Commodity Futures Trading Blog

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Many individual and institutional investors search for alternative investment opportunities when there’s a disappointing outlook for U.S. Equity markets.

As financiers try to diversify into different asset sectors, mostly hedge funds, many are turning to managed futures as a solution. But instructional material on this alternative investment vehicle is not yet easy to find.

So here we offer a helpful ( kind of due diligence ) primer on the topic, getting investors started with asking the most relevant questions. The term “managed futures” is about a 30-year-old industry made from pro money managers called “Commodity Trading Advisor” ( CTAs ). CTAs must register with the U.S. Government’s Commodity Futures Trading Commission ( CFTC ) before they can offer themselves to the general public as money managers. CTAs also need to go thru an FBI deep background check, and supply comprehensive notification documents ( and independent audits of finance statements each year ), which the National Futures Association ( NFA ), a self-regulatory watchdog organization reviews.

CTAs often manage their customer’s assets employing an exclusive trading program or a discretionary strategy, which will involve going long or short in futures contracts in areas like metals, grains, equity indexes, soft commodities and foreign currency and U.S bond futures. During the past few years, cash invested in managed futures has more than doubled and will likely keep growing in the approaching years if hedge funds returns flatten and stocks underperform.

A key debate for expanding into managed futures is their potential to lower portfolio risk.

Supporting such a discussion are many educational studies of the results of mixing standard asset groups with alternative investments like managed futures. Dr John Lintner of Harvard University is maybe the most cited for his research in this area. Taken like an alternative investment class alone, the managed futures class has produced comparable returns in the decade before 2005. As an example, between 1993 and 2002, managed futures had a compound average yearly return of 6.9%, while for U.S. Stocks ( based mostly on the SP 500 total return index ) the return was 9.3% and 9.5% for U.S. Treasury bonds ( based mainly on the Lehman Bros long term Treasury bond index ). Re risk-adjusted returns, managed futures had the smaller drawdown ( a term CTAs use to refer to the maximum peak-to-valley drop in a shares ‘ performance history ) among the 3 groups between Jan 1980 and May 2003. In this period managed futures had a -15.7% maximum drawdown while the Nasdaq had one of -75% and the SP 500 stock index had one of -44.7%.

A further advantage of managed futures includes cutting risk thru portfolio diversification by negative relationship between asset groups. As an asset sector, managed futures programs are inversely related with bond certificates and stocks. For instance, during times of inflationary pressure, making an investment in managed futures programs that track the metals markets ( like silver and gold ) or foreign currency futures can supply a valuable hedge to the damage such an environment can have on stocks and bonds. To explain, if bonds and stocks underperform because of rising inflation concerns, some managed futures programs might outperform in these same market conditions. So, mixing managed futures with these other asset groups may get the most out of your allocation of investing capital.

Commodity trading carries risks and is not suitable for all investors. Past performance is not indicative of future results.

 

Notionally Funding a Trading Systems or Managed Futures Account

When an investor looks at the performance of various trading systems or managed futures accounts, one of the most significant statistics is what the required minimum account size is. It makes no sense considering trading systems, or managed futures accounts that have $100,000 minimums if the investor only has $50,000 to invest.

However, it is valuable to know that frequently the investor can start with less than the minimum through notional funding. For example, an investor could notionally fund a managed futures account or trading systems account at the $50,000 level but tell the manager to trade at a nominal $100,000 level. In other words, the account will trade as though there were $100,000 in it, even though there is not. The investor is simply making use of added leverage.

In the previous example, this means that the account will be trading at 2-to-1 leverage. Meaning the investors will have gains and losses at twice the level. Had the investor only put up a third of the nominal amount minimum then he would see gains and losses at 3 times the level and so on.

Why those using Trading Systems or Managed Futures Accounts Might Want to Consider Notional Funding

Notional funding can be an efficient use of capital, because frequently a trading system or managed futures account will not come anywhere close to using all the money in the account. For example, in Hoffman Asset Management’s case we have a margin-to-equity ratio of generally less than 10%. What this means is that for every $100,000 invested, generally speaking, we will be using less than $10,000 at any given time for margin. The remaining $90,000 sits on the sidelines stagnant. Although it is true that interest on those unused funds can be earned, most investor’s feel they could do better investing those funds elsewhere. Often time’s high net worth individuals or institutions will even put NOTHING in their accounts and trade 100% notionally. The question for investors should be “how can I calculate a reasonable notional level to invest at”.

We feel the answer to that question is one that can be computed based on several statistics. Specifically, what is the maximum drawdown expected and what is the maximum margin that might be needed. For example, Hoffman Asset Management (as of this writing) has had a maximum drawdown of about 17% on a $125,000 nominal account size. This means a $21,250 drawdown in cash terms. The maximum margin usage is about 15% on $125,000 or, about $18,750 in cash terms.

