Speaker 1: Beneath the surface of every stock price, every single trade, there's a hidden language at play. It's um it's a language of powerful, often unseen signals guiding market movements. Almost as if the stock market is whispering secrets and if you know how to listen, you know, you can gain a significant edge. It's absolutely true. I mean, despite the common perception that financial markets are perfectly efficient, they consistently leave these subtle yet incredibly informative footprints.

Speaker 2: Yeah.

Speaker 1: So, our mission today is really to take a deep dive into two surprising sources of this hidden market intelligence. First, the often overlooked world of options trading.

Speaker 2: Okay?

Speaker 1: And second, the massive deliberate moves left by institutional whale activities.

Speaker 2: Whales, right? So, we're going to unpack exactly how these, let's say, less obvious market dynamics can predict future stock returns. And hopefully, this gives you a real shortcut to being truly well-informed. The big question we're wrestling with today, I guess, is

Speaker 1: how do transactions in one market like options or these huge strategic moves of those big players, the whales, how did they actually provide insights into what stocks will do next?

Speaker 2: Yeah. And maybe even more importantly, why aren't these signals just immediately obvious to everyone? Why isn't it priced in instantly?

Speaker 1: Exactly. Okay, let's start peeling back the layers then of this hidden language, maybe starting with options.

Speaker 2: Good.

Speaker 1: The foundation here is really quite simple, right? It's order flow. When you buy a stock, that's a buy order. When you sell, it's a sell order. Pretty basic. More buy orders generally push prices up. More sell orders push them down. That's uh that's market mechanics 101. Absolutely foundational. Right now, what's truly fascinating is how the options market interacts with this. So, when you or I buy or sell an option, there's always, well, almost always a market maker on the other side of that transaction. And to manage their own risk from that option trade, they uh they immediately turn around and execute a corresponding trade in the underlying stock. This essential practice is called delta hedging.

Speaker 2: Delta hedging. Got it. So, they're trying to stay neutral.

Speaker 1: Exactly. It's how they balance their books, manage their exposure from the option they just traded with you. And this is where the picture starts to get well much clearer, right? Our sources reveal that the total stock trading imbalance in the market, all of those buy and sell orders we just talked about, can actually be precisely broken down into two distinct parts.

Speaker 2: Mhm.

Speaker 1: First, you have what's called option induced order imbalance or OOI.

Speaker 2: Oi. Right.

Speaker 1: This is the imbalance in stock trades that directly results from options market makers doing their delta hedging. Like the ripple effect from options activity.

Speaker 2: That's a good way to put it. Yeah. The ripple effect.

Speaker 1: And then the rest of it, the other part is the stock order imbalance or SOI. This is the remaining imbalance in stock trades. All the activity that's entirely unrelated to options hedging. It's the, you know, the pure direct stock market buying and selling.

Speaker 2: Okay? So OOI from options hedging, SOI from everything else. Now here's the bomb. shell. I guess this tiny ripple effect from options, the OOI, you said it averages what, only about 3.4% of total trading.

Speaker 1: Yeah, it's surprisingly small on average.

Speaker 2: Right? But it isn't just noise. Our sources say it's like a crystal ball for future stock returns.

Speaker 1: It really is remarkably predictive. And what's truly groundbreaking, I think, is that this signal seems to be based on permanent information flow. It's not just some fleeting trend. It doesn't reverse even over longer horizons.

Speaker 2: Wow. Okay. So, permanent information, not just temporary blips.

Speaker 1: Exactly. And if you contrast this sharply with the SOI, the stock order imbalance,

Speaker 2: the non-options part,

Speaker 1: right? That part doesn't significantly predict future stock returns. I mean, it shows a large immediate price impact, sure, but that impact is temporary. It reverses pretty quickly.

Speaker 2: So, that suggests the direct stock market order flow might be more about say short-term liquidity needs or maybe index fund rebalancing, things like that, not necessarily deep lasting information.

Speaker 1: That seems to be the implication. Yes. the lasting information or at least a significant chunk of it seems to be embedded in that OOI signal from the options market.

