We studied over 20,000 trades to measure the average time between return extremes over the life of a trade. From all that data and research, see what stands out.

Traders hate leaving money on the table. But, how do you know when to exit a position? How much profit do you give up by closing a trade early? What if a winning trade goes against you because you held out for more profit?

These are real scenarios traders face every day, and this article gives you valuable context for making those decisions.

We examined over 20,000 options trades to see how long it takes for winners to turn into losers, losers to turn into winners, and the length of time between position extremes.

We know no one has a crystal ball and hindsight is 20/20. The next time you consider your position management decisions, we hope this research gives you actionable context as you weigh the possibilities. Let’s dig in.

Position Types and Market Conditions

We studied more than 20,000 options trades on eight different strategies over six months. The market had been in a steady uptrend, so traders held mostly bullish positions during the period studied.

Most positions were short duration, with the average trade open for 5.4 days.

After the extended uptrend, markets became choppy, providing ideal conditions to study swings in position value.

The Magnitude of Position Value Swings

A position’s final P&L only tells part of the story. Position returns can vary widely before exiting the trade.

Two metrics describe these position swings.

• Maximum favorable excursion (MFE) is the highest profit reached at any point while the position is open.
• Maximum adverse excursion (MAE) is the largest unrealized loss during a position’s duration.

MFE tells the trader how much profit they “left on the table.” MAE quantifies how the position performed relative to its largest drawdown.

During the period studied, traders missed out on the most upside while trading iron butterflies, long calls, and long puts.

Interestingly, iron butterflies also had the highest MAE. This can probably be attributed to short at-the-money contracts’ gamma exposure.

Trying to capture all the missed profit and catch every market move for each position is a fool’s errand and unrealistic. Still, smart adjustments to strategy decisions and personal trading rules could enable traders to capture a few dollars of lost profit to produce more powerful compounding.

For example, traders could adjust profit targets depending on days until expiration, implement trailing stops once a profit target is reached, or adjust all of these parameters and more based on current market conditions.

Timing of Position Profitability

We can go one step further and analyze the time between profit extremes.

Why? Understanding the time between position extremes gives you insight into position duration and trade management.

For example, knowing that iron condors had a longer average time between their max profit and loss can help you adjust exit criteria or give you more confidence when being patient with your exits.

There is high variability in the time between a position’s maximum and minimum profit. The average iron condor was open 9.1 days and the average days between max profit and max loss was 5.4 days. So, swings in position value relative to the time the position was open are significant.

How This Impacts Your Trading

From all that data and research, here’s what stands out.

Some strategies have much higher favorable and adverse excursions (e.g., iron butterfly, long calls, and long puts). If you know your strategy’s typical return profile, you can make more informed trading decisions.

For example, if you trade iron condors, you have to consider their return profile looks different than trading put credit spreads. An iron condor’s neutral profile means two sides of the trade are in play. So, the time between a position’s maximum and minimum return can be longer than a one-sided trade like a put credit spread or call credit spread.

Meanwhile, the variability between position highs and lows is smaller for iron condors than any of the eight strategies tested.

The point is not to extol the virtues of the iron condor but to demonstrate that strategies have their own unique return profiles.

Can a position turn around? You bet. It goes both ways, though. There’s often a two or three-day difference between the position’s highest and lowest unrealized returns on short-duration trades.

Understanding the variability of your favorite strategy’s returns gives you unique insight into your management decisions and can help remove emotional decision-making from your trading.

It’s easy to get fixated on percentages when discussing and labeling market moves, especially when those moves are to the downside. The S&P 500 can be 9.99% below its peak and its crickets – cross the 10% threshold and it’s a “Correction” – cross the 20% threshold and banner headlines announce a “Bear Market.”

There are plenty of problems with this approach. A market environment that has the S&P 500 down 9.9% from its peak is likely not materially different from one that has the index down 10.1%. The same can be said on either side of the bear market threshold. Problems go beyond the arbitrariness of the specific thresholds. The questions it raises reflect its lack of utility for everyone except headline writers. Is a market that is on its way to, but has not yet achieved a 20% peak to trough decline in a bear market, or is it still a bull market? And what happens after it enters bear market territory but nudges higher so that the peak to trough decline is now less than the 20% threshold? Is this still a bear market?

Pundits can wrestle with these questions. Historians can come in after the fact and put dates on market cycles (in the same way that dates are put on economic cycles) after peaks and troughs are clearly established. When trying to identify and operate within a market environment in real time, we don’t have those luxuries.

So how can we proceed?

Rather than looking at thresholds, I choose to look at participation when it comes to identifying market environments. Specifically, if more stocks (across the NYSE & NASDAQ) are consistently making new 52-week highs than lows, that seems like a bull market. If we are seeing more new lows than new highs, that is bear market behavior. All of the net gains in the indexes (looking particularly at the S&P 500 and the Value Line Geometric Index) over the past 2+ decades have come when our net new high A/D line has been trending high. In other words, when new 52-week highs have persistently outnumbered new 52-week lows. This isn’t rocket science, it’s a reality that index-level strength will struggle to persist if more stocks are moving lower and making new lows than moving higher and making new highs.

This dynamic has been playing out in recent months. Go back to early 2021 and the number of stocks making new highs started to wane and new low lists were expanding. Until November, however, news highs still outnumbered new lows. That changed in the final six weeks of 2021 and new lows began to outnumber new highs. The S&P 500 managed to hold up for a time and made a new high on the first trading day of 2022. It’s been underwater the year since then. From early January to late March, we experienced 57 consecutive days of more stocks making new lows than new highs. By the time the conventional questions about bear markets were being asked in late-February and early-March, we were already in the longest consecutive stretch of more lows than highs since the financial crisis (in 2008/2009).

That streak has since ended. We could start a new streak of more new lows than news highs. In which case I would conclude that the bear market remains intact (this, in fact, is what happened in late-2008/early-2009). Alternatively, we could begin to accumulate more new highs and the net new high A/D line, which has been moving lower since November, could turn higher. In either case, we can listen to the market, lean on the data and let the evidence write the headlines.