To compute a notional investment amount, we suggest that an investor add the maximum expected drawdown and the maximum expected margin usage. This figure would give the investor the absolute minimum they could invest in the account without having a margin call.

In the previous example, if an investor had started on the worst possible day, and had a $21,250 drawdown, and simultaneously had the maximum margin usage of $18,750, he would have needed a $40,000 of cash in the account to fund that $125,000 nominal account size. Once again, some institutions and individuals who are not worried about margin calls may even decide to fund the account with less than that (or zero).

Benefits of Notional Funding to the Trading Systems or Managed Futures Account Investor

This allows for the smaller, but more aggressive investor to participate in the program without needing to tie up the entire amount in cash. This will amplify their gains and losses at the added leverage level they are using. If, for example, the manager made a 30% return with a 17% drawdown, then the investor at 2-to-1 leverage would have experienced 60% gains with a 34% drawdown.

Once again, this is a more aggressive approach, and we recommend this only for investors who fully understand the benefits and risks of notional funding, but for the right investor, this can be a valuable tool to have in his or her arsenal.

Dean HoffmanHoffman Asset Management

Commodity trading carries significant risks and is not suitable for all investors. Past results are not necessarily indicative of future results

TAGS: Managed Futures Accounts, Managed Futures Account, managed futures

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With computers as powerful as they are today, it is easy optimize a trading system to make it look exceptional, but an optimized system is not always a reliable one. Just because a trader can program a computer to have 20/20 hindsight does not mean that the programs future performance will be anything like its past.

The primary problem with optimizing a computer’s past performance is that all markets change. A low-volatility market may become a high-volatility market. A market that is prone to trends may become choppy and directionless, and a market that previously had high leverage can change into a market with low leverage. What tends to happen is that oddly enough, market X will tend to start acting like market Y, and market Y will start to act like market Z. If a trader has thoroughly optimized his system to trade market X, he will be in trouble when it starts to trade like market Y.

This is a common problem with many trading systems, especially stock index trading system that tend to be optimized to only one market. Despite the occasionally impressive looking results of these trading systems, there is a poisonous strain in their mix. Now contrast the previous scenario with one in which the trading systems design works well with almost all the markets, A through Z. In this case it does not matter if market Z starts to act like market Y, or if market A starts to act like market P The markets can change as many times as they please and it will not affect performance because the trading systems design is universally robust and it can deal with nearly ALL the various types of markets. Once again, even if the characteristics of the market reshuffle countless times, the system acts as a Swiss army knife easily dealing with any scenario.

Good trading systems are universally robust. As markets and conditions change, these systems are able to deal with the various types of changing market characteristics.

Commodity trading carries risks and is not suitable for all investors. Past performance is not indicative of future performance.

 

A good future investing platform is without a doubt very important with regard to your good results in futures trading as an active trader along with futures software developer. No matter if you're a novice in futures buying, ... Read the rest of this entry »

A Managed Futures Account is a sort of alternative investment. Unlike a fund, managed futures techniques can take both long and short positions in futures contracts and options on futures contracts in the worldwide commodity, Interest rate, equity, and Forex markets. Managed futures are controlled by a licensed Commodity Trading Advisor, or CTA, who are controlled in the U. S. by the commodities trading Commission and the National Futures Association, or NFA. Some are compensated on a performance charge basis, usually 15% to 30 percent of profits. Other CTAs are compensated by charging a per trade cost whenever the account or fund trades. Most CTAs also charge a management charge each year, customarily between 1% to 2% of the account size. Managed futures accounts include, but aren’t restricted to, commodity pools and commodity funds. MFAs could be traded using any number of techniques, the commonest being trend following. Trend following involves purchasing markets that are making new highs and shorting markets that are making new lows.

Differentiations in trend following managers include duration of trend caught ( short term, medium term, long-term ) as well as definition of trend ( i.e. What is regarded as a new high or new low ) and the cash management / risk handling methodologies.

There are more strategies managed futures advisors use, including fundamental strategies, option writing, pattern recognition, arbitrage, and so on. Nevertheless trend following and adaptations of trend following are the paramount system. For the years 1980 to 2010, managed futures, as measured by the CASAM CISDM CTA Equal Weighted Index, had a compound average yearly return of 14.52%, while for U.S. Stocks ( based mostly on the SP five hundred total return index ) the return was 7.04%. Managed futures have traditionally displayed extraordinarily low correlations to conventional investments ,eg stocks and bonds. Following modern portfolio concept, this shortage of link builds the robustness of the portfolio, reducing portfolio volatility and risk, without major negative impacts on return. This dearth of relationship stems from the proven fact that markets have a tendency to “trend” the best during more erratic periods, and periods in which markets decline are the most uncertain. In reality the CISDM CTA Equal Weighted Index has been up twenty-six out of the 32 times the SP 5 hundred has been down five percent or bigger since 1980.

