Transcript:
Easan Arulanantham:
Can I have too much stock in my portfolio? With this, like caused me to have a lower chance of success in the long run?
Tom Vaughan:
Yeah, so this is actually a question that came up in a strategy session with our clients. And this is really interesting, it revolves around the situation of you know, what, how much money should I have in stock for my particular retirement. And it’s kind of fascinating, it doesn’t always, you know, translate to make sense. So, I’m going to share my screen here. And we’ll take a look at kind of a example I made. And so this is what we call finding a retirement path. This is all part of this whole component, we think this is super important. So education is part of that. But really part of retirement path is how much money should I have in stocks or bonds, you know, throughout my retirement. And so it’s kind of fascinating. Here’s, here’s what I’m going to show you for an example. Very simple. This is a financial plan, lots of information behind the scenes, I’m going to give you the high level piece. So here’s a portfolio 58% stock, it’s got a bond and cash or the other two pieces in there. And the projected average rate of return on this is 7.7%. You know, this is from money guide, pros financial planning program. And so what we would do, then, with that particular mixture, we could run Monte Carlo simulation. And so I’m going to push this button here in just a second to basically, you know, run their financial plan 1000 times. So just understand behind the scenes, we have these assets, we have inflows, so security and those types of things that will be coming in someday. And then we have outflows for things that they need to have to live off of. And so when I push this button, it’s going to run their financial plan 1000 times, and see how many times it works. And it allows the computer to randomly choose amongst the different variables. And it’s supposed to replicate your life by running it enough times, kind of the average is what you’re looking at there. So once I go ahead and push this button, there we go.
Alright, so this is what you end up with is this big, you know, green spaghetti, so to speak. And so for this particular sample, we have 930 successes out of 1000 different tries, running through this Monte Carlo simulation. So it’s a 93% success ratio, which is very good. Anything above 85%, in my opinion, is very, very good. And so at the 58% exposure to the stock market, this plan works quite well, right? So not not bad at all as far as that goes. But just to show you kind of a difference. And something I think is interesting. What if we, oops, what if we move that same portfolio into a scenario where we know the stock market’s going to fall, right, so this is what we call a stress test. So here, we had a 93% success ratio. But if we run this, again, with one known variable is that we’re about to have a stock market crash. In this case, just like the Great Recession loss, if you remember, the Great Recession loss started in 2007, actually, but most people look at as 2008, we ended up with a 57% drop in the S&P 500. The percentage loss for this portfolio is projected at 23%. But you can see their their probability of success drops all the way back to 56%. So obviously, a big stock market downturn is something to be concerned about in this particular situation. And we have strategies for what we would do with that.
But I just want to compare that to a different mixture. So here now we’re going to take that same plan and assign a much more aggressive portfolio. So here’s 96% stock, the other 4% is just money in the banks, basically, average rate of return is expected to be 9.74%. So if you remember, the previous one was 7.77. So almost 2% more per year. Theoretically, that should work better, correct, but it doesn’t. And so if I now click on this one, same parameters, I just changed the portfolio, it drops back from 93 to 89%. So even though there’s a higher average rate of return, the success ratio drops back by 4%. And the reason is because we just added more volatility to the overall portfolio. And when you run that through 1000 times, there’s going to be some of those times where the stock market just so terribly, that you end up with a situation of failure where you can see these red ones across the bottom here. And that’s when, you know, the basically the money ran out before you did, which is obviously not ideal. Still not bad at 89%. That’s still higher than my threshold of 85. But it’s not as optimal as the 58% portfolio where we had a 93% and it’s kind of exaggerated by the fact that if we run the stress test and reevaluate this thing, with a great recession coming, we drop back to 13% success ratio, which is really, you’re running out of money at that point. And that’s why there’s more red situations in there. And obviously, you can see that, you know, it has a 49% projected drop in the value of the portfolio.
So that, that, you know, again, lots of things happening behind the scenes and what have you. But that’s a really critical component of well, you know, what we’re looking at as far as that goes, and so overall, I think it’s important to, you know, use this tool to try to figure out what, you know, what we’re going to do. And one of the biggest questions we get, and we’re trying to answer that sort of here now, is how much, you know, stock to use in the portfolio. And so what I do is I’ll run that MonteCarlo simulation, you know, 20%, stock 40 6080 100. And, you know, usually come up with a range, I could say, okay, the optimum, you know, success ratios for you and your situation seem to be 40 to 80% range, or 20 to 60% range, or whatever it might be, it’s different for everybody. And even sometimes, the higher the 80, and 100% is optimal, depending on your parameters. But what we’re trying to point out here is that higher rates of return and higher risk don’t always relate, in every case, to a higher probability of success throughout retirement. Because there’s just too many other things that can come into play there. So I think it’s a great way to look at it. It’s very interesting. But to answer that question, yeah, you have to be a little bit careful about, you know, just adding more stock with a thought process of, hey, you know, more stocks make more money, but they also have these big periods of time where they can make less, and if you know, if you’re living off of them at that point in time, that could be a problem.
Easan Arulanantham:
So so what happens on the emotional side, you know, some people, you know, they can’t handle, you know, it just feels so slower, like the returns are so low when they do 6040. But because they’re so used to the 100% model, you know, it lowers their success, chance, is it? Do you? Would you stick still at that 100% model, when you maybe go in between the two is like, how do you balance that like, emotional aside? Versus is that just the pure numbers?
Tom Vaughan:
Yeah, pure data analytics. That’s a good, it’s a good point. He said, Because really, what happens here is that the emotional side actually dominates the analytical side in the end, because it’s one of the things I learned about with the 2008 downturn, you know, we can, we can go through a planning process analytical side, say, Hey, you should have 80% in the market. But then we have a big drop, and people are selling out at the bottom, because it really didn’t meet their emotional needs, in terms of how much risk you were taking. And you’re exactly right can actually go the other way to where you’ve got 40% exposure, because that’s what the model says you should have. And people are dissatisfied during a big upturn. And they’re constantly wanting to move up. And obviously, sometimes they move up at the wrong times, right, right at the end of the big run. So one of the things that we really look at there ever since 2008. So we really try to point out, you know, what the, you know, what the average rate of return was on the upside, so you can see, you know, hey, and then what you might have lost, you know, on the downside, and we specifically will look at the 2008 downturn and kind of model that. So somebody knows, hey, I might lose 30%, I think they just need to be comfortable. It does help to know the range that’s recommended by the plan. And that’s a piece of the puzzle. But in the end, it’s really about the emotional side. So we try to grab the emotional side by showing kind of the extremes you know, how much you can make on a good market and how much you can lose in a bad market and make sure that they’re comfortable with that range. But in the end, emotional people throw the, you know, the plan out the door, when, when they’re when they’re nervous, or you know, what have you as far as that goes, so, I’ve seen more people having too much risk in their portfolio over the years then not enough, you know, that doesn’t come up as often. Usually, it’s a fear factor that comes in and so anyway, that’s what’s that that’s a good question. It’s a good point.