- Exploiting Order Flow for the Discretionary Quant - Part 1
- Exploiting Order Flow for the Discretionary Quant - Part 2
- Simple Mechanical Trend Following in the Forex Market
- Is a Reward to Risk Ratio Inherently Better Than Another?
- Robots Aren’t What They’re Cracked Up To Be
- Creating a Trading System Using Neural Networks
- Function Based Trailing Stop Mechanisms
- The Seven Deadly Sins of Automated Trading
- Exploiting the Volume Profile
- Building Robust FX Trading Systems
- Know Your Currencies
- Automating FX Trading Strategies
- Grammatical evolution
- Identifying an Edge
- Interview with Salvatore Sivieri
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There are many ways to define a move, such as a change in momentum, expansion of the range, the divergence of two moving averages, the RSI crossing through the 50% level, or even standard deviations. However, let us take the simplest definition of a trend, being that of a new high or low.
We know that the lowest volume time of day is the New York close, or 10pm in London and highest volume is between 1pm and 4pm. Therefore, if we consider the New York close to be the end of one trading day and the beginning of the next, we can apply a simple trading rule to test our theory:
Buy if the market makes a new high or sell if it makes a new low, between 1pm and 4pm.
This simple strategy, without any money management, or stops, produces the following returns, based on a £100,000 account, with the portfolio being an average of the three equity curves.
Slippage, costs and interest have not been included, as these will vary from account to account, though these factors are more than offset by the addition of some basic money and risk management principles.
We can see that the trading rule doesn’t make money in all currency pairs in all years and has significant drawdowns, as well as extended periods to new equity highs. However, going with a move during the London afternoon clearly provides a robust trading edge, whether used in isolation, or as a filter to be used in combination with other trading strategies.
Again, as with the other behaviour discussed in this series of articles, we can see that while there are countless trading strategies that may work for short periods of time, based on arbitrary mathematical algorithms, there are some trading strategies that are genuinely robust, based on sound, predictable market behavior.