Commodity trading carries risks and is not suitable for all investors. Past performance is not indicative of future results.

To the new futures trading system developer one of the most exciting things to play with is optimization. Optimization is using the power of the PC to look at each possible sequence of parameters and rules, and then using only those rules and / or parameters that have worked the very best. With enough PC crunching power, it is possible to find futures trading systems that completely predicted the past! We can run number crunching PC’s on automated routines and have them research many billions of bits of info even while we are sleeping. Many traders do this long enough and later “discover” the holy grail of futures trading systems. They hop straight into the markets with their new super predictive procedures only to find they fall apart in real trading!

What happened? they ask. The answer’s that what they created was likely a commodity trading system that was a statistical coincidence (known as a “curve fit”). Curve fitting is where you force a trading system to conform to historic data. The difficulty is that the markets will behave much differently moving forward; therefore, a “perfect” trading system may be rendered worthless. For example, your computer finds the perfect dates historically to have bought and then sold the market. These dates are likely coincidental and have no future value yet sometimes people will base a commodity trading system on them. This is a clear example; nevertheless most curve fits are some complex form of this basic concept.

Let’s look at another flawed example. Presume we wanted to optimize nickels that were most inclined to land on heads. What we could do is flip millions of nickels and only select those that landed on heads. Then, we can take those remaining nickels and flip them again, once more only choosing the ones that land on heads. We could repeat this process repeatedly, every time only choosing those nickels that land on heads. At about that point, we would conclude that we had narrowed down our nickels to only a tiny handful that were optimized to land on heads. We could then go out and wager large gambles with those nickels putting all our cash on heads. We’d quickly make a fortune, right? WRONG!

We would quickly lose our money. Those nickels were not optimized for heads; they always had 50 / 50 odds. What might have confused some is that they thought they’d found predictable nickels. All they found was a probabilistic coincidence!

As there is so much data, and so much computing power available, these sorts of mistakes find their way into commodity trading systems all of the time. When developing a commodity trading system it is vital to avoid optimizing as much as practical. You need to find NON curve-fit, robust trading systems. There can be a place for some sorts of optimizing, but it must be handled in the right way.

Commodity trading carries risks and is not suitable for all investors. Past performance is not indicative of future results.

Originally introduced in 1975, managed futures – hedge funds use futures, forwards, and options to get access to the commodity, currency, interest rate, and equity markets. A futures contract is a contract to buy or sell an asset at a particular price at a later time.

When creating a contract position, a trader must post a performance bond, also known as margin, to cover likely losses on the position. As costs change across the life of a futures contract, the trading accounts where performance bonds are held are debited and credited accordingly. Profits are made when the market or spot cost of a commodity surpasses the futures’ price. Extra returns can be made when traders replenish or roll contracts and the sale cost of the old contract surpasses the price of buying the new contract. Interest earned on margin posted in the trading account also makes a contribution to returns.

In 2008, when US and world instruments dropped 38% and 45 percent, respectively, managed futures were up 14%. Managed futures provided robust, uncorrelated returns to normal asset groups that suffered in this period. Establishments and high value people took note, boosting total investment in managed futures to its current level of over $200 bill in assets under management.

 

Managed futures trading provides a source of liquid return often not linked to other investment classes. This was obviously seen in 2008, when many stockholders thought they’d achieved satisfactory diversification with their investments in long / short equity and event-driven hedge fund secrets, or other possible choices like high-yield debt and real-estate. It seemed of these investments were highly related to Standard & Poor’s five hundred stock index, and financiers found their alternative investments falling in lockstep with their standard investments.

One of the most significant lessons learned during 2008 was that portfolio diversification does not come from the quantity of managers or positions in a portfolio. Diversification comes from building a portfolio of essentially different return streams and managed futures offer various drivers of positive and negative returns.

Managed futures are one of the few alternative investments that have nil or negative link to the equity markets. Since their establishment in the 1970s, managed futures have frequently produced non-correlated returns during periods of stock exchange dislocation. Dr. John Lintner of Harvard Varsity , one of the co-creators of the Capital Asset Pricing Model, first released his seminal work on managed futures in 1983. He concluded that portfolios composed of equity and fixed earnings investments exhibit significantly less variance at each possible level of predicted return when mixed with managed futures. As illustrated in the chart above, Linter’s work remains as current today as it was in 1983. Adding even a bit of managed futures, as represented by the BTOP fifty Index, to a normal portfolio of shares and bonds has offered better returns at lower risk over a twenty year period one which has included Black Monday ( 1987 ), the 1st Gulf War ( 1990 ), long-term Capital Management / Russian debt default ( 1998 ), terrorist attacks on the World Trade Center and Pentagon ( 2001 ), and the up to date liquidity crisis ( starting 2007 ).

Commodity trading carries risks and is not suitable for all investors. Past performance is not indicative of future results.