2018 brought more volatility to the markets, which so far has spilled into 2019. Let’s take a look at the long term volatility history picture using the Dow Jones Industrial Average: Indeed, 2018 was the most volatile year since 2011. Relatively speaking however, the volatility is on the low end for a bear ... [Read more...]

The selloff on Christmas eve was so bad it looked like a typical bear market capitulation. The following rally merely confirmed it. As mentioned in the last post, at the time the correction reached 16%, at the close of December 21st, the oversold indicator was not lighted. What followed was the ... [Read more...]

October and December have been devastating for stocks. It wasn’t until Friday though that we officially reached the depths of a bear market. There are different theories, the most common is 20% pullback in an index. As readers of this blog are aware, I follow a slightly different definition, based ... [Read more...]

Recently, while working on the Azure Data Lake R extension, I had to figure out a good way to create a zip file containing a package together with all its dependencies. This came down to understanding where does R store and search for packages. Despite the documentation, it did require ... [Read more...]

There are only a few well-known signals which I consider reliable. One of them is the Dow Theory. According to it, or at least to some interpretations of it, the bull market cycle almost ended this Friday. This time I am adding something new. I recorded myself while doing some ... [Read more...]

When I wrote the original post, I wasn’t planning on writing a follow-up. Certainly not the week after. But what a difference a week can make in a dynamic system like the US stock market. While re-running the computations testing the latest version of RStudio, I noticed something surprising – ... [Read more...]

Coming back to markets and trading (after a while), the feeling has been that the markets, and the economy as a whole, are doing good. How good? Since I haven’t been following things closely, I had to do some forensics. Friday was the 234th trading day after the election. ... [Read more...]

About a couple of years ago, I rolled out the flock package to help me synchronize R processes. I have used it ever since, but it wasn’t until recently that I found the time to move the source code to GitHub, and to add the package to CRAN. The ... [Read more...]

For quite some time now I have been using R’s caret package to choose the model for forecasting time series data. The approach is satisfactory as long as the model is not an evolving model (i.e. is not re-trained), or if it evolves rarely. If the model is ... [Read more...]

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The other day I run a machine learning backtest on a new data set. Once I got through the LDA and QDA initial run, I decided to try xgboost. The first thing I observed was a really bad performance. The results from the following debugging session were quite surprising to ... [Read more...]

It is a common knowledge that Bollinger Bands (price standard deviation added to a moving average of the price) are an indicator for volatility. Expanding bands – higher volatility, squeezing bands – lower volatility. A bit of googling and you get the idea. In my opinion – that’s wrong, unless, one uses ... [Read more...]

Lately I have been doing calendar analysis of various markets (future contracts). Not an overly complicated task, but has a few interesting angles and since I haven’t seen anything similar on the Net – here we go. The world of futures is not friendly – pretty much every contract has its ... [Read more...]

Markets are very smart in absorbing and reflecting information. If you think otherwise, try making money by trading. If you are new to it, make sure you don’t bet the house. In other words, markets are efficient. At least most of the time. So then why people trade? The ... [Read more...]

Life has been busy and has kept me away from blogging, and from trading, mostly. Still, I can’t stay away from monitoring the markets, and, with the recent rally, I started asking myself – has the situation changed since the 200 day SMA signaled an exit. What do you think – make ... [Read more...]

In the previous post, I went through a simple exercise which, to me, clearly demonsrtates that 60% out of sample guess rate (on daily basis) for S&P 500 will generate ridiculous returns. From the feedback I got, it seemed that my example was somewhat unconvincing. Let’s dig a bit further ... [Read more...]

One statistic which I find useful to form a first impression of a backtest is the success/winning percentage. Since it can mean different things, let’s be more precise: for a strategy over daily data, the winning percentage is the percentage of the days on which the strategy had ... [Read more...]

Rotational strategies on ETFs have been a common occurrence on this blog, and I have been using something similar for real life trading for about two years now. Readers of this blog may have also noticed concerns about the stability of the computations of such strategies. At the end it ... [Read more...]