Momentum by rate of change

The code

The script prints the total before costs, the costs, and the total after, so the three can be compared directly.

Data the script reads: invented-prices.csv. Invented values, never a real market. Save it in one folder and run the script from that folder.

The file that was run: momentum_roc.py

# Momentum by rate of change: how far has price moved over the last N days, in percent?
# Prices come from invented-prices.csv: a random walk made by a script, never a real market.
# The result therefore says nothing about any real market. Read it for the method.
import csv

closes = []
with open("invented-prices.csv", newline="") as f:
    for row in csv.DictReader(f):
        closes.append(float(row["close"]))


def rate_of_change(prices, end, days):
    """Percentage change over `days` days, ending at position `end`."""
    return (prices[end] / prices[end - days] - 1) * 100


# Example values, picked only because they are easy to follow. They are not a suggestion.
DAYS = 10            # how far back to look
COST = 0.10          # points paid on every completed trade, a stand in for the spread

holding = False
entry = 0.0
results = []
START = DAYS + 1

for day in range(START, len(closes)):
    # Measured up to yesterday's close. Today's close is only the price we act at.
    roc = rate_of_change(closes, day - 1, DAYS)
    price = closes[day]

    if not holding and roc > 0:
        holding, entry = True, price          # price is higher than N days ago: get in
    elif holding and roc < 0:
        results.append(price - entry - COST)  # price is lower than N days ago: get out
        holding = False

if holding:
    results.append(closes[-1] - entry - COST)

before_costs = sum(results) + COST * len(results)
print("Rate of change on the last day:", round(rate_of_change(closes, len(closes) - 1, DAYS), 2), "percent")
print("Trades:", len(results))
print("Trades that ended above zero:", len([r for r in results if r > 0]))
print("Total points before costs:", round(before_costs, 2))
print("Costs paid:", round(COST * len(results), 2))
print("Total points after costs:", round(sum(results), 2))
print("Simply holding over the same days:", round(closes[-1] - closes[START] - COST, 2))

What the run printed

Rate of change on the last day: -0.58 percent
Trades: 45
Trades that ended above zero: 20
Total points before costs: 8.56
Costs paid: 4.5
Total points after costs: 4.06
Simply holding over the same days: -10.11

Output of the run on 9 Oct 2026, copied as printed. Every input to this run was invented, so the result says nothing about any real market.

How to read it

This run ended above zero while holding ended below it. Read that with great care, because it is exactly the kind of result that misleads people.

The prices are a random walk. The script that made them gives tomorrow no memory of today, so there is no momentum in the file to capture. The result is luck, and the page on how a backtest lies shows that a rule made of coin flips can score higher on the same file.

Forty five trades, fewer than half of them above zero, and more than half of the total before costs went on costs. The section on costs on that page uses this same rule: at double the cost per trade the total is below zero. A result that depends on the cost being exactly what you guessed is not a result. None of this says anything about any real market.