How to size a position when the risk does not have a date
Some market risks arrive on a schedule. Others have no schedule at all. The type of risk you are carrying changes how much you should put on. This lesson teaches you how to tell the difference, how to size for each type, how to build a track record before risking real capital, and how to know whether your approach is actually working.
Two types of risk. One has a date. One does not.
Before you size a position you need to identify what kind of risk you are dealing with. Most traders skip this step, asking how much they should put on without first asking what kind of situation they are in. The sizing answer depends almost entirely on the type answer.
A number drops at a known time. You can define the likely scenarios in advance: an inflation print, a central bank decision, an earnings report. The event happens, the market prices it, the uncertainty resolves. Your job before the event is to define your plan for each outcome.
A situation that can develop in any direction on any morning: a geopolitical conflict, a regulatory investigation, a banking concern. There is no announcement time. It can escalate, ease, or stay unresolved for weeks. You cannot build a plan around a date because there is not one.
You will face both types throughout your time in markets, sometimes in the same week. A scheduled earnings report and an ongoing geopolitical conflict can both be affecting your position at once. The key is recognizing which is which and adjusting your approach accordingly.
Why the type of risk changes how much you put on.
The core curriculum taught Kelly and fractional Kelly. The formula answers a specific question, given a known edge, how much should you bet. The key word is known: Kelly requires a win rate and a payoff ratio built from a track record large enough to be meaningful. Binary events give you something to work with, you can look at how markets have historically responded and estimate a rough probability and payoff range. Open-ended risk gives you almost nothing, every conflict and every regulatory situation is different, and you cannot run Kelly on odds you cannot honestly estimate.
This is not a reason to sit on the sidelines. It is a reason to size differently. Two approaches from the core curriculum apply directly here.
Risk no more than 1% of total capital on any single position. This requires no probability estimate and no payoff calculation, the right default when you are new to a setup, the environment is genuinely uncertain, or open-ended risk makes honest probability estimation impossible. Trading psychologist Van Tharp identified fixed fractional sizing as the most practical starting point for retail traders. At 1% per position, fifty consecutive losing trades reduce capital to around 60% of the start, survivable, still in the game.
If you have a track record on a specific setup, apply quarter Kelly rather than half Kelly when the broader environment is uncertain. Half Kelly is the professional standard; quarter Kelly fits when your probability estimates are genuine but the environment adds uncertainty you cannot quantify. Open-ended risk running alongside your trade is exactly that kind of environment.
If you have a track record on a setup, use quarter Kelly when open-ended risk is present. If you are still building one, use fixed 1%. Either way, size smaller than you would in a clean environment with only a binary event to navigate. The goal is staying in the game long enough for good setups to compound, one oversized loss in an uncertain environment can take you out entirely.
The full Kelly framework, expectancy formula, and fractional Kelly table are covered in Module 8. This lesson builds on that foundation, start there first if you have not read it.
Read Module 8: Risk Management →Building your track record before you risk real money.
The core curriculum tells you to check expectancy before sizing up. Expectancy requires a track record, and a track record requires completed trades. The answer is a demo environment, a simulated account using live market prices but no real money. Most major derivatives platforms offer one. Prices are real, positions feel real, only the consequences are not.
Before every trade, write down why you are entering, your stop level, and the outcome you expect. If you cannot write it down clearly you do not have a thesis yet. Use the same 1% rule you would apply live, the goal is simulating the real experience, not experimenting with sizes you would never use with real money.
A covered call, a carry trade, and a directional position are three different setups with three different risk profiles. Keep them separate in your journal. The win rate on covered calls tells you whether that strategy works; mixing strategies together produces a number that tells you nothing.
Before moving to real capital, calculate win rate and average win versus average loss from the journal. If expectancy is zero or negative, the setup is not working and going live will cost you money. If it is positive across a range of conditions, not just a handful of trades in one direction, you have something worth sizing up. Module 8 uses 50 journal entries as the benchmark for when that number becomes trustworthy rather than noise — the earlier you are in your journal, the more that expectancy figure can swing on a lucky or unlucky streak.
