Musings on Naked Puts in Retirement Accounts (Part 4)

If a vertical spread lowers the standard deviation (SD) of returns and max drawdown (DD) compared to a naked put (NP) then its résumé is bolstered as an alternative candidate for retirement accounts. This was an unlikely result in the first example studied.

Rather than quintupling position size for the vertical spread, what if I double it? The potential return would be $4 (rather than $10), which is a 33% increase over the NP. The NP risk is now cut by 80% (rather than 50%) to $20K, which is the breakeven for both trades.

The risk graph now looks like this:

Like the previous example, the vertical spread outperforms if the market rises or if the market falls less than 7%. If the market falls between 7% and 20% then the naked put outperforms. If the market falls more than 20% then the vertical spread outperforms. A market correction over 20% is more likely than a market correction over 50% and this is where the risk metrics (SD of returns and max DD) would be improved by the vertical spread.

Of course, the vertical spread could be traded in equal position size to the NP. This would generate the first graph shown in Part 3. In that case, no gap of underperformance exists for the vertical spread and any market correction over 10% would generate better risk metrics for the vertical spread.

So going back to my statement in Part 1, does the vertical spread actually improve risk metrics?

The largest market crashes (e.g. fall 2008) will give rise to a lower SD of returns and a lower max DD for vertical spreads.

Unfortunately, these severe crashes occur so rarely that it’s hard to plan a trading strategy around them. The vertical spreads may or may not yield improved risk metrics depending on whether the market corrects, how often it corrects, and the exact magnitude of corrections during the time interval studied.

Compared to NP’s, vertical spreads may improve risk metrics. This is far from guaranteed.

Musings on Naked Puts in Retirement Accounts (Part 3)

Today I resume discussion of vertical spreads instead of naked puts (NP) in retirement accounts. I mentioned previously that [OTM] vertical spreads don’t usually affect standard deviation (SD) of returns or maximum drawdown (DD). In case of a significant market downturn, however, they certainly can.

Let’s begin with the risk graph comparison posted earlier:

Notice how the green line (vertical spread at expiration) goes horizontal once the market drops ~16% to 419. That is where max loss is hit. The farther the market drops beyond that point, the more the NP (purple line) loses relative to the vertical spread. This represents a lower SD of returns and a lower max DD for the outperforming vertical spread.

This analysis assumes equal position size and offers an important distinction between ROI and gross PnL. In percentage terms, the vertical spread loses more than the NP if market falls the 16%: 100% for the vertical spread versus [under] 16% [buffered by initial premium collected] for the NP. In terms of gross dollars, the NP and vertical spread lose similar amounts until the vertical spread has lost 100% at which point the NP continues to lose more. 16% is the loss threshold beyond which the vertical spread delivers a lower SD of returns and a lower max DD than the NP.

Now let’s reconsider the naked 1000 put example I presented here. If I sell a 1000 put for $3.00 then [gross] risk is $100,000. If I buy the 900 put for $1.00 then I cut risk by 90%. I could, therefore, trade five times as many verticals while still halving the NP risk. Potential ROI on the vertical spread would be 6.7-fold greater.

Here are the risk graphs of the vertical spread (red line) and NP (blue line):

The problem with the vertical spread is the possibility of losing the entire $50K should the market fall from 1000 to 900 (10%). For the NP to lose $50K the market would have to fall to 500 (50%), which is circled in red. In this case, the vertical spread outperforms if the market rises or if the market falls less than 7%. If the market falls between 7% and 50% then the NP outperforms. If the market falls more than 50% then the vertical spread outperforms.

Because a fall over 50% is so unlikely, this particular vertical spread position would probably post a larger SD of returns and a larger max DD than the NP were the market to enter a meaningful correction.

In the next post I will compare a different vertical spread position to see how it measures up.

