Hi everyone, I'm so happy to be here virtually. Today, I'm going to talk to you about quitting, specifically how we can improve our exit decisions and why we really want to do that. The problem we face as decision-makers is that uncertainty makes it very hard to start things, because two forms of uncertainty exert themselves on any decision we make.

The first is just plain luck, which means that we can make a great decision, we can make a decision that's going to work out 90% of the time, but 10% of the time it's not going to work out. And when we observe that 10% is wholly determined by luck, and that makes it very hard for us to start things because we're trying to get more control than we actually have over what the outcome might be, which is probabilistic in nature.

The other form of uncertainty that makes the decision to start things hard is that we know very little in comparison to all there is to be known. And so this can make it so that we really slow our decisions down in a way that isn't actually productive, trying to get to a level of certainty that is actually unattainable.

So those two forms of uncertainty are making starting things hard. The good news for us is that for most things that we decide to do, we have the option to quit later. That quit might have varying costs associated with it, but almost anything that we decide to start, we can actually quit.

And what that means is that the uncertainty that makes it really hard for us to start things, this option to quit later makes that start easier, because we can anticipate the ability to exit when we observe that the world isn't going in our direction or when we observe that we're getting signals that we're learning new things that tell us that our choice wasn't actually that good.

So you can think about it like we've all had that feeling of I wish I knew then what I know now. The option to quit actually makes it so that we can act on that feeling when we learn new information.

But here's the really big problem is that even though we have this incredibly valuable option, and I would actually argue that it's the single most valuable option that we have in decision-making, is this option to walk away, the problem is that we actually are quite bad at quitting. We tend to walk away from things much too late compared to when, if you were just judging expected value, would be the correct time to actually walk away.

So we're going to talk about this problem that we have with quitting, we're going to talk about why it is that we have such a problem with quitting, and then I'm going to hopefully give you some solutions that are going to make this all a little bit easier for you.

Okay, so here's the important thing. Remember I said, after we start things, we get new information and we have this very strong intuition that when we get information from the world that things aren't going that well, we'll actually pay attention and walk away. So when we get those adverse signals, we're going to stop what we're doing and that's what we all think, but that intuition is actually wrong.

Instead, in the face of those negative signals, we escalate our commitment. And actually, in reference to the previous speaker, I use mountain climbing as an example for this. We've all heard of summit fever, we have the intuition that if it gets dark and we're still climbing, or if a blizzard is coming in, that we're all going to stop climbing. And it turns out that we don't.

And you can just look to for example, 1996 on Mount Everest to know that people will continue past the point when they already have adverse signals, 1996 being that tragic year when Rob Hall and Doug Hansen died.

So this is a well-known effect, it's called escalation of commitment, that we get these signals and instead of actually reducing our commitment to the cause, having gotten those adverse signals, we actually escalate our commitment to the cause. And of course, continuing to do something that is no longer worthwhile doesn't just have costs associated with doing something that's negative expectancy itself, but there are also opportunity costs associated with it.

So we have this added cost of failure to cut our losses that we can't take that Capital, our time, attention, our money, our effort and put it into something that would actually be worthwhile. So one of the ways that we can think about the grit and quit is not as oppositional, but as kind of the same decision. We should stick to things that are worthwhile and we should quit things that aren't. And the failure to quit things that are no longer worthwhile also has opportunity costs associated with it. So this becomes even more important to get this quit grit quit decision down.

Now this is really important, experts are in no way immune to escalation of commitment. They're no way in no way immune to this failure to quit things on time. There is lots and lots of data and I've got three studies shown here, G. Garvey and Murphy, Woodcock, so on so forth, that show that while expert investors are alpha generators when putting risk on, they give Alpha back on their exit decisions.

