1 00:00:03,200 --> 00:00:07,800 Speaker 1: Broadcasting live to New York, Bloomberg even to Washington, d C. 2 00:00:08,000 --> 00:00:13,280 Speaker 1: Bloomber to Boston, Bloomberg twelve hundred to San Francisco, Bloomberg 3 00:00:14,120 --> 00:00:18,520 Speaker 1: to the Country General one and around the globe the 4 00:00:18,560 --> 00:00:23,079 Speaker 1: Bloomberg Radio Plus happened, Bloomberg got gone. This is taking Stock. 5 00:00:23,520 --> 00:00:26,440 Speaker 1: Coming up on taking Stock. Will be speaking with Margaret Tolla, 6 00:00:26,880 --> 00:00:30,560 Speaker 1: is our White House correspondent for Bloomberg News, to be 7 00:00:30,600 --> 00:00:32,239 Speaker 1: giving us a little bit of a wrap up of 8 00:00:32,360 --> 00:00:35,320 Speaker 1: last night's debate and find out what's next for the candidates. 9 00:00:36,720 --> 00:00:39,279 Speaker 1: That's a very interesting question, isn't it. PM. Let's get 10 00:00:39,360 --> 00:00:41,519 Speaker 1: right to Charlie Pelton news room. He's got a Bloomberg 11 00:00:41,520 --> 00:00:44,440 Speaker 1: business flash and I thank you very much. Kathleen Hayes, 12 00:00:44,479 --> 00:00:47,040 Speaker 1: thank you, pim Fox, the dal V, SMP, NEZ DAK 13 00:00:47,120 --> 00:00:49,960 Speaker 1: all trading close to the best level of the day. 14 00:00:50,159 --> 00:00:53,720 Speaker 1: Stocks are advancing after last night's presidential debate. If you 15 00:00:53,800 --> 00:00:55,920 Speaker 1: tuned in, you know that one of the topics that 16 00:00:56,000 --> 00:00:59,040 Speaker 1: came up last night was the Federal Reserve. The said 17 00:00:59,320 --> 00:01:02,360 Speaker 1: is doing political by keeping the interest rate at this level. 18 00:01:02,680 --> 00:01:05,360 Speaker 1: And believe me, the day Obama goes off and he 19 00:01:05,440 --> 00:01:07,120 Speaker 1: leaves and he goes out to the golf course for 20 00:01:07,160 --> 00:01:09,520 Speaker 1: the rest of his life to play golf. When they 21 00:01:09,600 --> 00:01:12,720 Speaker 1: raise interest Rich, You're gonna see some very bad things 22 00:01:12,720 --> 00:01:15,200 Speaker 1: happen because the Fed is not doing the job. The 23 00:01:15,280 --> 00:01:20,000 Speaker 1: FED is being more political than Secretary Clinton. Well, what 24 00:01:20,080 --> 00:01:23,120 Speaker 1: about a Trump presidency and the Federal Reserve. Dana Peterson 25 00:01:23,240 --> 00:01:25,800 Speaker 1: is an economist at City Group Global Markets, and she 26 00:01:26,000 --> 00:01:29,360 Speaker 1: was interviewed this morning on Bloomberg Television. Well, Mr Trump 27 00:01:29,400 --> 00:01:33,920 Speaker 1: has indicated that potentially Janet Yellen would not be the 28 00:01:33,959 --> 00:01:37,080 Speaker 1: second would not experience a second term. Do we think 29 00:01:37,120 --> 00:01:39,679 Speaker 1: that she would He would try to oust her in 30 00:01:39,760 --> 00:01:42,200 Speaker 1: the first year of his term and also the last 31 00:01:42,240 --> 00:01:44,640 Speaker 1: year of her term. Most likely not, but we would 32 00:01:44,680 --> 00:01:49,200 Speaker 1: expect that he probably choose a federal governor um a sorry, 33 00:01:49,200 --> 00:01:55,559 Speaker 1: a terror person who might potentially uh handle monetary policy 34 00:01:55,560 --> 00:01:59,000 Speaker 1: a little bit