I should say it is hard for a single trader. I think a true statistical edge is in having teams of data curators so you can process massive amounts of data, then have teams of signal finders so then you can put on hundreds or thousands of bets at a time. This is where you can see that the time average does not equal the ensemble average. You can't find that many bets at a time though as one person. Statistics spread across in time are problematic because of ergodicity.
For sure. When to make that split is such a hard problem though. I feel like I know a little about it but so much is a mystery.
I built a predictive model (leading indicator) using financial engineering and quant finance techniques. It makes typical approaches look like a joke.
My edge is discovering profitable ways to break or circumvent the myriad of gurus rules and find ways to pragmatically employ the discoveries in trading. Since most traders are hell bent on following their rules and since most traders lose...well...you catch my drift...right?
I checked your threads a few times. You like to work an average price, i.e. "scale in" or "average down" and it causes many to criticize you. We all know that the distance of a stop from the market influences the probability of that trade being profitable on a risk-reward basis. In other words, the closer the stop, the more likely it is to get hit, all things being equal. The thing is, most of the market moves intraday are highly contested. So, if you are bullish, and buying as the market is moving down, usually a large group of traders are selling into the move. This could be because they bought and are being forced out of the market, or because they know (with a high probability) that it will move down a little more (even just a few ticks). The trick is to figure out when the market is about to stop moving in the direction it's going and have exposure just before that time. I think you are right to trade the way you do. Just remember that with that strategy the bigger the bank-roll and the more aggressively you increase size the better. This is because even if you double your exposure with each new trade, your average price will be away from market. I know for a fact, that there are automated robot ES traders that aggressively increase size up to about 100 million dollars notional and then will dump at the first moment the liquidity will allow them to exit at a profit. So, you are not alone when you trade like that.
Volatility clustering, path dependence and Convexity But here is a nice post from macro-ops.com Find Your Trading Edge By Exploiting Errors May 25, 2017 / Alex Barrow / Market speculation is a zero-sum game. In order for someone to win, someone else needs to lose. You can think of the market as a collection of players… some weak, some average, and some strong. Your goal is to take action against the weak players and relentlessly separate them from their money. To do this you’ll need a trading edge. Now the word edge is thrown around a lot in finance, but what it really means is the ability to exploit the errors of your opponents. If you can’t find these errors, or if your opponents just aren’t making them, you can’t win. Why? Because to make a bet with positive expectation, someone else needs to make a bet with negative expectation. A bet with positive expected value or “positive EV” means that placing it repeatedly will result in net profits. The outcome of any single instance may be negative due to variance or luck, but over the long-run the bet’s edge will express itself and profit. The opposite is true for a “negative EV” bet. A negative EV bet may win in the short-term due to variance or luck, but over the long-term it’ll produce net losses. To thrive in this zero-sum environment you need a relentless focus on other players’ errors. You need to find and exploit them. How To Find Errors Finding errors begins with asking the right questions: Which market players make the most errors? Why do they make them? What market situations trigger these errors? In answering these questions, we can break market errors into two types — unintentional and intentional. Unintentional Errors Unintentional errors are made by players who try to win, but then fail because of flaws in their process and implementation. Taking advantage of these errors can be very lucrative. Here’s a list of the most common reasons weak players make bad bets: Ego Fear Myopia Labeling Ego Many players are only in the market to stroke their own ego. True or not, they want the world to know they have the “biggest dick” in the room. In the poker world we call these guys “ballers”. They aren’t at the casino to win, but are instead trying to bully the table in order to come off as rich and aggressive. They could care less about making positive EV bets. These guys are there to show off. You can easily spot ego-driven market players on Finance Twitter. These are the ones who hold onto particular narratives with a vice grip until the bitter end, win or lose. In the process they make tons of negative EV bets which are perfect for the astute Operator to exploit. Look no further than the gold bugs to see ego in action. Gold bugs will never stop buying gold. It doesn’t matter where the price