Speaker 2: Okay. So what exactly makes this options signal this OOI so potent then? The research points to a few fascinating factors, doesn't it?

Speaker 1: It does. Uh first, it's really about who is trading in the options market. The predictive power of OI seems to come largely from informed traders.

Speaker 2: Informed traders, people who know something the rest of the market doesn't yet.

Speaker 1: Precisely. They're leveraging options because They possess some kind of superior information about the underlying stock. And this effect is strongest, interestingly, for firms that are harder to analyze publicly.

Speaker 2: You mean like uh informationally opaque companies?

Speaker 1: Exactly. Those with a high probability of informed trading, what's often measured as PYN, companies with low analyst coverage, larger bides spreads, smaller market caps, that sort of thing. It points towards information asymmetry being key. And it's not just any option. trade that carries this signal is it?

Speaker 2: No, you're right. The data shows the valuable information primarily resides in at the money ATM and in the money ITM options.

Speaker 1: Okay. ATM and ITM significantly not the out-of-the-money OTM options.

Speaker 2: Why not OTM? They offer huge leverage, right?

Speaker 1: They do offer high leverage, but they seem to be used more often by say volatility traders and their hedging activity might cancel out the market makaker's impact in a way or perhaps the high transaction costs for OTM options just outweigh the leverage benefit for these informed traders.

Speaker 2: Interesting. So, the type of option matters, the type of company matters. What else influences how strong the signal is?

Speaker 1: Well, the OI is also more informative for stocks with low institutional ownership.

Speaker 2: Low institutional ownership. Why would that matter?

Speaker 1: Because those stocks typically have higher short sale costs. It's harder or more expensive to bet against them directly by shorting the stock.

Speaker 2: Ah, okay. So, informed traders with negative news might use options, specifically puts, as an alternative way to profit from that information.

Speaker 1: Exactly. It points to options being used to bypass market constraints like short selling difficulties. And logically, the signal is also stronger when the options market for that particular stock is more active and liquid, more trading, potentially more informed trading.

Speaker 2: And here's a really interesting twist I saw. The predictive power mainly stems from negative OOI.

Speaker 1: Yes, that's a key finding. Negative OOI means seller initiated option trades. Think buying puts or selling calls. So people betting on the price going down or at least not going up much, right?

Speaker 2: And this really supports that idea we just mentioned that informed traders are using options specifically to bypass those short sale constraints when they have bad news.

Speaker 1: Okay, this is fascinating. But what's the real world impact? Can you actually trade on this?

Speaker 2: Well, the research suggests you can. An investment strategy based purely on this OOI signal was shown to generate substantial annualized excess returns. Uh for instance, in the period they analyzed, April 2008 to August 2010, Such a strategy could have yielded something like 22% annually.

Speaker 1: Wow. 22% annualized excess return. That's that's definitely significant.

Speaker 2: It is. And remember that was during a pretty volatile market period too. And what's even more compelling you mentioned earlier is how this predictability holds true not just over longer periods but even intraday like half-hour intervals.

Speaker 1: That's right. The signal seems to contain information that persists even at very short time scales.

Speaker 2: Which raises the question just how early can this signal anticipate major market moves because the really groundbreaking part for me was that the OOI significantly predicts stock price movements a full 5 days before corporate earnings announcements.

Speaker 1: Yes, that's a powerful finding particularly for events with large earnings surprises or negative forecast errors or high analyst dispersion situations where there's more uncertainty or potential for hidden information.

Speaker 2: It strongly suggests that private information is somehow leaking into the options market well in advance of the public earnings release. It certainly seems that way. So, the key takeaway here, I think, is that information from the options market isn't immediately and fully priced into the stock market.

Speaker 1: And why not? Why the delay?

Speaker 2: Well, several possibilities. Maybe it's the sheer complexity of options trading and pricing. Maybe it's the cost and difficulty of monitoring option order flow in real time and decomposing it this way. Or maybe, you know, it's just too nuanced for many investors to grasp and act upon quickly enough.