And in fact, this 2023 paper showed that endowments when they put positions on are generating between 120 and 180 bips on those an alpha on those decisions, but their exit decisions they're actually giving about 70 to 80 bips back. Woodcock and then also Garvey and Murphy talk about the the fact that intraday traders are also finding this and Alex Emus has shown this as well, very very good on the entry giving a lot of that Alpha back on the exit.

And that's why I think this option to quit is so incredibly valuable because this is the place where we can actually pick up, we can generate a lot of alpha compared to our to compared to our competitors.

So why is it that it's so hard for us to quit things? Well, it turns out that there's a lot of cognitive biases that kind of pile up on top of us that make us slow to quit. I'm going to walk through some of them pretty quickly, I'm not going to cover every single one of them, but we the sunk cost effect, endowment, status quo bias, Omission commission bias, optimism bias, loss aversion and sure loss aversion. So I'm going to walk through these somewhat quickly.

The sunk cost effect is when we take into account what we've already spent on something and deciding whether to continue on and spend more. In other words, what happens is that we have that feeling of we want to get our money back or don't want to have wasted what we already put into something. The problem of course is that waste is not a retrospective problem, it's a prospective problem. What we'd ideally like to do is if it is something that we would start today, then we should be willing to continue it. If it is not something that we would start today, then we should not continue it.

But what happens with sunk cost is that instead of this Forward Thinking where we're saying is this something that we would actually do start today? Would we put this position on today for example? We take into account what we've already put into it and deciding whether to continue on and spend more. Now the problem is it doesn't really matter what you've lost coming up to that moment of the decision. What matters is whether the next dollar or the next unit of effort that we put into something is positive expectancy. So the sunk cost effect causes us to continue things that are no longer worthwhile.

We also have the endowment effect, which is just we value things that we own more than identical things that we don't own. So the things that we already have in our portfolio, the positions that we already have on, this is even true of our own ideas, the thesis that we're trading, the ideas that we have, we value more than things that don't we don't own. So obviously when we're making that decision about whether it's worthwhile to continue on, we're going to distort our view of what the expected value is, just because we think that the things that we own are more valuable that they have more value to them.

Then we have sure loss aversion. This comes from the late Danny Kahneman and Amos Tversky, which is essentially this problem that we're biased against converting paper losses into realized losses and we actually pay to avoid having to do so. So this is from their original 1979 paper on prospect theory, which shows that when people are in the losses on a gamble, say I've lost $100, and I'm offered a fair coin flip, where I can either get even or I'll lose $220, that they'll prefer to take the flip. There, in other words, they're paying $10 for the opportunity to try to get even, and that's because of this aversion to turning a paper loss into a sure loss.

And obviously that's a huge problem when we're in the losses on a position that we're holding and we can kind of think of all of those under this umbrella of we just don't like to close accounts in the losses. And it's not just paper accounts, this has to do with our mental accounts. So we can have a paper account that's in the gains and yet our mental account is in the losses. If we buy a stock at 50, it goes up to 75, and then it goes down to 60, mentally we're in the losses even though on our paper Ledger we're in the gains. And so this problem with not wanting to close accounts in the losses makes us very slow to quit.

We also have status quo bias, a preference for sticking with the status quo. Omission commission bias, we're much more tolerant of losses that come from sticking with the status quo, in other words, making a decision not to switch as opposed to making a decision to switch. So if we're holding a position, we're going to be more tolerant of the losses that might generate from that, than we are going to be tolerant of generating from losses that come from us switching from that position to something new, which also makes us very slow to quit.

And then the last thing is just cognitive dissonance, identity and validity, both the way we view ourselves and the way that other people view us. We want to be seen as consistent individuals over time. Part of the decisions that we make create part of our identity and that's particularly true if those decisions are making us stand out from the crowd.

