Forex Factory (
-   Commercial Content (
-   -   Institutional Equivalent Education? (

ianf0ster Sep 29, 2019 8:43am | Post# 941

At last Boris Schlossberg (of BK Forex) has sent out an interesting email again.
My comments are within it in blue:


Dear Ian

Trading Systems?
Forget Mr. Right, Choose Mr. Right Now
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. -That may be partly true if ignoring the most important aspects of trading and just concentrating on Price Action. In actual fact each market moves based upon the actions of the participants in that particular market. And hardly any professional institutional trader will trade all the markets - they specialise!
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. - The problem here is to have a robust system without it being cherry-picked. If your system is cherry-picked then it will not be robust when the market changes slightly - for example when most of the top professional traders go away on vacation and their less experienced juniors are left to handle the desk!
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 way Boris puts this makes it read like complete garbage of course all trading systems don't fail all the time. Otherwise nobody would ever make a profit! I think what he means is that if you run a trading system for long enough - then eventually it will fail. On the other hand, if once it fails you continue running it for long enough it will start to win again!
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. - Easier said than done!

ianf0ster Oct 11, 2019 5:51am | Post# 942

2 Attachment(s)
I haven't posted about my personal trading for a while, I do so now - but don't expect regular updates!

I have just posted in another thread because somebody in there though that a profit of 10% in a month was actually good!
It isn't because:
A). A month is too short a period
B). you don't know how much risk was taken
C). Depending upon the trading style and hour traded, 10% per week is possible.

Here is my Post:
I'm a lousy trader - but much better than most!

The reasons I am better than most are because:
1. I have been taught by probably the best. Taught both Fundamentals and OrderFlow (though I don't use Orderflow much- its too fast for me).
2. I have found a style and some markets (Major currency pairs for News, Oil for Inventories, Oil at major levels) that works for me.
3. I use a money/trade management system that suits my personality (multiple units, plus scaling both in and out).

Here is a short record of all my completed trading days so far in October - just so you know that I was not hypeing or B*S*ing in my post above:
Click to Enlarge

Name: Trading-October-1.png
Size: 120 KB

Click to Enlarge

Name: Trading-October-2.png
Size: 136 KB

That is a profit from trading only (after Fees and Commissions) of $5400 in 7 trading days. Or more meaningfully a net profit of + 18%


ianf0ster Oct 23, 2019 5:41am | Post# 943

5 Attachment(s)
Some Key Times of Day for Oil (CL) Trades:

(The following is a portion of a larger update I'm working on for the 'Oil Trading' document that I produced for those Sharp Edge students who joined my free 'Self Help Group'. The original document has not been updated for years because it is primarily focused on just the EIA Crude Oil Inventory release. And of which I have posted some details for the 'Sammy Trade' in this thread.)

London Open, US CL Open, London Close, Daily (Energy Product) Futures Settlement

Of these I hardly see anything about the Daily Settlement - so I guess it is a less obvious one.
I have found that there is often a (short-term ) reversal in CL price starting around 14:28 Eastern Time (= usually 19:28 UK Time).
I often see at least 2 prior 2 min candles going in one direction before the Settlement Candle (and often several others) reverse direction.
Click to Enlarge

Name: Oil-DailySettlementTime.png
Size: 27 KB
Click to Enlarge

Name: Oil-LessObvious-KeyDailyTimes.png
Size: 108 KB
Click to Enlarge

Name: Oil-LessObvious-KeyDailyTimes-DailySettlement.png
Size: 61 KB
Click to Enlarge

Name: Oil-LessObvious-KeyDailyTimes-DailySettlement-1.png
Size: 177 KB
Click to Enlarge

Name: Oil-LessObvious-KeyDailyTimes-DailySettlement-2.png
Size: 215 KB

While this is hardly ever a large move, it is mostly quite predictable and the predictability can be enhanced by other factors such as Levels, Value and OrderFlow (such as the Voltic and the Pressure Line).

ianf0ster Oct 23, 2019 6:42am | Post# 944

2 Attachment(s)
Some Key Times of Day for Oil Trades: London Open ..
Click to Enlarge

Name: CL-LDO-Ray.png
Size: 636 KB
Click to Enlarge

Name: CL-LDO-Ray-2.png
Size: 73 KB

1st image is from Ray's Tweet. Apart from the time and the Value , also notice the typical London game playing with levels.
I added the white vertical dotted lines in (on the 07:55 and 08:55 candles) so you can see the times on the bigger picture.

ianf0ster Oct 27, 2019 8:39am | Post# 945

At last an interesting email from Boris Schlossberg: In Trading, Why is the Obvious not so Obvious?

Dear Ian

In Trading, Why is the Obvious not so Obvious?
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 Puerto 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.

Amazingly, I have no comments other than that it is nice to see that Boris admits that some of his signals sometimes work better in reverse!

mcquak Nov 22, 2019 5:44am | Post# 946

1 Attachment(s)
The value lines concept works out perfectly when applied correctly.
This morning another nice trade with value lines were in confluence with L2 shorts.

Easy money.
Click to Enlarge

Name: Screenshot_20191122-113741_TradingView.jpg
Size: 520 KB

© Forex Factory