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RUT Weekly Calendar Trade #4 (Part 2)

As discussed in the last post, my weekly calendar trade was still down after Day 2 (5/6/15) but farther away from the downside adjustment point.

The market was up on Day 3 and the trade was profitable by noon. At the close, the market was at 1225 and somewhat comfortably within the adjustment points.

Friday was the big day with the jobs report to be announced at 8:30 AM. The market liked the report and opened around 1235. My contingent order to close was triggered and I got out with a profit of 8.5%.

I will say that I wasn’t entirely happy with this result because I’ve been aiming to close with a profit of 10% or better. In this case, I opened the trade for $6.70 and closed for $7.30.

Here’s how it should have gone:

Bought 2 @ $6.70 = $1,340
Add $8 for commissions on eight contracts: $1,348
Add 10% profit target: $1,348 * 1.1 = $1,483
Price per calendar = $1,483 / 200 = $7.415

I should have entered a contingent order to close for $7.42 or $7.45 (if I wanted to round up to the nearest nickel) rather than $7.30. Oh well… any win is much better than a loss!

I could look to get 8% on the trade if out by Friday. That would mean accepting a slightly lower profit to avoid the weekend risk. I don’t want to be taking losses much larger than 8% when it doesn’t go my way, however. My max loss has been 15% and my two losers closed for several percentage points worse than that simply due to slippage and fast market movement. This might or might not be viable depending on how much this trade wins.

In four weeks, I have thus far won on two of them. I’m down money overall, though.

We’ll see what next week brings.

RUT Weekly Calendar Trade #4 (Part 1)

I opened my fourth weekly calendar trade Tuesday morning (5/5/15) at the 1230 strike. This was a big down day for the market. I placed my original order around 9:45 AM for a 1235 put calendar. The market was quickly down to 1230 and I lowered the strike. I got filled about 10 minutes later with the market down to 1226 and I had caved a nickel to get that done (it filled 0.05 better than the then mark).

Before the day was out, the market had bottomed out near 1211! My downside breakeven was around 1205 and I had an alert in at 1208 to adjust. This time, I figured if an adjustment point was hit on the very first day then I would just exit the trade for a loss rather than trying adjusting and quite possibly being at max loss after the adjustment.

Psychologically, I was in no shape to adjust this trade anyway. My expectations are to average about +2% per week on this trade. In three weeks, I’ve lost 21%, made 10%, and lost 19%. I therefore expect to be “due” [it must be bad karma to even think that much less write it or say it] for a preponderance of winning trades to improve that average. We have possibly been through a very volatile time in the market recently: something that does happen every now and then.

With the market closing Tuesday at 1215, I survived Day 1.

Day 2 was mostly higher, which made for an easier day to hold the trade and watch paint dry. The market bottomed at 1211 on this day and it closed near 1220. The trade was down about $58 at the close, which was frustrating, but I felt comfortable being 10 points from the downside breakeven and still having 10 points of upside until I hit the short strike. The upside adjustment point was still over 20 points away.

I will conclude this trade summary in the next post.

RUT Weekly Calendar Trade #3

I opened my third weekly calendar trade Tuesday morning (4/28/15) at the 1255 strike. I paid 6.45, which I thought was an excellent price! I later realized this was lower than usual because it was a call calendar instead of put calendar. That shouldn’t make too much difference but if I’m getting used to prices in one (puts) then seeing prices in the other (calls) could throw me off.

The market really tanked yesterday. This trade had been up as much as 6% on Wednesday although I’m not sure I could have gotten executed there. Yesterday morning, the downside adjustment point was hit. I rolled one of the 1255 call calendars to a 1225 put calendar. Unlike my first weekly calendar trade where I was able to do this roll for just 0.06, this one cost 2.25. Again though, much of that was probably due to the difference in implied volatility between calls and puts.

The market continued lower yesterday and I eventually closed this trade for [more than] max loss: -19%. This was not as bad as my first loser, which was 21%. Still doesn’t make me feel any good, though.

The question remains: how often does this happen? No doubt the market is shaky this week. Certainly the market does seem much calmer when it’s doing the slow grind upward but it just so happens that in the three weeks I have been doing this trade, it’s looked ugly and more ugly. RUT fell 31 points during the course of this trade. In trade #1, the market fell only eight points from open to close but did a sharp reversal.

I’ll lick my wounds and get ready for next week.

RUT Weekly Calendar Trade #2

On Tuesday morning, April 21, I got filled at 7.25 in about 30 minutes. I caved 0.15 over that time and got filled 0.05 off the the mark. Breakeven points at expiration were 1248 and 1283.

The trade was never challenged. I had a contingent GTC order working to close for 8.09.

I watched the trade all day yesterday. At 3:50 PM, the market was 7.9 / 9.0, which is a mark of 8.45. My order was therefore 36 cents off the midprice and still not filled! I was a bit surprised.