is going. They have a certain set of beliefs about inflation and central bank policy that need to be proven right. The system has to fall apart, vindicating the gold bugs who can finally yell “told ya so!” Nothing else matters. Their desire to be right about gold is purely to satisfy their own ego. Making a trading decision based on ego instead of positive expectation is a huge error that can easily provide you with profit. A gold bug will always be there to buy the gold you’re trying to short in a downward trend. And as you know, it’s pretty easy for a bear to crush a bug… Fear Fear is a key evolutionary emotion that helped keep us alive over millions of years. But in the game of speculation, it only kills us. Succumbing to fear creates large unintentional trading errors. A great example is the investing public that consistently sells at market lows. Fear overwhelms their trading decisions and leads to them sell at the bottom when they should be buying. It takes a considerable amount of time, effort, and mental rewiring for an investor to overcome the fear of losses. But doing so gives you an edge over those who haven’t. Take hedge fund titan David Tepper for example. In 2009 he loaded up on shares and debt of various banks when everyone thought they were headed for bankruptcy. By the end of the year he pocketed himself a cool $2.5 billion… Watch for trades made out of fear. You can take the opposite side for huge gains. Myopia It’s tough for investors to picture a future drastically different than their immediate past. Weak players lack the imagination and foresight to do so. This can be exploited. Many short sellers, for example, constantly step in front of innovation trains and get mowed down in the process. The unimaginative bears in Tesla have been getting flattened for years… Their first mistake is not accepting that Tesla could indeed revolutionize both the auto and energy industries. Their second mistake is discounting the power of other investors’ belief in that same possibility. Herding and reflexivity can push prices much higher than what “conventional” valuation methods infer. Watch for these trigger happy short sellers fighting large upside momentum. Most of them can’t take the pain and puke out. The resultant buying pressure they create from covering their shorts will send the market screaming higher once again. It’s easy to benefit if you’re on the right side. Labeling In professional fund management there exists a game within a game. You have the trading game and then you have the asset gathering game. Managers have to balance both. This means that sometimes a manager may have to take a negative EV action in trading because it’s a positive EV action in asset management. I call this “labeling”. Since a manager may be known as the “oil bull”, “equity bear”, or “value guy”, he’s forced to tilt his bets towards his brand. That way he can maximize the business side of his fund (sales and marketing). The charming and brash founder of Eclectica, Hugh Hendry, paid greatly for his industry label. Hugh defined his brand by betting on a market collapse in 2008. He knocked it out of the park and his assets under management swelled. But from then on he was forced to stick to his permabear view. That’s what his new investors hired him to do. They didn’t want him to own beta. They wanted protection if the global economy went double dipped. Unfortunately for Hugh that meant fighting the central banks and putting up multiple years of poor performance. Eventually this label drove him mad. In late 2013 he finally decided to flip the cards and go full bull. I was actually on the investment call the moment he announced his decision to bet on higher prices. The fund of funds at my prior employer had money with him. His reasons for turning bullish were sound. The central banks had too much control over the current macro narrative and it was a fool’s errand to fight them. But his investor base didn’t listen. Everyone began pulling out like crazy, including my employer. And guess what? Hugh ended up being right! Despite the fact that he took a positive EV bet in the trading game, Hugh took a massive negative EV bet in the asset gathering game. His fund management business suffered greatly for it. Hugh’s assets under management are now a fraction of what they were even though he’s trading better. Errors stemming from the reality of professional fund management make fertile hunting grounds for traders on the outside. Track the “big brands” and fade their trades when the data clearly supports the opposite of their brand biases. Intentional Errors Capitalizing on unintentional errors is definitely lucrative, but it takes significant time and energy. Players making these errors still want to win the game. They’ll put up a fight and force you to wrestle their money away. Sometimes they’ll even beat you if you aren’t on your A-game. On the other hand, players committing intentional errors are literally giving you their money. These guys are much easier targets. Intentional errors come from players who don’t care if their trade has positive expected value. They’re willing to lose on trades because their goal isn’t long-term profitability. Now that may sound a little crazy… who