CointegrationQuant tradingTrading strategiesZorro
In our previous post, we looked into implementing a Kalman filter in R for calculating the hedge ratio in a pairs trading strategy. You know, light reading… We saw that while R makes it easy to implement a relatively advanced algorithm like the Kalman filter, there are drawbacks to using it as a backtesting tool.
BacktestingCointegrationQuant tradingRTime series modellingTrading strategies
This Kalman Filter Example post is the first in a series where we deploy the Kalman Filter in pairs trading. Be sure to follow our progress in Part 2: Pairs Trading in Zorro, and Part 3: Putting It All Together. Anyone who’s tried pairs trading will tell you that real financial series don’t exhibit truly
BacktestingFactorsQuant tradingRZorro
When tinkering with trading ideas, have you ever wondered whether a certain variable might be correlated with the success of the trade? For instance, maybe you wonder if your strategy tends to do better when volatility is high? In this case, you can get very binary feedback by, say, running backtests with and without a
Think like a traderTrading as a business
One of the biggest wins we have at Robot Wealth is in helping aspiring traders see the markets, and profitable trading, for what it really is. Rather than utilising a tried and tested approach that has generated real money in the markets, in practice, many aspiring traders gravitate to seemingly exciting approaches with the weakest
CointegrationQuant tradingRTime series modellingTools of the tradeTrading strategies
Some price series are mean reverting some of the time, but it is also possible to create portfolios which are specifically constructed to have mean-reverting properties. Series that can be combined to create stationary portfolios are called cointegrating, and there are a bunch of statistical tests for this property. We’ll return to these shortly. While
Backtesting
The Federal Reserve publishes the yield-to-maturity of US Treasury bonds. However, the actual returns earned by investors are not publicly available. Nor are they readily and intuitively discerned from historical yields, since “a bond’s return equals its yield only if its yield stays constant and if all coupons (cash payments) are reinvested at that same
Quant tradingZorro
Before you commit your precious time to read this post on Shannon Entropy, I need to warn you that this is one of those posts that market nerds like myself will get a kick out of, but which probably won’t add much of practical value to your trading. The purpose of this post is to
PythonQuant tradingRTools of the trade
I’m a bit late to the party with this one, but I was recently introduced to the feather format for working with tabular data. And let me tell you, as far as reading and writing data goes, it’s fast. Really fast. Not only has it provided a decent productivity boost, but the motivation for its
Quant tradingTools of the tradeTrading infrastructure
If you’ve ever delved into the world of retail foreign exchange trading, you’ll have come across the MetaTrader platform. Let’s be clear. The platform has its drawbacks. If you’ve traded “grown-up” markets, some of the features will leave you scratching your head. But one thing’s for sure – MetaTrader provides fast, convenient access to pretty
BacktestingQuant tradingRThink like a trader
In our inaugural Algo Bootcamp, we teamed up with our super-active community of traders and developed a long-only, always-in-the-market strategy for harvesting risk premia. It holds a number of different ETFs, varying their relative weighting on a monthly basis. We’re happy with it. However, the perennial question remains: can we do better? As you might
Quant tradingThink like a traderTrading strategies
This risk premia post is part of a series derived from one of our recent Bootcamps, in which we developed a strategy for harvesting risk premia. We have allocated proprietary capital to the strategy, and many of our members are trading it too. In our Bootcamps we develop trading strategies in collaboration with the Robot
Quant tradingThink like a trader
This is Part 2 in our Practical Statistics for Algo Traders blog series—don’t forget to check out Part 1 if you haven’t already. Even if you’ve never heard of it, the Law of Large Numbers is something that you understand intuitively, and probably employ in one form or another on an almost daily basis. But
Think like a trader
Think like a trader
Think like a trader
Trading strategies
Trading strategies