December 2009 • Volume 3, No. 12
IMPROVING STRATEGY
PERFORMANCE
with money
management
p. 6
BETTER BREAKOUT
trading
p. 10
OPTIONS STRATEGIES:
Gamma scalping
p. 12
PLAYING RESISTANCE
in treasuries
p. 28
TRADING THE
parabolic SAR with
credit spreads
p. 17
COMMERCIAL TRADERS
Contributors . . . .
5
Trading Strategies
Trading with maximum portfolio risk . . . .
6
Using a dynamic position-sizing approach turns a so-so system into a significant winner.
Tuning up the Turtle . . . .
10
After two decades, traders are still intrigued by the trend-following strategy followed by the Turtles in the 1980s. Does it still work?
By Anthony Garner
The options straddle battle . . . .
12
Can two traders succeed if they make completely opposite bets on market volatility?
By Dan Keegan
Options Trading System Lab
Parabolic SAR with credit spreads . . . .
17
Trading credit spreads when this indicator changes direction.
By Steve Lentz and Jim Graham
Futures & Options Calendar . . . .
19
New Products and Services . . . .
20
Futures & Options Watch:
COT extremes . . . .
21
A look at the relationship between commercials and large speculators in all 45 futures markets.
Options Watch . . . .
21
Vanguard Value ETF components
Futures Snapshot . . . .
22
Momentum, volatility, and volume statistics for futures.
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MoneyShow | Githler Center | 1258 North Palm Ave. Sarasota, FL 34236 USA Rob Booker Author The Currency Trader’s Handbook ActiveTraderAd-NYTE10_Layout 1 11/25/09 11:39 AM Page 1
Options Radar . . . .
23
Notable volatility and volume in the options market.
Key Concepts . . . .
24
References and definitions.
Managed Money . . . .
25
Top 10 option strategy traders ranked by August 2009 return.
Events . . . .
26
Futures Trade Journal . . . .
28
Resisting the temptation to fade resistance.
Options Trade Journal . . . .
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Trading gaps in a range-bound holiday market.
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CONTRIBUTORS
5 December 2009 • FUTURES & OPTIONS TRADER
Editor-in-chief: Mark Etzkorn
Managing editor: Molly Goad
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Volume 3, Issue 12. Futures & Options Trader is pub-lished monthly by TechInfo, Inc., 161 N. Clark St., Suite 4915, Chicago, IL 60601. Copyright © 2009 TechInfo, Inc. All rights reserved. Information in this publication may not be stored or reproduced in any form without written permission from the publisher.
The information in Futures & Options Trader magazine is intended for educational purposes only. It is not meant to recommend, promote, or in any way imply the effectiveness of any trading system, strategy, or approach. Traders are advised to do their own research and testing to determine the validity of a trad-ing idea. Tradtrad-ing and investtrad-ing carry a high level of risk. Past performance does not guarantee future results.
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CONTRIBUTORS
After Oxford University, Anthony Garner spent a few
formative years as a solicitor with Slaughter and May, a London commercial law practice. He joined Swiss Bank Corporation International in the mid-1980s and spent several years as an investment analyst, with postings in Tokyo, Hong Kong, Singapore, and Zurich. He left conventional employment in 1995 and began working for himself. Garner now designs, tests, and trades simple mechanical investment strategies. He recently published A Practical Guide to
ETF Trading Systems (Harriman House). Together with his colleague Roeland
Phillippe, Garner provides Zurich-based fund manager IFIT Advisory AG with mechanical trading strategies. The firm uses Garner’s strategies in its Cardio Angels Fund.
Dion Kurczek([email protected]) is a private trader, software
engi-neer and trading system researcher. In 2000 he founded Wealth-Lab Inc. and launched an interactive trading system development laboratory on the Web (www.wealth-lab.com). He is currently vice president of Wealth-Lab Product Development at Fidelity Investments.
Volker Knapphas been a trader, system developer, and
researcher for more than 20 years. His diverse background encompasses positions such as German National Hockey team player, coach of the Malaysian National Hockey team, and president of VTAD (the German branch of the International Federation of Technical Analysts). In 2001, he became a partner in Wealth-Lab Inc. (www.wealth-lab.com), which he still runs.
Dan Keegan is from Rochester, New York and earned an economics
degree from Marquette University in 1977. After graduation, Keegan moved to Chicago and soon began working at the Chicago Board Options Exchange (CBOE). The CBOE was only four years old when Keegan began working at a series of several jobs both on and off the trading floor. In 1982, Keegan began trading on the CBOE floor with backing from legendary adventurer Steve Fossett who made his fortune backing young traders like Keegan. After more than 20 years as an independent floor trader, Keegan has become an options educator and advisor. He frequently guest lectures in options at Marquette University, is an advisor for i2i Analytics, and a regular contributor to finan-cial trade publications. Keegan is the co-founder and director of options for the Chicago School of Trading. He and his wife Lesly live in Hinsdale, Ill. with
their three children.
Jim Graham ([email protected]) is the product
manager for OptionVue Systems and a registered investment advisor for OptionVue Research.
Steve Lentz ([email protected]) is a
well-estab-lished options educator and trader and has spoken all over the U.S., Asia, and Australia on behalf of the CBOE’s Options Institute, the Options Industry Council, and the Australian Stock Exchange. As a mentor for DiscoverOptions.com, he teaches select students how to use complex options strategies and develop a consistent trading plan. Lentz is constantly developing new strategies on the use of options as part of a comprehensive profitable trading approach. He regularly speaks at special events, trade shows, and trading group organizations.
OPTIONS STRATEGY LAB
TRADING STRATEGIES
Trading
with maximum portfolio risk
A basic price pattern with mediocre results when tested on a single-contract basis takes off
when a dynamic money-management regime is introduced.
Note: A version of this article origi-nally appeared in the November 2003 issue of Active Trader magazine.
T
he two-bar breakout(2BB) system attempts to capture short trends by going long or short based on the behavior of the two most recent price bars. It trades fre-quently and has a very brief aver-age holding period — typically one or two bars on average (six or seven bars when a good trend move materializes). Also, it uses a very tight stop to limit losses.
Many traders would likely be skeptical that such a basic price pattern could produce useful results. However, such traders might overlook the role money management — specifically, adjust-ing the number of contracts
accord-ing to current account equity — can play in makaccord-ing the most of a strategy.
The 2BB essentially looks for a reversal of the immedi-ate directional momentum, buying if price exceeds yester-day’s high if yesterday was a down day, and selling if price falls below yesterday’s low if yesterday was a down day. The rules are:
Long trades:
1. Go longwith a stop order on the next bar (at the current high plus one tick) if:
a. the low is less than the previous bar’s low; b. the high is less than the previous bar’s high; c. the close is less than the open.
Exit longusing a trailing stop at the current bar’s low. Short trades:
4. Go short with a stop order on the next bar (at the current low minus one tick) if:
a. the low is greater than the previous bar’s low;
b. the high is greater than the previous bar’s high; c. the close is greater than the open.
2. Cover short using a trailing stop at the current bar’s high.
Figure 1 shows sample trades in natural gas (NG). The system was relatively active, triggering around 20 trades during this roughly two-month period. Losing trades are stopped out quickly.
