Strategy families & whose mistake pays you

IntermediateDuration ~30 min video + 25 min hands-onTools A notebook or text file, Python 3 + pandas (optional)

Why this lesson

Most people collect strategies like recipes — trend, breakout, mean reversion — and never ask the only question that decides whether one can work: whose mistake pays you? A strategy shape is just a label for when you buy and sell. The edge source underneath it is the actual reason the market should hand you money, and for a retail CFD trader most named edges are either noise or structurally out of reach. This lesson gives you a taxonomy that filters ideas before you waste a backtest on them.

Watch

Two short segments. The first builds a complete trend-following idea out loud so you can hear how a shape becomes a strategy. The second is the anchor author of this course’s worldview explaining why trend following pays at all — the behavioral edge underneath the shape.

Segment: 0:00–16:27 — defining trend following, absolute vs relative momentumwatch full video

Watch for: Radge separates absolute trend following (are you above your own past prices?) from relative momentum (are you rising faster than peers?). Notice this is all about the shape of the entry — nothing here yet names why the trade should pay. Hold that gap; the next video fills it. Stop at 16:27; the later portions are portfolio construction we return to in Level 2.

Segment: 27:16–37:04 — the cognitive bias behind trend-following's edgewatch full video

Watch for: Carver (ex-AHL) argues trend following works because other traders under-react to news and then over-react late — a behavioral edge, not magic. This is the 'named counterparty error' idea in the wild: the profit has a source, and the source is somebody else's predictable mistake. He is honest that the resulting edge is small (a Sharpe near 1 is a realistic ceiling).

The explainer

Start with the shapes, because you need a shared vocabulary. There are five that cover almost everything a retail FX/CFD trader will meet:

• Trend — buy what has been going up over a slow horizon, sell what has been going down, and hold until the direction changes. You are betting a move continues.
• Momentum — a faster or relative cousin of trend: rank instruments by recent return and hold the strongest. Trend asks “is this rising?”; momentum asks “is this rising faster than the alternatives?”
• Breakout — enter when price pushes beyond a reference level (a prior range, a session high). A breakout is really a fast, event-triggered way to catch the start of a trend.
• Mean reversion — the opposite bet: price has stretched too far from a fair value or a recent average, so you fade the move and profit as it snaps back.
• Carry — you get paid simply for holding a position: in FX, the interest-rate differential between the two currencies, collected as positive swap.

Here is the trap. Two traders can run the identical breakout shape and one has an edge while the other is donating money — because the shape is not the edge. So this course enforces one rule above all others: no strategy without a named counterparty error. If you cannot say, in one sentence, whose repeatable mistake funds your profit, you do not have a strategy — you have a chart pattern. Every credible framework, from Carver’s Systematic Trading to the Robot Wealth writing on edge economics, starts here.

The reasons the market pays anyone fall into four edge source families:

1. Risk premia — you are paid for holding a risk that others pay to shed. Trend and momentum (documented for decades), carry (you collect the interest differential), and the volatility premium all live here. These are slow, capacity-large, and retail-accessible in principle — but the margin is thin, and at retail CFD costs, carry is largely eaten by the broker’s swap markup.
2. Behavioral effects — you are paid because other traders act on predictable biases: under-reaction to news (momentum continuation), over-reaction (short-term reversal), the disposition effect (selling winners too early). The Barber & Odean line of research documents the losing side of these trades in exhaustive detail. This is the most plausible home for an intraday retail technique — e.g., a breakout that pays because traders fade a real move too early.
3. Structural / flow effects — some market participants must trade regardless of price: session-open volatility (the London Breakout family), month-end fixing flows, index rebalancing. These are calendar-anchored, which makes them the most testable of all — the events recur on a schedule, so sample sizes accumulate fast. The session structure of FX is real; the only question is whether an effect survives your spread.
4. Liquidity provision — you are paid the spread for supplying immediacy (market making, HFT). This one is structurally inaccessible to retail. On a CFD platform you pay the spread to a counterparty that is frequently your own broker’s B-book. You are on the taking side by construction. Any retail strategy that claims a liquidity-provision edge is misdescribed — it is describing the trade your broker is making against you.

So the honest hunting ground for a retail trader is families 2 and 3, with 1 as slow ballast. Whatever you validate later must beat the cost stack you learned to measure in Level 1 after naming its counterparty — because published edges also decay: most anomalies fade by about a third within a few years of being written up (McLean & Pontiff, Journal of Finance).

