- Speaker #0
Hello and welcome back to Papers of the Backtest podcast. Today we dive into another Algo Trading research paper. We'll be looking at Do Momentum and Reversals Coexist by Jason Y. It's from February 2011.
- Speaker #1
Yeah, this paper is really interesting. You know, it challenges some basic assumptions about, you know, how the stock market works. It uses data from the NYSE, Amex and Nasdaq all the way from 1964 to 2009 to see if two like seemingly opposite things can actually happen at the same time. Momentum and reversals.
- Speaker #0
Okay. So momentum, everyone's heard of momentum. Buy a stock that's going up, hope it keeps going up. And reversals are kind of the opposite. Betting that a stock that's been doing poorly will bounce back.
- Speaker #1
Exactly. And traditionally, those have been seen as separate things happening at different times. But what's so cool about this paper is that it kind of digs deeper. It sorts stocks by size, how much their price jumps around their volatility and past returns. And guess what it finds that for large cap stocks, Momentum and reversals can coexist within the same six month period.
- Speaker #0
Wait, so in that same timeframe, some large caps are going up while others are going down. How does that even make sense?
- Speaker #1
Yeah, that's the question, right? The study found that large cap stocks with high volatility, so you know, think of the ones making big moves, they tend to keep riding that momentum wave. But large cap stocks with low volatility, the ones that are usually seen as more stable, they actually show reversals.
- Speaker #0
So it's like, the steady, reliable stocks are the ones throwing a curveball.
- Speaker #1
Exactly. And this goes against a lot of the traditional theories about return predictability. What's even more interesting is that the study looked at small cap stocks. And for small caps, it found that momentum was really the dominant force, regardless of volatility. It's like they're wired to keep climbing, at least in the short term.
- Speaker #0
So volatility seems to be the key here, like the secret sauce to figure out if a stock will continue its trend or to a complete 180. But why is that?
- Speaker #1
Well, Wei argues that volatility is like a stand in for this thing called information uncertainty. Think about it this way. For big, well-established companies with low volatility, the future seems more predictable, right? There's less uncertainty about how they'll perform. But that can actually make investors overreact to any news, good or bad, causing those short term reversals.
- Speaker #0
So it's like, oh, no, big stable company had a tiny hiccup. Everyone panic. Hmm.
- Speaker #1
But then things settle down and the stock goes back to normal.
- Speaker #0
Yeah, that's the idea. Now, for smaller companies or those with high volatility, there's just more uncertainty surrounding them. Investors might underreact to news because the future is less clear, which could explain why momentum tends to persist in those stocks.
- Speaker #1
That makes sense. But how does this all translate into actual trading rules and potential profits? We need to know if these patterns are actually useful for making money. Yeah, that's where the rubber meets the road. And luckily, this paper gives us some concrete data to work with. Let's take a look at table two. Wei breaks down the returns for different combinations of evaluation and holding periods. It's kind of like a recipe book for momentum and reversal strategies.
- Speaker #0
OK, so for large cap stocks, where we see this interesting mix of momentum and reversals, what kind of patterns emerge?
- Speaker #1
Well, the paper highlights that for large stocks with low volatility, there's a significant reversal effect. When looking at evaluation and holding periods that add up to seven or eight months, so for example, if we look at stocks that perform poorly over a one-month period and then hold them for another six months, they tend to outperform. The stocks that did well initially, it's like a tortoise and hare situation.
- Speaker #0
So if you buy the losers, they might actually turn into winners over that time frame. But what happens if you hold them even longer?
- Speaker #1
That's where it gets a little tricky. The paper shows that this reversal effect kind of fades as the holding period gets longer. For those... classic six-month evaluation and six-month holding periods, the advantage for low volatility large cap stocks isn't as clear-cut.
- Speaker #0
So timing is key. You need to catch those reversals early before the effect wears off. What about the large cap stocks with high volatility? Do they follow a different pattern?
- Speaker #1
Well as we discussed those tend to exhibit momentum and looking at table two we can see that the momentum effect is pretty strong. especially for shorter evaluation periods. So if a high volatility large cap stock has been doing well, chances are it'll keep doing so, at least for a little while.
