Seventh Quarter–Synthetic Portfolio Performance Analysis

As we finish up the first quarter of the year, we are also finishing up our seventh full quarter of implementing this strategy in  our group paper-trading account.  Our results this quarter were negative, making this quarter our worst to date.  Starting with January we had our single worst month, but February made up for that month and then some.  March, however, was another down month for us.  In the end, we were not profitable this quarter (our first down period).  Our benchmark closed almost flat for the quarter.

Starting with our absolute returns for the quarter, our losses were driven  mostly by the whipsaw action we saw in January on our protective trades.  This brought our average monthly return down quite a bit from where it was in December.  I think this volatility is going to be here to stay for awhile – at least until the Fed actually does start raising rates.  That will probably lead us into a correction of 10% or more, so our protective strategy will still be used as it is.

Our geometric mean shows us a little more of an equal comparison than our absolute returns.  Here you can see that we are still outperforming over the past 7 months, but it has fallen to about .about a .7 difference while last quarter it was nearly 2.  This is also obvious on the trend comparisons of our average monthly returns.

For those who prefer using the Internal Rate of Return (IRR) for measuring performance, we see that the overall returns remain strong, however not as strong as they were last quarter with our account IRR dropping from ~40 to ~30 while our benchmark dropped only 3 points.

Lastly here is a look at our Sharpe Ratio comparison. Here we can see that the Sharpe Ratio for our benchmark is relatively unchanged however our own ratio dropped by about 2 points.  This further illustrates the challenges that this quarter gave us.

So what does that leave for the coming quarter?  I suspect that the market will go through a correction later this year – possibly as soon as this summer – but overall I think we will end the year higher than where we started.  I looked at the charts for SPY on a quarterly view, and it shows just how strong the returns have been.  What I focused on though was the quarters where SPY was down, and not surprisingly our protective strategy would have us positioned bearishly before those down moves completed and moving back to neutral and bullish as the quarter(s) recovered.  So considering everything, and looking at the back testing that we did on this strategy, it appears to continue to be taking us down the right track. 

Sixth Quarter–Synthetic Portfolio Performance Analysis

With 2014 now behind us, it’s time to go through the performance analysis for our group's Synthetic Stock account.  Before getting into the details, I wanted to discuss how the average monthly returns are calculated for the Absolute Returns and the Sharpe Ratio.  There are two ways one might calculate the average monthly return – take the percentage for each month and average them out, or take the percent return between the starting and ending balances and divide it by the number of months.  I am using the latter method because it makes more sense to me… I suspect that either method is fine, but if the numbers are used for analyzing future projections, be aware that the results will be less reliable with the former method.

So starting with the basics, here is a look at our absolute returns compared to SPY.  Since we started this account back in June of 2013 we’ve seen a return of almost 83%.  That work%s out to a monthly average of a little over 4.6% or an annualized average a little over 55.2%.  As I’ve pointed out during other quarters, the comparisons to our benchmark include dividends paid to the benchmark.  The net results contained here don’t include deposits that we make to our paper-trading account.

The Geometric Mean is a useful method of getting a direct comparison of investment choices.  Here I’ve shown that, using this method of comparison, the synthetic strategy that we are using is outperforming our benchmark reasonably strongly (about two times on a monthly percentage basis:  1.49 verses 2.90).  To look at this a little differently, consider the chart below, which shows the running monthly average returns compared graphically for the past eighteen months.

The Internal Rate of Return is a good method of comparing returns that allows withdrawls and deposits to be taken into consideration.  Even though we probably won’t be simulating using this account for monthly income for a few years, I still include it as a method for comparison since so many like to use it.  The IRR is showing that we’re outperforming our benchmark by a little more than two times.

The main benefit achieved from analyzing the Sharpe Ratio is understanding the comparative amount of risk taken.  The higher the Sharpe Ratio, the better.  For this strategy, we already know that our risk is higher than our benchmark because we are using the leverage offered by options to achieve our results, so our Sharpe Ratio is going to reflect that with a lower calculation than our benchmark.  The Sharpe Ratio calculations also include the standard deviation from the monthly mean is about 2.88%, so we can  expect our monthly return to be in the area of 1.73% to 7.49% most of the time. 

With only 18 data  points, we are getting to a level where the standard deviations are statistically relevant, but we aren’t quite there yet.  As it stands, we have a few months that easily fall outside of three standard deviations.  This tells us that either our data does not fall within a normal curve, or we still need a couple more years of returns to build this data set.  
All in all, I am still happy with the results of this strategy so we’ll continue working with it in 2015.  I’m bullish for the coming year, but I think we will have a pullback that is in the 10% range.  Not to worry, our plan includes a method for profiting during the pullback when it does finally come.  In the meantime, good luck in the new year!

Synthetic Stock Strategy Details

Our third session on our synthetic stock strategy dug into the details of how we are using this strategy as a means to invest rather than simply trade.  We covered how to select a ticker (and why we are using only SPY), selecting an expiration month, and selecting a strike price.

