Forex system

Grid trading is an automated currency trading strategy where an investor creates a so-called “price grid”. The basic idea of the strategy is to repeatedly buy at the pre-specified price and then wait for the price to rise above that level and then sell the position (and vice versa with shorting and covering). We will explore the basics and show favorable and unfavorable scenarios in the first article about this trading style. Later articles will dig deeper and investigate how Grid trading is related to other systematic trading strategies.

There are many ways one can lose money when investing, and exchange rates are one of the potential risk factors. Luckily, there are several ways to minimize this type of loss in your portfolio. Systematic FX hedging that uses currency factor strategies is a way of protecting an existing or anticipated position from an unwanted move in an exchange rate. It does not eliminate the risk of loss completely but helps to manage currency exposure better.

The foreign exchange market (FOREX) is opened 24 hours a day, but traders from different parts of the world tend to prefer different trading hours. However, various dominant trading sessions around the globe can lead to time-dependent market characteristics. Novel research by Doman and Doman (2020) has studied how does the daily volatility of FX rates depend on the time of day of calculation. The volatility changes through the day, and the underlying dynamics depend on the time of the estimate. The results can have important implication for practitioners since the volatility differences are large enough so they can influence trading/risk management decisions.

Authors: Małgorzata Doman and Ryszard Doman

Title: How Does the Daily Volatility of Foreign Exchange Rates Depend on the Time of Day at Which the Daily Returns Are Calculated?

During past months we made a set of articles analyzing the performance of equity factors and selected systematic strategies during coronavirus crisis. These articles were short-ranged with data only from the start of the year 2020, which is enough for the purpose of the quick blog posts, but very short-sighted to see the nature of these strategies. Therefore, we expanded the time range by 20 years. For a better understanding of hedge possibilities of these strategies, we have added a comparison to essential safe-haven assets, not only to equities.

A lot of backtests of systematic trading strategies omit transaction costs (in the form of spreads and fees). Simulation is then simpler, but resultant model portfolio and its performance can be misleading. In the case of currency factor investing, backtest without the costs simulation can pick currencies with wider spreads and higher volatilities. And in real trading, with real-world transaction costs, a strategy can, therefore, perform significantly worse than expected. A research paper written by Melvin, Pan, and Wikstrom offers an elegant optimization methodology to incorporate transaction costs into the backtesting process which allows strategies to retain their alpha …

Authors: Michael Melvin, Wenqiang Pan, Petra Wikstrom

Title: Retaining Alpha: The Effect of Trade Size and Rebalancing Frequency on FX Strategy Returns

The idea of buying an investment asset for a lower price than a fair-value is the cornerstone of value factor strategies. Various value strategies were popularized by famous investor Benjamin Graham (and his successors like Warren Buffett) and were firstly employed in the stock market. This idea of looking for investment opportunities that can be bought cheaply can also be applied in currency markets – Currency Value Factor strategy. There is, however, one catch – an investor must know the fair-value exchange rate for currencies. The most popular equilibrium exchange rate model used for this purpose is based on PPP (purchasing power parity). A new research paper written by Ca’ Zorzi, Cap, Mijakovic, and Rubaszek analyzes two additional models – Behavioral Equilibrium Exchange Rate (BEER) and the Macroeconomic Balance (MB) approach to assess which model has the best forecasting power.

Authors: Ca’ Zorzi, Cap, Mijakovic, Rubaszek

Title: The Predictive Power of Equilibrium Exchange Rate Models