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If Bloomberg 2 00:00:06,559 --> 00:00:09,640 Speaker 1: dot Com the Radio plus Mobile act and on your radio. 3 00:00:09,920 --> 00:00:14,240 Speaker 1: This is a Bloomberg Business Flash from Bloomberg World Handquarters. 4 00:00:14,240 --> 00:00:17,720 Speaker 1: Sim Charlie tell us, the DAL, the smpneztack Hall declining 5 00:00:17,760 --> 00:00:20,040 Speaker 1: today and this subtat is brought to you by Sector 6 00:00:20,079 --> 00:00:23,680 Speaker 1: Spider e t fs y by a single stock when 7 00:00:23,760 --> 00:00:26,400 Speaker 1: you can invest in the entire sector of visits sector 8 00:00:27,000 --> 00:00:29,240 Speaker 1: sp d r S dot com or call one A 9 00:00:29,480 --> 00:00:33,280 Speaker 1: six six sector e t F A move lore for 10 00:00:33,360 --> 00:00:36,320 Speaker 1: u S equities today, as investors await next week's Federal 11 00:00:36,360 --> 00:00:40,120 Speaker 1: Reserve meeting, economic indicators pointing to uneven growth in the 12 00:00:40,200 --> 00:00:44,720 Speaker 1: US economy. Banks and energy producers carrying the steepest losses today. 13 00:00:45,040 --> 00:00:48,440 Speaker 1: Crude oil down one point six percent. West Texas Intermediate 14 00:00:48,440 --> 00:00:51,320 Speaker 1: now at forty three twenty two of barrel down sixty 15 00:00:51,400 --> 00:00:55,120 Speaker 1: nine cents, Gold down four sixty VONN stropping four tents, 16 00:00:55,160 --> 00:00:58,120 Speaker 1: up one percent, the thirteen O nine the Tenure up 17 00:00:58,120 --> 00:01:02,400 Speaker 1: one thirty second with the yield of one point Equities lower, 18 00:01:02,520 --> 00:01:06,800 Speaker 1: SMP five index down eight nine I dropped. There are 19 00:01:06,800 --> 00:01:10,039 Speaker 1: four tenths of one percent down. Industrials down eighty eight 20 00:01:10,040 --> 00:01:12,800 Speaker 1: points a drop of five tenths of one percent. I'm 21 00:01:12,880 --> 00:01:17,600 Speaker 1: Charlie Pellett, and that's a Bloomberg Business flash. You're listening, 22 00:01:17,640 --> 00:01:21,200 Speaker 1: you're taking stock with Pim Box at Kathleen Hayes on 23 00:01:21,319 --> 00:01:25,520 Speaker 1: Bloomberg Radio. This is taking stock. I'm Pim Fox. Well, 24 00:01:25,600 --> 00:01:30,240 Speaker 1: what about exchange traded funds that say that they can 25 00:01:30,240 --> 00:01:34,920 Speaker 1: outsmart the market? Well, that might be called smart beta. 26 00:01:35,160 --> 00:01:38,120 Speaker 1: What is it? Does it really work? Let's find out 27 00:01:38,160 --> 00:01:41,920 Speaker 1: more from Melissa Brown, Senior director of Applied Research at 28 00:01:42,040 --> 00:01:46,480 Speaker 1: Axioma Axioma's Buyer Beware Research. Tell us more about this, 29 00:01:46,560 --> 00:01:52,840 Speaker 1: Melissa Brown, Hi, Yes, Well, the buyer beware really refers 30 00:01:52,880 --> 00:01:56,800 Speaker 1: to um the fact that many funds, many of these 31 00:01:57,040 --> 00:01:59,760 Speaker 1: so called smart beta E t F that have very 32 00:02:00,000 --> 00:02:02,440 Speaker 1: similar names, let's say they all have high dividend yield 33 00:02:02,440 --> 00:02:05,960 Speaker 1: in the name, actually look extremely different from each other. 34 00:02:06,600 --> 00:02:10,400 Speaker 1: And alternately, when many have very similar names are very 35 00:02:10,440 --> 00:02:13,440 Speaker 1: different names, they actually look quite similar to each other. 36 00:02:13,960 --> 00:02:16,880 Speaker 1: So you really need to dig a little deeper into 37 00:02:17,880 --> 00:02:21,280 Speaker 1: what's driving the returns in the fund to really understand 38 00:02:21,320 --> 00:02:23,959 Speaker 1: if you're getting something that's the same or different. Certainly, 39 00:02:24,040 --> 00:02:27,160 Speaker 1: certainly sounds to sounds like it makes a perfect sense. 