To start, we’ll test the system trading only one contract per position, then evaluate other position-sizing strategies later in the article. The initial account equity was set to $1 million, and $20 was deducted per round-turn trade for slippage and commissions. Testing was conducted on daily data on the following 19 markets: DAX30 (AX), corn (C), crude oil (CL), German bund (DT), Eurodollar (ED), Eurocurrency (FX), gold (GC), copper (HG), Japanese yen (JY), coffee (KC), live cattle (LC), lean hogs (LH), Nasdaq 100 (ND), natural gas (NG), soybeans (S), sugar (SB), sil-ver (SI), S&P 500 (SP) and 10-year T-notes (TY). The test FIGURE 1 — SAMPLE TRADES
This cross section of long and short trades in natural gas (NG) illustrates how the system rides short trends nicely, but exits at the first sign of a reversal.
FUTURES & OPTIONS TRADER • December 2009 7
spanned September 1993 until December 2002.
Fixed position test results
The system returned a 45-percent profit over the test period, but was somewhat hobbled by the one-contract-per-trade position-sizing rule and the large starting capital in the test account. As a result, the system sat in cash for most of the test period. Nonetheless, the equi-ty curve showed steady increases in both the long and the short sides of the system (Figure 2).
Another interesting characteristic of the equity curve is that on three occasions (1995, 1998, and 2002) the account ratcheted up sharply, followed by longer periods of much more moderate volatility. Because the system traded one contract per trade, very large mar-kets have a far greater impact on the overall results than small ones.
Although the system’s annualized return over the test period was a meager 3.93 per-cent, the maximum drawdown was only -6.56 percent (Figure 3). Once again, the very con-servative position sizing limited the system’s potential during the test run.
Let’s see if using a more dynamic position-sizing approach might extract more value from the trade rules. Dynamic position sizing
with maximum portfolio risk
One of the most important aspects — some would argue the most important aspect — of futures trading is position siz-ing. Intelligent position sizing can produce much-improved returns even on simple trend-following systems. One approach is called “maximum portfolio risk,” which establishes the position size so if the initial
stop-loss is hit, the amount of money lost will equal a certain percentage of the total account equity.
A second test of the two-bar breakout sys-tem used a maximum portfolio risk level of 1 percent, along with a filter that required the number of contracts to not exceed 1 percent of the total trading volume for that day. Finally, two ticks of slippage were added to both the entry and the exits for each trade. Figure 4
shows the results of this test. The difference between it and Figure 2 is clear. The equity curve’s ascent is much sharper, although also more volatile, and the ending profit much higher. However, in this case the increased reward seems worth the higher risk.
continued on p. 8
FIGURE 2 — STATIC POSITION SIZE EQUITY CURVE
Trading one contract per market produced a very low-key equity curve. However, both the long and short sides of the system were profitable.
Reducing the risk per trade also decreased the system’s maximum drawdown.
TABLE 1 — ADJUSTING THE RISK LEVEL
Maximum APR Net Maximum
risk (%) (%) profit (%) drawdown (%)
1.00 28.65 1,052.00 -30.82
0.75 22.82 635.00 -27.84
0.50 14.95 286.00 -23.89
0.25 5.65 70.00 -13.14
FIGURE 3 — DRAWDOWN
The average drawdown was -3-percent and the maximum drawdown was only -6 percent.
Table 1 shows the relationship between maximum risk, annualized return, and maximum drawdown. Net profit increased to an annual rate of 28.65 percent, but maximum drawdown also increased dramatically to -30.82 percent. However, the system still boasts a healthy recovery factor (net profit/maxi-mum drawdown) of 2.58. The draw-down can be reduced by reducing the maximum portfolio risk.
Sizing matters up
An intelligent position sizing strategy can help minimize losses and extract the full potential out of the strategy. Although the trade setup only uses the most recent two bars of market data, it proved to be robust — and quite prof-itable when combined with dynamic position sizing.
—Submitted by Vetri Vel —Compiled by Dion Kurczek and Volker Knapp of Wealth-Lab Inc. For information on the authorsee p. 5.
TRADING STRATEGIES
STRATEGY SUMMARY
Profitability Trade statistics
Net profit: $453,934.00 No. trades: 4,884
Net profit: 45.39% Win/loss: 38.74%
Exposure: 1.86% Avg. gain/loss: 0.08% Profit factor: 1.21 Avg. hold time: 2.44 Payoff ratio: 1.77 Avg. profit (winners): 2.08% Recovery factor: 4.67 Avg. hold time (winners): 3.78
Drawdown Avg. loss (losers): -1.18%
Max. DD: -6.56% Avg. hold time (losers): 1.60 Longest flat days: 388 Max. consec. win/loss: 10/14 LEGEND: Net profit — Profit at end of test period, less commission •
Exposure — The area of the equity curve exposed to long or short positions,
as opposed to cash • Profit factor — Gross profit divided by gross loss •
Payoff ratio — Average profit of winning trades divided by average loss of
losing trades • Recovery factor — Net profit divided by max. drawdown •
Max. DD (%) — Largest percentage decline in equity • Longest flat days — Longest period, in days, the system is between two equity highs • No. trades — Number of trades generated by the system • Win/Loss (%) — The
percentage of trades that were profitable • Avg. trade — The average prof-it/loss for all trades • Avg. winner — The average profit for winning trades
• Avg. loser — The average loss for losing trades • Avg. hold time — The
average holding period for all trades • Avg. hold time (winners) — The average holding time for winning trades • Avg. hold time (losers) — The average holding time for losing trades • Max. consec. win/loss — The max-imum number of consecutive winning and losing trades
STRATEGY SUMMARY (2% RISK)
Avg. Sharpe Best Worst Percentage Max. Max.
return ratio return return profitable consec. consec. periods profitable unprofitable
Weekly 0.08% 0.70 7.90% -3.11% 49.11% 7 6
Monthly 0.33% 0.77 7.02% -3.24% 55.93% 7 5
Quarterly 0.97% 0.76 10.42% -3.13% 65.00% 7 2
Annually 4.01% 0.58 20.20% -2.68% 70.00% 6 2
LEGEND: Avg. return — The average
percent-age for the period • Sharpe ratio — Averpercent-age return divided by standard deviation of returns (annualized) • Best return — Best return for the period • Worst return — Worst return for the period • Percentage profitable periods — The percentage of periods that were profitable • Max.
consec. profitable — The largest number of
con-secutive profitable periods • Max. consec.
unprofitable — The largest number of
consecu-tive unprofitable periods
FIGURE 4 — DYNAMIC POSITION SIZE EQUITY CURVE
Normalizing the position size for all contracts by risking 1 percent of account equity increased returns significantly.
TRADING STRATEGIES
Tuning up the turtle
D
o markets change? Is it necessary toundertake continued research and development and adapt a trend-fol-lowing system to maintain its prof-itability over the years?
To attempt to answer these questions, the fol-lowing study tracks the strategy of the “Turtles,” a group trained by legendary traders Richard Dennis and Bill Eckhart in the 1980s. The Turtles were used to conduct an experiment about whether it was possible to teach people to become successful traders.
One trading system salesmen recently argued that it is “nonsense” and a “specious argument” to suggest trend-following rules must adapt to changing market conditions.
Others argue a trend-following system does not simply self-adapt but needs continued monitoring and refining. Some well-known trend-followers have indeed stated they still trade the same system as when they started out 30 or 40 years ago. But what do those man-agers really mean?
