1 00:00:02,000 --> 00:00:14,760 Speaker 1: That humans are a species of incredible innovation in art, science, literature. 2 00:00:15,320 --> 00:00:19,480 Speaker 2: Yet of all the things we're brilliant at, investing isn't 3 00:00:19,600 --> 00:00:23,919 Speaker 2: one of them. Why, Well, we're easily excited. We get 4 00:00:23,960 --> 00:00:27,880 Speaker 2: focused on the wrong things, obsessed with what just happened 5 00:00:28,080 --> 00:00:32,519 Speaker 2: rather than what might happen next. We're bad at understanding maths, 6 00:00:32,640 --> 00:00:38,320 Speaker 2: and we despise delaying gratification. Top all of this off 7 00:00:38,720 --> 00:00:42,839 Speaker 2: with unjustified over confidence, and you have a recipe for 8 00:00:43,200 --> 00:00:48,160 Speaker 2: investing underperformance. As it turns out, when it comes to investing, 9 00:00:48,800 --> 00:00:52,199 Speaker 2: we're just not built for it. I'm Barry Redults and 10 00:00:52,240 --> 00:00:55,240 Speaker 2: on today's edition of At the Money, we're going to 11 00:00:55,320 --> 00:01:00,240 Speaker 2: discuss how to become more systematic and rules based in 12 00:01:00,360 --> 00:01:03,680 Speaker 2: managing our money. To help us unpack all of this 13 00:01:03,800 --> 00:01:07,119 Speaker 2: and what it means for your portfolio, let's bring in 14 00:01:07,160 --> 00:01:11,520 Speaker 2: doctor Daniel Crosby. He's the Chief behavior Officer at Orion, 15 00:01:11,640 --> 00:01:15,959 Speaker 2: where he develops tools, training, and technology to help financial 16 00:01:16,000 --> 00:01:21,560 Speaker 2: advisors apply behavioral science in their practice. He is also 17 00:01:21,680 --> 00:01:25,720 Speaker 2: the author of the book The Laws of Wealth, Psychology 18 00:01:25,880 --> 00:01:30,240 Speaker 2: and the Secret to Investing Success. So, Daniel, let's start 19 00:01:30,280 --> 00:01:34,080 Speaker 2: with just a basic idea. Why is a rules based 20 00:01:34,200 --> 00:01:36,800 Speaker 2: approach to managing money. So important. 21 00:01:37,440 --> 00:01:39,800 Speaker 3: Yeah, very good to be with you. Well, one reason 22 00:01:39,880 --> 00:01:42,400 Speaker 3: is because rules work. You know, when we look at 23 00:01:42,400 --> 00:01:45,280 Speaker 3: a meta analysis, so this is a study of all 24 00:01:45,360 --> 00:01:49,440 Speaker 3: the studies on how rules fare. Simple rules fare against 25 00:01:49,720 --> 00:01:55,160 Speaker 3: a PhD level discretionary decision making. Rules match or beat 26 00:01:55,360 --> 00:01:58,760 Speaker 3: expert level decision making ninety four percent of the time, 27 00:01:58,800 --> 00:02:02,680 Speaker 3: which is pretty staff. And we see this across context. 28 00:02:02,720 --> 00:02:06,400 Speaker 3: We see this everywhere from medical diagnosis to stockpicking, to 29 00:02:06,520 --> 00:02:11,440 Speaker 3: financial planning to prison recidivism studies. That one's one of 30 00:02:11,520 --> 00:02:14,640 Speaker 3: my favorite. They went from sort of having these soul 31 00:02:14,720 --> 00:02:18,920 Speaker 3: searching interviews with prisoners to looking at two variables. You know, 32 00:02:19,000 --> 00:02:22,000 Speaker 3: what are they in for and how did they act 33 00:02:22,120 --> 00:02:25,079 Speaker 3: while they were in And they increase the efficacy of 34 00:02:25,120 --> 00:02:29,200 Speaker 3: their judgments by almost four hundred percent. So they work 35 00:02:29,440 --> 00:02:32,920 Speaker 3: is one reason. And they're cheap is another reason. You know, 36 00:02:33,120 --> 00:02:36,560 Speaker 3: it's a lot cheaper to set up a checklist or 37 00:02:36,600 --> 00:02:38,320 Speaker 3: a simple set of rules than to pay a bunch 38 00:02:38,320 --> 00:02:41,800 Speaker 3: of CFAs to try and get it right. So they work, 39 00:02:41,840 --> 00:02:43,040 Speaker 3: and they work on a budget. 