Category Archives: R

Markets Performance after Election

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.

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Better Model Selection for Evolving Models

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 re-trained often – the approach has significant computational overhead. Interestingly enough, an alternative, more efficient approach allows also for more flexibility in the area of model selection.

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Forecasting Opportunities

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.

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Labeling Opportunities in Price Series

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 identify them. Once the opportunities are identified – we can try to explain (forecast) them using historical data.

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Too Much Parallelism is as Bad

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 me.

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Creating Calendars for Future’s Expiration

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.
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Trading Autocorrelation?

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 general believe is that there are windows during which prices of certain assets are inefficient. Thus, there are opportunities to make money. Is the presence of autocorrelation one such opportunity? Let’s find out.
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