Industry Benchmark Performance
Hedge Fund early reporting for March shows small losses in equities and in most CTA benchmarks.
The BTOP50, the index of large futures funds, is showing a loss for 2017; however, the SG CTA index shows a net gain for 2017 while the individual breakdown of short-term and trend are both losses. It seems inconsistent.
Change in Futures Portfolios
(This is repeated at the beginning of the Futures section)
We have reduced exposure to agricultural markets in all daily and weekly portfolios. We prefer using the exact same macrotrend logic and parameters for ag markets, because it qualifiies as “robust.” This worked well when there were large changes in the value of the US dollar and interest rates. But commodities have a much shorter cycle than most other financial markets, due to both seasonality and short-term changes in supply and demand. Without major moves driven by macrofactors, we need to use a much shorter calculation period to take advantage of those moves. We will be replacing those ag markets and other commodity futures with a similar program specifically oriented to this time frame.
March Performance in Brief
Daily futures posted strong gains while all equity portfolios posted fractional losses. Equities are still holding onto good returns for the year, with 16 of the 18 portfolios profitable. The Timing Program had the largest loss but still shows the best profits for the year, 6.52% for the small portfolio, ahead of the 5.92% for the S&P.
In futures, the daily program posted from just under 3% to just under 5% returns for March, turning all portfolios profitable for the year, and well ahead of the industry, as shown in the Barclay’s report.
Major Equity ETFs. The Russell (IWM) has stalled out since the election in November, while the S&P and Nasdaq have continued their upwards march (although not very strong in March). You can find plenty of analysis on the business news channels, but we have always thought that the market now needs some new legislation, not Executive Orders, to offset the effects of the Fed raising rates. We couldn’t put a date on it, but the market now seems to be on hold waiting for something concrete to happen.
Blogs and Recent Publications
Nothing new since the March 2017 issue of Technical Analysis of Stocks & Commodities VIX or Historic Vol – Which is Better for Position Sizing? This article shows the effects of using volatility parity based on both historic volatility and implied volatility (VIX) to find the right position size for your trade. However, a new article on intraday trading using a combination of high momentum and mean reversion has been sent to TAS&C. We’ll let you know when it will be published.
Andrew Swanscott at BetterSystemTrader.com (a good source for trading systems) has put up an edited version of an older presentation of Mr Kaufman’s. It’s all about price noise and the Efficiency Ratio. Coincidentally, so is the article in the next section of this report, “Matching the Markets to the Strategy.” We hope you find it valuable.
Last month Mr Kaufman posted an article in ProActive Advisor Magazine, “Low Volatilty – High Returns?” This article shows how to turn periods of low volatility into high returns, and why you want to avoid high volatility.
Look for other articles by Mr Kaufman on Seeking Alpha (www.seekingalpha.com), Forbes (https://www.forbes.com/sites/perrykaufman). www.equities.com, Modern Trader, Technical Analysis of Stocks & Commodities, and Proactive Advisor Magazine. You will also find many articles posted under Articles on our website, www.kaufmansignals.com. You can address any questions to firstname.lastname@example.org.
Matching the Markets to the Strategy
At the risk of being too “geeky,” not all markets will be profitable with all systems. Part of being successful trading is to know which strategies to apply to which markets. We can never be perfect because economics and supply/demand can change, but most markets can be put into a category that favors one trading method over another.
For example, if you’re a macrotrend trader, holding positions for weeks or months, then the Eurodollar interest rate futures is the all-time favorite. It closely tracks Fed action, which evolves slowly, hence it has a strong trend and little distracting noise. At the other end of the spectrum are the equity index markets, which have high noise relative to the net price change. Don’t be fooled by a few years of S&P trending, in the long run it’s only the slowest trends that work, avoiding the frequent dips.
Let’s be clear about the concept of “noise,” which has been something that I’ve found useful for many years. Noise represents the unnecessary ups and downs when prices move from one point to another. I like to compare it to a drunken sailor’s walk, staggering back and forth but eventually getting back to the ship. It’s the opposite of when he left the ship to find the pub, walking quickly in a straight line. Then a straight line means no noise and staggering around represents different degrees of noise. We can measure this with the formula for the “efficiency ratio” (ER) on day t (today), using the past N days:
ER(t) = abs(close(t) – close(t-N))/SUM(abs(close(i) – close(i-1)), i=t-N+1 to t)
The numerator is the absolute value (always positive) of the change in price from N days ago (t-N) to today (t). The denominator is the sum of all the daily price changes, each taken as a positive number. If prices only go up over the N days, the value of ER(t) = 1. If they go up and down a lot, then the value of ER(t) will be near zero.
How Do You Use It?
The conclusion is simple. Markets with low noise favor trending systems and markets with high noise favor mean reversion. If you use the wrong markets, you’ll struggle to make money.