40 00:02:43,600 --> 00:02:47,080 Speaker 2: So I love the idea of the checklist because it 41 00:02:47,240 --> 00:02:51,000 Speaker 2: plays very much into an issue that's a pet peeve. 42 00:02:51,080 --> 00:02:55,280 Speaker 2: Of mine, which is investors tend to obsess about all 43 00:02:55,320 --> 00:02:58,960 Speaker 2: these things they cannot control, things that are out of 44 00:02:59,000 --> 00:03:04,000 Speaker 2: their diction, while ignoring the things that they can control. 45 00:03:04,400 --> 00:03:08,400 Speaker 2: Talk a little bit about how creating a checklist allows 46 00:03:08,400 --> 00:03:11,959 Speaker 2: you to focus on things that are within your control. 47 00:03:12,560 --> 00:03:15,120 Speaker 3: Yeah, very When I wrote the book, you know, the 48 00:03:16,160 --> 00:03:19,440 Speaker 3: very first chapter, and I was intentional about the ordering. 49 00:03:19,880 --> 00:03:22,400 Speaker 3: The very first chapter in the book is you control 50 00:03:22,440 --> 00:03:25,480 Speaker 3: what matters most. Because I found what I think you 51 00:03:25,520 --> 00:03:27,760 Speaker 3: find when you tell someone you work in markets, that 52 00:03:27,800 --> 00:03:31,520 Speaker 3: you work in finance, they ask you about one hundred things. 53 00:03:32,200 --> 00:03:34,880 Speaker 3: All one hundred are outside of their power. What's the 54 00:03:34,920 --> 00:03:36,880 Speaker 3: FED going to do, what's the virus going to do, 55 00:03:37,000 --> 00:03:39,280 Speaker 3: what's the war going to do, Who's going to win 56 00:03:39,320 --> 00:03:44,080 Speaker 3: the election? Stuff that is a almost inevitably unknowable and 57 00:03:44,200 --> 00:03:47,560 Speaker 3: be outside of their power. So what I think we 58 00:03:47,640 --> 00:03:50,240 Speaker 3: have to encourage people to do is to take the 59 00:03:50,360 --> 00:03:54,280 Speaker 3: power back and to frame it that way, because things 60 00:03:54,360 --> 00:03:59,200 Speaker 3: like fees, things like diversification, choosing to work with a professional, 61 00:03:59,760 --> 00:04:02,280 Speaker 3: all of these things are within our control and are 62 00:04:02,560 --> 00:04:06,640 Speaker 3: far more predictive of you crossing your financial finish line 63 00:04:06,880 --> 00:04:08,760 Speaker 3: than any of that other stuff. 64 00:04:09,640 --> 00:04:13,440 Speaker 2: There's a great story in Michael Lewis's book about Sam 65 00:04:13,480 --> 00:04:17,920 Speaker 2: Benkman Free and FTX about Jane Street Trading, and even 66 00:04:17,960 --> 00:04:24,920 Speaker 2: though they got the twenty sixteen election results correct, they 67 00:04:25,000 --> 00:04:27,960 Speaker 2: still were unable to anticipate what the market reaction would be. 68 00:04:28,240 --> 00:04:30,760 Speaker 2: So not only are these things out of your control 69 00:04:30,880 --> 00:04:35,200 Speaker 2: and they are unknowable, but even when you know it, Hey, 70 00:04:35,400 --> 00:04:37,960 Speaker 2: what's the reaction of tens of millions of traders going 71 00:04:38,000 --> 00:04:39,799 Speaker 2: to be? We really have no idea. 72 00:04:40,360 --> 00:04:43,080 Speaker 3: Yeah, no, it's true, like no one thought Trump would win, 73 00:04:43,200 --> 00:04:45,599 Speaker 3: and then most folks who thought that he would win 74 00:04:45,680 --> 00:04:48,719 Speaker 3: thought it would tank the market. Both things were proven wrong. 