differently. Delta Airlines studying a purchase of 35 00:01:59,120 --> 00:02:01,960 Speaker 1: roomier regional jets with a list value of as much 36 00:02:02,000 --> 00:02:05,120 Speaker 1: as two point three billion dollars, provided the company can 37 00:02:05,160 --> 00:02:08,080 Speaker 1: get the pilots union to accept an overhaul of the 38 00:02:08,320 --> 00:02:12,320 Speaker 1: small plane fleet. Delta shares they're advancing today by two 39 00:02:12,320 --> 00:02:16,240 Speaker 1: point eight percent. Airline stocks are rallying SMP five hundred 40 00:02:16,280 --> 00:02:19,480 Speaker 1: index up thirteen fifty nine, a gain there of six 41 00:02:19,520 --> 00:02:22,480 Speaker 1: tenths of one percent. Down Industrial is up one thirty 42 00:02:22,520 --> 00:02:24,880 Speaker 1: now a gain of seven tenths of one percent, and 43 00:02:24,919 --> 00:02:27,560 Speaker 1: has stack up nine tenths of one percent. The tenure 44 00:02:27,840 --> 00:02:30,920 Speaker 1: up seven thirty seconds, the yield one point five six percent, 45 00:02:31,320 --> 00:02:34,200 Speaker 1: Gold down twelve fifty, the ounce dropping nine tenths of 46 00:02:34,200 --> 00:02:37,480 Speaker 1: one percent, and crude oil and West Texas Intermediate down 47 00:02:37,520 --> 00:02:40,960 Speaker 1: two point seven percent to forty four sixty eight. And 48 00:02:41,000 --> 00:02:42,720 Speaker 1: now let's take a look at some of the other 49 00:02:42,800 --> 00:02:46,640 Speaker 1: stories making news. Thank you Charlie from the Bloomberg News Room. 50 00:02:46,680 --> 00:02:49,120 Speaker 1: I'm Rami in a cent cio. This news update is 51 00:02:49,120 --> 00:02:51,639 Speaker 1: brought to you by your Mercedes Benz Tri State Dealer 52 00:02:51,880 --> 00:02:55,480 Speaker 1: Experience the twenty seventeen Mercedes Benz g LC at your 53 00:02:55,520 --> 00:02:58,720 Speaker 1: Mercedes Benz Tri State Dealer. It has something make that 54 00:02:58,880 --> 00:03:01,919 Speaker 1: everything for every one. Go to m b USA dot 55 00:03:01,919 --> 00:03:05,920 Speaker 1: com for details. President Obama says last night's presidential debate 56 00:03:05,960 --> 00:03:09,440 Speaker 1: demonstrated a sharp contrast between the candidates. Speaking on on 57 00:03:09,600 --> 00:03:12,240 Speaker 1: air with Ryan Seacrest, the President said he encounter shows 58 00:03:12,240 --> 00:03:15,240 Speaker 1: Donald Trump, in his words, doesn't have the preparation, the temperament, 59 00:03:15,360 --> 00:03:19,520 Speaker 1: or the core values to be president. I'm admittedly biased. 60 00:03:19,560 --> 00:03:22,840 Speaker 1: I have worked with Gillary. I know her. Uh. She 61 00:03:23,040 --> 00:03:26,240 Speaker 1: is well prepared. She's got the right temperament for the job. 62 00:03:26,360 --> 00:03:29,359 Speaker 1: She's well respected around the world. She's serious, she does 63 00:03:29,400 --> 00:03:32,240 Speaker 1: her homework. Last night's Face Off delivered a likely contender 64 00:03:32,320 --> 00:03:35,480 Speaker 1: for one of the year's biggest TV events, but Bloomberg's 65 00:03:35,480 --> 00:03:37,840 Speaker 1: Bomb Moon reports we don't yet know if it was 66 00:03:37,920 --> 00:03:42,360 Speaker 1: the most watch debate ever. The initial partial ratings from ABC, CBS, NBC, 67 00:03:42,480 --> 00:03:46,000 Speaker 1: and