundamentally cheap because they have previously been priced on flat or declining expectations of economic growth. They also have strong underlying asset support to their valuations, which potentially limits the downside if growth expectations are not realised. In the 2016 case, this was been driven by and related sectors as they rallied off their cyclical lows. Low P/E stocks, on the other hand, are priced purely on future earnings expectations which are much less conservative and more volatile than estimates of future book value. In our prior note we discussed the likely rotation of performance from book yield into both earnings yield and earnings/price momentum. This rotation has played out through the beginning of 2017 with earnings multiple strategies outperforming book multiple strategies. Figure 4 Moving from book yield to earnings yield Panel A: Book Yield Outperforms Earnings Yield in 2016 Panel B: Earnings Yield has been stronger in Jan 29-Feb 31-Mar 30-Apr 31-May 30-Jun 31-Jul 31-Aug 30-Sep 31-Oct 30-Nov Earnings Yield Book Yield Source: Macquarie Research, Factset, March 2017 Earnings Yield Book Yield In Figure 5 below, we examine the sector composition of top-quintile baskets in each composite style. The top two charts show the make up a greater proportion of the earnings yield basket compared to mid last year. We see a lower representation when looking at book yield. The rotation is consistent with the forecast from our Rallying to Value note. have become less cheap and more stocks now have cheap relative book multiples. 3 March

4 Figure 5 Changing Sector Representation across styles, March 2017 vs August 2016 High Earnings Yield Sector Representation Pharmaceuticals, Biotechnology & High Book Yield Sector Representation Pharmaceuticals, Biotechnology & Mar Aug-16 Mar Aug-16 High Revisions Sector Representation Pharmaceuticals, Biotechnology & High Momentum Sector Representation Pharmaceuticals, Biotechnology & Mar Aug-16 Mar Aug-16 3 March

5 % Correlation Pharmaceuticals, Biotechnology & High Alpha Sector Representation Mar Aug-16 Source: Macquarie Research, Factset, March 2017 The Resources and Financials trade, which has been supported by higher commodity prices and a more optimistic outlook for growth, has been reflected in other signals. This is clearly evident in our Alpha model (pre- sector neutralisation). Such a rotation, whereby industries move from Value through to Earnings and Price momentum, is natural should there be persistence in a trend. This again helps explains the stronger style returns we have witnessed to start Making Stock-picking Great Again Should the current environment be good for stock-picking? 2016 saw elevated levels of correlation across global markets. The impact of this is that stocks become driven by a common factor (often macro) and company fundamentals have far less influence. After peaking in mid-2016 the chart below shows that correlations amongst stocks have reduced to more normal levels. This means there is greater dispersion amongst individual stock returns and a skilful bottom-up manager will have more opportunities to identify outperforming stocks from underperforming stocks. Figure 6 Pairwise correlations have retraced to lower levels 80% 70% 60% 50% 40% 30% 20% 10% 0% 1M Rolling Daily Correlations 1Y Rolling Daily Correlations Source: Macquarie Research, Factset, March March

6 Mar-11 May-11 Jul-11 Sep-11 Nov-11 Jan-12 Mar-12 May-12 Jul-12 Sep-12 Nov-12 Jan-13 Mar-13 May-13 Jul-13 Sep-13 Nov-13 Jan-14 Mar-14 May-14 Jul-14 Sep-14 Nov-14 Jan-15 Mar-15 May-15 Jul-15 Sep-15 Nov-15 Jan-16 Mar-16 May-16 Jul-16 Sep-16 Nov-16 Jan-17 Rolling 3m Daily Return Correlation Moving up a layer to the factor level, we have also seen a reduction in correlations. The figure below displays the time series correlations for different pairs of styles using three months of daily data. For each style, we calculate long-short returns by sorting stocks in five equally-weighted portfolios that are rebalanced monthly. For most of 2015 and the first half of 2016, style correlations were stretched between high price momentum, low risk, and high earnings momentum. These styles had extreme, negative correlations with Value strategies, making the outcome of many decisions binary. A similar trend has been seen in global markets. Translating this back to fundamentals in the context of the Australian market, the binary trade manifest itself as one of two strategies. The first was a bet in defensive, high-yield, and highgrowth stocks, which paid off until early The second, a bet in commodity-related sectors and other beaten-up cyclicals, reversed strongly in February 2016 and has outperformed significantly in the subsequent period. Correlations have retraced significantly in recent months, which increases the dimensionality of the market and outcomes for stock returns. Figure 7 Style correlations have eased dramatically 100% 80% 60% 40% 20% 0% -20% -40% -60% -80% -100% CV/DV CV/PM DV/PM CV/LR DV/LR PM/LR PM/EM Source: Macquarie Research, Factset, March Style correlations are calculated using long-short style daily returns over 63 days, CV stands for Cyclical Value, DV for Defensive Value, PM for Price Momentum, EM for Earnings Momentum, LR for Low Risk Overall, 2017 offers a more favourable environment for active managers with lower correlations, stronger factor tailwinds, and less extreme spreads. 3 March