75 00:04:49,080 --> 00:04:52,680 Speaker 2: H really amazing. So let's bring this back to the 76 00:04:52,720 --> 00:05:00,279 Speaker 2: investing decision making process. You emphasize why the process of 77 00:05:00,320 --> 00:05:04,039 Speaker 2: making good decisions is so much more important than trying 78 00:05:04,080 --> 00:05:05,800 Speaker 2: to predict market movements. 79 00:05:05,960 --> 00:05:10,719 Speaker 3: Explain, Yeah, it's really about being the house and not 80 00:05:10,880 --> 00:05:12,160 Speaker 3: the degenerate gambler. 81 00:05:12,240 --> 00:05:12,400 Speaker 1: Right. 82 00:05:12,440 --> 00:05:14,680 Speaker 3: If you look at all the bright lights in Vegas, 83 00:05:14,800 --> 00:05:19,040 Speaker 3: all that gets paid for by tilting probability in favor 84 00:05:19,240 --> 00:05:21,360 Speaker 3: of the house. And if you look at a lot 85 00:05:21,400 --> 00:05:25,360 Speaker 3: of casino games, the edge the house has is not dramatic. 86 00:05:25,720 --> 00:05:30,279 Speaker 3: I mean, in some cases it's infinitesimly small, but tilting 87 00:05:30,440 --> 00:05:33,719 Speaker 3: probability in your favor time and time and time again. 88 00:05:34,200 --> 00:05:36,920 Speaker 3: Showing up doing the things that are within your power 89 00:05:37,000 --> 00:05:39,640 Speaker 3: time and time again, pays for some nice lights and 90 00:05:39,680 --> 00:05:42,760 Speaker 3: some nice fountains, as we see in Vegas. So that's 91 00:05:42,880 --> 00:05:46,320 Speaker 3: all we're trying to do here, control the controllable tilt 92 00:05:46,360 --> 00:05:48,839 Speaker 3: probability in our favor in a small way. You're not 93 00:05:48,960 --> 00:05:51,520 Speaker 3: always going to get it right, but you're always going 94 00:05:51,600 --> 00:05:52,560 Speaker 3: to be at the wheel. 95 00:05:52,800 --> 00:05:56,200 Speaker 2: So I mentioned in the introduction that we're all filled 96 00:05:56,200 --> 00:05:59,880 Speaker 2: with so much over confidence. You have a chapter titled 97 00:06:00,440 --> 00:06:04,240 Speaker 2: You Are Not Special. Tell us about why investors need 98 00:06:04,320 --> 00:06:07,719 Speaker 2: to stay humble and why we're all subject to the 99 00:06:07,760 --> 00:06:10,960 Speaker 2: same biases and errors as everybody else. 100 00:06:11,600 --> 00:06:14,200 Speaker 3: Well, I love this one because I think it demonstrates 101 00:06:14,200 --> 00:06:18,400 Speaker 3: how psychological biases can serve us. They serve us well 102 00:06:18,440 --> 00:06:20,919 Speaker 3: in some domains in life. If we look at over 103 00:06:21,000 --> 00:06:24,880 Speaker 3: confidence bias, it serves us really nicely. In some ways. 104 00:06:24,960 --> 00:06:28,599 Speaker 3: People who exhibit it are happier, they're more successful, they're 105 00:06:28,640 --> 00:06:32,400 Speaker 3: more likely to be successful entrepreneurs. God, they're definitely more 106 00:06:32,480 --> 00:06:35,559 Speaker 3: likely to run for office. Right, There's all of these 107 00:06:35,680 --> 00:06:40,200 Speaker 3: things that over confidence does, but when you apply it 108 00:06:40,240 --> 00:06:44,839 Speaker 3: to markets. There's three specific ways that we're over confident. 