It’s going to be difficult to show an entire research study including different strategies and results, so we’ll show a sample of trending and noisy markets beginning in 2004. The data interval does change the results, so looking at a longer period would give more consistency, but for ETFs it’s difficult to go back very far.
Separating Noise from Volatility
Noise is not the same as volatility. Volatility is only the change in price, daily for us. The ER value can be zero (high noise) when prices are unchanged no matter what the volatility was. Almost any sideways period will show high noise. At the other end, if you have high volatility but an even larger price move, and the ER value be high (relatively low noise) so that a fast trend will still work. Let’s look as some sample markets.
Chart 1 shows annualized volatility of a selection of futures markets (left) and ETFs (right). For futures, heating oil and natural gas are the most volatility, while Eurodollar rates and EuroStoxx are the least volatile. When choosing markets to trade, a mean reversion strategy prefers high volatility, but not if prices are making big directional moves at the same time. For that we need to look at noise.
Chart 1 (Left) Futures annualized volatility expressed in dollars. (Right) ETF annualized volatility from daily returns.
Using the same markets, Chart 2 shows the ranking of futures and ETFs according to noise. For futures, Eurodollars has the highest ER value, meaning the lowest amount of noise. We take that as the best trending candidate and, combining it with the lowest volatility (in Chart 1), we have an ideal situation. For ETFs the best choice is NASDAQ (QQQ) followed by the technology sector (XLK). Both have a medium amount of volatility, which means they will need a slower trend, but still are good for trending.
Chart 2 (Left) Futures noise. (Right) ETF noise.
If you’re looking for mean reversion markets, the you want the highest value of volatility and the lowest ER value. You should start by looking at the noise, which mean prices aren’t going anywhere relative to the volatility. Then the Russell is the best choice in futures, while IWM is about the lowest ER value in ETFs. EuroStoxx is also good, but has low volatility. To find the best combinations for mean reversion, we can create a scatter diagram of noise versus volatility, looking for the lowest ER value and the highest volatility.
In Chart 3, the best trending markets would have low volatility (the bottom of the left scale) and a high ER value (right on the bottom scale). The point in the left chart, far right, bottom corner, is Eurodollars. The best mean reversion markets would be diagonally opposite, in the upper left corner. The dotted straight line is the regression through those points. Because it is nearly horizontal, it shows that there is no relationship between volatility and noise. Table 1 shows the numbers used for these charts, so that you can make the decisions for yourself.
Chart 3. Noise (ER value) versus volatility. (Left) Futures. (Right) ETFs.
Table 1 (Left 3 columns) ETFs with ER value and annualized percent volatility. (Right 3 columns) Futures with ER value and annualized dollar volatility.
Performance, the Final Test
This is all theory until you run a trend-following system using these markets, then compare the profits against the noise value. Remember that this is a small sample and chosen without first looking at the results; therefore, the results will be realistic rather than optimistically good. Such is real life.
We will expect the markets with low noise (high ER values) to perform better with trend following, and those with high noise (low ER values) to be best with mean reversion. We won’t show mean reversion results, only infer them from the trend performance. There are too many ways to implement mean reversion. We’ll use a 120-day trend to capture the idea of a macrotrend.
Chart 4 is a scatter diagram of the trend-following results versus the ER value. Trend-following results are expressed as an information ratio, annualized returns divided by annualized volatility, my best measure of reward to risk. Futures (left), show Nasdaq at the far right, Eurodollars at the top, and the Russell, EuroStoxx, crude oil, and natural gas clustered at the bottom left. This means Nasdaq was the best performer while Eurodollars was modestly profitable with low noise, no doubt due to the flattening and turning of short-term rates in the past few years. The cluster on the bottom left would be the best candidates for mean reversion.
Chart 4. Trend-following results, expressed as an information ratio (annualized returns divided by annualize risk). (Left) Futures markets. (Right) ETF markets.
For ETFs, the relationship between noise and profits is much stronger, as seen by the angle of the regression line. Nasdaq (QQQ) is again at the top right, consistent with futures, and IWM, XHB, and XLP at the bottom left, the best choices for mean reversion. The best (Nasdaq) and worst (Russell) are consistent across both futures and ETFs. Two other good markets at the upper right are XLK (technology), and SPY (sector SPDRs).
While there is a gray area in the middle where a market may be good for both trending and mean reversion, the extremes are clear. A high ER value is good for trends, and a low value is good for mean reversion. If you only eliminate the worst offenders from your portfolio, you will significantly improve your results.
March Insight: Waiting for Anything?