What your win rate is actually telling you.
Most traders look at win rate first. That is the wrong place to start. A 70% win rate with small winners and large losers loses money over time. A 35% win rate with winners two to three times larger than losses can be highly profitable. What matters is not win rate alone, it is whether your win rate clears the breakeven point for your reward-to-risk ratio.
The breakeven win rate is the minimum percentage you need to win just to avoid losing money, and it depends entirely on your reward-to-risk ratio. At 1:2, risking $100 to make $200, you need only 34% wins to break even. At 1:3, only 25%. Many professional traders run win rates between 35 and 50% and are consistently profitable because their average winner is significantly larger than their average loser.
Do not ask: is my win rate above 50%? Ask: is my win rate above the breakeven point for my reward-to-risk ratio?
A 40% win rate with a 1:3 ratio is a strong system. A 60% win rate with a 0.5:1 ratio loses money. Focus on the ratio first, then check whether your actual win rate clears the floor.
Sample size matters. A handful of trades tells you almost nothing, a lucky or unlucky streak of that length is completely normal. The more trades in the journal, the smaller the gap between measured win rate and actual edge. Build the sample before drawing conclusions and before moving to live capital — Module 8's benchmark of 50 entries is a reasonable target to work toward, not a hard cutoff.
Using the market environment as a sizing input.
Your baseline size comes from Kelly or fixed 1% as the core curriculum describes. But the environment should adjust that baseline up or down. Work through these questions before every new position.
Run this table before every new position. More than two yes-to-size-down answers is a clear signal to size down regardless of confidence. If the environment is clean across the board, your baseline from Kelly or fixed 1% applies in full.
Add up total risk across all open positions, not just the new one. Van Tharp called this portfolio heat. If each position risks 1% and you have eight open simultaneously, total exposure is 8%. His rule of thumb keeps total open risk below 6–10% of capital regardless of how good any individual setup looks. A concentrated losing day across correlated positions can do as much damage as a single oversized trade.
The pre-trade checklist for any environment.
Before every position, work through these five steps. They take five minutes and are the difference between a trade you fully understand and one that catches you off guard.
Name it. Is there a binary event with a date this week that affects this position? Is there open-ended risk that can move it any morning? Both? Write it down before you enter. If you cannot name the risks clearly you are not ready to size the position.
Run the sizing table above. If open-ended risk and a binary event are both present, use fixed 1%, not a timid position but one you can hold through volatility without reactive decisions.
For a binary event, the stop sits at the price level the bad outcome would produce. For open-ended risk, give the stop more room, a catalyst with no schedule can move the market before you react, and too tight a stop takes you out before your thesis has a chance.
Calculate it before you enter and write it down. If the number makes you uncomfortable you are too big. Entry price, stop level, target, and maximum dollar loss all exist before you click confirm. If any is unclear, do not enter.
If your journal on this setup is thin, you should be in demo. An uncertain environment is not the place to build a track record with real capital, use uncertain periods to add to your demo journal and go live once the numbers support it.
Two risks in the same week. July 2026.
Binary risk has a date and a defined range of outcomes. Open-ended risk has neither. Identifying which type you are dealing with before you size is the step most traders skip. Use fixed 1% or quarter Kelly when open-ended risk is present. Use a demo environment to build your track record before risking real capital. Track each strategy separately so your win rate actually means something. Run the sizing table before every new position. The goal is not to maximize any single week, it is to still be in the game when the environment clears and the clean setups arrive.
Module 8 of the core curriculum covers the full Kelly framework, expectancy in detail, liquidation mechanics, stop types, and the complete risk framework. Read it alongside this lesson.
Module 8: Risk Management →This content is produced by Harmonic for educational purposes. It is strategy education, not investment advice.
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