This is the third part in a series describing how to approach the creation of a new trading strategy, including everything from idea generation, universe selection, data generation, proper in/out of sample testing, necessary considerations before live trading and the eventual big decision: do I want to trade that? The first posts can be found … Continue reading The birth of a strategy pt. 2 – extending VXX history and other data concerns
There exists a vast amount of studies that show an increase in correlation between global equity indices during bear markets and propose ways to measure/forecast this correlation (see for example Campbell, Koedjik and Kofman or Capiello, Engle and Sheppard, and many, many more). These studies differ greatly in their methodologies and complexities but they more or less all show … Continue reading A single value to measure equity market correlation
The recent decision by Yahoo to screw with their API for financial data (and in the process disabling all packages/functions in various programing languages obtaining EOD (end-of-day) data, at least temporarily) shows us two important things: Nothing is free and reliable forever It's a good idea to have a database set up So for everyone … Continue reading The time has come: setting up a DB with MySQL and R
Here it goes, finally a strategy backtest (sort of) on this blog (what an intro). In their 1973 paper "Risk, Return and Equilibrium: Empirical Tests", Fama and MacBeth introduce a method for estimating betas and risk premia for any risk factors that determine asset prices. Under the assumption that the only common risk factor that … Continue reading Risk Premia Market Timing?
As you are reading this blog you are definitely familiar with the concept of backtesting trading strategies, and probably have done so a significant amount of times. But do you also backtest your risk metrics? They are as important of a building block of your portfolios overall performance as the trading strategies themselves. So if … Continue reading Food for thought: Risk Backtesting?
Imagine this, you have backtested a strategy adhering to all the "general rules": you did proper in/out of sample testing, you have stable parameters (if the strategy has any), you didn't overfit, you account for transaction costs and slippage, everything seems good and you are ready to deploy your strategy and earn you some money. … Continue reading Constrained by capital or why rounding down is bad for you