As we mention earlier in the brief comment, the market seems to have stalled out waiting for something more significant than tweets to move it higher. Because it hasn’t declined, there is still optimism. If we look only at the financial sector (XLF, left below) and the 30-year bond futures, we can see that optimism is being tempered by the impending threat of two more rate hikes this year. If nothing happens to improve business, such as reduced regulation (Dodd-Frank), or some tax reform (lowering corporate taxes), then the Fed will be the main event putting pressure on stock prices. While we see some relief using Executive Orders, we don’t see anything getting through Congress anytime soon. Expect more of the same.
XLF (left), 30-year bond futures (right)
Portfolios Selected by Performance are High Beta
As a reminder, our automatic portfolio selection process uses past performance to select stocks and futures. Markets that are outperforming the averages tend to continue to outperform, but they also have higher volatility than the broad index. Outperformance means that profits on any day are higher, which also means that on a losing day, losses will usually be larger. It’s the basic principle of volatility and risk: you can’t achieve higher returns without higher risk.
Smaller portfolios that are less diverse are more likely to generate higher returns during “good” markets (the ones that work well for the strategy) and larger losses during “bad” markets. More diverse portfolios will have smaller gains and losses. To decide which is best for you, you must determine your risk tolerance and how much capital can be put at risk.
Trend Strength Index
One measure of market strength is our Trend Strength Index. Our Trend strategy is a composite of many trends, medium term to slow applied to about 250 stocks. When combined, these determine the position size of the current trade. If the faster trends are down but the slower one up, then the position size might be zero. The appearance is that trend positions scale in and out based on the strength of the trend. The Trend Strength Index appears at the bottom of the Trend Stocks All Signals report each day. We’ve tracked it from the beginning of 2014, and the chart below compares it with the SPY. TSI is the Trend Strength Index and SPY is the SPDR ETF. TSI values about zero indicate a positive trend. The range of the TSI is +1 to -1.
The Trend Strength Index fell short of the highs of 60 and made a sharp turn down, indicating that the momentum of our stocks looks weak. It is possible for stock prices to move sideways with low volatility waiting for something to happen, in which case the Trend Strength Index will decline without any trading opportunity. Right now it indicates a lack of enthusiasm in the overall market.
We offer this Index for those investors who select their own trades rather than following our sample portfolios. Daily Index values are available to subscribers.
Strongest and Most Undervalued Sectors
There are two ways to view sector rotation, trade the strongest expecting them to stay strong, or trade the weakest expecting the business cycle to rotate them to the top. We have both. The Trend Rotation trades the strongest and the Timing Rotation trades the weakest. The Trend program may hold positions for a long time, so it’s possible for two ETFs to be in both programs. For example, XOP (Oil and Gas) can be in a long-term uptrend, but a short-term oversold situation. The new Sector Rotation program also buys the strongest sectors and is reviewed with the Trend Equity Program.
The Trend Sector ETF program buys the 6 strongest sectors of the SPDRs.
At the end of January, we held Materials (XLB), Industrials (XLI), Metals & Mining (XME), and Technology (XLK), Consumer Discretionary (XLY) and Staples (XLP). We replaced Materials (XLB) and Metals&Mining (XME) with Financials (XLF) and Utilities (XLY). We now hold:
Industrials (XLI), Technology (XLK), Consumer Discretionary (XLY), Staples (XLP), Financials (XLF), and Utilities (XLU).
The Timing Program buys 4 ETFs that are undervalued with respect to SPY, in expectation of rotation. We started March with Energy (XLE), Metals & Mining (XME), Retail (XRT), and Materials (XLB). This month we exited all but Energy (XLE). We now hold:
Energy (XLE), Reit (VNQ), Financials (XLF), and Industrials (XLI).
When an ETF appears in both the Trend and Timing programs, it means that market is very strong but is in a short-term retracement.
A Standing Note on Short Sales
Note that the “All Signals” reports show short sales in stocks and ETFs, even though short positions are not executed in the portfolios. Our review of using inverse ETFs to hedge stocks during a decline showed that downturns in the stock market are most often short-lived and it is difficult to capture those moves with trend systems. This confirms our approach to the Timing systems, which hedges up to 50% of the long stock risk using multiple trends. In the long run, returns from the hedges are net losses; however, during 2008 the gains were welcomed and reduced losses. In any correction, we prefer paying for risk insurance, even without the expectation of a net gain.
Portfolio Methodology in Brief
All of the programs, stocks, ETFs, and futures, use the same basic portfolio technology. They all exploit the persistence of performance, that is, they seek those markets with good long-term and short-term returns, rank them, then choose the best, subject to liquidity, an existing current signal, with limitations on how many can be chosen from each sector. If there are not enough stocks or futures markets that satisfy all the conditions, then the portfolio holds fewer assets. In general, these portfolios are high beta, showing higher returns and higher risk, but have had a history of consistently out-performing the broad market index in all traditional measures.