Testing the Turtle
By back testing the original Turtle strategy, we can ascertain whether this one particular system, which was highly profitable back in the early 1980s, has stood the test of time or needs updating.
At its core, the Turtle strategy is a trend-following system that attempts to capture short- and medium-term trends in a portfolio of futures markets (Table 1).
For example, Turtles bought the market after 20-day highs and sold short after 20-day lows. Figure 1 shows trade examples in cocoa
futures (CC), which shows the effect of pyramiding: Units were entered short on Jan. 6 and 7, 1970, and all units wereexited at the same time on March 5, 1970 as the market
pen-After two decades, traders are still intrigued by the trend-following strategy followed by
the Turtles in the 1980s. This preview of an article in the February 2009 issue of Active Trader tests
their strategy and suggests how to improve it.
FIGURE 1 — TRADE EXAMPLES — TURTLE SYSTEM
The original Turtle strategy sold short in cocoa futures in January 1970 and exited at a profit in March.
Source: Trading Blox
TABLE 1 — MARKETS TRADED BY TURTLES
Market
Bonds: 30-year T-bonds (US), 10-year T-note (TY), Eurodollar (ED)
Softs: Coffee (KC), cocoa (CC), sugar #11 (SB), cotton (CT) Currencies: Swiss franc (SF), Euro (EC), British pound (BP),
Japanese yen (JY), Canadian dollar (CD) Stock indices: S&P 500 (SP)
Metals: Gold (GC), silver (SI), copper (HG)
Energy: Crude oil (CL), unleaded gas (RB), heating oil (HB) The original trend-following strategy traded by the Turtles included 21 futures markets. This test replaces the Deutsche mark and French franc with the Euro and excludes the 90-day T-bill contract.
Source: Way of the Turtle: The Secret Methods that Turned Ordinary People into
Legendary Traders (McGraw-Hill, 2007).
etrated the 10-day high.
We tested the Turtles’ strategy on 21 futures markets from Table 1 from Jan. 1, 1970 to Sept. 23, 2009. These were the markets traded by the original Turtles. Note: French francs and the 90-day U.S. T-Bill were omitted from the original portfolio, and the Euro was substi-tuted for the Deutsche mark.
Figure 2 shows its equity curve. The strategy was highly profitable before and during the Turtle exper-iment, which spanned from 1983 to 1988. Average trade length was rel-atively short: 43 calendar days for winning trades and 13 days for los-ing trades.
However, since the early 1990s, the system has essentially been
unprofitable. Large drawdowns of up to 66 percent would have made this system difficult to trade unless you had exceptionally strong nerves. The original Turtle system needs considerable updating in the light of current market conditions.
Rethinking the strategy
Let’s stick with the basic approach, but wait to buy the mar-ket at longer-term highs and sell short at longer-term lows
(instead of 20-day thresholds). Similarly, wait to exit long (short) trades at longer-term lows (highs) instead of just 10-day extremes. These changes produce a longer-term system that is more likely to avoid some of the increased noise in today’s markets.
For information on the authorsee p. 5.
Read the full article in the February 2010 issue of Active Trader, on newsstands in January.
FIGURE 2 — EQUITY CURVE
After impressive growth in the 1980s, the equity curve flattened in the early 1990s, suggesting the system has broken down.
OPTIONS STRATEGY LAB
TRADING STRATEGIES
The options straddle battle
C
an two traders both make money tradingvolatil-ity if one of them is short while the other is long? At first glance, that seems unlikely because options trading is a zero-sum game. When you place a trade, someone takes the other side and only one of you will succeed at expi-ration.
However, both traders might be profitable if they adjust the position correctly. Establishing a trading position with an edge is always helpful, but proper-ly managing that position is more important. The following examples use options straddles (same-strike, same-month puts and calls) on corn futures to demonstrate this point.
Historical and implied volatility
When deciding whether to buy or sell options, traders often use the relationship between historical
andimplied volatility(HV and IV) as a guide. Historical volatility is the realized volatility of the underlying over a given time period. Generally, this measure is calculated by the standard deviation of returns in a given period. HV is empirically based. By contrast, implied volatility is the reverse engi-neering process in which the current option prices imply the underlying’s volatility.
A wide divergence between HV and IV can mean one of two things. Either the relationship is out of line with past levels, suggesting it might soon revert back to normal, or the relationship has changed and may stay that way. For example,
implied volatility may increase before an expected announcement while his-torical volatility holds steady. Or IV may drop well below HV as traders anticipate a calm market. If you believe extremely high or low IV will eventually move back toward HV, you could sell high-IV “expensive” options or buy low-IV “cheap” options.
But the wide divergence could also remain intact, and any attempts to exploit a move toward their historical relationship could result in losses. Unfortunately, there is no crystal ball.
The long-short debate
A common approach to trading volatility is the options
Traders on opposites sides of the market aren’t necessarily locked into a battle for success,
as this comparison of options straddles in corn futures shows.
FIGURE 1 — DECEMBER CORN FUTURES
By entering a long options straddle on December corn futures, you are betting corn either rallies above the upper breakeven point or below the lower breakeven point by expiration. Traders of the opposite position — a short straddle — will benefit if corn trades in between these thresholds. However, either position can ultimately be profitable if adjusted correctly.
Source: eSignal
TABLE 1 — CORN STRADDLE DETAILS
December corn (CZ09) traded at 372 on Oct. 16.
Position Total price per bushel Dollar amount 10 December 3750-strike calls $1.78750 $8,937.50 10 December 3750-strike puts $1.98750 $9,937.50
Total cost (risk): $3.7750 $18,875.00
Lower breakeven point: 412.75 Upper breakeven point: 337.25
Straddle buyers pay to enter this spread and will profit if December corn exceeds one of the breakeven points. Straddle sellers get paid to open the spread and hope the underlying doesn’t move much.
FUTURES & OPTIONS TRADER • December 2009 13
straddle. If you believe the underlying is poised to move sharply (in either direc-tion), widening the spread between IV and HV, you could enter a long straddle
by purchasing at-the-money (ATM) calls
and buying ATM puts in the same expi-ration month. However, if you believe the underlying will trade in a range, nar-rowing the IV-HV spread, you could take the opposite position by selling those same calls and puts.
If one trader buys a straddle and another sells the opposite position, only one will make money if they don’t adjust those positions before they expire. But if both traders adjust the strategies based on underlying moves, each lowers risk and increases their odds of success. Implied volatility in corn
The first step is to examine IVs of indi-vidual options on corn futures. One corn futures contract represents 5,000 bushels, and a strike price of 3750 represents $3.75 per bushel.
Figure 1 shows December 2009 corn futures closed at 372 on Oct. 16, and the December 3750-strike call had a 41-per-cent IV. By contrast, the March 2010 and May 2010 3900-strike calls had IVs of 35 and 32 percent, respectively. And the ATM call IVs for July, September, and December 2010 and March 2011 were roughly 32 percent.
Why was the highest IV at the nearest month? This could mean traders expect corn futures to break out in either direc-tion. Over the past six months, near-term IVs swung between 34 and 38 percent, with a few exceptions touching 30 and 40 percent. If you believe corn futures could move sharply in either direction, you could buy a straddle in December ATM options.