in their right mind is willing to consistently lose on every trade? Answer: Central banks and hedgers. Central Banks CB’s are the ultimate source of intentional errors. They’re like the guys at the casino willing to donk off millions of dollars with no regard for risk control. In poker we call these players Whales. Nothing is more profitable than exploiting a Whale. Nothing. CB’s don’t care if their trades have positive expected value. Their goal, no matter the cost, is market stability (whatever that means). Post-2008 CB’s made their intentions very clear when injecting record stimulus into the system. They said they’d buy bonds no matter the price. You can make a TON of money exploiting scenarios like this. Ray Dalio has been taking advantage of CB’s for decades. He modeled their behavior into his macro machine and has been benefiting ever since. George Soros plays the CB’s like a fiddle as well. Back in 92’ he broke the Bank of England by taking the other side of their negative EV trade defending the European Exchange Rate Mechanism. Then in late 2012, when Japan began their unprecedented QE program, Soros shorted the yen and massively increased his Scrooge McDuck sized chip stack. These guys know how to exploit a whale — a must-have skill for any serious speculator. Hedgers Central banks may be the most lucrative whale in the game, but they’re not the only profit gusher. Hedgers make plenty of intentional errors you can take advantage of too. Trader’s have been extracting profits from commodity hedgers since the beginning of the futures markets. When a farmer shorts grain futures, he’s doing so to avoid unexpected shocks to his income come harvest time. The farmer isn’t worried about his hedges’ expected value. He’s only focused on his crop and its profits. A large portion of the CTA industry lives off this fact. They consistently make money by taking the other side of farmers’ hedging. The same goes for FX markets as well. Multinationals hedge foreign currency exposure to keep their core operations running smoothly. And once again, they’re not focused on making positive EV bets on the trading side. In equity markets, large institutions like pension and insurance funds hedge their accounts to meet short-term cash flow obligations during volatility events. They purchase protection at a premium and are willing to consistently lose money to avoid liquidity crunches. These negative EV hedging trades create extraordinary opportunity for the nimble speculator who can take the other side when conditions align. Attack The Whales First Whales making intentional errors don’t care that they’re losing. They’re willing to pay you for decades without batting an eye. You can systematically extract profits without them noticing. Compare that to a weak speculator. They need to win or at least break even to stay active. If they’re consistently losing it won’t be long until they go broke or evolve to stop the bleeding. Once they leave the game, there’s nothing left for you to harvest. Ask yourself, “How long can I expect this player to continue making errors?” The best edges come from those who are willing to make mistakes repeatedly without changing their strategy. Use this concept as a starting point for your search. It’s All One Giant Competition Speculation means fighting for a living. Instead of delivering value in exchange for dollars, you need to find weak players and take their dollars. This means constantly searching for poorly performing players and the errors they make. If you’re not thinking in this fashion… then you’re probably the one getting exploited. I’ll let Buffett close this one out. “If you’ve been playing poker for half an hour and you still don’t know who the patsy is, you’re the patsy.” If you’d like to learn more about exploiting errors, then check out our Trading Handbook here.
I agree with what you said in your post, but have you ever witnessed a day when above strategy is unable to dump out of shares? Such days are rare, but they wipe out months of profits in the BEST-case scenerio. God forbid you have them clustered. In my mind averaging down is risk:reward equivalent to selling naked options (short gamma) while trading with tight stops and pyramiding is equivalent to buying options(long gamma). People can trade any way they wish, as long as risks are understood and accepted. IMHO, trading with tight stops requires more skills/edge.
Well, my understanding is that tight stops will increase the fail rate of the trade, but reduce the size of the loss (allowing more leverage). Wide stops will increase the success rate but increase the size of the loss as well (limiting leverage). Not always true, but a heuristic nonetheless. It's kind of tricky because you will select the trade and choose the stop size and leverage at the same time, or maybe not. In other words, the stop, the desired pnl and the trade decision can influence each other. Also, many traders size a trade based on the 'setup' and so the price action or perceived risk will influence the size, the stop, and the decision. I really prefer discretionary trading and having fluid instead of rigid rules, but will honor some kind of risk based stop. But, at the same time, all of these ideas are useful.