40 00:02:27,200 --> 00:02:30,480 Speaker 1: But what if you could describe what is beta and 41 00:02:30,680 --> 00:02:34,600 Speaker 1: what is smart beta when it comes to exchange traded funds. Ah. Yes, 42 00:02:35,120 --> 00:02:40,440 Speaker 1: so beta refers to having some exposure to some source 43 00:02:40,560 --> 00:02:44,280 Speaker 1: of systematic return. In other words, if you think that 44 00:02:44,639 --> 00:02:47,840 Speaker 1: stocks that are cheaper are going to outperform stocks that 45 00:02:47,880 --> 00:02:51,560 Speaker 1: are more expensive, in other words, value stocks should do well, 46 00:02:52,280 --> 00:02:57,240 Speaker 1: then um a stocks how it stock looks in terms 47 00:02:57,280 --> 00:03:01,560 Speaker 1: of its value score or its exposure or um That 48 00:03:01,800 --> 00:03:05,480 Speaker 1: is what it's beta is, its sensitivity to the movement 49 00:03:05,520 --> 00:03:10,080 Speaker 1: in that factor. Smart data is a term, and there's 50 00:03:10,120 --> 00:03:14,120 Speaker 1: many other terms systematic beta and many other ways of 51 00:03:14,160 --> 00:03:19,320 Speaker 1: describing this, but smart data is um a way of 52 00:03:19,639 --> 00:03:23,160 Speaker 1: getting that kind of exposure, getting that kind of systematic 53 00:03:23,240 --> 00:03:28,800 Speaker 1: return um to and using factors that are expected to 54 00:03:28,840 --> 00:03:32,239 Speaker 1: outperform the market, whether it's value or momentum or high 55 00:03:32,280 --> 00:03:35,440 Speaker 1: dived in yield or low volatility or you know. I 56 00:03:35,480 --> 00:03:38,200 Speaker 1: could go on and on. There are many different categories, 57 00:03:38,240 --> 00:03:40,960 Speaker 1: but those all kind of generally fall into this idea 58 00:03:41,000 --> 00:03:44,480 Speaker 1: of smart data. Would it also would would another not 59 00:03:44,880 --> 00:03:48,680 Speaker 1: another but an additional definition of this? Would it be 60 00:03:49,280 --> 00:03:54,080 Speaker 1: invest an investment strategy that puts the emphasis on the 61 00:03:54,200 --> 00:03:59,480 Speaker 1: use of alternative index construction rules rather than more traditional 62 00:04:00,200 --> 00:04:06,240 Speaker 1: UH market based industries like market capitalization or or market price. 63 00:04:06,320 --> 00:04:09,880 Speaker 1: I mean doesn't that kind of it emphasizes capturing these 64 00:04:09,920 --> 00:04:13,920 Speaker 1: factors or inefficiencies and then turning them into rules in 65 00:04:14,560 --> 00:04:19,680 Speaker 1: ways that people can understand exactly. So they may a 66 00:04:19,720 --> 00:04:22,920 Speaker 1: manager may take let's say the hundred most attractive stocks 67 00:04:22,960 --> 00:04:26,800 Speaker 1: and equally wait them, or they may wait them by 68 00:04:27,000 --> 00:04:30,360 Speaker 1: their exposure. So the highest dividend yielding stock, it's the 69 00:04:30,440 --> 00:04:33,400 Speaker 1: highest weight in the portfolio. So there's there are a 70 00:04:33,480 --> 00:04:36,400 Speaker 1: number of different ways, um that you can wait them 71 00:04:36,440 --> 00:04:39,840 Speaker 1: that are you're, as you said, it's absolutely right, going 72 00:04:39,880 --> 00:04:42,360 Speaker 1: to move them away from the index, or they're gonna 73 00:04:42,360 --> 00:04:45,000 Speaker 1: look very different, even if they have the same names. 74 00:04:45,160 --> 00:04:47,320 Speaker 1: That waiting scheme in and of itself is going to 75 00:04:47,400 --> 00:04:52,000 Speaker 1: make them look very different. Why are they attractive now, Well, 76 00:04:52,400 --> 00:04:55,960 Speaker 1: they are. First of all, many of these types of 77 00:04:56,040 --> 00:05:01,919 Speaker 1: portfolios have actually outperformed broader major market indices. So that's 78 00:05:01,960 --> 00:05:05,240 Speaker 1: that's one reason. So they have that the performance wind 79 00:05:05,279 --> 00:05:10,039 Speaker 1: at their backs. Another reason is that, um, I think 80 00:05:10,279 --> 00:05:13,359 Speaker 1: personally that you put smart in the name of something 81 00:05:13,800 --> 00:05:18,200 Speaker 1: and it at least