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1 Average Information Co-efficient AUSTRALIA Stocks that typically perform well in high Uncertainty environments ranking well on the Macquarie Quant model Stock Code Description Alpha and Uncertainty Rank Down days beta (6M) ALL Aristocrat Leisure 93% 0.78 TLS Telstra Corp Ltd 87% 0.83 TPM Tpg Telecom Ltd 87% 0.86 CSL CSL 86% 0.83 SGP Stockland 83% 0.72 FDC Federation 81% 0.69 Centres RMD Resmed Inc 77% 0.44 CTX Caltex Australia 77% 0.93 WES Wesfarmers Ltd 76% 0.53 BOQ Bank Of QLD 75% 0.93 Time series volatility has increased but still below prior peaks Embracing Uncertainty Event We examine the impact of uncertainty on equity returns and identify stocks more likely to thrive in uncertain times. This follows on from our latest Quantamentals report. Impact Both volatility and uncertainty began to rear their heads in mid-june when the Chinese stock market bubble unofficially burst. The VIX index peaked on the 24 th of August as global markets were at their highest levels of distress. Inside we show that the current levels of volatility are still quite some way from prior peaks (chart on left) however we anticipate continued uncertainty with China and US interest rates expected to dominate headlines. In periods of high volatility, investors retreat to safety favouring Earnings Certainty, Large Caps, Dividend payers and stocks with good profitability (ROE). Style returns in the chart below are split by vol regime. Style returns in high vs low volatility regimes (2010 to present) 12% 10% PE Ratio Dividend Yield 12m Momentum 3m Earnings Revisions ROE Low Volatility Size (Large over Small) Eanrings Certainty Investors resort to Quality in high Volatility environments 8% 6% 4% 2% 0% -2% -4% -6% Low Market Volatility Mid High Market Volatility Regimes of High, Low and Mid market volatility are defined by the trailing market volatility. High is the top 25% of observations and low the bottom 25%. Our Quantamentals report created a score defining each stock s exposure to uncertainty. This was an effective stock picking signal globally and performed especially well in uncertain and volatile markets. 23 September 2015 Macquarie Securities (Australia) Limited Stocks that are expected to do well through uncertainty and rank highly on the Macquarie Alpha model include Aristocrat Leisure (ALL), Telstra (TLS), TPG Telecom (TPM), CSL (CSL) and Wesfarmers (WES). Analysis This spike in volatility coincided with reporting season in Australia and a number of extreme returns were seen by stocks surprising the market. Our analysis reveals that the excess returns were in line with prior reporting seasons with a slight positive tilt. Materials even more so. This is despite the fact that earnings and sales were broadly downgraded. Please refer to page 7 for important disclosures and analyst certification, or on our website

2 Quick recap of reporting season The August 2015 reporting season broadly saw net downgrades to EPS and Sales expectations. The domestic economy continues to face headwinds as it attempts to transition from mining investment-led growth to broader-based economic growth. See Reality Bites for further detail. Whilst there was some positivity in the FY15 numbers we saw downgrades in FY16 estimates. We show below the change in both FY15 and FY16 Earnings and Sales estimates from the end of July (pre reporting season) to the end of August (post reporting season). Fig 1 Change in Earnings and Sales estimates from pre to post reporting season (Industrials) Fig 2 Change in Earnings and Sales estimates from pre to post reporting season (all ASX200) 0.8% 1.00% 0.6% 0.4% 0.2% 0.0% -0.2% -0.4% 0.50% 0.00% -0.50% -1.00% -1.50% -0.6% -2.00% -0.8% FY15 Earnings FY16 Earnings FY15 Sales FY16 Sales -2.50% FY15 Earnings FY16 Earnings FY15 Sales FY16 Sales Macro volatility also took hold of the market through August with a severe sell-off in Chinese equities spreading to global markets.the S&P ASX200 sold off 8.6% capping its worst month since the GFC. Stocks that were perceived to surprise the market reacted aggressively on report date both on the positive and negative side. Below we simply show ASX300 stocks that experienced an excess return of plus or minus 3% on the reporting date. Fig 3 Extreme stock excess returns on reporting date ANN-AU DSH-AU ISU-AU SEK-AU ORG-AU APN-AU FMG-AU DOW-AU MRM-AU EVN-AU BLD-AU CPU-AU SXY-AU PRT-AU COH-AU NAN-AU SPL-AU IVC-AU ARI-AU NXT-AU MML-AU ASB-AU CAR-AU MQA-AU QAN-AU MIN-AU SFR-AU MVF-AU WHC-AU PGH-AU HIL-AU IAG-AU IMF-AU IGO-AU OZL-AU CWN-AU IRE-AU BEN-AU JHC-AU MOC-AU ASL-AU HSO-AU Negative Excess Rets on Rep Day -20.0% -15.0% -10.0% -5.0% 0.0% APO-AU MPL-AU AGI-AU BSL-AU SGM-AU PBG-AU TWE-AU DLS-AU FLT-AU JBH-AU SRX-AU CVO-AU NWH-AU RFG-AU ACR-AU AAD-AU TRG-AU TME-AU SHV-AU PRY-AU WOR-AU AHY-AU SKI-AU SGH-AU PPT-AU HSN-AU FXJ-AU BRG-AU PDN-AU RHC-AU NCM-AU FXL-AU CCL-AU RCR-AU DNA-AU MYX-AU PTM-AU TPI-AU EPW-AU CGF-AU AZJ-AU VLW-AU SPO-AU Positive Excess Rets on Rep Day 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% 18.0% Excess return on report date 23 September

