Weekly Forex Trading Calendar for November 11, 2019

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of Nov 11, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

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Weekly Forex Trading Calendar for November 4, 2019

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of Nov 4, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

PDF version of calendar110419

Excel version of calendar110419

Weekly forex trading calendar for the week of October 28, 2019.

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of October 28, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

Excel version calendar102719

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In Trading, Why is the Obvious Not So Obvious?

Boris Schlossberg

What do monkeys have to teach us about trading? Quite a lot actually. The following is an excerpt from the Hidden Brain podcast by Shankar Vedantam in which he interviews Yale University psychologist Laurie Santos who studies monkeys on a Caribbean island, Cayo Santiago off the coast of Peurto Rico.

VEDANTAM: I want to get to your experiments in a moment. But just being on this island has apparently revealed all kinds of similarities between humans and other animals. One problem you’ve had to guard against on the island is unethical behavior. Tell me about the monkey thieves that you’ve encountered on Cayo Santiago.

SANTOS: Well, you know, it’s kind of sad to admit that you’re getting ripped off by monkeys, but (laughter) it happens more than you’d think on the island. You know, they’re wily creatures who are often pretty hungry. And humans have backpacks filled with things like lunches and delicious fruit objects for studies and so on. And one of the big inspirations for some of the work we were trying to do on deception and kind of how monkeys think about other minds came from this act of theft on behalf of one of the monkeys. We were running a study about numbers where we were showing monkeys different numbers of objects. And there was one research day that we actually had to go home from the island early because the monkeys had ripped off all of the fruit we were using to display the numbers in the study.

VEDANTAM: (Laughter).

SANTOS: And I think it was really on that boat ride home that I started thinking, you know, they’re doing this in a successful way. You know, it’s not just that we’re dumb researchers and they can outsmart us. They’re specifically trying to steal from us when we’re not aware of what they’re doing, or maybe even when we have a false belief about what they’re doing. And so it really launched this line of research to be, like, OK, how are they thinking about that problem, you know, that they’re duping us in? You know, what are the representations they’re using to solve this task?

VEDANTAM: And is it true that they are not just simply stealing but in some ways going after the easiest targets, in some ways what criminologists might call a rational model of crime?

SANTOS: Yeah. In lots of ways. In fact, we set this up as a study. This was work, early work that I did with John Flombaum. We basically set up an experiment where we gave monkeys the opportunity to steal rationally. What we did was we had them experience -- they’re kind of walking around, and they see two people who are standing in front of a grape, which is a tasty piece of food for monkeys. One of those people is kind of looking at the grapes so if you tried to steal it, he’d probably stop you, whereas the other person is not paying attention, either because he’s turned around or he has a barrier in front of his face and so on.

And we just gave monkeys one trial. And what we found is that, even on that first trial, monkeys selectively stole from the person who couldn’t see them. In other words, they’re rationally calculating, you know, whether or not someone could detect that they’re about to do something dastardly.

Why do I find this story about our primate relatives so fascinating? Because financial markets are as close to a jungle as human society allows and our behavior within that arena is far more similar to monkeys than we care to admit. Tom Sosnoff, who runs TastyTrade and has seen his share of monkey antics on the floor of the CBOE once told me that most new traders approach the market with the assumption that every trade is a 50-50 bet. In reality, the bet is more like 25 for 75 against, because the markets are always lying to you trying to trick you into the wrong position.

I wrote last week that our ability to lie is the only thing that keeps the markets interesting and available to us humans. Otherwise, computers would have been able to take over long ago and just like in chess beat us senseless every time we trade.

I’ve told you how K and I recently developed a series of visual indicators to help us make better, faster trading decisions. But this week I discovered that these tools can also help me spot some of the market lies. After hours and hours of studying a trading strategy using my visual cues, I realized that the very opposite signals, under certain conditions were actually far better, more profitable and more predictable trades.

In trading, the art of lying is why obvious is not so obvious and why so many good-natured logical people get rolled by the action. That’s why having a flexible attitude is perhaps the greatest skill you can develop in the markets which are almost never what the seem to be.

Making Trading Human Again

Boris Schlossberg

If there is one thing true about the past decade in markets it’s that computers now dominate all trading. Its truly been the decade of Virtu and Citadel and the glory days of the individual prop trader are as quaint as the pictures of fat sweaty guys battling it out in Chicago pits.