7 Reporting Season Recap The February reporting season saw more positive reporting-date reactions than negative ones, with 47 stocks having excess returns of greater than 3% compared to 40 stocks underperforming by more than 3% 1. We plot below the 50 biggest outperformers and underperformers on the company reporting date. In our Catching the Drift note we documented the returns to the post announcement drift. Over the past 10 years, stocks that have a positive surprise tend to experience significant postannouncement drift. The average 30-day drift following a >2% market reaction surprise is a further 3%. Figure 8 Top and Bottom returns on reporting date through reporting season CSV-AU AAD-AU GMA-AU DMP-AU SPO-AU WOR-AU BXB-AU MML-AU IFL-AU TOX-AU RWH-AU SWM-AU BBN-AU TLS-AU IGO-AU ACX-AU SDA-AU BEN-AU JHC-AU FBU-NZ MTR-AU SXL-AU TAH-AU SGF-AU MGC-AU MFG-AU TWE-AU SPK-NZ PEP-AU MPL-AU TTS-AU CVW-AU AHG-AU AOG-AU WSA-AU SKT-NZ FMG-AU ISD-AU OZL-AU AYS-AU BAP-AU FXL-AU NXT-AU ING-AU ORA-AU SBM-AU VAH-AU ORG-AU REA-AU SGM-AU Top 50 Negative Excess Return on Reporting Day -20% -15% -10% -5% 0% Average = -6.3% n = -4.7% 40 stocks less than -3% excess return DOW-AU IEL-AU MND-AU NCK-AU WTC-AU NHF-AU CWN-AU MMS-AU AHY-AU FXJ-AU NEC-AU CAB-AU CAR-AU RCR-AU CIM-AU WPP-AU TCL-AU SUL-AU AUB-AU SKC-NZ PPT-AU PRT-AU QAN-AU SAR-AU BLD-AU CHC-AU CCL-AU AIR-NZ AFG-AU EPW-AU PRU-AU GTY-AU 3PL-AU AQG-AU LNK-AU BSL-AU AGL-AU WOW-AU MYO-AU CPU-AU LLC-AU AMP-AU ABC-AU AMC-AU IRE-AU GUD-AU MGX-AU IPH-AU MOC-AU QBE-AU Top 50 Positive Excess Return on Reporting Day 0% 5% 10% 15% 20% Average = 5.8% n = 5.2% 47 Stocks greater than 3% excess return Source: Macquarie Research, Factset, March Universe is stocks under Macquarie coverage. How did this compare to prior reporting seasons? We look at the daily cross-sectional volatility of stocks throughout February in prior years in the chart below. The observed volatility in 2017 was significantly below both recent years and longer-term averages. This suggests that market expectations were more aligned with actual results, and that the volume of surprises across the market was relatively benign. 1 Based on coverage universe of Macquarie Analysts 3 March

8 Average Excess Return Figure 9 Average Cross-Sectional Volatility in February by year (daily returns) 5.0% 4.5% 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% Avg Daily Cross Sectional Volatility by year in February Long Term Average Source: Macquarie Research, Factset, March 2017 Capital Returns still key Companies that surprised the market by returning capital to shareholders also reacted strongly on the day of announcement. The chart below shows the report date excess return of stocks that beat or missed Macquarie fundamental analyst expectations of EPS or DPS. The market had a stronger reaction to a positive dividend surprise (1.84%) compared to an earnings surprise (1.07%). Figure 10 Performance of stocks on report date that beat Macquarie DPS and EPS Estimates 2.00% 1.84% 1.50% 1.00% 1.07% 0.50% 0.00% -0.50% -0.18% -0.18% -1.00% -1.50% -0.84% -1.07% Positve Surprises Negative Surprises All EPS DPS Source: Macquarie Research, Factset, March QBE (QBE), AMP Limited (AMP), BlueScope Steel (BSL) and Coca-Cola Amatil (CCL) also announced buybacks that were well received by the market. The average excess return on report date for these companies was 3.9%. This is consistent with history as we reported in our deep dive analysis of capital returns. Furthermore we found that the outperformance continues with an average excess return of 1% in the month following the buyback announcement. 3 March