Fox or of over the first Obama Romney debate 68 00:03:46,040 --> 00:03:48,480 Speaker 1: four years ago, which was watched by about forty six 69 00:03:48,560 --> 00:03:51,480 Speaker 1: million people. According to The Hollywood Reporter, That puts this 70 00:03:51,520 --> 00:03:53,720 Speaker 1: event on track to be a record center or very 71 00:03:53,760 --> 00:03:55,720 Speaker 1: close to an all time high, though it may fall 72 00:03:55,800 --> 00:03:58,720 Speaker 1: short of the one million mark. Those Big four overnight 73 00:03:58,800 --> 00:04:02,360 Speaker 1: ratings don't include p yes, cable, online streaming, or other sources. 74 00:04:02,480 --> 00:04:05,520 Speaker 1: Those estimates should come tomorrow. The first Carter Reagan debate 75 00:04:05,560 --> 00:04:07,960 Speaker 1: in the nineteen eight election was watched by a record 76 00:04:08,000 --> 00:04:11,680 Speaker 1: eighteen million viewers. Bob Moon, Bloomberg, Radio, and public school 77 00:04:11,680 --> 00:04:14,320 Speaker 1: students from low income families will no longer have to 78 00:04:14,320 --> 00:04:16,400 Speaker 1: pay a fee to apply to the City University of 79 00:04:16,400 --> 00:04:18,440 Speaker 1: New York. Official say the move is part of an 80 00:04:18,480 --> 00:04:21,359 Speaker 1: effort to encourage more young people to go to college. 81 00:04:21,720 --> 00:04:23,760 Speaker 1: Global News twenty four hours a day, powered by more 82 00:04:23,760 --> 00:04:27,479 Speaker 1: than journalists and analysts in more than one hundred twenty countries. 83 00:04:27,640 --> 00:04:31,599 Speaker 1: I'm Rainey in Essencio. This is Bloomberg, Charlie, and we 84 00:04:31,680 --> 00:04:35,159 Speaker 1: thank you and again recapping US equities are advancing SMP 85 00:04:35,320 --> 00:04:39,719 Speaker 1: five hundred index up nine, a gain of six tenths 86 00:04:39,720 --> 00:04:43,120 Speaker 1: of one percent. I'm Charlie Pellett and that's a Bloomberg 87 00:04:43,160 --> 00:04:46,839 Speaker 1: business flash. This is taking stock with Bim Fox and 88 00:04:46,960 --> 00:04:51,960 Speaker 1: Kathleen Hayes on Bloomberg Radio. Dal Trump had one job. 89 00:04:52,320 --> 00:04:55,760 Speaker 1: Don't take the bait, but let Hillary Clinton get under 90 00:04:55,760 --> 00:04:59,440 Speaker 1: his skin minutes into their first presidential debate Monday night, 91 00:04:59,800 --> 00:05:04,640 Speaker 1: so writes Margaret Talent, Bloomberg News White House Correspondent. In 92 00:05:04,680 --> 00:05:07,480 Speaker 1: her piece, co written was Sahil Kapoor on the Bloomberg 93 00:05:07,520 --> 00:05:10,920 Speaker 1: Today on Bloomberg dot Com. Margaret joins us, Now if 94 00:05:11,080 --> 00:05:16,719 Speaker 1: it's interesting, Margaret, because after the Democratic National Convention, when 95 00:05:16,960 --> 00:05:22,040 Speaker 1: the Muslim American UH family spoke about their son who 96 00:05:22,120 --> 00:05:24,719 Speaker 1: was killed in action, there was a very interesting peace 97 00:05:24,760 --> 00:05:28,720 Speaker 1: online comparing Hillary Clinton to a very skilled matador who 98 00:05:28,760 --> 00:05:31,599 Speaker 1: had manipulated the bull in the ring Donald Trump to 99 00:05:31,680 --> 00:05:34,560 Speaker 1: take the bait. Is your sense according to your story, 100 00:05:34,560 --> 00:05:36,520 Speaker 1: it seems it is that this happened again last night. 