Speaker 1: Whatever the reason, it creates this valuable window of opportunity, doesn't it, for those who know how to look?

Speaker 2: Absolutely. A window where information exists but isn't yet fully reflected in the stock price. And that window of opportunity is kind of what the biggest players, the whales of the market are also exploiting, right? Though maybe in a different more colossal way.

Speaker 1: That's a great transition because if the options market has its hidden language, then the truly massive moves of institutional investors are like these uh silent powerful rumblings beneath the market surface.

Speaker 2: The whales in the ocean of trades.

Speaker 1: Exactly. These are the giants often moving deliberately to be unnoticed but leaving subtle yet significant traces. And analyzing these movements reveals another hidden layer of market intelligence. So this brings us to exponential technology incre analytic you mentioned. What does that do exactly?

Speaker 2: Right. So Xtec Flow is this tool specifically designed to identify buying and selling activity. It distinguishes between institutional buyside firms, market makers, and even retail traders all gleaned from the US consolidated feed the main tape.

Speaker 1: Okay. Now, the general assumption is that when big institutions are buying or selling that flow reflects something about the stock's fundamental value, right?

Speaker 2: That's the common wisdom. Yes. However, our sources highlight a crucial point. The sheer volume of shares these institutions trade is massive. And because of market liquidity constraints, you can't just dump millions of shares instantly without moving the price against you. They're Trading activity is often slow, spread out over time.

Speaker 1: Makes sense. They don't want to show their hand or disrupt the price too much.

Speaker 2: Exactly. And because it's slow, it's often inefficiently priced into the market in the short term. Xtec product aims to detect these subtle extended footprints and essentially leverage that inefficiency.

Speaker 1: Okay. So, it's looking for these long slow burns of buying or selling from the big guys. Is there evidence this actually works? That these flows aren't just random noise?

Speaker 2: Oh, definitely. The analysis of these institution flows reveals something crucial. They aren't random at all. There's a strong persistence in these large trades, momentum, if you will,

Speaker 1: like an oil tanker, as you said, hard to turn quickly.

Speaker 2: That's a perfect analogy. Autocorrelation tests, for example, show that something like 71% of symbols show significant non-random patterns in institutional flow. It's not just chance. Wow. Over 70%.

Speaker 1: Yeah. And other measures like the Hurst exponent average around 65, which also demonstrates this inherent momentum in equity flow. It's statistical proof that these large trades aren't immediately absorbed. They create a predictable pattern, at least for a while.

Speaker 2: That's a powerful idea, right? But can this kind of flow detection really anticipate major market moves ahead of time, or is it more of a sort of backward-looking confirmation?

Speaker 1: No, it can be incredibly predictive. Our sources provide a really stunning case study. Bergkshire Hathaway's massive sale of Apple stock earlier this year.

Speaker 2: Ah, yes. I remember the headlines when the 13F came out, right? But remember that 13F filing where big institutions disclose their holdings that often comes out weeks or even months after the quarter ends. So the information is significantly delayed.

Speaker 1: So the public found out months after the trades actually happened.

Speaker 2: Yeah.

Speaker 1: How early could Xtec see it?

Speaker 2: Get this. Xtec's flow indicator detected significant seller activity in Apple starting way back on March 22nd, 2024.

Speaker 1: March 22nd.

Speaker 2: Yep. And the indicator then showed the selling appeared to stop around May 1st, 2024. Now the actual 13F filing, the one that revealed that whopping $51.1 billion Apple sale wasn't public until August 14th, 2024.

Speaker 1: August 14th. So March, April, May, June, July. That's more than 135 days.

Speaker 2: Over 135 days after Xtec had already pinpointed the trade start and end. And apparently they even estimated its total size within about 3% of the actual value just from the flow data.

Speaker 1: That is that that's an incredible lead time. It perfectly illustrates the edge, doesn't it?

Speaker 2: Absolutely. Identifying these large trades in real time or Near real time Xtec offers daily or even one minute granularity delivered end of day or even intraday so you could potentially act on it much sooner.