Straddling stalks of corn
To enter a long straddle on Oct. 16, you could buy 10 December 3750-strike calls for 17 7/8 ($0.17875 per bushel) each and purchase 10 same-month, same-strike puts for 19 7/8 ($0.19875 per bushel). At expiration, you will be long 10 December corn futures if the calls finish
in-the-continued on p. 14
FIGURE 2 — LONG STRADDLE
The easiest way to make money with a long straddle is with a large underlying move in either direction. But there are other ways to profit if a significant move doesn’t materialize.
money(ITM) or short 10 December corn futures if the puts finish ITM.
This long-volatility position costs 37 6/8 ($0.3775 per bushel, Table 1). Figure
2shows the trade’s potential gains and
losses on three dates: Trade entry (Oct. 16, dotted line), halfway until expiration (Nov. 3, dashed line), and expiration (Nov. 21, solid line).
There are three ways to make money on this position. First, do nothing and hope December corn finishes above 412 6/8 or below 337 2/8. Second, the uncer-tainty surrounding the corn crop could increase, inflating implied volatility. If this happens, the straddle will climb in value and you can exit the position.
But what if December corn never breaches either of the straddle’s breakeven points and implied volatility stays flat or decreases? You still have opportunities to make money on the trade, but it won’t be easy.
If December corn drops lower, the long puts are more likely to expire ITM, boosting the odds of a short futures posi-tion. (Long put holders have the right to sell the underlying at the strike price.) In response, you can buy the underlying futures contracts to reduce the risk of holding a short position. At that point, if the underlying bounces back, you can sell the underlying contracts at a profit.
If December corn rallies, the long calls are more likely to expire ITM, which could result in a long futures position. (Long call holders have the right to buy the underlying at the strike price.) You can then sell the underlying to lower the risk of holding a long position. And if December corn slips, you can buy back the underlying at a profit.
You will make money with this tech-nique if the profit earned from these underlying trades exceeds the decay in the option’s time value. This “scalping” approach works best when the underly-ing is range-bound, not when it moves in a straight line.
Short straddle example
Let’s compare a long straddle with a short one in December corn options on Oct. 16. The position includes the same
TRADING STRATEGIES
FIGURE 3 — SHORT STRADDLE
The short straddle can only lose money on one side of the market at expiration. However, potential losses are large.
FUTURES & OPTIONS TRADER • December 2009 15
options, but they were sold instead of bought.
The short straddle’s risk-profile
graph is shown in Figure 3. Note
the risks and rewards are reversed: By selling those options, the maxi-mum profit is 37 6/8 and the total possible loss is nearly limitless. And unlike the long straddle, the short one is profitable if December corn trades within the upper and lower breakeven points.
The short straddle can only lose money on one side of the market at expiration. If the short calls move into the money, they will convert into a short underlying position; if the short puts move ITM, they will convert into a long underlying position.
If you do nothing until expira-tion, and December corn never exceeds the upper or lower breakeven points (412 6/8 and 337 2/8), the position will make money. Another way to profit is to buy back the position after the underlying trades side-ways and the options’ time value drops.
But what happens if December corn exceeds one of the breakeven points? As the underlying declines, the short puts will act more like long underlying futures. To hedge against this directional risk, you can sell the underlying after it declines. This step essentially converts the position’s short puts into short calls. The position is now somewhat hedged against market declines.
If December corn increases, then you can buy futures contracts, which con-verts the short calls into short puts and mitigates the pain of further market ral-lies. If the underlying market is choppy, these trades may lose money. But that’s fine as long as the short options’ daily time decay exceeds the losses from trad-ing the underlytrad-ing.
Adjusting the position
Figure 4 shows implied volatility of options on corn futures climbed from Oct. 16 to Nov. 12 — two weeks before expiration. The December 3750-strike call
FIGURE 4 — CORN VOLATILITY
Implied volatility of options on corn futures (blue line) climbed from Oct. 16 to Nov. 12.
Source: OptionVue
IV increased to 47 percent. Does that spell disaster for the short straddle? Not necessarily.
Those calls now trade at 19 5/8 ($0.19625 per bushel) and have a 75-per-cent chance of expiring ITM. The puts now trade at 4 5/8 ($0.04625 per bushel) with a 25-percent chance of finishing ITM (Table 2). A position of 10 short calls with a 75-percent chance combined with 10 short puts with a 25-percent chance adds up to holding five short futures contracts at expiration [(10 * 75 percent) + (10 * 25 percent)]. To flatten those prob-abilities, you could have purchased five futures contracts along the way. Thus, you are now short 15 puts and five calls. The overall short position has a -500
delta; you could buy five futures (+100 deltas each) to lower its total delta to zero.
If you had originally bought the strad-dle for 37 6/8, it has since shrunk to 24 2/8. To offset that unrealized loss, you could trade the underlying. For example, December corn opened at 392 on Nov. 12 and hit a high of 398 2/8. Suppose you sell three futures at 395 before the under-lying drops to a low of 382 4/8 and you buy them back. Then you buy another futures contract at 383 and three more at 385. Finally, you sold this long underly-ing position at 390. The profit earned from scalping corn futures combined with a rise in corn above the 3750 strike means you could have made money overall.
How frequently should you trade the underlying? The answer depends on your risk tolerance, but some traders use the overall position’s delta as a guide. For example, the original short straddle had a basically flat delta (-38) at entry. However, it fell to -500 after the underly-ing gained 6.9 percent within a week. At that point, you could have bought five futures to bring delta back down to zero, which lowers directional risk.
But you don’t have to wait that long. Other traders might be more comfort-able adjusting the position after delta moves by 200 or 300 in either direction.
For information on the authorsee p. 5.
TRADING STRATEGIES
Related reading:
Corn futures:
“A season for volatility in the grains,” Futures & Options Trader, July 2007. Implied volatility extremes help uncover straddle and strangle opportunities in the soybean and corn futures.
“Corn: The new crude oil?” Futures & Options Trader, April 2007.
Corn – it’s not just for dinner any more. This commodity’s expanding economic importance could make this an exciting year for the July-December futures spread trade.
Options straddles:
“Searching for the short-straddle edge” Futures & Options Trader, December 2008.
The difference between implied and actual volatility offers an advantage for selling straddles on the S&P 500.
“Straddling the COT report,” Futures & Options Trader, September 2007. Tracking shifts in large-trader sentiment can signal trade opportunities. This long straddle was triggered by an extreme reading in the S&P 500 futures. “Straddles vs. strangles, round two,” Options Trader, January 2007. To choose between the two, calculate points at which both strategies generate identical returns and compare them to your underlying price target.
“Seasonal straddles,” Options Trader, December 2006.
Long straddles can profit from a price move in either direction, assuming the market moves enough to overcome the trade’s cost. Finding low-implied volatility markets with strong seasonal price tendencies may be your best bet for this trade.
“Long straddles and strangles,” Futures & Options Trader, July 2006. They are popular trades that offer limited risk and unlimited reward, but long straddles and strangles require large underlying price moves in order to profit. Learn the differences between these positions and discover when they are most appropriate to trade.
“Long straddles: The importance of buying time” Options Trader, July 2005.
Buying options has a bad reputation in some trading circles because you're always fighting time decay. But knowing how to find options with the best volatility characteristics and tapping into LEAPS can allow you to construct higher-probability long straddles.