101 00:05:37,160 --> 00:05:39,440 Speaker 1: It's so interesting that you compare the two, because I 102 00:05:39,440 --> 00:05:42,440 Speaker 1: think we are seeing a lot of that today in 103 00:05:42,600 --> 00:05:47,040 Speaker 1: terms of uh, Mr Trump's treatment of Alicia Machado, this 104 00:05:47,160 --> 00:05:50,559 Speaker 1: former Miss Universe contestant who at the time when Trump 105 00:05:50,760 --> 00:05:53,200 Speaker 1: oh the Miss Universe pageant, he was critical of her 106 00:05:53,360 --> 00:05:57,640 Speaker 1: weight gain and rather than kind of, you know, I say, hey, 107 00:05:57,640 --> 00:06:00,120 Speaker 1: that was a long time ago, I know, apologize or 108 00:06:00,200 --> 00:06:04,200 Speaker 1: my statements, or saying something like books she's entitled her opinion, 109 00:06:04,360 --> 00:06:07,640 Speaker 1: let's move on, sort of doubling down on her, saying, hey, 110 00:06:07,720 --> 00:06:09,479 Speaker 1: you know the business man and there was a big 111 00:06:09,480 --> 00:06:11,520 Speaker 1: problem she gave the massive amount of weight. And this 112 00:06:11,640 --> 00:06:13,760 Speaker 1: does have sort of echoes to what happened there with 113 00:06:13,800 --> 00:06:17,040 Speaker 1: the con family, where these are grieving parents, obviously entitled 114 00:06:17,040 --> 00:06:19,960 Speaker 1: to their opinions, and rather than just sort of let 115 00:06:19,960 --> 00:06:22,800 Speaker 1: it go, he decided to engage with them and uh 116 00:06:23,000 --> 00:06:25,640 Speaker 1: and criticize them for criticizing him. That didn't bode well 117 00:06:25,680 --> 00:06:28,960 Speaker 1: for him in those days after the convention, um, you know, 118 00:06:29,040 --> 00:06:31,480 Speaker 1: and Hillary Clinton is hoping to kind of take maximum 119 00:06:31,560 --> 00:06:35,359 Speaker 1: advantage of that today coming out of that debate, Margaret, 120 00:06:35,600 --> 00:06:39,599 Speaker 1: What are negative emotion words? Uh? And what and what 121 00:06:39,640 --> 00:06:41,720 Speaker 1: are they? What are they and why are they noteworthy? 122 00:06:42,800 --> 00:06:46,559 Speaker 1: They're noteworthy for two reasons. Uh. One is to watch 123 00:06:46,600 --> 00:06:49,159 Speaker 1: the pace and the sort of propensity with which they're 124 00:06:49,200 --> 00:06:51,800 Speaker 1: used in the debate and in others because they give 125 00:06:51,800 --> 00:06:54,520 Speaker 1: you a sense of how a candidate is trying to win. 126 00:06:54,560 --> 00:06:56,880 Speaker 1: Are they trying to sell a positive message of themselves 127 00:06:56,960 --> 00:06:59,680 Speaker 1: or a negative message of their opponent on both fronts. 128 00:07:00,080 --> 00:07:02,919 Speaker 1: What you see from sort of an initial survey of 129 00:07:03,360 --> 00:07:05,880 Speaker 1: you know, the words use last night is that Donald 130 00:07:05,920 --> 00:07:09,880 Speaker 1: Trump uh was turning increasingly to negative words as as 131 00:07:09,880 --> 00:07:12,360 Speaker 1: the debate got worse for him. And this is look, 132 00:07:12,440 --> 00:07:16,000 Speaker 1: this has been actually a tactic of both phenomenes, because 133 00:07:16,160 --> 00:07:19,600 Speaker 1: neither one of them is particularly like beloved by anyone 