Two strategies recur throughout this course as worked references, and both live in the accessible families:

• London Breakout — mark the high and low of the quiet Asian session, then trade the break of that range at the London open. Edge family: structural / flow (session-open volatility is a real, calendar-anchored pattern). Counterparty error: traders positioned inside the overnight range get run over when European volume arrives.
• Dual Thrust — a general intraday breakout by Michael Chalek: measure a Range from the last N days’ highs, lows, and closes, then set an upper trigger at Open + K1 * Range and a lower trigger at Open - K2 * Range; go long or short on the break. Edge family: breakout / behavioral — it monetizes the follow-through that fades-too-early traders leave on the table.

Neither is presented as profitable. They are presented as specifiable — the raw material for the formalization, statistics, and backtesting you do next.

Do it

You will classify strategies the way you will classify every idea a mentor or a stranger hands you.

1. In a note, make a table with columns: shape, edge family, named counterparty error (one sentence), survives retail costs? (guess + why).
2. Fill a row for each: London Breakout, Dual Thrust, a long-EUR carry trade (hold EUR/USD for positive swap), and one strategy of your own or a mentor’s.
3. For any row where you cannot write the counterparty-error sentence, mark it REJECT — it is a chart pattern, not a strategy, until that sentence exists.
4. For the carry row specifically, write why the edge is real (rate differential) but thin at retail (broker swap markup eats most of it — you met this in Level 1’s cost stack).

Then make one strategy concrete with a few lines of pandas, so “breakout” stops being an abstraction. This computes the Dual Thrust trigger lines from daily bars:

import pandas as pd

# df: daily OHLC with columns Open, High, Low, Close, indexed by date
N, K1, K2 = 4, 0.5, 0.5

hh = df['High'].rolling(N).max()      # highest high over N days
lc = df['Close'].rolling(N).min()     # lowest close
hc = df['Close'].rolling(N).max()     # highest close
ll = df['Low'].rolling(N).min()       # lowest low

rng = pd.concat([hh - lc, hc - ll], axis=1).max(axis=1)   # the "Range"

# Today's triggers are set off today's open using yesterday's Range:
upper = df['Open'] + K1 * rng.shift(1)
lower = df['Open'] - K2 * rng.shift(1)

# A long fires when price crosses above `upper`; a short when it crosses below `lower`.
signal = pd.Series(0, index=df.index)
signal[df['High'] >= upper] =  1
signal[df['Low']  <= lower] = -1
print(signal.value_counts())

Notice the .shift(1) — the Range must come from bars that already closed. If you compute it from today’s data you have peeked at the future, which is exactly the look-ahead bias Level 2 spends a whole lesson hunting. Formalizing and de-biasing this description is the next two lessons.

Terms introduced

Terms introduced in this lesson

• trend
• momentum
• breakout
• mean reversion
• carry
• edge source
• counterparty

Each term links to the glossary, where it is defined by the way you just used it.

Check

Check yourself

1. The rule this lesson enforces before any strategy is worth testing is:

   no strategy without a named counterparty errorno strategy without a stop lossno strategy without at least 30 tradesno strategy without a backtest

2. Which of the four edge families is structurally inaccessible to a retail CFD trader?

   behavioral effectsrisk premiastructural / flow effectsliquidity provision

3. London Breakout — trading the break of the Asian-session range at the London open — is best classified as an edge from:

   a risk premium you get paid to hold overnightstructural / flow effects (calendar-anchored session volatility)liquidity provision (earning the spread)pure trend following on a monthly timeframe

4. Carry as a retail FX edge is thin mainly because:

   the swap you would collect is largely eaten by the broker's swap markupcarry is illegal for retail accounts under ESMAinterest rate differentials no longer existit only works on stocks, not currencies

Check answers

You can move on when you can… classify any strategy into trend / momentum / breakout / mean reversion / carry, name its edge source (risk premium / behavioral / structural-flow / liquidity provision), and explain why liquidity provision is structurally inaccessible to retail.

Mark this lesson complete

Go deeper

• Robot Wealth blog — the most honest free writing on where retail edge actually comes from; read their posts on edge economics and “why your backtest lies.”
• BabyPips: trading sessions — the mechanics behind the structural/flow family and the London Breakout window.
• McLean & Pontiff (2016) — the paper on post-publication edge decay; internalize the ~33 bps/month number.
• The book that owns this topic: Robert Carver, Systematic Trading, Part One — the case for rules and the behavioral premium behind trend following. His shorter Leveraged Trading rebuilds the same framework specifically for FX/CFD retail traders.