Data analysisR
Back in May 2020, in the eye of the Covid storm, we looked at overnight vs intraday returns in US equities. Intuitively, we’d probably expect to see higher average returns overnight when the market is closed – because it’s much more difficult to hedge and manage our exposures when the cash market is closed, so
Think like a trader
Industry veterans sometimes remark that successful gamblers tend to make good traders, and engineers tend to make lousy traders. This is a gross generalisation, of course, but one reason is that trading, at the most fundamental level, is a game of pricing uncertain outcomes. This requires probabilistic thinking, and engineers tend to be trained to
Think like a trader
The first thing you need as a trader is a clear edge. What do I mean by “edge?” Edge comes from a market inefficiency that means you can buy cheap and sell rich on average over the long run. Said differently, edge is positive expected value. Expected value is the return you expect to realise
OptionsThink like a trader
If you trade liquid stocks or futures contracts, the first thing you will notice about equity options trading is that the contracts are illiquid and the bid/ask spread is wide. This sucks, but it makes perfect sense. There is only one AAPL stock to trade, but there are a ton of different options contracts trading
DataRTime series modelling
Last week, we looked at simple data analysis techniques to test for persistence. But we only looked at a feature that is measured over a single day – the absolute range. Such a feature makes it easy to test persistence because you don’t have the problem of overlapping data. Each data point is entirely self-contained
Data analysis
An assumption we often make in trading research is that the future will be at least a little like the past. I see a lot of beginners making this assumption implicitly without recognising that they’re making it or thinking about whether it’s reasonable to do so. That’s a mistake. If you are making this assumption,
PythonQuant tradingTrading strategies
Here’s a thing that I suspect will make money, but that I haven’t yet tested (for reasons that I will explain shortly): Every day, at the start of the trading day, get the SPX straddle price and convert it to an expected SPX price move. Then at the end of the trading day, take the
Tools of the tradeTrading infrastructure
Here at Robot Wealth, we trade with Interactive Brokers (IB) primarily because they offer access to global markets at a reasonable price. In recent times, IB has put some time and effort into upping its tech game, including development of an API for interacting with its desktop trading applications. An application that interacts with IB’s
Quant tradingR
Navigating Tradeoffs with Convex Optimisation This is the final article in our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and
Quant tradingRTrading strategies
This article continues our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way to manage turnover and not get
FactorsQuant tradingRTime series modellingTrading strategies
Modeling features as expected returns can be a useful way to develop trading strategies, but it requires some care. The main advantage is that it directly aligns with the objective of predicting and capitalising on future returns. This can make optimisation and implementation more intuitive. It also facilitates direct comparison between features and provides a
BacktestingFactorsQuant tradingRTrading strategies
Every time we trade, we incur a cost. We pay a commission to the exchange or broker, we cross spreads, and we might even have market impact to contend with. A common issue in quant trading is to find an edge, only to discover that if you executed it naively, you’d get killed with costs.
Think like a trader
Think like a trader
Think like a trader
Think like a trader
Think like a trader