134 00:07:19,640 --> 00:07:22,120 Speaker 1: outside of a core base, right and so they've both 135 00:07:22,120 --> 00:07:26,160 Speaker 1: found up until now more success and kind of uh 136 00:07:26,360 --> 00:07:29,160 Speaker 1: addressing the other one down raising concerns about the other 137 00:07:29,200 --> 00:07:33,200 Speaker 1: one than in burnishing their own positive image. Hillary Clinton 138 00:07:33,600 --> 00:07:36,120 Speaker 1: may have an opportunity coming out of this debate to 139 00:07:36,200 --> 00:07:39,640 Speaker 1: sell a more positive image of herself, both to the 140 00:07:39,680 --> 00:07:41,960 Speaker 1: places where she should be strong, like the woman's vote, 141 00:07:41,960 --> 00:07:45,000 Speaker 1: and the places where she's really had trouble men, middle 142 00:07:45,000 --> 00:07:49,200 Speaker 1: class voters, working class voters, and young people. She's trying 143 00:07:49,200 --> 00:07:51,560 Speaker 1: to see that windows now. She hasn't had much success 144 00:07:51,640 --> 00:07:53,680 Speaker 1: until now. You know, Margaret, I just have a hard 145 00:07:53,680 --> 00:07:56,400 Speaker 1: time figuring out what people really think about who won, 146 00:07:56,480 --> 00:07:59,240 Speaker 1: and I'll tell you why. For example, are Bloomberg News 147 00:07:59,280 --> 00:08:02,600 Speaker 1: story quotes, CNN snap poll finding a six voters who 148 00:08:02,600 --> 00:08:05,520 Speaker 1: watched the Clinton won the debate for Trump. Now I'm 149 00:08:05,520 --> 00:08:09,760 Speaker 1: looking at another thing, the Drudge Reports online vote. Let's 150 00:08:09,800 --> 00:08:13,520 Speaker 1: see said trump one. Uh, if you look at a 151 00:08:13,520 --> 00:08:17,760 Speaker 1: Fox News online vote, trump won with of respondents. Is 152 00:08:17,760 --> 00:08:21,160 Speaker 1: there a definitive pole or polls that we can say, well, 153 00:08:21,640 --> 00:08:25,720 Speaker 1: this wasn't somehow self selective in terms of the nation's 154 00:08:25,800 --> 00:08:28,280 Speaker 1: view of who won. Or is it just impossible because 155 00:08:28,280 --> 00:08:32,760 Speaker 1: everyone so polarized. Well, certainly when you have online or 156 00:08:32,760 --> 00:08:36,880 Speaker 1: sort of instant polling, who's participating, you know matters. Typically 157 00:08:36,920 --> 00:08:38,839 Speaker 1: it takes a few days for the results of something 158 00:08:38,880 --> 00:08:41,640 Speaker 1: like this to really settle in terms of how much 159 00:08:41,679 --> 00:08:44,200 Speaker 1: does it shape people thinking going forward. The one area 160 00:08:44,240 --> 00:08:46,680 Speaker 1: where Trump did do very well in the debate was 161 00:08:46,720 --> 00:08:48,920 Speaker 1: sort of that first twenty minutes to thirty minute window 162 00:08:48,920 --> 00:08:51,679 Speaker 1: where he was going after Hillary Clinton aggressively on her 163 00:08:51,800 --> 00:08:55,200 Speaker 1: support of trade and her husband's support of trade policies 164 00:08:55,280 --> 00:08:57,439 Speaker 1: during his time as president, and the idea that that 165 00:08:57,520 --> 00:09:01,040 Speaker 1: had helped to undercut job stability ages in some key 166 00:09:01,040 --> 00:09:04,360 Speaker 1: battleground states like Ohio and some places that Trump is 167 00:09:04,400 --> 00:09:07,760 