Articles by quintuitive

2018 Volatility Recap

January 6, 2019 | quintuitive

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 Christmas Eve Selloff was a Classic Capitulation

December 26, 2018 | quintuitive

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...]

The Bear is Here

December 22, 2018 | quintuitive

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...]

Package Paths in R

March 31, 2018 | quintuitive

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...]

The Bull Survived on Friday, but Barely

March 24, 2018 | quintuitive

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...]

Markets Performance after Election: Day 239

October 21, 2017 | quintuitive

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...]

Markets Performance after Election

October 15, 2017 | quintuitive

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...]

The flock Package is on CRAN

November 12, 2016 | quintuitive

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...]

Better Model Selection for Evolving Models

September 25, 2016 | quintuitive

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...]

Forecasting Opportunities

September 13, 2016 | quintuitive

The previous post in this series, showed a way to identify trading opportunities. The approach I implemented used time series daily data to identify good entry points in terms of risk-reward. The natural next step is to try to make use of these opportunities using machine learning. To refresh: the ...
[Read more...]

Labeling Opportunities in Price Series

August 13, 2016 | quintuitive

One approach to trading which has been puzzling me lately, is to sit and wait for opportunities. ? Sounds simplistic, but it is indeed different than, for instance, the asset allocation strategies. In order to be able to even attempt taking advantage of these opportunities, however, we must be able to ...
[Read more...]

Loading Data with Pandas

June 27, 2016 | quintuitive

On at least a couple of occasions lately, I realized that I may need Python in the near future. While I have amassed some limited experience with the language over the years, I never spent the time to understand Pandas, its de-facto standard data-frame library. Where does one start? For ...
[Read more...]

Too Much Parallelism is as Bad

May 7, 2016 | quintuitive

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...]

Volatility and Bollinger Bands

February 13, 2016 | quintuitive

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...]

Creating Calendars for Future’s Expiration

January 17, 2016 | quintuitive

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...]

Trading Autocorrelation?

November 15, 2015 | quintuitive

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...]

Has the S&P 500 Cleared the Earlier Sell?

October 25, 2015 | quintuitive

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...]

When is a Backtest Too Good to be True? Part Two.

September 19, 2015 | quintuitive

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...]

When is a Backtest Too Good to be True?

September 9, 2015 | quintuitive

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...]
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