Execution has become so efficient that brokers all now offer free trades and still make tons of money from kickbacks in the spread. There is no argument that you can no longer compete with a robot on a sub-second level. The machines will always beat you.

Yet anyone who has ever run an algo on any longer time frame knows just how stupid computers can be. Like idiot-savants, they are excellent at producing one single task well, but can’t adjust to even the slightest change of environment. Last month was yet another example of algo apocalypse amongst some of the most famous names in the business as the growth/value books completely broke down creating massive losses that some of the most sophisticated trading models never anticipated.

As I’ve said many times before our greatest asset as humans is our ability to lie. Without lying poker would be a dry boring game between machines and financial markets would have all the excitement of a cell phone bill. It is precisely the messy, inefficient friction introduced by lies and random human activity that keeps markets from devolving into perfectly efficient engines of boredom.

Aside from lying, humans excel at one other activity that binary systems like computers simply cannot master well -- pattern recognition. 200,000 years on the Savanah plain and several billion neurons later have taught us to take note of even the slightest change in the environment.

Kids do this naturally. Move your 5-year-old favorite toy just a few inches off-angle on a shelf and they will notice it right away. I am always astounded at how my older kids when they were younger and my little one now would instantly sense even the most minute changes in our apartment building such as a blinkering lightbulb in the ceiling of the lobby.

Lately, K and I have started to exploit our human skill at pattern recognition by creating visual indicators for TradingView charts that help us make trading decisions in seconds. This has been revolutionary for our business. In the last 10 weeks alone K made more than 1000 pips in swing trades by using her Zip Trader heatmap indicator to help her pick the right trades. I managed to bang out 90% winners in my Flow trades by looking at the visual charts I created for that setup.

The irony is that we haven’t really changed much of the logic of the original strategies. The math behind the set up remains pretty much the same, but the ability to contextualize it visually has not only helped us see the trades faster but also choose them much better.

I am very excited about this project and feel that for the first time in ages we have a true edge on the machines. Next week we will be doing a free webinar about this project of ours so stay tuned. I think you’ll find it very interesting.

Weekly Forex Trading Calendar for Week of October 21, 2019

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of October 21, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

PDF version of calendar102119

Excel version of calendar102119

In Trading Strategies Don’t Work – But This Does

Boris Schlossberg

Over the years I’ve amused many if you with my never-ending battle of the bulge. I’ve gone through the salad and sardines diets, the paleo diets, the intermittent fasting diets in my many attempts to lose the extra 15lbs.

Nothing ever worked. Or rather it worked for a little bit but never worked for long.

Until now.

Happy to say that I am near my high school fighting weight, have held steady at that level for more than three months without any effort whatsoever and generally feel good.

What’s my secret?

I went on a European diet. What’s a European diet? That where I eat anything I want anytime I want but at 1/3rd the lardass American portion. Not 2/3rd’s not 1/2 but 1/3rd -- because that is actually how Europeans eat.

I stumbled across this idea after my tenth visit to David Aranzabal’s annual forex conference in Madrid. As always, when there I fully enjoyed myself, eating and drinking everything that was put in front of me.

When I came back to New York I was certain that put on at least 10lbs, but was shocked to find out that I gained nothing. This made me rethink my whole approach and the rest is history.

I’ve written about the similarities between trading and dieting before. Both enjoy a 95% rate of failure. Both have millions of gurus trying to sell you their “secret” solution and both are multi-billion dollar industries based on hope rather than results.

This time I realized that there is even a deeper connection between the two. Just as there is no “diet” that will help you lose weight in the long run, there is no trading strategy that will make you money for life. This actually explains why books on some of the world’s greatest traders sound like interviews with idiot-savants. That’s because there is no “secret” strategy there.

First of all, when you read accounts of the greatest traders you always walk away amazed at the variety of their approaches. Some trade trends. Some are pure mean reversion traders and some are momentum riders often on the opposite side of the trade from the other guys. Furthermore, often they will contradict themselves in an interview and will talk about how they’ve switched their approaches mid-stream to adjust to market conditions.

What becomes clear is that all great traders are consistent at only one thing -- execution. Just as with “dieting” the only thing that really matters is portion control and natural non-processed ingredients, so too with trading there 2-3 things that will determine long term success.