Speaker 1: hoping to take away from Clinton, Michigan, Wisconsin, that sort 168 00:09:07,800 --> 00:09:10,200 Speaker 1: of thing, if that ends up being what stuck you 169 00:09:10,240 --> 00:09:14,040 Speaker 1: could have I suppose a really sort of uh, you know, 170 00:09:14,320 --> 00:09:17,960 Speaker 1: going against conventional wisdom. Uh. Look, if if Donald Trump 171 00:09:18,000 --> 00:09:21,120 Speaker 1: is to make key games in key battleground states with 172 00:09:21,360 --> 00:09:24,760 Speaker 1: formerly Democratic working class voters, then none of the rest 173 00:09:24,760 --> 00:09:27,200 Speaker 1: of it matters. But the problem for him is that 174 00:09:27,280 --> 00:09:29,520 Speaker 1: he actually needs to be picking up states, not just 175 00:09:29,640 --> 00:09:34,280 Speaker 1: holding states from from Romney's performance in twelve and sort 176 00:09:34,280 --> 00:09:36,200 Speaker 1: of the general thought coming out of this debate is 177 00:09:36,240 --> 00:09:38,839 Speaker 1: that although he did well on sort of the trade, jobs, 178 00:09:38,920 --> 00:09:42,200 Speaker 1: economy issues, uh, he bungled so many things when it 179 00:09:42,200 --> 00:09:45,240 Speaker 1: comes to two women and minorities and and kind of 180 00:09:45,280 --> 00:09:48,840 Speaker 1: maybe sort of centrist um moderate Republicans that he may 181 00:09:48,880 --> 00:09:52,520 Speaker 1: have done himself more harm than good market. Just quickly, here, 182 00:09:52,520 --> 00:09:54,480 Speaker 1: I'm going to give you a couple of states. Tell 183 00:09:54,559 --> 00:09:59,360 Speaker 1: of your thoughts. Because it's Wisconsin, Illinois, Indiana, Pennsylvania and 184 00:09:59,440 --> 00:10:03,120 Speaker 1: New hamps Sure, what is what is common? Democrats are 185 00:10:03,200 --> 00:10:08,520 Speaker 1: likely to pick off some Senate seats. Yeah, look, those 186 00:10:08,559 --> 00:10:12,760 Speaker 1: are all really interesting states for different reasons. Uh, the Democrats, 187 00:10:13,200 --> 00:10:15,200 Speaker 1: if it came down to a very close race, New 188 00:10:15,200 --> 00:10:18,480 Speaker 1: Hampshire could actually be very important and interesting. Democrats have 189 00:10:18,559 --> 00:10:22,200 Speaker 1: to think about holding Pennsylvania for presidential purposes. Anything after that, 190 00:10:22,280 --> 00:10:25,480 Speaker 1: it's gravy. Donald Trump's betting on two places that I 191 00:10:25,480 --> 00:10:29,120 Speaker 1: would watch look at look at Florida and look at 192 00:10:29,160 --> 00:10:31,920 Speaker 1: that kind of area right up by Michigan and Wisconsin 193 00:10:32,280 --> 00:10:34,880 Speaker 1: for the Democrats. Uh, the sent its great, but the 194 00:10:34,880 --> 00:10:37,920 Speaker 1: president and surprise and that was all about Still, thank 195 00:10:37,960 --> 00:10:41,440 Speaker 1: you very much. Margaret tal of White House, correspondent for 196 00:10:41,520 --> 00:10:45,319 Speaker 1: Bloomberg News, joining us from Washington, d C. Homes of 197 00:10:45,360 --> 00:10:48,760 Speaker 1: Bloomberg's one and one oh five point seven h D two. 198 00:10:48,920 --> 00:10:52,439 Speaker 1: You can follow Margaret on Twitter at Margaret Tala t 199 00:10:52,679 --> 00:10:56,600 Speaker 1: A L e V. 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