For the longest time, there has been something “bugging” me [at least the last few years]; and for as long, I have gone down so many “blind alleys” trying to solve this particular problem, each time not producing anything of tangible value in terms of finding a solution. I’m smart enough to know and fully accept the mathematical proof of Kurt Gödel’s [1906 – 1978] Incompleteness Theorem , which proves any axiomatic system [which is to say ANY financial market trading algorithm like mine] must have limitations and is “incomplete”, in the sense that there are always non computable flaws that cannot be solved. In other words, there is no “Holy Grail” of trading that will get you 100% winners 100% of the time, no matter how many filters and/or schemes you dream up.
For example, in my volatility algorithms for the various markets, I need above average intraday volatility for the algorithms to be profitable with a very high probability of success; what happens when they aren’t, and where do you exactly draw the line that says “volatile” on one side, and “non volatile” on the other? Because no matter how precise you want to be, there will be instances where either side will produce undesired effects; either losses or profits not realized. Therefore, all you can really do is take a stab at whether or not anything you produce, in terms of improvement, is raising your long term probability of success.
Most traders, when they mess with any algorithm, trading system or method, end up reducing profitability unintentionally when they add technical filters and/or rules, that they think, will reduce losses; what they fail to measure or think about is what it does to profitable trades as well. Remember, when it comes to financial trading, you never get something for nothing. Never.
Many of you know that I have been working on the stock indices volatility algorithm since Summer 2016; what has happened in this financial trading arena during 2016 has “opened my trading eyes” to not only the individual world indices, it has made me “re-think” other markets as well, specifically gold [XAUUSD] & USDJPY.
What is unique about 2016 in the stock indices is what I call the “barbell” effect; extreme volatility at the upper & lower “black swan” tail risk areas for January & February, Brexit, and the U.S. election, with the rest of the year stuck in mind numbing nothingness with daily ranges so small they look almost like “dots” or small “smudges” on the daily candlestick charts. How do you trade something that is “bat excrement” crazy one week, then like watching corn grow a month later?
The problem I am referring to is the “2 headed fire breathing dragon” of 1) “chop”; the manifestation of watching every buy/sell signal give a “false positive”, thus leading to a small loss or [worse] losses in succession, and 2) market reversals and leaving a substantial amount of money on the table by not being in them.
During the Summer, I read an interesting response a “quant” fund manager gave in an interview from a financial reporter asking about how he was dealing with the political [Brexit & upcoming U.S. election], and financial [Fed threatening to raise rates one day with one speaker, and then softening the tone days later with another speaker] macro events happening in the stock market. His response was something along the following [paraphrasing], “I’m constantly adjusting my positions according to historical standard deviations from a proprietary predetermined mean, and if a new position is profitable I ‘let it run’, and if it isn’t performing I cut it loose”. Well, this response got my creative juices flowing.
One of the very big problems you run into when you trade stock indices, from a trader standpoint, is the very nature of stocks themselves, i.e. the historical evidence of stock prices rising about 80% of the time [up & flat] and going down only about 20% of the time, which can cause real trading problems. We all want to be able to profit from the “ups & downs”, but I can tell you straight up I have seen, first hand from the trading floor, plenty of trader bodies buried in the “Chicago Trader’s Cemetery” from selling the SP500 “in the hole” [meaning as it’s going down] and getting the position shoved so far up their ass their tonsils hurt.
Since the dawn of electronic trading [end of the 1990’s], directly below the chart of the SP500 as a proxy for the entire stock market.
And what do we see here? About 3 years out of 20 where holding or consistently shorting the index made you money, and the other 17 years good frickin’ luck; so, about 85% up [or flat] and 15% down.
By the same token, two 10 year charts directly below; the first is gold and the second USDJPY. EXIT QUESTION: “Do either of them come anywhere close to an 85% bias in one direction or the other”?
SHORT ANSWER: “No”.
My approach so far, in using the volatility algorithms, has been to initiate buy/sell positions based on time vectors [plum & yellow lines on the M1]; from the standpoint of USDJPY, it works well when the market is active and moving in one direction, but breaks down almost to the second when volatility stalls either on the M1, M30, or HR1. In gold, for the longest time since this market has been tradeable with decent enough spreads so you can actually trade it [about the last 5 years], I have not been able to accurately raise the probability of successful trading from the short side; this has bothered me greatly, and I knew it meant there was a fundamental flaw in my approach to the short side, so the volatility algorithm has left the short side alone and by default, has meant we have given away a tremendous amount of money to the marketplace by not positioning on the short side. And last but not least, whether you trade the DAX30, DOW30, or the SP500 [or any other index for that matter], it isn’t the “long side” of the equation that is the problem; the problem trading these indices is effectively trading them from the short side when there is a “compelling” market narrative [like last January & February when the market as a whole got caught by the idiotic Fed’s December 2015 raise in rates along with a “dot plot” for raises in 2016 nobody expected.] to be short by selling the rallies. Will “time” signals hold up on the downside like they do on the upside?
