RTime series modelling
Exponential weighting schemes can help navigate the trade-off between responsiveness and stability of the inherently noisy estimates we make from market data. We previously saw examples of calculating the exponentially weighted moving average of a vector, and estimating the correlation between SPY and TLT using an exponential weighting scheme [link]. In this article, we’ll implement
Quant tradingRTime series modelling
A big part of the job of the indie trader is data analysis. We’re always looking in the past data to validate (or more often, invalidate) a hypothesis about what might predict future returns. And one could argue that recent data is more useful than past data, since it may reflect the current state of
Think like a traderTrading as a business
Your job, as a trader, is to take all the information we have available now and make a judgment on whether something is trading at the right price or not, given things you can know here: Is it the wrong price? Can we buy it too cheap, or sell it too rich? Let’s say we
DataOptionsQuant tradingR
I’ve previously discussed the Volatility Risk Premium (VRP) and how it differs from the Equity Risk Premium (ERP). Probably the most interesting difference, from the perspective of the trader, is that the VRP may be somewhat amenable to timing – more than the ERP at any rate. In this article, I’ll use some of the
OptionsQuant tradingThink like a traderTrading strategies
Lately, I’ve been thinking a lot about the Volatility Risk Premium (VRP). The VRP makes much more sense (to me, at least) when I have the Equity Risk Premium (ERP) for context and comparison. So, in this article, I want to discuss the ERP and the VRP, their similarities and differences, and how I seek
DataR
Sometimes it’s nice to step away from the deep technical stuff and just build something simple and useful. What Is an IPO Calendar and Why Use One? I’ve linked the free IPO calendar below if you just want to jump in and explore. But if you’re not familiar, an IPO calendar is a tool that
FactorsQuant tradingThink like a trader
I want to discuss a couple of simple trade-off considerations around quant trading signals that may not be obvious. Here’s the price of some asset: Our main job is to predict how it’s likely to move. To do this, you use information about it that you think is predictive. And at any point in time:
DataRTools of the trade
Traders typically have many ideas for trading strategies – more than they can ever implement in practice! Therefore it’s useful to be able to move quickly in the early research phase. You want to disprove things as quickly as possible so that you can move onto the next thing. Obviously there is immense value in
Quant tradingThink like a traderTrading as a businessTrading strategies
In 2021, James, I, and a small team decided to set up a crypto trading venture. We faced several problems, but knowing almost nothing about crypto was the most significant. We sensed that the fractured, developing nature of the crypto market would likely be a good place to seek out inefficiencies, but beyond that, we
Think like a trader
When you do anything with data, you should think about the intuition of each thing you do, and what it represents “in the real world”. Let’s take the example of log returns, which some people tell me they find confusing. Consider an asset whose price goes from $100 to $200 Assume there are no other cash
DataRTrading infrastructure
In this blog post, I will demonstrate how to work with stock price data using the DuckDB database management system in R. DuckDB is a fast and lightweight analytical database engine that is designed to work with various programming languages, including R. You can use Duck DB from the command line or from a client
Think like a traderTrading as a business
Independent traders don’t have the same resources, speed, or balance sheets as large institutions. But that doesn’t mean they can’t compete. The key is to avoid crowded battles and instead focus on niches where the playing field is uneven. Alpha, consistent trading profits above the market, comes from exploiting these edges. Why Traders Buy and
Quant trading
Think like a trader
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CryptoData analysisThink like a trader