- Speaker #0
So it sounds like for these high flying stocks, riding the momentum wave might be a better bet than trying to time a reversal. But how do we know when to jump in and more importantly, when to jump out?
- Speaker #1
That's where things get even more interesting. The paper doesn't just look at the overall holding period. It also breaks down the returns month by month after you form your portfolio. This gives us a much more detailed picture of when exactly those momentum and reversal effects kick in.
- Speaker #0
All right, let's dive into those monthly breakdowns. I'm dying to know when these strategies start to pay off and how long those sweet spots last.
- Speaker #1
Yeah, so if we look at table three, we can see that for those large cap low volatility stocks, the reversal effect is strongest in the first few months. after you put the portfolio together. In many cases, that upward momentum doesn't really kick in until like the fourth or fifth month.
- Speaker #0
So for a trading strategy based on this reversal effect, it sounds like a shorter holding period might be the way to go. You can touch those early gains and then get out before the momentum shifts.
- Speaker #1
Yeah, that's one way to do it. And for high volatility stocks, the opposite might be true. That momentum effect is often evident like right from the start. So holding on for longer could lead to bigger profits.
- Speaker #0
Okay. Now what about those small cap stocks? We talked about how they tend to show momentum like across the board. Does the data back that up?
- Speaker #1
Oh, yeah, absolutely. If you look at table two again, you can see that the returns for small cap momentum strategies are generally higher than for large caps. Yeah. Especially when you hold them for longer.
- Speaker #0
So it seems like just a classic momentum strategy. Buy the winners and hold on tight might work well for small caps.
- Speaker #1
Yeah, potentially. But there's a catch. Remember, small caps are often more volatile. They're riskier than those big established companies. And this kind of ties back into that concept of information uncertainty. The future of a small company is often less predictable. So there's a higher chance of things, you know, not going as planned.
- Speaker #0
Right. So even though the potential rewards might be higher, you also need to be prepared for a much bumpier ride with small caps.
- Speaker #1
Exactly. And that's why it's so important to think about risk management and diversification. Don't put all your eggs in one basket, especially when dealing with smaller, more volatile stocks.
- Speaker #0
So even though this paper provides some valuable insights into momentum and reversals, it's not like a foolproof guide to easy profits. We still need to be smart about how we apply these findings.
- Speaker #1
Absolutely. This research gives us a framework for understanding how these phenomena might work. But you can't just blindly follow the patterns and expect to get rich quick. The market's constantly evolving. What worked in the past might not work in the future.
- Speaker #0
Right. The human element, all those unpredictable emotions and reactions that drive the market, you know, can always throw a wrench into the best laid plans. But one thing this paper does really well is it challenges those traditional risk factors. Didn't the author use the Fama French three factor model to see these patterns were just a matter of certain stocks being riskier than others?
- Speaker #1
You got it. And what's fascinating is that. Even after controlling for those factors like market risk size and value, the reversal effect for large cap, low volatility stocks is still there.
- Speaker #0
So it's not just that these stocks are riskier and therefore expected to have lower returns. There's something else going on, something the traditional models don't capture.
- Speaker #1
Exactly. It suggests that behavioral factors, those irrational human impulses, might play a bigger role than we previously thought, especially when it comes to these like predictable large cap companies.
- Speaker #0
OK. That makes the whole thing even more intriguing. But let's get back to the practical side for a second. How can we use this knowledge to build actual trading strategies? What are some concrete examples of how these patterns could be exploited?
- Speaker #1
Well, one strategy could involve buying those large cap, low volatility stocks that have experienced like a recent dip, betting that the reversal effect will kick in and push the price back up.
- Speaker #0
So essentially buy the losers and wait for them to become winners. But wouldn't you need to be very precise about your entry and exit points? After all, we saw that the reversal effect fades over time.
- Speaker #1
That's right. You'd need to carefully consider your evaluation and holding periods to maximize the chances of capturing those early gains. And of course, risk management is crucial. You wouldn't want to put all your money into a single stock, no matter how promising the pattern seems.