3 A natural question was whether or not the stock day reactions were more or less severe than we d seen in previous reporting seasons. To answer this, we examined the excess return distribution of stocks in the days around their reporting dates. This is shown in the box plots below split out between Industrials (left) and Resources (right). The distributions look consistent with historic reporting seasons with the median excess return slightly higher. Resources (chart on right) had a positive skew in returns with the overall numbers appearing higher than they have been in the last 5 years. Fig 4 Distribution of excess returns by reporting season: ASX 200 Industrials Fig 5 Distribution of excess returns by reporting season: ASX 200 Resources Looking purely at excess returns suggests that it was a reasonably benign reporting season. Shifting the analysis to a total return space however tells a different story. The distribution of total returns was back to levels experienced around the crisis. Below we show the counts of stocks with a total return of either less than -5% (red), greater than 5% (blue) or everything else (green). Industrials is the top row and Resources the bottom. The narrowness of the green patch and also the number of big negative returns shows how the macro flowed into stock returns and we witnessed extreme total returns around report dates. An investigation of the volatility of stock returns in the days around reporting will also reveal a similar verdict. Fig 6 Total returns bucketed by size and reporting season shows the increased volatility 23 September

4 Livin la Volatility Loca Volatility began to rear its head in mid-june when the Chinese stock market bubble unofficially burst. One characteristic of volatility is that it is sticky, i.e. it tends to stick around for extended periods of time. This time has been no different and volatility has persisted. We saw a peak in the VIX index on the 24 th August as global markets were showing their largest signs of distress (low for the S&P 500). But how does the current volatility rank compared to historical measures? We measure both the time series volatility and the cross sectional volatility of the ASX200 below and this reveals we are still some way off levels reached in prior crises. Time series and cross sectional volatility have a meaningful impact on portfolio returns. High cross sectional volatility should be good for (effective) stock pickers as the outperformance from making the right stock calls will be superior. Time series volatility however can wipe this out as the macro aggressively impacts the performance. An ideal environment for stock pickers has been low time series volatility and high cross sectional volatility. Fig 7 Weekly time series volatility increasing Fig 8 Weekly cross sectional volatility increasing For context we take quarterly snapshots of time series and cross-sectional readings over the last 10 years and plot them below. Today s reading is highlighted in red. The current market is still much more subdued than what we saw through the GFC and also the European debt crisis that began to stabilise in Fig 9 Time series and cross sectional volatility intersect by quarter (current in red) Current Period 23 September

5 Average Information Co-efficient Macquarie Wealth Management The volatility also impacts investment style returns. We show below the returns to styles grouped into different volatility regimes. In periods of high volatility, investors retreat to safety favouring Earnings Certainty, Large Caps, Dividend payers and stocks with good profitability (ROE). Fig 10 Style returns in high vs low volatility regimes (2010 to present) PE Ratio Dividend Yield 12m Momentum 3m Earnings Revisions ROE Low Volatility Size (Large over Small) Eanrings Certainty 12% 10% Investors resort to Quality in high Volatility environments 8% 6% 4% 2% 0% -2% -4% -6% Low Market Volatility Mid High Market Volatility Regimes of High, Low and Mid market volatility are defined by the trailing market volatility. High is the top 25% of observations and low the bottom 25%. What about uncertainty? Volatility is just one way to measure risk. In our most recent Quantamentals note we examine the concept of Uncertainty which identifies something different. Risk and uncertainty are often used interchangeably to refer to the unpredictable future outcomes that we are not sure about. According to Knight 1 however, there is a well-defined distinction between risk and uncertainty: risk is present when future events occur with measurable probability; while uncertainty is defined as people s inability to forecast the likelihood of events happening. In other words, in contrast to risk for which we know probability distribution over known events (to flip a coin, for example), uncertainty applies when it is hard to assign a sensible probability distribution to this. In the report, we introduce new novel ways to measure uncertainty including: o o Macroeconomic Uncertainty measured by the dispersions in professional forecasters views about future macroeconomic outcomes; Economic Policy Uncertainty measured by volumes of policy-related uncertainty news discussed in public newspapers; A time series of each index is plotted below with a noticeable increase occurring in recent times. Fig 11 Macroeconomic Uncertainty index Fig 12 Economic Policy Uncertainty index 1 Knight, F. H. (1921) Risk, Uncertainty, and Profit. Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin Company 23 September