At 3:58 PM, the market was 7.4 / 8.8, which is a mark of 8.1. I figured I surely wouldn’t be filled since my order would need to be at least 20 cents under the midprice if not more than 36 cents to be hit!

Then at 4:02 PM, What do I hear at 4:02 PM, after the regular session had ended:  Ding!  Ding!

Indeed, my order for 8.09 was filled! The market at that time showed 7.0 / 8.9, which is a mark of 7.95. My order got filled 14 cents better than the midprice!  That is a shocker but, of course, I’ll take it any day.

Nothing should surprise me yet since I’m still observing and learning how these things work.  This was only my second trade, after all.   Once I have a larger sample size of experience then I can look back to determine what is unusual and what is not.  Maybe I’ll see a handful of trades executed after the close like this.  Who knows?

For this week though, 8.09 – 7.25 minus a few dollars for transaction fees gives me a return of 10.4% in four trading days.

I look forward to the next one!

RUT Weekly Calendar Trade #1 (Part 3)

Today I will continue and complete the postmortem on my first live weekly time spread.

In the last post I illustrated the differences in risk graphs.  That’s huge and something I need to eventually figure out.

The final point is retrospective:  should I have closed this trade at the first adjustment point?  My profit target is 10% with a 15% max loss.  In the backtesting I tried to do, if I was anywhere close to max loss at the adjustment point then I wanted to exit the trade.  After slippage, I’d likely be at or beyond max loss after adjustment and it can only get [much] worse from there should the market continue moving against me.

The problem here was that I had no idea I was so close to max loss.  It came fast (within one day) and the market did not seem to move a great deal to get there!  Between OptionVue and my TOS account, I just did not have it modeled acceptably.  I probably need to get this into my DDE spreadsheet and then maybe I can create an “after adjustment P/L” cell to project where I would be after 0.10 slippage is applied per leg (for example).

On this trade, I lost 21.2%!

However, in legendary terms, “I’LL BE BAHK” [phonetics mine].

This is why we trade small:  to learn the nuances and how the trades work. I think this was a case of whipsaw; the market ran up forcing an adjustment and then ran down even harder. I was going to check before I went out this morning and had I been at the helm, I probably could have saved some of the loss.  Market activity like this is just not going to work for this trade, however.

So was this a fluke occurrence or does it happen on a semi-regular basis?

Only time will tell.

RUT Weekly Calendar Trade #1 (Part 2)

I previously gave an overview of my first live weekly time spread. Today I want to run through a few more details.

Compare and contrast:

Figure 1

Figure 2

Figure 3

Figure 4

 

Which pictures portray the correct representation?!  Figure 1 has breakevens of 1253/1277 whereas Figure 2 has breakevens of 1249/1281.  Figure 3 has breakevens of 1265/1282 whereas Figure 4 has breakevens of 1262/1283.  These differing breakevens can significantly affect when to adjust.  In addition, the Figure 3 expiration graph is downright ugly!  That’s a trade I might not even want to keep.  Figure 4?  That trade looks to have much more potential.

The only way to truly understand which risk graph is more likely to be accurate is to get a number of these trades under my belt.  As the days go by, I’ll be able to see my live P/L and compare that to what the risk graphs tell me.  The risk graphs might change over time too and morph into something better aligned with my P/L.  Again, only by trading these and learning will I gain the necessary experience to understand.

It’s hard enough to figure this stuff out by trading it live.  It might have been foolhardy to ever think I could backtest these with OptionVue, at least, given data in 30-minute increments.  Maybe another tool offering finer data (like 5-minute increments) could give me a fighting chance to accurately represent.

I’ll “stick a fork in it” with my next post.

RUT Weekly Calendar Trade #1 (Part 1)

This is the week I decided to junk the backtesting and try a real one live!

On Tuesday, RUT opened down on the day. I entered an order to buy 2 @ 7.40, which would have been around the mark or a little better. RUT rallied to 1265 and I did not get filled over the next few hours.

I canceled that order and did get filled on a 1265 spread for 8.14. The order was placed at the midprice and sat for two hours before I caved 0.10 and got filled about nine cents off the mark.

The market rallied on Wednesday and around midday, I rolled one of the 1265 spreads to 1280. I did this for six cents but I was down nearly 15% on the trade when it was done. I caved about 0.20 off the midprice to do this: one dime off each spread.

Today, the market tanked out of the gate. I ran some errands and came back 30 minutes into the session to see the market around 1256. I entered an order to close the DC at the midprice around 10:01. The market fell over one point in a minute and I ended up caving 0.95 over two minutes. I got filled 0.08 off the then mark, which ended up being 0.43 off my original limit price and 0.52 better than the modified order I had submitted to close. My total loss on the trade was an ugly 21.2%.

Think about that slippage for a moment: 0.43! I suppose that’s not horrible. That is roughly 0.11 per leg, which is usually the worst I would include in backtesting. The long options here were pretty expensive too and those spreads are pretty wide. One of my short options was 1.50/2.50. That seems a bit absurd. In fast-moving markets those spreads will widen and I guess given that, it’s not horrible to lose only this much in slippage.