So Bers and Milkman showed that when analysts take positions that are non-consensus on earnings forecasts, when they're non-consensus and the world turns against them and gives them information that their forecast actually wasn't correct, they'll actually double down on the forecast. But when they make when they make forecasts that are in consensus, they're perfectly willing to change according to what the world tells them. And that's because the non-consensus forecasts are actually much more part of somebody's identity. And obviously as Traders or as investors, we're investing against the market, so we're often trying to stand out from the crowd, do something where we think that the market is not efficient, and that makes it actually much harder for us to walk away because it's an attack on our identity if we actually have to jump ship.

Okay, so I told you a lot of the reasons why we don't stop. Now I want to give you quickly a few reasons how we can help you to get better at these stopping decisions. The first is to set very specific kill criteria, which are just criteria for killing a project, cutting your losses, or changing a plan.

So the first step is to identify the way that things might go wrong or right, and then identify the early warning signals to develop a list of kill criteria. In other words, what are those signals that I think I might ignore in the future that would tell me that it's time to walk away? And then pre-commit to your reaction to those criteria.

So I've worked with a lot of investors and they have that intuition while I have a thesis, and let's say the thesis has to do with the directional movement of interest rates. So they their thesis is that interest rates are going to go above above a certain point, or stay within a particular band, or go down, whatever that thesis is. They have the intuitions that that when interest rates move against them that they will get off the position that they will take risk off, but we know that they don't. They tend to get thesis creep or they escalate our commitment or they say now it's really cheap, I know my forecast is still correct.

And so what I'm doing here is saying, okay, if you have a thesis, that thesis is implying certain things about what the world is going to look like in the future, right down what that thesis is actually implying, and then develop kill criteria. In other words, if interest rates move out of a certain band, then I will do X, Y, or Z. So if they go above a certain band, maybe I'll put more risk on, but if they go below a certain band, that means that the world has moved against my thesis, and I need to actually take the risk off.

Now that might seem like a distinction without a difference. If I have a thesis, it's predicting certain things about the future, why is it different if I just write those things down and pre-commit to them? And it turns out just cognitively that makes a huge difference, to think ahead, actually identify what those kill criteria are, and then and then pre-commit to to the actions that you're going to take when you see those signals develop.

The next thing is to create better feedback loops. One of the problems that we have on the quits when we take risk off is that we really don't have a good feedback loop on how those decisions compare to a benchmark. So we consistently track positions we have on, and obviously because they're in our portfolio, we also even track positions that we're considering putting on because we'll create Shadow books.

But what we don't do is consistently track positions that we take off. So what we want to do is create a benchmark against which we can actually measure the quality of our quitting decisions. So we can do that in a couple ways. One thing is for example, if we're freeing up Capital, we can create a benchmark which is what if I randomly freed this Capital up from anywhere in my portfolio and actually judge my quit decision against that over the course of a period of time.

You can also actually start to track your things that you hold and look at what would have happened if I had actually sold those things earlier at the time that I considered it. But be creative and try to actually create benchmarks against which you can actually start to judge your quitting decisions so that you can start to get feedback on whether you're generating Alpha on those exit decisions or giving Alpha back on those exit decisions.

And the last is this is a big favorite of mine, go get yourself a quitting coach, because an honest broker, someone who's standing on the outside looking in on your situation is going to see your situation more clearly than you can. And the reason is that they're not carrying all of the sunk cost, they're not carrying the endowment, they don't they don't have the same kind of biases piled up on them that are making them not be able to see that situation so clearly.

So someone from the outside looking in is going to see your situation more clearly than you can. And so if you work with them to pre-commit to an exit plan with a quitting coach, it actually makes it more likely that you'll follow through. So they can both see the decision more clearly than you can and they create accountability that are going to make you actually follow through on those quitting plans.

So actually when I've worked with for example solo PMs, I've paired them together so that they can coach each other on these exit decisions. So I hope that this bit about exiting you're going to find helpful. I really believe that this could be the single biggest Alpha generator for you right now in your own investing life, because we are so bad at it and nobody's really paying attention to how good these exit decisions are. So if you can get better at these exit decisions, I think this is going this will vastly improve your returns. Thank you so much.