109 00:06:45,640 --> 00:06:50,320 Speaker 3: The first is we think we're better than average right, smarter, better, faster, stronger, 110 00:06:50,440 --> 00:06:53,200 Speaker 3: better at picking stocks, And that's the one that gets 111 00:06:53,200 --> 00:06:56,920 Speaker 3: the most publicity. But there's actually two others as well. 112 00:06:57,400 --> 00:07:00,839 Speaker 3: One is we think we're luckier than average. Ask people, 113 00:07:00,880 --> 00:07:03,680 Speaker 3: you know, what's the likelihood of something happening to you, 114 00:07:03,720 --> 00:07:06,960 Speaker 3: like getting divorced, and like, effectively, no one says they'll 115 00:07:06,960 --> 00:07:09,440 Speaker 3: get divorced, even though you know one and two people 116 00:07:09,480 --> 00:07:12,200 Speaker 3: gets divorced. No one thinks they're going to get cancer 117 00:07:12,480 --> 00:07:14,960 Speaker 3: or you know, have diabetes, or you know, on and 118 00:07:14,960 --> 00:07:17,880 Speaker 3: on and on. But if you ask people about their 119 00:07:17,880 --> 00:07:21,920 Speaker 3: odds of finding love or winning the lottery, they dramatically 120 00:07:22,120 --> 00:07:27,320 Speaker 3: overrate these probabilities. So we sort of tend to own 121 00:07:27,360 --> 00:07:30,600 Speaker 3: the optimistic and delegate the dangerous. That's a second sort 122 00:07:30,600 --> 00:07:33,720 Speaker 3: of facet of overconfidence. And then the third one is 123 00:07:33,760 --> 00:07:36,360 Speaker 3: we think that we're more prescient about the future than 124 00:07:36,400 --> 00:07:39,640 Speaker 3: we actually are, Like we think we're better at forecasting 125 00:07:39,680 --> 00:07:43,800 Speaker 3: what's going to happen. So these three forms of overconfidence 126 00:07:43,840 --> 00:07:47,760 Speaker 3: are a pretty toxic cocktail of bad decision making. So 127 00:07:47,960 --> 00:07:51,000 Speaker 3: we really you know, our mutual friend Jim O'Shaughnessy has 128 00:07:51,040 --> 00:07:54,800 Speaker 3: this great line in his seminal work What Works on 129 00:07:54,840 --> 00:07:58,040 Speaker 3: Wall Street that I'll butcher here, but it's effectively like, look, 130 00:07:58,240 --> 00:08:03,080 Speaker 3: rule one. Step one is understanding that you are prone 131 00:08:03,160 --> 00:08:06,240 Speaker 3: to all of the same screw ups as the next person, 132 00:08:06,600 --> 00:08:10,559 Speaker 3: and until you sort of deeply internalized that you shouldn't start. 133 00:08:11,120 --> 00:08:14,480 Speaker 2: Yeah, Jason's why. I guess Danny Khneman what he does 134 00:08:14,560 --> 00:08:18,880 Speaker 2: to avoid all of the behavioral biases and heuristics that 135 00:08:19,000 --> 00:08:23,120 Speaker 2: him and Amos Tversky discovered. And his answer was nothing. 136 00:08:23,160 --> 00:08:26,240 Speaker 2: We can't avoid it. They're just totally unavoidable. Hey, if 137 00:08:26,320 --> 00:08:29,080 Speaker 2: Danny Connoman can't avoid them, you know what hope did 138 00:08:29,120 --> 00:08:29,880 Speaker 2: the rest of us have? 139 00:08:30,440 --> 00:08:31,480 Speaker 3: Yeah? 140 00:08:31,560 --> 00:08:36,080 Speaker 2: So there's another line I really appreciate, And this perhaps 141 00:08:36,120 --> 00:08:39,080 Speaker 2: is because I began on a trading desk, and what 142 00:08:39,320 --> 00:08:41,880 Speaker 2: led me to realize it was time to move on 143 00:08:42,640 --> 00:08:46,400 Speaker 2: was how much fun I was having, regardless of my 144 00:08:46,559 --> 00:08:50,920 Speaker 2: p and L. You right, if it's fun, you're probably 145 00:08:51,000 --> 00:08:53,880 Speaker 2: not making money. I bet a lot of traders can 146 00:08:53,920 --> 00:08:57,520 Speaker 2: confirm this. Tell us why fun and making money are 147 00:08:57,559 --> 00:09:01,880 Speaker 2: not necessarily consistent, and what we need to do to 148 00:09:02,559 --> 00:09:05,160 Speaker 2: be more methodical and more disciplines. 