“Straddles vs. strangles,” Options Trader, December 2005.
It's the volatility-spread decision: Do you trade a straddle or a strangle? You might be surprised by the clear advantages one strategy has over the other in most situations.
TABLE 2 — AND THE VERDICT IS…
December corn (CZ09) traded at 390 4/8 on Nov. 12.
Total price Dollar
Position per bushel amount
10 December 3750-strike calls $1.96250 $9,812.50 10 December 3750-strike puts $0.46250 $2,312.50 Short straddle gain (without adjustments) $2.4250 $6,750 Long straddle loss (without adjustments) -$2.4250 -$6,750 The straddle lost value since Oct. 16, suggesting straddle sellers made money while straddle buyers lost money. However, a long straddle could have been profitable if you traded the underlying futures against it, selling after rallies and buying after declines.
FUTURES & OPTIONS TRADER • December 2009 17
OPTIONS STRATEGY LAB
OPTIONS TRADING SYSTEM LAB
Market: Options on the S&P 500 index
(SPX).
System concept: The most profitable
options lab we have tested used the direc-tional movement index, developed by Wells Wilder in 1978. This lab tests another of Wilder’s indicators — the parabolic SAR.
Sometimes known as the stop-and-reverse system, the parabolic SAR is a calcu-lation that acts as a stop-loss point under-neath long trades and above short trades (Figure 1). The parabolic SAR is often used to determine the direction of an asset’s momentum and when momentum has a higher-than-normal probability of switching directions.
If the parabolic SAR lies below the current price, the market could be bullish, and if it is above price, the market may be bearish. In this lab, all transactions are placed when price crosses the parabolic SAR calculation. Bullish signals are triggered at the close after price crosses above yesterday’s parabolic SAR value. Bearish signals are triggered at the close after price crosses below yester-day’s parabolic SAR value. (Standard set-tings were used: an acceleration factor of 0.02 with a maximum of 0.20.)
When signals appear, the system enters
credit spreadsby selling an option (a put for bullish signals, a call for bearish ones) at the first strike beyond one standard deviation. The system also buys a same-type option 10
points farther OTM — far enough
out-of-the-money(OTM) to ensure the credit is
suf-ficient. Note: This distance varies depending on the under-lying and current market conditions.
Ideally, credit spreads make money as time passes. If the underlying’s price goes nowhere or moves away from the short strike, the spread’s value will decline toward zero as
the likelihood of the short strike finishing in-the-money
(ITM) decreases.
Figure 2 shows the potential gains and losses of a November 1030-825 bear call spread entered on Oct. 26, 2009 when the S&P 500 index closed at 1067. The trade will be profitable if the S&P 500 closes below 1130.89 at Nov. 20 expiration.
Trade rules:
Bullish signal
When price crosses above yesterday’s parabolic SAR value, enter a bull put credit spread as follows: 1. Sell five puts at the first strike that is beyond one
standard deviation.
2. Use the first expiration month with 21 or more days remaining.
3. Buy five puts at a strike price 10 points farther OTM.
OPTIONS TRADING SYSTEM LAB
Parabolic SAR
with credit
spreads
FIGURE 1 — PARABOLIC SAR CHART
The parabolic SAR works best during strong trending periods, which developer Welles Wilder estimated occur roughly 30 percent of the time.
Source: MetaStock
A November 1030-825 bear call spread was entered on Oct. 26, 2009 when the market closed at 1067.
Source: OptionVue
FIGURE 2 — BULL PUT SPREAD RISK PROFILE
Exit: Let the spread expire worthless unless a bearish trade is triggered.
Bearish signal
When price crosses below yester-day’s parabolic SAR value, enter a bear call credit spread as follows: 1. Sell five calls at the first strike that is beyond one standard deviation.
2. Use the first expiration month with 21 or more days remaining, 3. Buy five puts at a strike price 10
points further OTM.
Exit: Exit if underlying touches the short option’s strike. Otherwise, allow the credit spread to expire worthless.
Starting capital: $10,000.
Execution:All entries occur at the close when price
cross-es ycross-esterday’s parabolic SAR value. The system may hold both bullish and bearish positions at the same time. However, duplicate signals are ignored until a position clos-es.
Option trades were executed at the average of the bid and ask prices at the daily close, if available; otherwise, theoret-ical prices were used. The standard deviation was calculat-ed with a probability calculator using the implied volatility
(IV) of the at-the-money call in the relevant month. Each spread held five contracts per “leg.” Commissions were $5 per trade plus $1 per option ($20 per spread). No commis-sions were included when a spread expired worthless.
Test data: The system was tested using options on the
S&P 500 index (SPX).
Test period: Jan. 12, 2004 to Nov. 20,
2009.
Test results: Figure 3 shows the
per-formance of the system, which gained $13,250 (133 percent) in six years, a 22.6-percent annual return. In the test’s first four years, the strategy had a winning percent-age of 93 percent. But in the final 18
months, the winning percentage dropped to 70 percent, reducing the overall win rate to 85 percent.
— Steve Lentz and Jim Graham of OptionVue The parabolic SAR system gained 133 percent since January 2004.
Source: OptionVue
FIGURE 3 — SYSTEM PERFORMANCE
Initial capital: $10,000 Net gain: $13,250 Percentage return: 133% Annualized return: 22.6% No. of trades: 82 Winning/losing trades: 70/12 Win/loss: 85% Avg. trade: $161.59
Largest winning trade: $1,580.00 Largest losing trade: -$2,340.00
Avg. profit (winners): 447.93
Avg. loss (losers): -1,508.75
Avg. hold time (winners): 36
Avg. hold time (losers): 19
Max consec. win/loss: 29/2
Option System Analysis strategies are tested using OptionVue’s BackTrader module (unless otherwise noted).
If you have a trading idea or strategy that you’d like to see tested, please send the trad-ing and money-management rules to
STRATEGY SUMMARY
LEGEND:
Net gain — Gain at end of test period.
Percentage return — Gain or loss on a percentage basis.
Annualized return — Gain or loss on a annualized percentage basis. No. of trades — Number of trades generated by the system.
Winning/losing trades — Number of winners and losers generated by the system. Win/loss — The percentage of trades that were profitable.
Avg. trade — The average profit for all trades.
Largest winning trade — Biggest individual profit generated by the system. Largest losing trade — Biggest individual loss generated by the system. Avg. profit (winners) — The average profit for winning trades.
Avg. loss (losers) — The average loss for losing trades.
Avg. hold time (winners) — The average holding period for winning trades (in days). Avg. hold time (losers) — The average holding period for losing trades (in days). Max consec. win/loss — The maximum number of consecutive winning and losing trades.
December 2009 • CURRENCY TRADER 19
MONTH
Legend
CPI: Consumer price index ECI: Employment cost index FDD (first delivery day): The first day on which delivery of a commodity in fulfillment of a futures contract can take place.
FND (first notice day): Also known as first intent day, this is the first day a clearing-house can give notice to a buyer of a futures contract that it intends to deliver a commodity in fulfillment of a futures contract. The clearing-house also informs the seller. FOMC: Federal Open Market Committee
GDP: Gross domestic product
ISM: Institute for supply man-agement
LTD (last trading day): The first day a contract may trade or be closed out before the delivery of the underlying asset may occur. PPI: Producer price index Quadruple witching Friday: A day where equity options, equity futures, index options, and index futures all expire.
