A method for de-trending asset prices

Financial market prices and return indices are non-stationary time series, even in logarithmic form. This means not only that they are drifting, but also...

Tradable economics

Tradable economics is a technology for building systematic trading strategies based on economic data. Economic data are statistics that - unlike market prices -...

Reinforcement learning and its potential for trading systems

In general, machine learning is a form of artificial intelligence that allows computers to improve the performance of a task through data, without being...

How to build a quantamental system for investment management

A quantamental system combines customized high-quality databases and statistical programming outlines in order to systematically investigate relations between market returns and plausible predictors. The...

Analyzing global fixed income markets with tensors

Roughly speaking, a tensor is an array (generalization of a matrix) of numbers that transform according to certain rules when the array’s coordinates change....

The power of R for trading (part 1)

R is an object-oriented programming language and work environment for statistical analysis. It is not just for programmers, but for everyone conducting data analysis,...

Commodity trends as predictors of bond returns

Simple commodity price changes may reflect either supply or demand shocks. However, filtered commodity price trends are plausibly more aligned with demand, economic growth...

Natural language processing for financial markets

News and comments are major drivers for asset prices, maybe more so than conventional price and economic data. Yet it is impossible for any...

U.S. Treasuries: decomposing the yield curve and predicting returns

A new paper proposes to decompose the U.S. government bond yield curve by applying a ‘bootstrapping method’ that resamples observed return differences across maturities....

Systematic trading strategies: fooled by live records

Allocators to systematic strategies usually trust live records far more than backtests. Given the moral hazard issues of backtesting in the financial industry, this...

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Through 'R' and 'Python' one can apply a wide range of methods for predicting financial market variables. Key concepts include penalized regression, such as...

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