9 Excess Returns Over the longer term, the average return of stocks is strong with an excess return of 3.4% over 12 months and 9.1% over 24 months (see chart below). Large-cap (ASX100) companies undertaking buybacks have superior performance to small-cap firms undertaking buybacks. This behaviour is unique with many quant anomalies finding stronger performance in the small caps. There are also more large-cap deals, suggesting small-cap firms are focussed on growth as opposed to returning capital to shareholders. Figure 11 Longer-term returns of stocks around announcement of a buyback 12.0% 10.0% Mean n 8.0% 6.0% 4.0% 2.0% 0.0% -2.0% -4.0% Source: Macquarie Research, Factset, March Days around announcement 3 March

10 This publication was disseminated on 03 March 2017 at 09:45 UTC. Important disclosures: Recommendation definitions Macquarie - Australia/New Zealand Outperform return >3% in excess of benchmark return Neutral return within 3% of benchmark return Underperform return >3% below benchmark return Benchmark return is determined by long term nominal GDP growth plus 12 month forward market dividend yield Macquarie Asia/Europe Outperform expected return >+10% Neutral expected return from -10% to +10% Underperform expected return <-10% Macquarie South Africa Outperform expected return >+10% Neutral expected return from -10% to +10% Underperform expected return <-10% Macquarie - Canada Outperform return >5% in excess of benchmark return Neutral return within 5% of benchmark return Underperform return >5% below benchmark return Macquarie - USA Outperform (Buy) return >5% in excess of Russell 3000 index return Neutral (Hold) return within 5% of Russell 3000 index return Underperform (Sell) return >5% below Russell 3000 index return Volatility index definition* This is calculated from the volatility of historical price movements. Very high highest risk Stock should be expected to move up or down % in a year investors should be aware this stock is highly speculative. High stock should be expected to move up or down at least 40 60% in a year investors should be aware this stock could be speculative. Medium stock should be expected to move up or down at least 30 40% in a year. Low medium stock should be expected to move up or down at least 25 30% in a year. Low stock should be expected to move up or down at least 15 25% in a year. * Applicable to Asia/Australian/NZ/Canada stocks only Recommendations 12 months Note: Quant recommendations may differ from Fundamental Analyst recommendations Financial definitions All "Adjusted" data items have had the following adjustments made: Added back: goodwill amortisation, provision for catastrophe reserves, IFRS derivatives & hedging, IFRS impairments & IFRS interest expense Excluded: non recurring items, asset revals, property revals, appraisal value uplift, preference dividends & minority interests EPS = adjusted net profit / efpowa* ROA = adjusted ebit / average total assets ROA / = adjusted net profit /average total assets ROE = adjusted net profit / average shareholders funds Gross cashflow = adjusted net profit + depreciation *equivalent fully paid ordinary weighted average number of shares All Reported numbers for Australian/NZ listed stocks are modelled under IFRS (International Financial Reporting Standards). Recommendation proportions For quarter ending 31 December 2016 AU/NZ Asia RSA USA CA EUR Outperform 57.53% 50.72% 45.57% 42.28% 60.58% 52.79% (for global coverage by Macquarie, 8.71% of stocks followed are investment banking clients) Neutral 33.90% 33.97% 43.04% 50.11% 37.23% 35.62% (for global coverage by Macquarie, 8.05% of stocks followed are investment banking clients) Underperform 8.56% 15.30% 11.39% 7.61% 2.19% 11.59% (for global coverage by Macquarie, 4.63% of stocks followed are investment banking clients) Company-specific disclosures: Important disclosure information regarding the subject companies covered in this report is available at Analyst certification: We hereby certify that all of the views expressed in this report accurately reflect our personal views about the subject company or companies and its or their securities. We also certify that no part of our compensation was, is or will be, directly or indirectly, related to the specific recommendations or views expressed in this report. The Analysts responsible for preparing this report receive compensation from Macquarie that is based upon various factors including Macquarie Group Limited (MGL) total revenues, a portion of which are generated by Macquarie Group s Investment Banking activities. General disclosure: This research has been issued by Macquarie Securities (Australia) Limited ABN , AFSL , a Participant of the ASX and Chi-X Australia Pty Limited. This research is distributed in Australia by, a division of Macquarie Equities Limited ABN AFSL ("MEL"), a Participant of the ASX, and in New Zealand by Macquarie Equities New Zealand Limited ( MENZ ) an NZX Firm. Macquarie Private Wealth s services in New Zealand are provided by MENZ. 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