149 00:09:05,840 --> 00:09:08,720 Speaker 3: Yeah, it's really like one of these harsh truths about 150 00:09:09,040 --> 00:09:11,640 Speaker 3: I refer to it in the book as Wall Street 151 00:09:11,679 --> 00:09:14,560 Speaker 3: Bizarro world. How the truths of every day are sort 152 00:09:14,559 --> 00:09:18,600 Speaker 3: of one eighty to the truths of markets. And one 153 00:09:18,600 --> 00:09:20,120 Speaker 3: of the things that we find is some of the 154 00:09:20,160 --> 00:09:24,040 Speaker 3: most exciting, most fun ways to try and make money 155 00:09:24,040 --> 00:09:26,720 Speaker 3: in the markets are the most deleterious to our wealth. 156 00:09:27,120 --> 00:09:29,560 Speaker 3: You know, you look at day trading. The most comprehensive 157 00:09:29,559 --> 00:09:32,720 Speaker 3: study on day trading ever done was out of Taiwan, 158 00:09:32,920 --> 00:09:36,560 Speaker 3: and they found that one in three hundred and sixty 159 00:09:36,679 --> 00:09:41,400 Speaker 3: day traders show evidence of skill. So is day trading fun? 160 00:09:41,440 --> 00:09:41,520 Speaker 1: Like? 161 00:09:41,760 --> 00:09:45,240 Speaker 3: Absolutely, it's a blast, right, Like making short term trades 162 00:09:45,280 --> 00:09:48,280 Speaker 3: can be fun, it can be intoxicating, it can be exciting, 163 00:09:48,880 --> 00:09:52,080 Speaker 3: but you know, the chances of you being good at 164 00:09:52,080 --> 00:09:55,640 Speaker 3: it are vanishingly small. You look at other stuff like 165 00:09:55,800 --> 00:09:59,480 Speaker 3: IPO investing. You know, everyone's got this story about if 166 00:09:59,520 --> 00:10:01,880 Speaker 3: you would you know, if you'd put ten thousand dollars 167 00:10:01,920 --> 00:10:05,400 Speaker 3: in video or Apple or whatever, you'd be a gazillionaire now. 168 00:10:06,320 --> 00:10:09,880 Speaker 3: But we know that on average, the average IPO does 169 00:10:10,000 --> 00:10:12,959 Speaker 3: twenty one percent worse than the s and P five 170 00:10:13,040 --> 00:10:16,160 Speaker 3: hundred in the first three years. And so again, is 171 00:10:16,480 --> 00:10:21,000 Speaker 3: IPO investing fun? Yeah? Absolutely, but you are the gambler. 172 00:10:21,840 --> 00:10:24,719 Speaker 3: You are the gambler and not the house, and you're 173 00:10:24,800 --> 00:10:28,240 Speaker 3: unlikely to secure that monet if you're engaging in these 174 00:10:28,280 --> 00:10:29,439 Speaker 3: sorts of fun behaviors. 175 00:10:30,320 --> 00:10:35,000 Speaker 2: Let's talk about forecasting is for weathermen. Why are we 176 00:10:35,120 --> 00:10:38,640 Speaker 2: so bad at forecasting? And what should we focus on? 177 00:10:39,200 --> 00:10:41,080 Speaker 3: Well, it goes back to that. You know, it's one 178 00:10:41,120 --> 00:10:44,160 Speaker 3: of those primary forms of overconfidence. And the research on 179 00:10:44,200 --> 00:10:47,360 Speaker 3: this is just wild. You know, Philip Tetlock did sort 180 00:10:47,360 --> 00:10:50,760 Speaker 3: of the seminal research on political and financial forecasting and 181 00:10:51,120 --> 00:10:53,760 Speaker 3: found that, you know, even the experts