I’ll cover a few more details about this trade in my next post.

Correlation Confound (Part 5)

Along with “diversification” and “pairs trading,”, “risk tolerance” can also be discussed in terms of advertising. How much product, in terms of AUM, has been sold by investment advisers (IA) purporting to use special care in recommending only what suits your unique situation, your goals, and your personal risk tolerance

Like correlation confound #1 where historical values change in the future, risk tolerance can also change.  How many investors prior to 2008 answered the questionnaire with 30% but started to experience rapid heartbeat, panic, and insomnia when their account was down only 10% during the last correction?

Psychological questionnaires are designed to ask enough questions to confirm responses and to avoid drawing conclusions based on fluke answers. I hope IA’s do the same. One multiple choice question isn’t good enough. Go into detail about a world with catastrophic headlines in the newspapers, blatant fear across Facebook, and dramatic shock and awe on the evening news. How would you feel in this scenario? What is your risk tolerance now?

Risk tolerance may not even be measurable and if this is the case, all mention about a “personal touch” employed to accurately assess it may reduce to deceptive marketing.  An online search turned up this:

> I say this from several decades experience in advising
> thousands of clients. Psychological risk tolerance is not
> a worthwhile a priori input. People routinely falsely report
> it or can’t really self-assess. Further, it changes over
> time, due to various factors, including the client’s age
> and other non-portfolio wealth factors.

Maybe risk tolerance should be taken out of the equation altogether?

At the very least, I think we should all be aware that “risk tolerance” is another buzzword often used by IA’s as an opportunity to express deep-rooted care and concern for our financial well-being.

I just hope it’s not an unquantifiable illusion—a manifestation of optionScam.com.

Correlation Confound (Part 4)

Today I continue by bringing optionScam.com into the discussion.

“Correlation,” “diversification,” and “pairs trading” are significant buzzwords for the financial industry.  The former is a buzzword used as a tool to achieve the latter two. The latter two are buzzwords for minimizing loss, sleeping well at night, and profitability.

It’s all good!

I wonder how much product, in terms of AUM, has been sold based on the advertising of “portfolio diversification?”

I wonder how much product, in terms of investment newsletters, trading services, and educational seminars, has been sold based on the advertising of “pairs trading?”

I would guess most of the advertising for either has made use of correlation and charts/tables to argue its efficacy as a profit-generating tool.

The story is usually incomplete, however, and this is where advertising becomes optionScam.com.

Correlation confound #1:  correlations based on historical price changes can and will change in the future.   The industry advertises diversification as having the potential to improve returns for a particular level of risk you choose based on your goals, time horizon, and tolerance for volatility.*  If I think I have achieved diversification by including noncorrelated assets in my portfolio then I may be surprised when the next market crash hits and all correlations converge to +1.0.

Correlation confound #2:  I thought I had good pairs to trade since they met the criteria for correlation but nobody told me about cointegration.  The concept of pairs trading is a very marketable idea because it makes sense that following divergence, two markets tending to move together will snap back toward each other like a stretched rubber band after release.  The problem is that correlated markets can move together but still, over time, be moving apart. Pairs trading without cointegration will be a losing proposition.

Correlation confounds can be optionScam.com when I make less money than expected or even lose money while somebody else is making money off me.

*—to be addressed in the next post

Correlation Confound (Part 3)

Correlation confound #1 dealt with portfolio diversification.  Today I will discuss correlation confound #2, which has to do with pairs trading.

To design a pairs trade, the first step is said to be finding stocks that are highly correlated. This could involve businesses in the same industry or sub-sector, index ETFs like QQQ and SPY, highly-correlated futures pairs, etc.

The next step is to monitor a chart showing price ratio between the two markets. When the price ratio diverges far enough, I want to go long (e.g. sell an OTM put spread) the relatively cheap market and go short (e.g. sell an OTM call spread) the relatively expensive market. Since the two markets generally move together (i.e. highly correlated), when they move apart I should expect mean reversion where they come together again.

Correlation confound #1 also applies to pairs trading.  Just because markets have been correlated in the past does not mean they will be correlated in the future.  That could cause problems for pairs trades.

Correlation confound #2 is something called cointegration.  Correlation measures the tendency of two variables to move together but it’s not guaranteed that they’ll stay close to each other. Look at the following charts of the gold and silver markets:

Believe it or not, in both charts these markets have the same statistical correlation of +0.75!  If you took on a traditional pairs trade when these markets were far apart with the expectation that they would get closer together, you might be sorely disappointed with the graph on the right but happy with the graph on the left.

Cointegration is a measure of how well assets are tied together. Two correlated variables are allowed to wander arbitrarily far apart but a cointegrated variable is not.  Cointegrated variables are expected to stay parallel to one another since the difference between the two will be corrected over time.