tod

@Bullfighter and @mccoyb53 I came upon the system I mentioned while researching sector rotation strategies. The web is full of references to how sector rotation beats the S&P. The same set of papers are dragged out to support this ad nauseum. One by Mebane Faber always gets a mention (I like Mebane Faber), but there's a dozen others; Asness (I like Asness), etc. I worked for sometime to validate this using the Spyder sector ETFs . I could never show the sector rotation strategy exceeded S&P returns in the long term. Unless they consider occasional returns in excess of 0.1% as outperformance. I could show spurts of outperformance, followed by underperformance, to ultimately end in the same place as simply owning SPY over a 20 year period. But with the code for testing that (I use R), I started playing around with other things. And I stumbled onto a set of parameters in unrelated "financial toolkits" that provided a novel entry and exit trigger; and I built a variant rotation scheme that did outperform SPY in a robust manner. I've found no reference to my happenstance discovery in system strategies, so I'm holding that secret sauce close to the vest for now. I don't mean to be a tease about this. I brought it up to emphasize the best systems are often simple. But finding them can take years and proves devilishly hard. I spent several hundred hours on what now I run with a few dozen lines of code. Most of that for grabbing data, compiling output. The actual 'secret sauce' is less than 50 lines of code. BTW, this system is not scalable beyond a 7 figure account, which may explain why it lives under the radar. My systems building philosophy is strongly influenced by a famous math theorem that states: for any continuous curve (any financial time series will do, drawn as a line chart), there exists a polynomial of finite degree that will match the curve to arbitrary precision. This theorem establishes the downfall of 99% of back testing efforts. A historic timeseries is a fixed, continuous curve. So the theorem above guarantees that with enough indicators and parameter adjustments, you can build a system that matches that time series dot for dot. So most back testing efforts are often futile exercises of crafting the (metaphorical) polynomial that matches the data curve they're testing on. The more indicators you're using, the greater the probability you're just building the equivalent of a curve matching polynomial, which holds true only for that one, fixed time series. As soon as I'm using more than 4 inputs (which is two to many), I get that "uh-oh" feeling. Of course, a complicated system that works on an in-sample set and proves robust on out-of-sample, or on time series from other classes that weren't used to develop the back test, is legitimate. So simple is not a requirement. But the combination of simplicity with robustness is a beautiful thing. I find CMLViz has some properties like that, so I wanted to defend it a bit.

Noticed this thread. Criticism appearing that the back tests are based on success in bull markets so recommendations are biased long. They have quite a bit of content where they test strategies in the 2007-2009 period, the grandaddy of recessions and bear markets of US history. Then there's the tech bubble and bear of 2000, and the covid sell off of 2020. A significant drawdown of 2018. The period 2000 - 2021 has provided a lab for a broad range of investing environments. So there's plenty of periods to test strategies that run into the power saw of bear markets. It hasn't been all roses. CML doesn't lend itself to complicated Rube Goldberg contraptions. It leans toward the simple side. But in my investing experience, some of the very best, most endurable strategies are quite simple (not SMA simple, that's not what I'm talking about.) They can be expressed with a few lines of code. I'm running a strategy (pure equity, no options) that combines two simple metrics and has doubled the S&P for 25 years and it's showing no signs of fatigue. Simplicity can be a good thing, indeed. The caveat of course is it has to be the right kind of simple. Finding the right simple is the hard part.

Thank you for the quick response. I checked my side and found the problem. It was me. Your site is coming through great, now! I'm glad I asked. I've received this error for several days and figured you were deep in site maintenance, so I used the time to practice patience. But the problem was on my end the whole time. Ready to rock and roll.

I've tried to sign up the last couple days. I get "Site not found; refuse to connect" error. This typical? Pinging the site delivers a response, so the route from my location to hqv is open.. Is this routine site maintenance? Something else?

I subscribed a few months back and after reviewing for a day immediately asked for my money back. Thankfully they returned it. They throw out so many suggestions they are bound to get some winners, purely by the "monkey throwing a dart at the stock page" process of picking. Knowledge of various strategies, technical versus fundamental, what works and doesn't work, a good screener and trading discipline will serve you better, IMO.