attracts people's attention whether um, you know, 82 00:05:18,240 --> 00:05:21,080 Speaker 1: whether in fact it's smart or not right full full 83 00:05:21,160 --> 00:05:25,599 Speaker 1: marks for marketing. Yes, exactly, exactly, And in fact, what 84 00:05:25,720 --> 00:05:28,640 Speaker 1: a lot of these funds do are no different from 85 00:05:28,680 --> 00:05:32,440 Speaker 1: what a lot of quantitatively driven or systematic managers have 86 00:05:32,520 --> 00:05:35,440 Speaker 1: done for years and years and years. Uh. They've just 87 00:05:35,560 --> 00:05:38,000 Speaker 1: kind of relabeled it and repackaged it into an e 88 00:05:38,120 --> 00:05:40,600 Speaker 1: t F format, which does make it easier to buy 89 00:05:40,640 --> 00:05:43,040 Speaker 1: and sell, makes it easier to buy and sell, and 90 00:05:43,080 --> 00:05:48,760 Speaker 1: would ostensibly make these products less expensive when compared to 91 00:05:48,800 --> 00:05:53,040 Speaker 1: those managers you just described. Or is that inaccurate? Yes? No, No, 92 00:05:53,400 --> 00:05:56,160 Speaker 1: Usually e t F T smart data e t F 93 00:05:56,800 --> 00:06:02,039 Speaker 1: are less expensive. They because they're so rules based. You know, 94 00:06:02,080 --> 00:06:04,320 Speaker 1: the rules are set up and they can just run. 95 00:06:04,360 --> 00:06:07,960 Speaker 1: You don't really need a manager sifting through the stocks 96 00:06:08,000 --> 00:06:09,919 Speaker 1: that you might be buying and selling, for example. So 97 00:06:09,960 --> 00:06:14,960 Speaker 1: they certainly can be cheaper and um and to some 98 00:06:15,160 --> 00:06:20,080 Speaker 1: extent deliver a similar return, except for that you don't 99 00:06:20,080 --> 00:06:23,360 Speaker 1: have that manager sifting through the stocks that are being 100 00:06:23,400 --> 00:06:26,120 Speaker 1: bought and sold to see if maybe you don't necessarily 101 00:06:26,160 --> 00:06:28,640 Speaker 1: want to buy this one or that one, Melissa, without 102 00:06:29,080 --> 00:06:32,159 Speaker 1: without pushing you to indoors or or or in any way. 103 00:06:32,520 --> 00:06:35,160 Speaker 1: Comment upond performance. Could you just give us an example 104 00:06:35,200 --> 00:06:38,400 Speaker 1: of one of these smart beta ETFs and how they work? 105 00:06:39,200 --> 00:06:42,040 Speaker 1: Um Yeah, so one of the ones that we've done 106 00:06:42,080 --> 00:06:46,360 Speaker 1: a recent study on our high dividend yield and we've 107 00:06:46,480 --> 00:06:49,400 Speaker 1: we looked at a number of different flavors of high 108 00:06:49,400 --> 00:06:55,000 Speaker 1: dividend yield um some are what's really interesting is their differences. 109 00:06:55,040 --> 00:06:57,640 Speaker 1: So some are very heavily weighted in the energy sector, 110 00:06:58,000 --> 00:07:02,039 Speaker 1: for example. Some may be much more heavily weighted in utilities. 111 00:07:02,839 --> 00:07:07,600 Speaker 1: Some are much more evenly distributed across different kinds of sectors. 112 00:07:08,200 --> 00:07:12,040 Speaker 1: Um So. But the thing they have in common is 113 00:07:12,080 --> 00:07:14,360 Speaker 1: they all have high dividend yields, but they get to 114 00:07:14,400 --> 00:07:17,440 Speaker 1: that dividend yield in a different way. So that would 115 00:07:17,440 --> 00:07:21,720 Speaker 1: be kind of one example of the type of fund 116 00:07:21,960 --> 00:07:24,920 Speaker 1: that might be put under the label of smart beta. 117 00:07:25,200 --> 00:07:28,800 Speaker 1: Thank you very much, Melissa Brown, Senior Director of Applied 118 00:07:29,000 --> 00:07:33,840 Speaker 1: Research at Axioma telling us about their buyer beware research 119 00:07:33,880 --> 00:07:36,720 Speaker 1: when it comes to smart beta et f s. Thank 120 00:07:36,760 --> 00:07:39,920 Speaker 1: you for listening to taking Stock. I'm pim Fox and 121 00:07:40,040 --> 00:07:47,920 Speaker 1: this is Bloomberg coming up. 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