  1. Take a stop. -- This always the hardest thing to do ALWAYS. You can stop out once, twice even three times, but eventually, you get stubborn or angry or both and fight the move. That’s why the most important execution skill for winning, in the long run, is to lose in the short one.
  2. Position size -- this is actually exactly the same as portion control in dieting. The bigger your size the greater your chance of dying (metaphorically speaking). Position size in levered markets can also be highly deceptive. 5 simultaneous positions at 3:1 lever factor are equivalent to 15:1 gearing for your account.
  3. Letting the trade come to you -- It doesn’t matter if you trade momo or mean reversion, every great trader trades only when the setup manifests itself. Chasing price for the sake of action is perhaps the greatest difference between amateurs and professionals and the less you chase, the better you will become.

That’s it. Just as my “European” diet is very simple so too is most trading success. Strategies change, but tactics are forever.

Weekly Forex Trading Calendar for Week of October 14, 2019

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of October 14, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

PDF version of calendar101419

Excel version of calendar101419

Trading Systems? Forget Mr. Right, Choose Mr. Right Now

Boris Schlossberg

The fundamental tenet of all system trading is that the strategy should work across a broad range of time ranges and a wide swath of products. For example, a “robust” algo in FX should be able to trade all the eight majors currency pairs and make money for 10 years back.

Otherwise, you are just cherry-picking and curve-fitting your data and all the serious data scientists will go tsk tsk in disapproval.

Exactly wrong.

Yes, I may be committing my greatest trading apostasy to date, but I am here to tell you that the ONLY way to make money from algo trading is to cherry-pick away.

First, let’s agree that all trading systems fail 100% of the time. It’s just a matter of time before they start to bleed money. Indeed very often the best-tested systems fail the worst, sometimes at an alarmingly rapid rate when they are put into production. If the laws of data science really applied that would not be the case.

The laws of data science, of course, do NOT apply at all which is why the whole philosophical foundation for determining what is or is not a “valid” trading system is incorrect.

The statistical method implicitly assumes that it is observing the truth. And when it comes to the physical world that assumption is generally correct. The laws of gravity do not change and the flip of a coin over a very large sample size will always end up to be a fifty-fifty bet. But the psychological world is not at all like the physical world. One of our most distinguishing characteristics as human beings is that we lie.

Statisticians in social sciences found out just how much we lie the hard way in the 2016 election. But elections are child’s play compared to financial markets. Financial markets are the absolute apotheosis of human lying. Whether on day trading time frame or investment time frame the function of the market is to sucker as many people as possible into making a false bet.

That’s why data scientists constantly talk about “noisy” data in the financial markets -- which is just a polite way of saying that everybody lies and you can’t draw any conclusion from past price action no matter how far back it goes in time.

So what’s the answer for the retail trader who wants to use algos? Stop looking for Mr. Right and go with Mr. Right Now. The single best way to have confidence that the system will work is to see if it’s been working in the past six months. The success of any trading system, in my opinion, is really a function of it being in sync with the current market regime and whatever unique exploitable patterns you may have found in an individual instrument. So yes, it is very possible for a system to make money in CADCHF and in no other pair and keep doing it for much longer than you think.

That’s why the only practical way to make money algo trading to cherry-pick away. Design the system, test in many pairs and only trade the absolute best most recent results. And then do it again with another system and another system and another system, because the key to making money from algo trading is to run a portfolio of systems that are working and then remove those that start to fail.

Next week, I’ll discuss exactly what I think “failure” means in this context, but in the meantime you still need to backest everything you try and as we know that can be unbelievably tedious, so my friend Daniel Sinnig created an Auto backtesting software that can let you run hundreds of tests while you sleep.

Here is his info here.

Save time and money with the MT4 Backtest bundle. 50% for a limited time at https://mt4.tradingexperience.com

Weekly Forex Trading Calendar for Week of Sept 23, 2019

Weekly Calendar Calls

We have just posted our weekly news trading calendar for the week of Sept 23, 2019. You can download the pdf and excel file by clicking on the Read More Link. These are soft biases on economic data and not trades that we directly trade or track like BK Swing and News.

PDF version of calendar092319

Excel version of calendar092319