Perhaps, but only if you think like a retail trader
Every now and then I receive a question about the markets being rigged. It isn’t a question as much as it is a statement on the futility of trading, especially for the retail trader.
The answer may depend on your definition of ‘rigged’, but I think the answer is yes no matter how you slice it.
Just a few months ago the SEC charged former Indiana Congressman Stephen Buyer with using inside information to buy $1.5 million in T-Mobile stock. If you take a moment to read the press release, you’ll notice that what he did sounds perfectly legit. Don’t get me wrong, I know it’s illegal, but it’s a bit like speeding. Lots of people do it, but only a few get caught, and even fewer care about the consequences of getting caught. Are you going to stop driving because of those speeders? You can just as easily learn how to avoid them by staying in your lane. I like to apply the same logic to the market.
Here’s an excerpt from one question I received concerning rigged markets:
This may sound cynical or paranoid, but I wonder about this [the market being rigged] when I see trading stats. Supposedly 99% of day traders fail. But since a trade is a two way exchange, that means 99% of something is winning and mopping up the profits. A 99% win rate would be beyond suspicious at any gambling table or auction house. So that begs the question… is the entire system rigged — are traders being played by the platforms and/or trading system itself? If so, then how? I have some theories confirmed by the FTC, but I wonder if these can still be beat.
(I asked him what those theories were and will share them with you in a moment.)
Okay, so this is hyperbolic and overly simplistic, but I get it. I’ve been there too. Trading is hard and the sharks are out to get you. Sharks are always going to play tricks. They are always going to exploit opportunities to move markets in their favor. They are always going to look for faster or better data.
Much of what you think is ‘rigging of the market’ is just a price test or a whale/shark exerting power. That power can also form a trend that anyone can follow. Instead of throwing your hands up in frustration, study the sharks/whales and follow their lead.
The Hunt For Better Information
I’ve read the biographies for many traders — my favorite trader is Jesse Livermore (to read more about my favorite traders, click here). In addition to market structure, they were all obsessed with data, especially the speed of data.
Many people think that Munehisa Homma (本間 宗久) 1724–1803, the creator of Candlesticks, was successful because of the development of Candlesticks, a type of calculus for bar formation, but what truly made him successful was the ability to get data faster than anyone else. Also referred to as ‘Sakata Rules’ — Homma traded rice at the local rice exchange in the port city of Sakata — Candlesticks were used to visualize market structure, but you still had to get the data.
As you can imagine, data wasn’t as easy to obtain back then, so as the story goes, Homma had a network of men spaced six kilometers apart — from Osaka to Sakata — to track market prices. While other rice traders were asking questions about rigged markets, this guy was revolutionizing the game.
Things haven’t really changed much. Traders are still looking for (and finding) better and faster ways to analyze and access data.
This is the point when many day traders give up. ‘The whales in the game are too massive to fight’, they say. ‘How can you possibly compete with the Homma’s of the world?’ The answer: You don’t have to compete — you just have to follow their lead.
Trading is a dark and scary forest — nothing is fair. If you meet a fair maiden in the forest, chances are she wants to kill you. Nature can be as ruthless as the market, so we can look to nature for clues on how to play the market.
A Remora, also called a “sharksucker”, has a suction disc on its head that looks like a Venetian blind. The disc allows the Remora to attach itself to the shark. In this way, the Remora gets free transportation and feeds on the scraps left by one of the most deadliest animals in the world. Something that would be wildly dangerous to most creatures is how this animal thrives. By understanding market structure and the ways in which the big boys wield power, you can become a market Remora.
Practically speaking, what does this mean?
It means you need to watch a market for at least 10,000 hours; you’ll begin to see patterns. These patterns are referred to as market structure. They were there 90 years ago when Richard Demille Wyckoff introduced the Wyckoff method and they are there today. These patterns are created by the rules of the market; more specifically, by the processes that move price. You can legitimately cheat the learning process by turning up market replay to 500x, but there’s no getting around developing an understanding for market structure. You’ll be able to identify power in the market and how it shape-shifts from whale to shark depending on the set-up. The good news is that once you understand the market structure for one market, you can transfer that knowledge to others.
“Lesson number one: Don’t underestimate the other guy’s greed!”
- Frank Lopez, Scarface
One of the most common questions I get regarding market manipulation relates to the 2014 article that came out in the New York Times (NYT) referring to the high frequency trading (HFT) algorithm Gravy.
Ultimately, Gravy was an HFT program that took orders on both sides of the market to boost the price of a stock at the end of the day. The example used in the article was for $Ebay (Nasdaq: EBAY) — they were able to push the price up $.03 at the end of the day; it’s not much, but it can be — thus the name Gravy.
I’m jaded so I have a hard time understanding what makes this illegal. Market anomalies get exploited and that’s probably what this bot was aimed at doing — finding an anomaly in market prices and exploiting it.
