Forex Trend Following: Time-Series Momentum Rules, Sizing and Tests

What time-series momentum is trying to capture

A trend-following rule buys after a sustained rise and sells after a sustained fall. It accepts that the signal can arrive late and that many moves will reverse. The economic idea is that information, hedging demand and investor positioning sometimes adjust gradually enough for a directional move to persist.

Time-series momentum compares a market with its own past. Cross-sectional momentum instead ranks different markets against one another. A currency can rank best within a weak group while still having a negative own return, so the two methods need not produce the same position.

The framework below is an educational specification for research, not a current market signal or a claim of expected profitability. Parameters are deliberately visible so another person can reproduce or reject the result.

What the academic evidence does and does not establish

Moskowitz, Ooi and Pedersen studied time-series momentum in 58 futures and forward contracts across currencies and other asset classes. They reported that an instrument’s past 12-month excess return helped predict its subsequent return in their sample, with persistence followed by partial longer-horizon reversal. Authors’ research page: Time Series Momentum.

That finding does not imply that a spot-price rule with retail CFD financing reproduces the study. Instruments, diversification, historical data, volatility targeting and implementation costs can all differ. Our example uses price change as a transparent signal proxy and explicitly models the retail contract’s financing.

Use the paper to motivate a testable hypothesis. Do not borrow a research paper’s historical return, Sharpe ratio or reputation and attach it to a different EA. Evidence belongs to the strategy and assumptions actually evaluated.

Fix the universe and information set

Select a modest liquid-pair universe before running results, for example EUR/USD, GBP/USD, USD/JPY and AUD/USD. This is a teaching universe, not a ranking of opportunities. Document the broker, timezone, daily close convention and handling of holidays and missing observations.

Use one consistent historical price series for signals, plus bid/ask or a defensible spread model for execution. Keep financing separate. A monthly signal needs at least 12 months of prior closes; ATR needs additional completed daily bars. Do not begin a strategy on an incompletely warmed indicator.

Record signal timestamps after the monthly close is known. The first permissible trade occurs at the next tradable quote under the specified execution window. Using the final close both to calculate and fill the signal can grant hindsight that would not be available in operation.

A fully stated monthly reference rule

1. On the final completed trading day of each month, calculate momentum = current monthly close ÷ close 12 months earlier − 1.
2. Use a long direction if momentum is positive, a short direction if negative and no position if exactly zero or data are incomplete.
3. Calculate 20-day ATR from completed daily data. Specify the same smoothing convention in the backtest and platform.
4. At the next defined tradable opening window, close any old position and open the new direction at the executable quote, using the sizing rule below.
5. Place an initial protective stop two ATRs from the new entry. There is no fixed profit target in this reference version.
6. If stopped, remain flat until the next monthly decision. Do not re-enter on every tick or increase size to recover.

The close-and-reopen convention makes the baseline easy to audit and deliberately charges both transactions. A production system that only trades the net size change is a separate implementation to reconcile and test.

Size the monetary risk and cap the portfolio

Illustration: equity is USD 20,000; the chosen research risk is 0.25%, or USD 50, per pair. EUR/USD’s completed 20-day ATR is 0.0060, equivalent to 60 conventional pips. A two-ATR stop is therefore 120 pips.

Assuming USD 10 per pip per standard lot and USD 20 per lot for estimated commission and slippage, volume is 50 ÷ (120 × 10 + 20) = 0.04098 lots. A 0.01 step rounds this down to 0.04 lots. Verify the currency conversion for other pairs and allow for financing over the expected holding period.

For this research example, cap total initial planned stop risk at 1% of equity and cap duplicate directional exposure to one currency at 0.5%. If signals exceed a cap, scale them proportionally before rounding down. These are declared assumptions to test, not universal safe levels. Stops cannot guarantee those losses during gaps.

Trace a signal from observation to exit

Suppose a completed month-end EUR/USD price is 1.1000 and the close 12 months earlier was 1.0500. Momentum is approximately +4.76%, producing a long candidate. With 0.0060 ATR and a next-session ask fill of 1.1004, the initial stop is 1.0884.

If the bid reaches the stop first, the position closes at the available execution price and the strategy waits for the next monthly rebalance. If it remains open, the next month-end calculation determines the following position. A lower price than the entry can still leave 12-month momentum positive; the strategy does not require every monthly trade to make money.

Write down both the rules’ result and the actual fill. The difference can arise from spread changes, delayed connectivity, a broker’s session or a stop gap. This separation helps distinguish a failed hypothesis from a correct hypothesis implemented incorrectly.

Test the portfolio and the implementation

Begin with a visual audit of a small sample and compare every monthly signal with a separate calculation. Then evaluate a long period including ranges, directional episodes, policy shifts and volatility shocks. Reserve a final chronological sample that has not influenced the rules.

Model spread, commissions, conversion and overnight financing. Long holding periods make financing especially relevant. Do not use today’s swap rate for many historical years without labelling that as an approximation and testing alternative assumptions. Charge costs for the baseline’s monthly close-and-reopen transactions.

Report equity drawdown, turnover, average holding time, losing streaks, worst gap and performance by pair and period. Test nearby lookbacks, such as 9 and 15 months, as sensitivity checks; disclose them rather than selecting whichever wins. Evaluate aggregate currency exposure, since several individually plausible pairs can create one large USD bet.

Expect whipsaws, lag and changing market conditions

During a range, the strategy can enter after a move has already exhausted itself and reverse after another loss. A rapid policy reversal can erase months of trend gains before the next scheduled decision. Protective stops reduce planned exposure but also alter the return pattern and can repeatedly remove a position before a trend resumes.

Volatility sizing has its own weakness: a quiet period can invite more volume just before volatility expands. Keep notional and margin limits alongside ATR sizing. Diversification may reduce concentration but cannot ensure independent returns during a common shock.

Before any forward trial, define a maximum tolerable drawdown, cost deterioration threshold and operational stop condition. Review on a schedule instead of redesigning the system after every loss. Continue only when the implemented rules, risk budget and evidence still agree; remaining flat is a valid outcome of the research.