Again, different markets with different problems, so how can the M1 “time“ be effectively utilized in all scenarios [i.e. long & short side] so that the respective algorithms can be highly profitable? SHORT ANSWER: “They can’t”. The good news is that they are “close” to the best and most optimal solution, kind of like Newtonian physics is to quantum mechanics, but it breaks down when things get either bat excrement crazy or go to sleep.
This last year, for the first time in memory, we got to see both extremes [bat excrement crazy on 3 occasions & nothingness for the better part of the rest of the year] in the stock indices, and because of that I got real time data that was simply unavailable before; and what I mean by “before” is the rise of Central Bank manipulation, HFT’s, VIX slamming, and Plunge Protection Teams deployed worldwide.
So, what can help eliminate “chop” [not totally because nothing can, but reduce it nonetheless] & allow us to capture [from a trading standpoint] reversals in price? The answer is deviations in price.
I will admit, this is a paradigm shift for me. It isn’t something I do lightly, but I can’t ignore the data either; logically it makes sense. For example, why should it matter to you if it takes 20 minutes or 3 minutes to make the same amount of money in any market, with the same risk? Over our short term time frames, everything else being equal, why does time matter? Price is what determines whether we win or lose and puts money in the bank. In essence, while time does still matter for other reasons, it’s like the difference between “point & figure” charts versus bar charts or candlesticks; they plot the same thing but look and feel a whole lot different.
A recent example from USDJPY will show what I mean; directly below is USDJPY from Friday the 13th.
Now, I don’t know about you, but about 2 hours into this day “chop” sets in, and 5 straight buy signals come up empty; not acceptable. Here’s the same chart with the scalper’s algorithm [and the new version 2 algorithm] signal lines directly below.
I could just as easily found examples from gold, the DOW30, and the DAX30. Bottom line is that using deviations is more accurate in keeping you on the right side of the market, whether you choose to scalp or hold the position slightly longer in scope, which is what Version 2 of the volatility algorithm does.
So, as you can probably guess, I’m changing the signal parameters in the volatility algorithms for each market; I’ll be updating the manuals in the next few days and reloading the newer versions back up into the cloud for your viewing and/or download. For those of you trading the volatility algorithm in XAUUSD [spot gold], buy/sell [yes, the sell side is now available in gold] M1 positions are initiated when the slope of all 3 lines [white, yellow, & plum] change; sloping “up” = buy, sloping “down” = sell. Liquidations are the same as before, no change.
Everything for gold [XAUUSD]has been updated and is now on the website; 1) vegas Gold Ver 2 MQ4, 2) Gold Ver 2 Volatility Algorithm Components, and 3) Gold Ver 2 Volatility Algorithm Implementation. These are the new Version 2 updates; please update and read the files and download the new mq4 for your MT4. USDJPY will follow in the next few days; the stock indices [DAX30 & DOW30] I’ll finish after USDJPY.
What, in essence these changes will accomplish, is less “chop”; the respective algorithms [of course] still have a limitation, and that still remains the threat of chop on those days where market action really dies down. When this happens, you have to be smart enough to walk away.
The scalper algorithm in USDJPY & the new volatility version 2 USDJPY algorithm have a lot of similarities; where they differ is in possibly holding and then liquidating a position. And with that said, you can use either to compliment the other, or decide to leave it alone; the flexibility offered you here is vast, and allows you the opportunity to adjust “on the fly” [within algorithm rules] when market situations present themselves either with more volatility than normal or less.
One thing I have never allowed myself to do in all my years of trading, is to become inflexible and immune to changes in the marketplace; most often when paradigms change, they never come back. Hoping things return to patterns where HFT’s, central banks, and gold manipulation are NOT factors, is like telling me IBM Selectric typewriters will be making a come back right along with the Pony Express; sorry, it’s the “new” paradigm, and you can bury your head in the sand and pretend that trading conditions are “A-Ok” when they are not, but your delusion is somehow going to translate into the money you want cuz … well … you want it to? “Ok, good luck with that and let me know how it goes AFTER you go back into the Pudding Business”. You can learn from the dinosaurs, or you can go the way of the dinosaurs; what’s it gonna be?
And so, whenever necessary, whether it’s once every 10 years or twice in a month, change isn’t going to wait for me so I can get on the train before it leaves the station, cuz it’s leaving whether I or you are on it. I have said before, in blog posts, seminars, and other publications I have released and published for the public; I spend every day thinking about markets, how they are trading, who is influencing them, how governments are reacting to them, how traders perceive the moves, and finally how the financial press reports on them. It most certainly isn’t to “get an edge” on a trade; it is to make sure the PARADIGM I’m trading in is still valid and operational, and if it changes to have the “balls” to admit it and then find a new solution. For the better part of 2016 it had me stumped; no more.
Have a great weekend everybody!
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