PERFORMANCE BY GROUP
NOTE that the charts show below represent performance “tracking,” that is, the oldest results are simulated but the newer returns are the systematic daily performance added day by day. Any changes to the strategies do not affect the past performance, unless noted.
Groups DE1 and WE1: Daily and Weekly Trend Program for Stocks and ETFs, including Sector Rotation and Income Focus
The Trend program seeks long-term directional changes in markets and the portfolios choose stocks and ETFs that have realized profitable performance over many years combined with good short-term returns.
Small losses all the Trend portfolios leaves the long-term picture unchanged. Stock performance remains near highs and ETF results continue to look like a recovery. We’re waiting for some positive business news.
The same holding pattern can be seen in the returns of the weekly program, in both stocks and ETFs. The stock portfolios still look very positive.
Income Focus and Sector Rotation
Pending interest rate increases offset interest income in March, posting a small loss for both the Daily and Weekly Income Focus program.
The Weekly Sector Rotation program took the largest loss of all portfolio this month, with most positions changing as the market “rotated.” It still retains an upward trend while it recovers from lows earlier last year.
Group DE2: Divergence Program for Stocks and ETFs
The Divergence program looks for patterns where price and momentum diverge, then takes a position in anticipation of the pattern resolving itself in a predictable direction, often the way prices had moved before the period of uncertainty.
The Divergence Program reflects the same small losses as the other equity programs, but holds on to positive returns in all portfolios, along with a clear upward trend to returns. The ETF program gained fractionally, and seems to be determined to move slowly higher.
Meanwhile, the ETF program moves upward, slowly but steadily.
Group DE3: Timing Program for Stocks and ETF Rotation
The Timing program is a relative-value arbitrage, taking advantage of undervalued stocks relative to its index. Its primary advantage is that it doesn’t depend on market direction for profits, although these portfolios are long-only because they are most often used in retirement accounts. When the broad market index turns down this program hedges part of the portfolio risk. The ETF Rotation program buys undervalued sectors, expecting them to outperform the other sectors over the short-term.
The Timing Program buys undervalued stocks so that it will buy the weakest even in a declining market until that stock shows that it is not expected to rally. Risk is protected with an absolute stop of 15% and also by hedging the broad index.
A setback in returns for both equity portfolios, but the 10-stock portfolio is still up 6.52% for the year, ahead of the S&P. The ETF program also took a loss, but is holding onto its recovery from the lows of last year.
Change in Futures Portfolios
(This is repeated from earlier in this report.)
We have reduced exposure to agricultural markets in all daily and weekly portfolios. We prefer using the exact same macrotrend logic and parameters for ag markets, because it qualifiies as “robust.” This worked well when there were large changes in the value of the US dollar and interest rates. But commodities have a much shorter cycle than most other financial markets, a function of both seasonality and short-term changes in supply and demand. Without major moves driven by macrofactors, we need to use a much shorter calculation period to take advantage of those moves. We will be replacing those ag markets and other commodity futures with a modified program specifically oriented to this time frame.
Groups DF1 and WF1: Daily and Weekly Trend Programs for Futures
Futures allow both high leverage and true diversification. The larger portfolios, such as $1million, are diversified into both commodities and world index and interest rate markets, in addition to foreign exchange. Its performance is not expected to track the U.S. stock market and is a hedge in every sense because it is uncorrelated. As the portfolio becomes more diversified its returns are more stable.
The leverage available in futures markets allows us to manage the risk in the portfolio, something not possible to the same degree with stocks. This portfolio targets 14% volatility. Investors interested in lower leverage can simply scale all positions equally in proportion to their volatility preference. Note that these portfolios do not trade Asian futures, which we believe are more difficult for U.S. investors to execute.
Using the same strategy and portfolio logic, the Weekly Trend Program for Futures has the added smoothing resulting from looking only at Friday prices. While it will show a larger loss when the trend actually turns, most price moves are varying degrees of noise which this method can overlook.
Please read the report describing our revised portfolio allocation methodology. It can be found in the drop-down menu under “Articles.”
The following charts reflect the historic performance of the new portfolio, with deleveraged agricultural markets. The recent drawdown in the daily program has now taken an upward turn, and the long-term performance is also higher. The weekly program is posting less of a loss but hasn’t had much time to reflect the changes. In actual trading this month, the daily program showed good profits but not the weekly. The weekly program will outperform the daily when longer term trends surface, because it will hold them and not get in and out as the daily program might.
Group DF2: Daily Divergence Portfolio for Futures
A good month for all portfolios in the Divergence Program, up from about 4% to 5%. A continued move higher would confirm that this program is volatile, but consistently recovers from drawdowns.
Insert Futures Divergence charts
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