are terrible at this, 182 00:10:53,880 --> 00:10:56,880 Speaker 3: and in fact, the more famous and expert, the worst 183 00:10:57,000 --> 00:11:01,400 Speaker 3: they tended to be because you get famous as a 184 00:11:01,440 --> 00:11:04,480 Speaker 3: market prognosticator is making sort of a once in a 185 00:11:04,520 --> 00:11:08,600 Speaker 3: lifetime black swan prediction, and then you tend to continue 186 00:11:08,600 --> 00:11:10,760 Speaker 3: to bang that drum because it worked the first time, 187 00:11:10,840 --> 00:11:14,640 Speaker 3: and you know, history on average is pretty average, and 188 00:11:14,679 --> 00:11:17,880 Speaker 3: then you're wrong. But the reason we're always going to 189 00:11:17,960 --> 00:11:20,400 Speaker 3: look for this is the way that we're wired. Right. 190 00:11:20,520 --> 00:11:23,080 Speaker 3: Our brains are are two to three percent of our 191 00:11:23,120 --> 00:11:26,000 Speaker 3: body weight. But they're twenty to twenty five percent of 192 00:11:26,040 --> 00:11:29,520 Speaker 3: our caloric expenditures in a given day. And so when 193 00:11:29,600 --> 00:11:32,319 Speaker 3: we look at people again hooked up to an fMRI 194 00:11:32,559 --> 00:11:36,559 Speaker 3: machine who are watching cable financial news, watching someone make 195 00:11:36,600 --> 00:11:39,960 Speaker 3: predictions about what's going to happen, the part of their 196 00:11:40,000 --> 00:11:44,040 Speaker 3: brain associated with critical thinking and decision making actually goes 197 00:11:44,120 --> 00:11:47,880 Speaker 3: to sleep, which is candidly what we are looking for, 198 00:11:48,120 --> 00:11:51,120 Speaker 3: right We're looking for that peace of mind. We're looking 199 00:11:51,160 --> 00:11:54,280 Speaker 3: to think less and go into energy saver mode. So 200 00:11:54,440 --> 00:11:57,800 Speaker 3: as bad as we are at forecasting, there will always 201 00:11:57,840 --> 00:12:01,440 Speaker 3: be a market for some sort of certainty. And I 202 00:12:01,440 --> 00:12:04,560 Speaker 3: think the only thing that we can do is to 203 00:12:04,679 --> 00:12:07,199 Speaker 3: work with a financial advisor who can give us some 204 00:12:07,240 --> 00:12:11,839 Speaker 3: sort of certainty around our plan, our purpose, our immediate 205 00:12:11,880 --> 00:12:16,200 Speaker 3: financial lives, instead of delegating that to some impersonal talking head. 206 00:12:16,800 --> 00:12:19,720 Speaker 2: So I'm glad you brought up the financial advisor. You 207 00:12:19,880 --> 00:12:23,800 Speaker 2: discuss how hard it is to do this alone and 208 00:12:24,200 --> 00:12:28,480 Speaker 2: why you should seek professional advice and support, if for 209 00:12:28,520 --> 00:12:30,960 Speaker 2: no other reason then to help you manage your biases 210 00:12:31,000 --> 00:12:37,120 Speaker 2: and your emotions. Discuss your experience with people working with professionals. 211 00:12:37,600 --> 00:12:41,319 Speaker 3: Yeah, this is one of probably the two most powerful 212 00:12:41,400 --> 00:12:44,000 Speaker 3: things you can do to manage those behavioral biases that 213 00:12:44,080 --> 00:12:47,079 Speaker 3: Danny Kneman talked about, right, I mean, he talks, as 214 00:12:47,120 --> 00:12:49,200 Speaker 3: you said, about the futility of it. I think the 215 00:12:49,280 --> 00:12:53,359 Speaker 3: two best hopes we have against behavioral bias is automation 216 00:12:53,600 --> 00:12:57,240 Speaker 3: and working with a professional. The data is very clear 217 