- Speaker #0
And on the flip side, for those high volatility, momentum-driven stocks, A simple trend following strategy might make sense. Buy the stocks that are going up and ride the wave until the momentum starts to falter.
- Speaker #1
Yeah, that's another approach. But again, timing is key. You need to be able to identify. You know when the momentum is shifting and get out before the tide turns against you.
- Speaker #0
So it sounds like this paper gives us like a toolbox of ideas, but we still need to figure out. the best way to use those tools. There's no one size fits all solution.
- Speaker #1
That's the beauty and the challenge of algo trading. It's all about understanding, you know, the nuances of market behavior and using that knowledge to create strategies that give you an edge. And this research definitely adds another layer of sophistication to our understanding.
- Speaker #0
OK, I'm starting to see how this paper could be a game changer for algo traders. It's not just about chasing momentum or betting on reversals. It's about understanding the interplay between those forces. And how they're influenced by factors like size volatility and information uncertainty.
- Speaker #1
Exactly. It's about moving beyond simple rules and embracing a more nuanced, data-driven approach to trading.
- Speaker #0
This has been an eye-opening discussion, but I feel like we've only scratched the surface of this paper. There's so much more to explore, like the robustness checks and the author's suggestions for new research directions. Yeah, you're right. There's a lot more to dig into here. For example, the paper looks at whether these patterns hold up. over different time periods and across different exchanges. It's one thing to find a pattern, But you know, it needs to be robust if we're going to base trading strategies on it.
- Speaker #1
Absolutely. And that's one of the things that makes this paper so compelling. Weiz is to great lengths to really test the validity of his findings. He looks at different subperiods within that larger data set, like the 1960s to the 2000s. And he also compares the results across, you know, NYSE, Amex and Nasdaq.
- Speaker #0
So he's making sure those patterns aren't just like a fluke, a one time thing that happened to show up in the data.
- Speaker #1
Exactly. And the good news is that the results are pretty consistent. the coexistence of momentum and reversals, the role of volatility, the impact of information uncertainty. These patterns hold up pretty well across those different time periods and exchanges.
- Speaker #0
That's reassuring for anyone thinking about using this research. To build trading strategies, it adds like a layer of confidence that these patterns are more than just random noise.
- Speaker #1
Right. It suggests that there's something fundamental going on here, something that's like deeply rooted in how markets work. And that's what makes this paper so valuable. It's not just providing a set of trading roles. It's giving us a deeper understanding of market dynamics.
- Speaker #0
Okay, I'm sold. This paper is officially on my must-read list. But before we wrap up, I have one more question. The paper mentions that existing behavioral models don't fully explain this coexistence of momentum and reversals. What kind of new models are needed?
- Speaker #1
That's a great question. And it's one that should keep researchers busy for years to come. Wei suggests that we need models that take into account the fact that Not all companies are the same and not all investors think alike.
- Speaker #0
So instead of assuming everyone behaves rationally and has perfect information, we need to acknowledge the messy reality of human psychology and the different ways that companies operate.
- Speaker #1
Precisely. He calls for models that consider both heterogeneous firms, meaning companies that reveal information in different ways, and heterogeneous investors, meaning investors with different biases and ways of processing information.
- Speaker #0
That's a pretty tall order. But I can see how those kinds of models could be revolutionary.
- Speaker #1
Yeah, imagine being able to predict how different growths of investors will react to specific news events, taking into account the company's communication style and the investors'own cognitive biases. That would be a game changer.
- Speaker #0
It's like being able to peek inside the minds of the market.
- Speaker #1
Exactly. And while we're not quite there yet, this paper is a big step in that direction. It's pushing the boundaries of our understanding and challenging us to think differently about how markets work.
- Speaker #0
Well, on that note. I think we've done a pretty thorough deep dive into this paper. It's been a fascinating journey, full of twists and turns, and I'm sure our listeners have learned a ton about momentum reversals and the role of information uncertainty.
- Speaker #1
It's been a pleasure.
- Speaker #0
Thank you for tuning in to Papers with Backtests podcast. We hope today's deep dive gave you some useful insights. Join us next time as we break down more research. And for more papers and backtests, find us at https.paperswithbacktests.com. Happy trading.