6 We then estimate stock sensitivities to these uncertainty indices and find that the signal is predictive of cross-sectional stock returns: stocks with greater exposures to uncertainty underperform. A summary of global results is in the figure below. The signal also exhibits low correlation to traditional risk measures such as volatility and beta. See the full report for further details. Fig 13 Performance summary of Uncertainty signal stock selection strategy The uncertainty indices have spiked in recent times similar to the volatility levels of markets. The big macro and policy focus over the coming months remains US interest rates. Broadly there is an expectation that the FED will raise interest rates however the timing of the increase and impact on markets remains a point of debate. Thus we anticipate uncertainty to continue. Stocks that will benefit from uncertainty So how can investors benefit from increasing uncertainty? We screen for stocks below that have a low sensitivity to Uncertainty (should perform well). We include also the stock s score from the Macquarie Alpha model and a downside and upside beta that simply shows the stock s beta on positive or negative market days over the last 6 months. Fig 14 Stocks that perform well in a high uncertainty environment Ticker Company name Combined Alpha and Uncertainty (higher = better) Alpha Rank (higher = better) Macro Uncertainty (lower = better) Downside Beta (Last 6M) Upside Beta (Last 6M) ALL AU ARISTOCRAT LEISURE 93% 97% 10% TLS AU TELSTRA CORP LTD 87% 84% 9% TPM AU TPG TELECOM LTD 87% 86% 13% CSL AU CSL 86% 82% 11% SGP AU STOCKLAND 83% 81% 14% FDC AU FEDERATION CENTRES 81% 83% 21% RMD AU RESMED INC 77% 63% 8% CTX AU CALTEX AUSTRALIA 77% 84% 29% WES AU WESFARMERS LTD 76% 72% 20% BOQ AU BK OF QUEENSLAND 75% 88% 38% GPT AU GPT GROUP 72% 73% 28% AMC AU AMCOR LIMITED 72% 70% 26% MGR AU MIRVAC GROUP 72% 64% 21% SYD AU SYDNEY AIRPORT 71% 63% 22% DLX AU DULUXGROUP LTD 67% 67% 33% AZJ AU AURIZON HOLDINGS 64% 95% 68% GMG AU GOODMAN GROUP 63% 68% 42% IFL AU IOOF HOLDINGS LTD 61% 83% 60% COH AU COCHLEAR LTD 61% 49% 27% AGL AU AGL ENERGY 60% 85% 65% DXS AU DEXUS PROPERTY GP 60% 58% 38% September

7 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 First South - 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 Banks/Insurance = 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 30 June 2015 AU/NZ Asia RSA USA CA EUR Outperform 46.23% 58.36% 47.27% 44.20% 60.65% 43.01% (for US coverage by MCUSA, 9.68% of stocks followed are investment banking clients) Neutral 37.67% 25.65% 29.09% 49.29% 34.19% 40.93% (for US coverage by MCUSA, 5.53% of stocks followed are investment banking clients) Underperform 16.10% 15.99% 23.64% 6.52% 5.16% 16.06% (for US coverage by MCUSA, 1.38% 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 Ltd 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 No ) a Participant of the Australian Securities Exchange (ASX) and Chi-X Australia Pty Limited. This research is distributed in Australia by Macquarie Equities Limited (ABN , AFSL No ) ("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. Macquarie Bank Limited (ABN , AFSL No ) ( MBL ) is a company incorporated in Australia and authorised under the Banking Act 1959 (Australia) to conduct banking business in Australia. None of MBL, MGL or MENZ is registered as a bank in New Zealand by the Reserve Bank of New Zealand under the Reserve Bank of New Zealand Act Any MGL subsidiary noted in this research, apart from MBL, is not an authorised deposit-taking institution for the purposes of the Banking Act 1959 (Australia) and that subsidiary s obligations do not represent deposits or other liabilities of MBL. MBL does not guarantee or otherwise provide assurance in respect of the obligations of that subsidiary, unless noted otherwise. This research is general advice and does not take account of your objectives, financial situation or needs. Before acting on this general advice, you should consider the appropriateness of the advice having regard to your situation. We recommend you obtain financial, legal and taxation advice before making any financial investment decision. 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