Everything described in books like Flashboys (getting access to information early, buying and then flipping) is what brokers have been doing for years — it’s not a scandal, it’s the market.
Traders can buy ahead of a client that is about to buy a large position. They can ramp the price up by buying without letting the market digest. They play a lot of games and they always have. With this in mind, here’s the rest of the question:
The FTC / SEC busted companies who were supposed to handle the digital order load for the stock market orders. Those companies were nestled next to the exchanges to help process orders. What they did instead was 1) observe the mass of orders coming in, 2) send their own orders ahead of them to work the price gap or even take a controlling position, 3) then allow the public orders to land on manipulated prices and newly moved targets — all within milliseconds.
This practice is known as front-running and can show up in various ways. It [is] being done by order processing middle men [and] is extremely devious and hard to detect since it seems hidden in the chop.
The reason I bring this up is this… the front running only happens in live trades. It never happens in back-testing. I believe it makes up a big part of the mystery as to why back-tested models don’t work in live trades. Basically a crooked middle man (or several) are between you and your targets.
Those of you on the hunt with us know that my ears perk up whenever I hear the word ‘backtest’. So this guy is suggesting that the discrepancy found between backtests and live results is due to internal front-running, but it’s important to realize that those crooked middle men ARE in backtests too. If they are in the price, they are in the backtest. Second, this doesn’t hurt you as much as it disenfranchises old school brokers, which is why you’re hearing about it.
So if front-running isn’t an issue, why are backtests inaccurate?
Backtest accuracy is a big issue. It plagues those of us that rely on backtests to test strategies without losses. The biggest issue is the historical calculation of data. In particular, how does the backtest platform calculate the previous bar. This is because most strategies are triggered by the closing price of the previous bar.
Bars are created (range, minute, volume) based on how the bar type is calculated. This is why it’s important to have a backtesting platform that uses more than the OHLC of the previous bar for historical data — you need tick level price changes to simulate a live market.
So, bar type calculation is the biggest issue for most backtest models, not front-running. The price data doesn’t change between when it’s stamped and when it becomes historical data, but the calculation of that historical data can greatly change backtest results. It is especially problematic for complex bar calculations, i.e., Renko or Point and Figure. Gaps or holes in the data can also be an issue, especially for long-dated backtests. This is one reason we only conduct backtests for one year. The further out you go, the more your audits will fail.
Another way we’re hacking backtest inaccuracy is by tracking real-time trades on a weekly basis and comparing them to the backtest. To be clear, the account we use is a simulated account, so the dollars are not real, but the strategy is run 23/7 on a virtual server located in Chicago and the trades are made based on real-time data, not backtest or historical data. The goal is to develop a list of strategies that make the same trades in real-time as they do in the backtest, which means we can trust backtest results.
I haven’t been able to find anything similar to this on the web. I can only speculate about why that is, but I’m sure it feels like a Pandora’s box to some. And, auditing backtest results isn’t as much fun as running backtests or optimizations. But, if you’re honest about the hunt for automated trade strategies, you must admit that backtest inaccuracy is one of your biggest enemies. I think what we’re doing has the potential to be a real game changer in our hunt and I’d love to get your feedback.
Real-time vs backtest reports just started two weeks ago and are published in the Mudder Report. To read the latest Mudder Report, click here. Look for more on this subject in the September 2022 update.
If most day traders fail, it’s due to the inability to manage emotion and ego, which feeds lack of discipline, not rigged markets. It’s important to know who your enemy really is (hint: it’s you) because discipline is a by-product of knowing how to manage your ego.
“Everyone has a plan until they get hit in the face.” — Mike Tyson
Trading is like combat. The goal is to practice so much that your subconscious takes over when you’re hit in the face (wax on/wax off). It’s about managing adrenaline.
It took years for me to develop a risk management system that could ‘manage my ego’. It’s the main reason I fell in love with automated trading strategies. Some of the primary challenges are the same, but on the whole, the hunt for the “holy grail of automated trading strategies” is different from the hunt for “what it takes to be a good day trader”. The latter requires the management of your reaction to a slap in the face. It’s about putting together an action plan to accomplish what you wish you’d done rather than what you normally do.
The following clip is 3 minutes long, which I know is an eternity for some, but it’s one of my favorite clips from the TV show Seinfeld. This is the scene where Jerry famously tells his best friend George: “If every instinct you have is wrong, then the opposite would have to be right.” I often reference this scene when thinking about the markets.
Brokers/retail shops know the psychology of their customer. They know your triggers. Many trade set-ups are manipulated to make you think the market is about to go down/up when it’s not. If the trade is obvious, it’s probably a trap/test.
So what should you be looking for? In addition to looking for obvious trades to go the other way on, I’m looking for heavy buying in the market. I’m looking for block trades. I’m looking for a price divergence from indicators (to learn more about how to spot divergence patterns click here). These are all clues that big money has entered the market and prices are about to be tested.