December
1
FDD: December crude oil, natural gas, gold, silver, copper, aluminum, platinum, and palladium futures (NYMEX); December corn, wheat, soybean products, oats, and T-bonds futures (CME); December coffee, cocoa, and cotton futures (ICE)U.S.:Weekly weather report
2
FND: December heating oil, RBOBgasoline, and propane futures (NYMEX)
U.S.:Petroleum status report
3
U.S.: Natural gas storage report4
FDD: December propane futures (NYMEX)LTD: December live cattle options (CME); January cocoa and U.S. dollar index options (ICE); December currency options
5
6
7
FND:December live cattle futures (CME)LTD:January sugar options (ICE)
8
FDD: December heating oil and RBOBgasoline futures (NYMEX)
LTD: December cotton futures (ICE)
U.S.: Weekly weather report
9
U.S.:Petroleum status report10
FDD:December live cattle futures(CME)
U.S.: Crop production, world agricultural production, and natural gas storage report
11
LTD: January coffee options (ICE)12
13
14
LTD: December corn, wheat, soybean products, and oats futures (CME); December U.S. dollar index (ICE); December currency futures15
FND: December U.S. dollar indexfutures (ICE)
LTD: December cocoa futures (ICE)
U.S.: Weekly weather report
16
FDD: December U.S. dollar index(ICE); December currency futures
LTD: January crude oil and platinum options (NYMEX)
U.S.:Petroleum status report
17
U.S.:Natural gas storage report18
LTD:December coffee futures (ICE);December single stock futures (OC); December index futures; January orange juice and cotton options (ICE); December index and equity options
U.S.: Cattle on feed
19
20
21
FND: January crude oil futures (NYMEX)LTD: January crude oil futures (NYMEX); December T-bonds futures (CME)
22
LTD: January sugar futures (ICE)U.S.:Weekly weather report
23
FND: January sugar futures (ICE)U.S.:Petroleum status report
24
LTD: January soybeans, soybeanproducts, and rough rice options (CME)
U.S.:Natural gas storage report
25
26
27
28
LTD: January natural gas, heating oil, RBOB gasoline, gold, silver, copper, and aluminum options (NYMEX)29
LTD: January natural gas futures(NYMEX); December gold, silver, copper, aluminum, platinum, and palladium futures (CME)
U.S.:Weekly weather report
30
FND:January natural gas futures(NYMEX)
U.S.: Agricultural prices and petroleum status report
31
FND: January gold, silver, copper, aluminum, platinum, and palladium futures (NYMEX); January soybeans, soybean products, and rough rice futures (CME)LTD:January heating oil, RBOB gasoline, and propane futures
(NYMEX); December live cattle futures (CME)
U.S.:Natural gas storage report
January
1
FDD: January crude oil and natural gas futures (NYMEX); January sugar futures (ICE)2
3
4
FND: January orange juice futures(ICE)
FDD: January gold, silver, copper, platinum, and palladium futures (NYMEX); January soybean, soybean products, and rough rice futures (CME)
5
FND:January heating oil and RBOBgasoline futures (NYMEX)
6
U.S.:Petroleum status report7
U.S.:Natural gas storage report8
LTD: January orange juice futures(ICE); February coffee and U.S. dollar index options (ICE); January currency options
DECEMBER/JANUARY
FUTURES & OPTIONS CALENDAR
The information on this page is subject to change. Futures &
Options Trader is not responsible
for the accuracy of calendar dates beyond press time.
JANUARY 2010 27 28 29 30 31 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1 2 3 4 5 6 DECEMBER 2009 29 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1 2
Fidelity Investments (www.fidelity.com) has launched a new online stock research center to help investors identify trading and investment ideas by deliver-ing independent expert insights about emergdeliver-ing opportuni-ties, popular stock screening strategies, stocks most fre-quently bought and sold online by Fidelity customers, and emerging topics on the Web. These new enhancements, combined with Fidelity’s current research offering, allow customers to understand what is happening in real-time across a wide variety of sources, including some top finan-cial blogs. The research center can be used to find emerging trends and opportunities among the most active stocks in the market; set predefined expert stock screening criteria that customers can fine-tune, save, and use; read expert analysis; track financial events such as earnings and splits; track upgrades and downgrades; and search for investment topics on the Web. The stock research center is available to all investors while expanded lists and intraday trading data are available only to Fidelity customers. Fidelity offers access to premium content on a subscription basis, and will be adding additional providers on an ongoing basis.
CQG, the order execution, charting, and analytics
provider for global electronically traded futures markets, has expanded its direct market access to include the Australian Securities Exchange (ASX), an operator of elec-tricity and natural gas futures and options markets in Australia and New Zealand. CQG customers will have access to trade ASX’s Australian feed barley, Australian sorghum, Australian milling wheat, and western Australian wheat contracts and the Mini S&P/ASX 50, 200, and 200 Property Trust indexes. These contracts are available on both the CQG Trader and CQG Integrated Client advanced trading platforms.
In addition, CQG has launched a Certified API Partner Program. CQG API Partner Certification provides program-mers, developers, and vendors the opportunity to become Certified API Partners with CQG. CQG certification indi-cates the partner has demonstrated expertise in working with either the CQG Data API or the CQG Trading API. Certified CQG API Partners will enjoy a host of benefits including joint marketing exposure, discounts on CQG sys-tems, membership in a private social network, and access to Level III support and CQG developers. For more informa-tion, visit www.cqg.com.
Futures Truth Magazine and Chicago-based
Trader Kingdomhave partnered, sharing viable content
such as access to Webinars, articles, newsletters, podcasts, and blogs to enhance subscriber experiences. Futures Truth Magazine subscribers are now able to access Trader Kingdom Webinars from the Futures Truth Web site (www.futurestruth.com). Systems trading experts now have greater reach to present strategies to education
seek-ers. Trader Kingdom (www.traderkingdom.com) is an
interactive trading tool; traders of all abilities are welcome to access the site with a valid email address. Visitors find valuable information, endorsed by major exchanges, and presented by veteran educators. Articles, research reports, podcasts, live and archived Webinars, newsletters, blogs, RSS news feeds, and special offers are regularly updated.
Trading software provider NinjaTrader has
announced a partnership with Steve Nison’s
Candlecharts.com. Nison has selected NinjaTrader (www.ninjatrader.com) as his preferred trading platform for the Nison Candle Scanner (NCS). The scanner allows traders to use NinjaTrader to uncover candlestick patterns in real time in any market. NCS users can apply Nison’s custom candlestick filter conditions in NinjaTrader’s pow-erful Market Analyzer. NCS provides updated condition alerts to traders in real time to identify intraday and daily trade setups. NinjaTrader makes it easy for traders to react quickly to these trade setups through its SuperDOM and chart-based order execution features. The orders can be sub-mitted to NinjaTrader’s worldwide network of supporting brokerages for futures, forex, and equities markets.