Speaker 1: Exactly. It allows for capturing that excess return or edge. The temporary market impact from such a large trade because it's slow creates a momentum signal. You could potentially trend follow that. Okay.

Speaker 2: And then maybe even more interestingly at the trade's conclusion which the flow indicator helps pinpoint arbitrage opportunities often arise because the stock price might mean revert back once that temporary pressure is off so you can play the momentum during the trade and the reversal after it finishes.

Speaker 1: Potentially. Yes. It's about having the right lens to see these large slow-moving operations as they happen, not just months later in a filing.

Speaker 2: And I imagine the usefulness goes way beyond just front running or anticipating 13F filings, right?

Speaker 1: What are some other ways this kind of flow analysis can be applied? Oh, it's incredibly versatile. You can apply it directly to flow-based momentum and mean reversion strategies like we just discussed, but also it provides really valuable real-time market color for execution traders trying to manage their own large orders or for risk managers trying to understand positioning.

Speaker 2: Okay, that makes sense. What else?

Speaker 1: You can use it to better interpret pre and post earnings stock behavior. Is the move driven by fundamentals or is there a big flow underneath? Interesting. You can use it to gauge macroeconomic impacts on specific stocks or sectors. It can act as a timing overlay for other strategies like statistical arbitrage. Maybe only take signals when institutional flow confirms the direction.

Speaker 2: You could probably use it to estimate market impact before doing a large portfolio rebalance yourself.

Speaker 1: Exactly. Predict opening and closing option imbalances. Identify intraday alpha signals. Even potentially predict 13D filings. Those are from activist investors taking a big state.

Speaker 2: Activist filings, right? Or M&A activity, maybe index additions or deletions. Those all involve big flows.

Speaker 1: Precisely. Index events, M&A positioning intelligence. It provides a really comprehensive view of those often hidden market mechanics driven by large players.

Speaker 2: And does this just work for stocks or?

Speaker 1: Actually no. Xtec also has a similar analytic called Apollo Flow for global futures. It offers daily insights kind of like the official commitment of traders report but without that typical T+ 4-day lag.

Speaker 2: So faster insights into futures positioning too.

Speaker 1: Yeah. Covering the top 100 to 300 global futures products. They even mentioned having a macro forecasting model for CPI built off related principles. with supposedly very high accuracy shows the breadth of the approach.

Speaker 2: So if we try to connect all these dots now the options induced flow the big institutional whale movements what's the unifying theme here?

Speaker 1: I think the unifying theme is pretty clear financial markets despite theories are not perfectly efficient at least not instantaneously.

Speaker 2: Right information does exist in the trading behavior itself and that behavior if you can decode it can actually predict future price movements.

Speaker 1: Absolutely. And what's fascinating is that what Whether you're looking at the very specific delta hedging of options market makers or the massive often deliberately obscured trades of institutional whales, the ability to decompose and analyze these subtle signals at a really granular level sometimes like you said down to the minute seems to be the key to understanding and potentially profiting from these market inefficiencies.

Speaker 2: So for you the listener, this deep dive hopefully reveals that simply looking at you know basic price charts or standard volume figures might mean you're missing some really significant hidden signals. Being truly well-informed means trying to understand these underlying drivers of demand and supply, these hidden flows and how they subtly hint at future value. It's really about recognizing that information dissemination in markets is complex. It's often delayed and that creates tangible opportunities for those who can decipher these deeper patterns.

Speaker 1: Well put. Today we explored how these specific patterns both in options trading and in Large institutional equity flows hold some surprising predictive power for stock returns. They reveal information long before it becomes common knowledge or hits the headlines. It's really a testament to the complex intricate dance of supply, demand, and information that dictates market prices.

Speaker 2: It truly is.

Speaker 1: So maybe a final thought for everyone listening, consider how these insights really challenge that textbook notion of perfectly efficient markets. If informed trading leaves such clear footprints both in options and institutional flows, what What other hidden signals might be out there waiting to be discovered?

Speaker 2: Yeah. And what does that imply for how we should approach investing or even just understanding the economy in this increasingly data-rich world we live in? It's definitely something to think about.

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