Playbooks: four briefs for levels, sessions and trends

1The same rules as Guide 12

These are research briefs, not setups. No results, no success rates, no recommended settings. Most published edges shrink or vanish after costs and once they're widely known. A cited source describes its own market and period. You test on yours, up the evidence ladder (Guide 11), one brief at a time.

Each brief has the six parts from Guide 12: the idea, why it might work, a rule template with blanks, what kills it, what the Bear should attack, and the "Start it" lines for the Strategy Scout.

One thing the map makes plain. Some of these briefs need the market to keep going and the others need it to turn back. No single day suits all eight. Any brief you test will have a kind of day that hurts it, and part of the test is finding out how much.

2Playbook · Prior-day high/low sweep and reclaim

The idea. Price trades through yesterday's high or low, fails to stay there, and closes back inside. The trade is taken back into yesterday's range.

Why it might work. Yesterday's high and low are on every chart, so they are natural places for resting orders: stops from traders positioned the other way, and entries from breakout traders. The reasoning is that a push through the level fills those orders, and if nothing follows, the traders who bought the break are now wrong and have to exit. There is academic evidence that orders do cluster at obvious prices. Carol Osler documented clustering of stop-loss and take-profit orders in currency markets and linked it to how prices behave around those levels ("Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis", Journal of Finance, 2003). Note the limits: her data is currency orders at round numbers, not prior-day highs in futures. It supports the mechanism in general. It doesn't test this trade.

Rule template.

Context (yes/no): 1) Level = prior {session/day} {high or low}, taken from {data source}
          2) Price traded beyond the level by at least {__} and at most {__}
          3) Time is between {__} and {__}
          4) Higher-timeframe filter: {rule, or "none"}
Trigger (yes/no): A {__}-minute bar closes back inside the level within {__} bars of the first trade beyond it
Entry:       {market on the reclaim close / limit at the level on a retest}
Stop:       {beyond the sweep extreme by {__}}
Target:      {prior-day midpoint / opposite side of the prior-day range / fixed R}
Time exit:     Flat by {__}
When not to trade: 1) Sweep happened inside a blackout window 2) Level already swept once today 3) {__}

What kills it.

• Real breakouts. On a trend day the level breaks, pulls back, "reclaims" for one bar and then goes. Every one of those is a full loss.
• Hindsight. On a finished chart, sweeps are easy to spot. Bar by bar, a sweep and a breakout look the same until the close. This brief is especially prone to look-ahead in manual testing.
• Definition drift. How far beyond is a sweep, and how fast must it come back? Loosen either after seeing results and the test is fitted.
• News. Many sweeps of the prior day's extremes happen on releases, where spreads and slippage are at their worst.

What the Bear should attack. In replay, was each decision made before the reclaim bar closed? How many "sweeps" in the sample were excluded as "obviously a breakout", and by what rule? Is the sample long enough to include trend weeks?

Start it.

My idea, in my words: "When price trades through the prior day's {high/low}, then closes back inside within {__} bars, I trade back into yesterday's range."
Market and instrument: {…}
Session and time zone: {…}
Timeframe I would trade it on: {…}
What I can test with: {…}
Rough round-trip cost per trade: {…}

3Playbook · London-session breakout (currencies and gold)

The idea. The quiet hours before London set a range. A break of that range early in the London session is taken in the direction of the break.

Why it might work. London is the largest centre for currency trading. In the Bank for International Settlements' 2022 Triennial Central Bank Survey, the United Kingdom accounted for 38% of global foreign exchange turnover. The reasoning follows from that: the hours before London are thin, positions and orders build up, and when the largest pool of participants arrives, price can leave the overnight range with real volume behind it. That is a statement about where business is done. It is not a study of this trade, and there is no well-known academic test to cite for the retail version. It has been taught on trading forums for many years, which also means the range edges are among the most watched levels of the day.

Rule template.

Context (yes/no): 1) Range = high and low between {__} and {__} (state the time zone, and how daylight saving is handled)
          2) Range width is between {__} and {__}
          3) No high-impact event on the event sheet before {__}
          4) Day-of-week filter: {rule, or "none"}
Trigger (yes/no): A {__}-minute bar closes beyond the range edge by {__}, between {__} and {__}
Entry:       {stop order at the edge / market on close / limit on retest}
Stop:       {opposite edge / midpoint / {__}}
Target:      {multiple of range width / fixed R / {__}}
Time exit:     Flat by {__} (before or after the New York open? decide and write it)
When not to trade: 1) Range wider than {__} 2) Rate-decision day for either currency 3) {__}

What kills it.

• Spread. Spreads on currencies and gold widen around session changes. A breakout entry pays that spread at its widest. Measure it on your account at that hour.
• The fake first move. A break one way, a reversal through the whole range, then the real move, is a well-known London pattern. A breakout brief takes the first loss in full.
• Clock errors. The range is defined by time. Daylight-saving changes move London relative to other zones twice a year, and a chart in the wrong zone silently tests a different range.
• Broker differences. Spot currency and gold prices differ between brokers. A break on one feed can be absent on another.

What the Bear should attack. Which hours define the range, and were they picked before looking? What is the measured spread at the entry time? Does the result depend on the weeks with central-bank news?

Start it.

My idea, in my words: "The hours before London set a range on {pair or gold}. I trade a break of it early in the London session."
Market and instrument: {e.g. EURUSD / gold}
Session and time zone: {London open, London time}
Timeframe I would trade it on: {…}
What I can test with: {…}
Rough round-trip cost per trade: {measure the spread at the open first}

4Playbook · Trend following on higher timeframes

The idea. Markets that have been rising tend, on average and over months, to keep rising for a while, and the same for falling. Enter in the direction of an established move on daily or weekly bars, stay until the trend measure turns, and accept many small losses for occasional long runs.