We also talked about how and when to roll synthetics out in time and up in price, as well as the methods that we use for placing protective trades to ride through (and profit from) short term down trends.  Lastly, we talked about how we will allow our protective positions to become our primary investment vehicle during bear markets and how our bullish positions turn into the new protective trade while a bear market is in place.

The slides used during this session are available here.

Synthetic Strategy Overview

During our second session, we went through an overview of the strategy that we are using.  This is builds upon our introduction and explains how the strategy is implemented.  We focused on the difference between short term sentiment and long term posture and how that relates to investing with this strategy. 

The slides used during this meeting are available for downloading here.

If you have any questions or comments, please feel free to leave them as a comment to this post.  During our next session we will be going into the details of how we are executing this strategy.

Introduction to Synthetics

Over the next several weeks we are going to be re-starting our instructional series on our synthetic long stock strategy.  This introduction describes how options can be used to create a position that mimics owning 100 shares of stock while tying up about a quarter of the funds that it would if we were to purchase those shares outright.

There are several benefits to this strategy over other option strategies, starting with the fact that it can be managed essentially the same way that one might manage their position if they owned the stock itself.  This means that we manage these positions as investments, not quick trades.

The presentation material is available here.

During the next meeting, we’ll be discussing an overview of the strategy that we have been  using in our group paper-trading account.

Synthetic Strategy: Quarterly Performance Analysis (4th and 5th quarters)

I’m a bit late in providing these updates, so here are the past two quarters.  As we go through our group introduction to this strategy for the coming year, I’ll be sharing the recorded sessions via YouTube as well. 
If you’re not familiar with the methods of measurement described in these two tables, scroll down to the previous post that gives a brief description of each.  Also, a couple of notes about the results displayed:

• They do not include the scheduled "deposits" that we make to the account.
• Performance of the full account is shown, which includes cash sitting on the sidelines.
• Our performance is compared to SPY with all dividends since we started the comparison included.
• SPY went ex-dividend in September, but the dividend isn't payable until October, so that dividend is not included.

Our first year results ended on June 30th.

Our fifth quarter results ended on September 30th

As you can see, we are beating the SPY on all measurements, and exceeding our goal of 2x out-performance.  The lower Sharpe Ratio reflects the added risk that we are taking; that shouldn't be surprising since we are using an option-only strategy for this account.

Synthetic Strategy: Quarterly Performance Analysis

Our group has been fully invested in this strategy with our paper money account for nine months now, and we finally have enough data to start doing our quarterly performance analysis.  Here are the results so far.

General Notes

• This analysis is at the account level.  It includes the actual positions as well as the unused cash that is sitting on the sidelines.
• Our benchmark for this account (SPY) has been updated to reflect dividends.  There were 3 dividends during this period that totaled $2.35.
  • $0.838 (September)
  • $0.980 (December)
  • $0.824 (March)
• Gross returns are shown for reference, but the analysis focuses on net returns.  All returns include commissions and fees.  Net returns exclude weekly deposits.

Absolute Returns

This is the return that an asset achieves over a certain period of time. This measure looks at the appreciation or depreciation (expressed as a percentage) that an asset - usually a stock or a mutual fund - achieves over a given period of time.

• Absolute return over the past 9 months was 59.57%
• Benchmark absolute return was 16.57$
• On an absolute basis, we beat our benchmark by 42.99%
• Annualized, we beat by 57.32%

Geometric Mean

This is calculated returns a monthly mean/average. The main benefit to using the geometric mean is that the actual amounts invested do not need to be known; the calculation focuses entirely on the return figures themselves and presents an "apples-to-apples" comparison when looking at two investment options.

• Our geometric mean was 1.0486 (+4.86%) for this period.
• Our benchmark was 1.0172 (1.72%)
• On a monthly basis, we beat our benchmark by 3.14%
• Annualized this is a 37.7% beat

Internal Rate of Return (IRR)

IRRs can be compared against prevailing rates of return in the securities market. If a the IRR is less than the returns that can be generated in the benchmark, it may be wiser to simply invest in the benchmark.

• The IRR of our strategy was 86.36%
• Our benchmark IRR was 22.67%
• We exceed our benchmark IRR by a multiple of 3.81

Sharpe Ratio

The Sharpe ratio tells us whether a portfolio's returns are due to smart investment decisions or a result of excess risk. Although a portfolio can reap high returns, it is only a good investment if those higher returns do not come with too much additional risk.

• The Sharpe ratio for our account is equal to our benchmark.
• This indicates that our returns were achieved at a risk level that is similar to that of our benchmark

Summary of Results

• We are beating our benchmark on all measures, while maintaining a similar level of risk.
• We are on track to beat the long term goal of growing this account to $500k by the end of 2018.
• The risk for achieving this goal is that the market stays flat or is down.
• Currently the plan to offset this risk in a down market is to use short synthetics that can be held even if the market goes bearish.
• We are analyzing a plan to use bear call verticals to increase returns during flat markets.
  • With rolls, these positions can evolve into short synthetics
  • If the market climbs unexpectedly, the short call can be rolled out and up and the long call left to grow.