TopCommodityBrokers.com— an interactive
com-modity/futures broker directory and educational and social networking Web site — is now up and running. This Web site gives commodity brokers the ability to upload a profile photo and video, include a professional bio, connect instantly with potential clients via Skype, link to their com-pany Web site and external blog, add detailed information about their organization, services and specialties, upload their company logo, and allow potential clients and fellow brokers to follow them on Twitter and Facebook. Registered companies will be listed within the Top Commodity Brokers searchable database. TopCommodityBrokers.com is targeted to commodity brokers as well as investors. The site also has a Community Blogosphere with a variety of topics including interviews with commodity brokers, broker com-missions, commodity broker trade shows, career classifieds, and weekly commentaries.
United-ICAP — a leader in technical analysis-based
price risk assessment for institutional hedgers and profes-sional energy traders — has launched new product
offer-ings and a revamped Web site (www.united-icap.com). The
new site offers a suite of customizable tools and technical analysis including daily, weekly, and monthly reports and emails, larger in-depth topical reports, live daily and week-ly Webcasts, and full anaweek-lyst support to discuss any of the report contents, investment ideas, or methodologies.
Note: The New Products and Services section is a forum for industry businesses to announce new products and upgrades. Listings are adapted from press releases and are not endorsements or recommendations from the Active Trader Magazine Group. E-mail press releases to [email protected]. Publication is not guaranteed.
FUTURES & OPTIONS TRADER • December 2009 21
Options Watch: Vanguard value ETF components (as of Nov. 30) Compiled by Tristan Yates
The following table summarizes the expiration months available for the 20 top holdings of the Vanguard Value ETF (VTV). It also shows each stock’s average bid-ask spread for at-the-money (ATM) December options. The information does NOT constitute trade signals. It is intended only to provide a brief synopsis of potential slippage in each option market.
spread as %
Stock of underlying
Stock Ticker price Call Put price
Exxon Mobil Corp. XOM X X X X X X 75.07 0.03 0.03 0.04%
Coca Cola Co. KO X X X X X X 57.20 0.03 0.03 0.05%
Proctor & Gamble Co. PG X X X X X X 62.35 0.03 0.03 0.05%
Chevron Corp. CVX X X X X X X 78.04 0.03 0.05 0.05%
Verizon Communications Inc. VZ X X X X X X 31.46 0.02 0.02 0.06%
Johnson & Johnson JNJ X X X X X X 62.84 0.03 0.05 0.06%
JP Morgan Chase JPM X X X X X X 42.49 0.03 0.03 0.07%
Goldman Sachs Group Inc. GS X X X X X X 169.66 0.10 0.14 0.07%
ConocoPhilips COP X X X X X X 51.77 0.04 0.04 0.07%
AT&T Inc. T X X X X X X 26.94 0.02 0.03 0.08%
Wells Fargo & Co. WFC X X X X X X 28.04 0.02 0.02 0.08%
Intel Corp. INTC X X X X X X 19.20 0.02 0.01 0.08%
Bank of America BAC X X X X X X 15.85 0.01 0.02 0.09%
Merck & Co. MRK X X X X X X X X 36.21 0.04 0.03 0.09%
Pfizer Inc. PFE X X X X X X 18.17 0.02 0.02 0.10%
General Electric Co. GE X X X X X X 16.02 0.02 0.02 0.11%
United Technologies UTX X X X X X X 67.24 0.10 0.09 0.14%
3M Co. MMM X X X X X X 77.44 0.13 0.11 0.15%
Walt Disney Co. DIS X X X X X X 30.22 0.08 0.09 0.27%
Citigroup Inc. C X X X X X X 4.11 0.02 0.01 0.33%
Legend:
Call: Three-day average difference between bid and ask prices for the front-month ATM call. Put: Four-day average difference between bid and ask prices for the front-month ATM put.
Bid-ask spread as % of underlying price: Average difference between bid and ask prices for front-month, ATM call, and put divided by the underlying’s closing price. Dec. Jan. Feb. March April May June July Jan. Jan.
2009 2010 2011 2012 The Commitments of Traders (COT) reportis published
each week by the Commodity Futures Trading Commission (CFTC). The report divides the open posi-tions in futures markets into three categories: commer-cials, non-commercommer-cials, and non-reportable.
Commercial traders, or hedgers, tend to operate in the cash market (e.g., grain merchants and oil companies that either produce or consume the underlying commodity). Non-commercial traders are large speculators (“large specs”) such as commodity trading advisors and hedge funds — professional money managers who do not deal in the underlying cash markets but speculate in futures on a large-scale basis. Many of these traders are trend-fol-lowers. The non-reportable category represents small traders, or the general public.
Figure 1 shows the relationship between commercials and large speculators on Nov. 24. Positive values mean net commercial positions (longs minus shorts) are larger than net speculator holdings, based on their five-year historical relation-ship. Negative values mean large speculators have bigger positions than the commercials.
In November, commercial positions in gold futures (GC) were overwhelming-ly short, a bearish dynamic that has recentoverwhelming-ly intensified. Similar relationships existed in platinum (PL) and palladium (PA) futures. On the other side, com-mercial long positions have outnumbered speculator long holdings in natural gas futures (NG) for several months.
— Compiled by Floyd Upperman
The commercials in November were overwhelmingly short in gold futures (GC).
FIGURE 1 — COT REPORT EXTREMES
For a list of contract names, see “Futures Snapshot.” Source: www.upperman.com
Is gold hot?
The commercials think not
Legend: Figure 1 shows the difference between net
commer-cial and net large spec positions (longs minus shorts) for all 45 futures markets, in descending order. It is calculated by subtract-ing the current net large spec position from the net commercial position and then comparing this value to its five-year range. The formula is:
a1 = (net commercial 5-year high - net commercial current) b1 = (net commercial 5-year high - net commercial 5-year low) c1 = ((b1 - a1)/ b1 ) * 100
a2 = (net large spec 5-year high - net large spec current) b2 = (net large spec 5-year high - net large spec 5-year low) c2 = ((b2 - a2)/ b2 ) * 100
x = (c1 - c2)
Option contracts traded
FUTURES & OPTIONS WATCH
Legend
Volume: 30-day average daily volume, in thou-sands (unless otherwise indicated).
OI: Open interest, in thousands (unless other-wise indicated).
10-day move: The percentage price move from the close 10 days ago to today’s close. 20-day move: The percentage price move from the close 20 days ago to today’s close. 60-day move: The percentage price move from the close 60 days ago to today’s close. The “rank” fields for each time window
(10-day moves, 20-(10-day moves, etc.) show the per-centile rank of the most recent move to a certain number of the previous moves of the same size and in the same direction. For example, the rank for 10-day move shows how the most recent 10-day move compares to the past twen-ty 10-day moves; for the 20-day move, the rank field shows how the most recent 20-day move compares to the past sixty 20-day moves; for the 60-day move, the rank field shows how the most recent 60-day move compares to the past one-hundred-twenty 60-day moves. A reading of 100 percent means the current reading is
larger than all the past readings, while a read-ing of 0 percent means the current readread-ing is smaller than the previous readings. These fig-ures provide perspective for determining how relatively large or small the most recent price move is compared to past price moves. Volatility ratio/rank: The ratio is the short-term volatility (10-day standard deviation of prices) divided by the long-term volatility (100-day stan-dard deviation of prices). The rank is the per-centile rank of the volatility ratio over the past 60 days.