00:12:57,280 --> 00:12:59,560 Speaker 3: now that people who work with the professional tend to 218 00:12:59,559 --> 00:13:02,240 Speaker 3: do better than those that don't. And when we look 219 00:13:02,280 --> 00:13:06,400 Speaker 3: at a twenty sixteen Merrill Lynch study, the things that 220 00:13:06,440 --> 00:13:10,559 Speaker 3: an advisor does for you are all additive. Like they 221 00:13:10,600 --> 00:13:13,200 Speaker 3: sort of broke this down by the different things that 222 00:13:13,240 --> 00:13:17,120 Speaker 3: an advisor does in his or her day, everything from 223 00:13:17,160 --> 00:13:21,120 Speaker 3: you know, security selection to asset allocation to tax alpha. 224 00:13:21,200 --> 00:13:22,079 Speaker 2: It all helps. 225 00:13:22,640 --> 00:13:26,000 Speaker 3: But the thing that helps the most is again this 226 00:13:26,120 --> 00:13:31,120 Speaker 3: behavioral coaching, the emotion management, the guidance around decision making, 227 00:13:31,360 --> 00:13:34,520 Speaker 3: keeping you from investing in your son in law's dumb business. 228 00:13:34,559 --> 00:13:37,720 Speaker 3: You know, just these these pivotal points along the way. 229 00:13:39,120 --> 00:13:41,960 Speaker 3: That's really where it adds about us four times as 230 00:13:42,080 --> 00:13:45,520 Speaker 3: much value as the other stuff. And what's cool for me, 231 00:13:45,800 --> 00:13:48,800 Speaker 3: as the son of a financial advisor who works with 232 00:13:48,840 --> 00:13:52,560 Speaker 3: financial advisors every day, is people who work with an 233 00:13:52,559 --> 00:13:56,680 Speaker 3: advisor have better marital communications. They have higher levels of 234 00:13:56,800 --> 00:14:00,920 Speaker 3: aggregate happiness. They're more prepared for an emergent. See like 235 00:14:01,000 --> 00:14:04,880 Speaker 3: they have all these non financial things in their life 236 00:14:04,880 --> 00:14:09,120 Speaker 3: that get lifted because money touches everything we do. So 237 00:14:09,200 --> 00:14:11,400 Speaker 3: if you can get that right, a lot of other 238 00:14:11,480 --> 00:14:14,319 Speaker 3: boats in your life to start to rise as well. 239 00:14:14,880 --> 00:14:18,000 Speaker 2: So to wrap up, humans are great at a lot 240 00:14:18,040 --> 00:14:22,760 Speaker 2: of things, but we also come prepackaged with a lot 241 00:14:22,760 --> 00:14:28,680 Speaker 2: of evolutionary baggage. We're easily excitable, we make poor decisions, 242 00:14:28,760 --> 00:14:35,040 Speaker 2: we think we're special, we're wildly overoptimistic, and we tend 243 00:14:35,080 --> 00:14:38,440 Speaker 2: to overreact to every sign of trouble like it's the 244 00:14:38,560 --> 00:14:41,480 Speaker 2: end of the world. We're much better off if we 245 00:14:41,600 --> 00:14:46,520 Speaker 2: have a rules based, systematic approach to managing risk and 246 00:14:46,560 --> 00:14:50,920 Speaker 2: investing for the future. Rather than making these decisions on 247 00:14:51,080 --> 00:14:54,360 Speaker 2: the fly to help your portfolio, you really need to 248 00:14:54,400 --> 00:14:57,920 Speaker 2: think about what is the best result for you over 249 00:14:57,960 --> 00:15:02,240 Speaker 2: the long haul, not just make making these decisions spur 250 00:15:02,400 --> 00:15:07,040 Speaker 2: the moment. I'm Barry Rudolts. You're listening to Bloomberg's at 251 00:15:07,040 --> 00:15:07,920 Speaker 2: the Money 252 00:15:08,400 --> 00:15:15,320 Speaker 1: Little little that you burnt, that you burn