End-of-Day Versus Intraday Trading (Part 2)

As I mentioned last time, a big part of the debate between end-of-day (EOD) and intraday trading involves the difference between the probabilities of touching and expiring. The markets are often regarded as random (Brownian motion). When a particular price level is reached, the market then has a 50/50 chance of moving higher or moving lower. The probability of expiring beyond that level is therefore less than the probability of touching it.

For intraday trading, this may be both an advantage and disadvantage. More winners can be exited intraday, which is an advantage. More losers—some of which would otherwise go on to be winners—will also be exited intraday, which is a disadvantage. On trend days, exiting losers (winners) intraday will avoid (preclude) what could otherwise be larger EOD losses (profits), which is an advantage (disadvantage).

This debate is not getting any easier.

Price action aside, another disadvantage to intraday trading is the need to be available and/or take action more than once and possibly whenever the market is open. This takes a lot of flexibility out of the workday.

The biggest disadvantage to intraday trading is arguably a much more complex (or impossible) backtesting proposition. OptionVue (OV) provides data every half hour. If I am going to “trade like I backtest” (mentioned here and here) then I must monitor trades every 30 minutes. Such backtesting would more than quintuple my current 2-5 months per backtest. Continuous market monitoring represents another magnitude of complexity because significant volatility can occur even between 30-minute prints. Backtesting this trading time frame would therefore require a much more granular database.*

As a net seller of option premium, I find time decay to be more certain than typical [random] price action. Every 24 hours an option gets one day closer to expiration. Implied volatility increase can offset time decay in the short-term but this only happens in some instances of down markets, which is [significantly] less than 50% of the time.

Given this additional reasoning, my gut instinct is to give the nod to EOD over intraday trading. A trade is more likely to be exited at an intraday stop-loss for the additional reason that option decay into the close may improve the PnL. Being directionally long also favors EOD trading by giving more time to allow for positive drift. The observations that many trades have small MAEs and only a select few have huge MAEs is additional evidence in favor of longer trade duration (EOD).

For me, the exponential complexity or impossibility of backtesting is the proverbial nail in the coffin for intraday trading. These restrictions actually make me wonder whether the perceived benefit of enhanced intraday opportunity is more illusion than anything else.

* – Any discretionary strategy that uses alerts to signal entries, exits, or adjustments implies this sort of intraday, continuous-monitoring approach.

End-Of-Day Versus Intraday Trading (Part 1)

One thing that came to mind from my recent blog series on backtesting frustration was the distinction between end-of-day (EOD) and intraday trading.

The most important aspect of EOD trading for me is once daily. This is much different from intraday trading where I could be watching the market continuously. For the sake of this discussion I will assume EOD takes place at the close but I really feel the exact time is arbitrary as long as it is consistent (e.g. 10:30 AM, 3:35 PM, etc.).

EOD trading has pluses and minuses. Checking in on the market once daily is a plus. This makes for a very flexible work schedule. Another plus is the opportunity to realize windfall profits in excess of my target. On the other hand, I believe the biggest minus is the potential to realize windfall losses. If the loss at trading time is beyond my stop then I must take it no matter how bad it is.

One advantage of intraday trading is a greater opportunity to exit trades at a price target. This is because the probability of touching a certain profit level exceeds the probability of closing at that level. Suppose I am up 8% on a long stock trade with a 10% profit target. A small amount of market volatility the next day will likely push the trade to +10%. To close at +10%, though, the market has to have an up day. In this case I would not be able to capitalize on so many of the choppy days where the market is higher intraday before closing lower.

Another advantage to intraday trading is the opportunity to realize tighter stops. Suppose my trade with a 15% stop-loss closed down 14% yesterday. As an EOD trader, should the downtrend continue today then who knows how far beyond -15% the trade might be when I have to exit at the close? Were I trading intraday, I could likely exit much closer to that -15%.

This is also a disadvantage to intraday trading, however. I may sometimes get stopped out for a loss on trades that briefly fall below my stop only to see them reverse higher as they ride off into the sunset without me, never looking back.

EOD or intraday? This is a tough, tough deliberation.

I will continue next time.