This information is for educational purposes only. Futures & Options Trader provides this data in good faith, but it cannot guarantee its accuracy or timeliness. Futures & Options
Trader assumes no responsibility for the use of this information. Futures & Options Trader does not recommend buying or selling any market, nor does it solicit orders to buy
FUTURES SNAPSHOT
(as of Nov. 27)
The following table summarizes the most actively traded U.S. futures contracts. The information does NOT constitute trade signals. It is intended only to provide a brief synopsis of each market’s liquidity, direction, and levels of momentum and volatility. See the legend for explanations of the dif-ferent fields. Volume figures are for the most active contract month in a particular market and may not reflect total volume for all contract months.
Note: Average volume and open-interest data includes both pit and side-by-side electronic contracts (where applicable). Price activity for CME futures is based on pit-traded contracts.
10-day move/ 20-day move/ 60-day move/ Volatility
Market Symbol Exchange Volume OI rank rank rank ratio/rank
E-Mini S&P 500 ES CME 2.02 M 2.49 M -0.18% / 0% 5.47% / 89% 8.76% / 32% .17 / 24%
10-yr. T-note TY CME 863.5 1.20 M 2.31% / 100% 3.24% / 100% 2.55% / 85% .49 / 95%
5-yr. T-note FV CME 436.9 756.3 1.53% / 100% 2.43% / 94% 0.87% / 40% .41 / 73%
Crude oil CL CME 341.2 288.9 -0.39% / 0% -1.23% / 22% 11.90% / 32% .23 / 23%
E-Mini Nasdaq 100 NQ CME 310.4 323.5 -1.62% / 29% 5.63% / 86% 9.68% / 23% .23 / 58%
Eurodollar* ED CME 276.4 841.7 0.22% / 35% 0.53% / 84% 0.65% / 55% .18 / 10%
30-yr. T-bond US CME 268.8 690.8 4.03% / 100% 4.09% / 97% 1.66% / 34% .55 / 88%
Eurocurrency EC CME 262.1 166.4 0.65% / 36% 0.78% / 12% 4.82% / 52% .24 / 32%
2-yr. T-note TU CME 259.1 938.4 0.11% / 35% 0.86% / 93% 0.11% / 37% .33 / 50%
Gold 100 oz. GC CME 158.4 296.2 6.11% / 71% 12.14% / 97% 20.00% / 93% .29 / 33%
Mini Dow YM CME 152.3 64.6 0.49% / 7% 6.50% / 98% 9.29% / 40% .13 / 8%
E-Mini Russell 2000 TF CME 146.0 387.7 -2.00% / 25% 2.12% / 24% 1.04% / 6% .35 / 82%
Corn C CME 142.3 397.8 1.74% / 23% 4.69% / 30% 24.44% / 92% .25 / 43%
British pound BP CME 127.3 97.7 -0.46% / 40% -0.32% / 4% 1.31% / 17% .43 / 52%
Natural gas NG CME 113.1 115.2 18.21% / 80% 2.91% / 11% 90.32% / 98% .45 / 62%
Japanese yen JY CME 94.0 118.2 4.06% / 100% 5.44% / 100% 6.19% / 89% .40 / 82%
Australian dollar AD CME 93.6 113.9 -1.59% / 50% -0.93% / 100% 8.38% / 26% .20 / 43%
Soybeans S CME 91.9 194.4 6.36% / 64% 6.86% / 58% 10.73% / 30% .35 / 72%
Canadian dollar CD CME 76.9 90.2 -0.74% / 11% 0.33% / 5% 4.07% / 30% .31 / 47%
Swiss franc SF CME 55.4 53.1 0.92% / 30% 1.10% / 30% 5.33% / 64% .25 / 43%
Wheat W CME 51.2 128.9 3.20% / 8% 8.94% / 54% 12.97% / 80% .35 / 52%
Sugar SB ICE 43.9 361.1 0.35% / 25% -0.18% / 7% -3.84% / 40% .20 / 23%
Silver 5,000 oz. SI CME 39.9 73.0 6.01% / 38% 9.89% / 58% 19.11% / 57% .20 / 13%
E-Mini S&P MidCap 400 ME CME 38.8 107.2 -2.35% / 30% 3.56% / 64% 4.50% / 11% .29 / 67%
Heating oil HO CME 36.7 49.2 -0.20% / 6% -2.14% / 17% 13.10% / 38% .26 / 50%
RBOB gasoline RB CME 35.8 49.6 0.52% / 57% -1.70% / 12% 7.44% / 35% .21 / 13%
Soybean oil BO CME 35.2 77.4 4.51% / 47% 6.88% / 61% 16.91% / 92% .24 / 30%
Soybean meal SM CME 28.4 55.6 8.47% / 73% 10.57% / 93% 8.72% / 32% .31 / 78%
Copper HG CME 26.7 68.6 4.95% / 46% 2.11% / 17% 9.47% / 22% .23 / 68%
Mexican peso MP CME 23.8 84.0 2.08% / 54% 1.11% / 28% 5.39% / 82% .36 / 12%
S&P 500 index SP CME 19.4 387.8 -0.17% / 0% 5.47% / 87% 7.46% / 20% .17 / 24%
U.S. dollar index DX ICE 15.8 36.0 -0.51% / 17% -1.88% / 75% -4.00% / 42% .24 / 38%
Live cattle LC CME 14.5 65.8 0.42% / 17% -3.56% / 61% -4.12% / 71% .23 / 13%
Lean hogs LH CME 13.3 53.0 8.40% / 92% 3.19% / 13% 20.89% / 71% .31 / 88%
Coffee KC ICE 12.5 59.4 5.30% / 80% 1.88% / 9% 14.28% / 84% .14 / 0%
Crude oil e-miNY QM CME 11.2 5.2 -0.39% / 0% -1.23% / 21% 11.81% / 34% .23 / 27%
Mini-sized gold YG CME 9.6 5.1 6.59% / 82% 12.33% / 97% 20.05% / 93% .29 / 30%
Nikkei 225 index NK CME 9.3 31.6 -5.73% / 94% -8.26% / 98% -10.00% / 88% .55 / 87%
Cocoa CC ICE 8.2 50.5 6.48% / 83% -0.76% / 14% 11.94% / 24% .40 / 82%
Fed Funds** FF CME 6.9 50.0 0.04% / 0% 0.19% / 73% 0.28% / 46% .07 / 13%
New Zealand dollar NE CME 5.6 22.6 -3.13% / 62% -3.45% / 92% 5.20% / 3% .32 / 90%
E-Mini eurocurrency ZE CME 3.5 2.5 0.45% / 33% 1.59% / 47% 4.55% / 46% .24 / 28%
Natural gas e-miNY QG CME 3.4 4.0 18.21% / 83% 2.91% / 11% 90.32% / 98% .43 / 60%
Nasdaq 100 ND CME 2.3 20.7 -1.62% / 29% 5.63% / 86% 9.68% / 23% .24 / 60%
Mini-sized silver YI CME 2.3 2.4 6.33% / 38% 9.77% / 57% 19.03% / 56% .20 / 14%
Feeder cattle FC CME 1.1 7.5 -0.48% / 8% -2.22% / 39% -6.19% / 46% .14 / 0%
Dow Jones Ind. Avg. DJ CME 0.7 14.4 1.01% / 7% 3.93% / 80% 10.94% / 60% .12 / 8%