Why it might work. This is the most studied idea in these two guides. The public reasoning is behavioural and structural: news is absorbed gradually, investors under-react and then pile in, and large participants move slowly. Tobias Moskowitz, Yao Hua Ooi and Lasse Pedersen documented the tendency across dozens of futures markets ("Time Series Momentum", Journal of Financial Economics, 2012), and Brian Hurst, Ooi and Pedersen extended the history back more than a century ("A Century of Evidence on Trend-Following Investing", Journal of Portfolio Management, 2017). The classic rule forms are a channel breakout, where you enter at a new multi-week high or low (Donchian channels, used in the Turtle rules described by Curtis Faith in Way of the Turtle, 2007), and a moving-average filter, where you hold only while price is above a long average (Mebane Faber, "A Quantitative Approach to Tactical Asset Allocation", Journal of Wealth Management, 2007).

Read the small print on that evidence. The studies are on portfolios of many markets, on monthly horizons, with position sizing by volatility. A single instrument traded by one person is a very different thing: fewer trades, longer flat stretches, and results that hang on one or two trends a year.

Rule template.

Context (yes/no): 1) Timeframe: {daily / weekly}
          2) Trend measure: {close above the highest high of the last {__} bars}
           or {close above the {__}-period moving average}
          3) Volatility measure for stop and size: {e.g. average true range over {__} bars}
Trigger (yes/no): The trend measure turns true on a bar close
Entry:       {next bar's open / stop order at the breakout level}
Stop:       {{__} × the volatility measure from entry / opposite channel of {__} bars}
Target:      None. Exit by rule only.
Exit rule:     {close below the lowest low of {__} bars / close below the moving average}
When not to trade: 1) Size rounds to zero with this stop 2) Position would be held through {events/weekends I don't allow} 3) {__}

What kills it.

• Ranges. In a sideways market every breakout fails. Long strings of small losses are the normal experience, and they can last many months.
• One market. The published evidence leans on diversification. On a single instrument the sample is tiny: a handful of trades a year.
• Holding. Positions are held overnight and over weekends. Many prop evaluations forbid that, and gaps can jump a stop.
• Patience. The brief only pays, if it pays at all, on the few trades that run. Exiting those early removes the whole point, and it is what most people do.

What the Bear should attack. How many trades will this produce in a year, and how many years until there are 30? Can the account sit through the losing run the test shows? Is holding overnight allowed on this account?

Start it.

My idea, in my words: "On {daily/weekly} bars, I enter when price {closes at a new {__}-bar high or low / crosses its {__}-period average} and hold until the opposite rule triggers."
Market and instrument: {…}
Session and time zone: {daily bars, exchange time}
Timeframe I would trade it on: {daily / weekly}
What I can test with: {bar replay on daily bars, spreadsheet}
Rough round-trip cost per trade: {include overnight financing or roll costs if they apply}

5Playbook · Mean reversion in ranges

The idea. When a market is moving sideways, moves towards the edges of the range tend to be given back. Fade the edges, target the middle.

Why it might work. In a range, by definition, neither side has been able to push price away. The reasoning is that at the edges the traders who would extend the move have already acted, and the ones taking profit or fading are next. Tools for measuring "stretched" are everywhere: bands set a number of standard deviations around a moving average are the best known, described by their author in John Bollinger's Bollinger on Bollinger Bands (2001). That book is a description of the tool. Its author is clear that a touch of a band is not, by itself, a reason to trade. The whole difficulty of this brief is in the first word of the idea: when. Knowing that a market is in a range, in advance and by rule, is the hard part. Fading an edge is easy.

Rule template.

Context (yes/no): 1) Range definition: {price has stayed between {level} and {level} for {__} bars}
           or {Analyst regime is RANGING and {measurable rule}}
          2) Stretch measure: {distance from the {__}-period average of at least {__}} / {touch of a band at {__} deviations}
          3) No higher-timeframe level within {__} beyond the edge
Trigger (yes/no): A {__}-minute bar closes back inside {edge/band} after trading beyond it
Entry:       {market on close / limit at {__}}
Stop:       {beyond the stretch extreme by {__}}. Fixed at entry. Never widened.
Target:      {range midpoint / moving average / opposite edge}
Time exit:     Flat by {__}
When not to trade: 1) Range broken on a bar close earlier today 2) EVENT DAY 3) Range narrower than {__} (costs eat the target)

What kills it.

• The day the range ends. Many small gains, then one loss that takes several of them back. This is the shape of every fading strategy, and it is why best-day dependence has a mirror image here: check the total without the worst day as well, to see how much one break costs.
• Adding to losers. Fading invites averaging down. The template forbids widening the stop for that reason.
• Costs against small targets. The target is the middle of a range, which may be only a few times your round-trip cost.
• Defining the range afterwards. In hindsight every range is obvious.

What the Bear should attack. Is the range defined by a rule that could be applied live, at the time? What is the largest single loss in the sample compared with the typical gain? How many trades does a week of trending take back?

Start it.

My idea, in my words: "When {market} has been in a range by {my rule}, I fade moves to the edge and target the middle."
Market and instrument: {…}
Session and time zone: {…}
Timeframe I would trade it on: {…}
What I can test with: {…}
Rough round-trip cost per trade: {…}