Trading is about more than just picking a system and trading it. Long-term trading profits require traders to diversify, manage risk and master the mechanics of order entry and technology. In addition, if you treat trading as a business — and you should — there is the issue of taxes, which ultimately can have a significant impact on your profit or loss.
Assume you are trading several systems with a $250,000 account. Position sizing will be based on equalizing trade risk based on volatility. The problem is we might have existing positions that carry a large open profit that we anticipate we’ll give back before trade exit. If we treat that open trade profit as real equity for purposes of trade sizing, we may welcome big losses on unreasonably large trades because of the equity curve giveback of trend-following systems.
This allocation strategy is complex, but software can simplify its application. For example, if we start trading after a given date, we can’t just take each trade of each system and manually sum them. Making this work requires taking only new trades by disallowing those prior to a given date. "Time management" (below) shows some sample code that achieves this.
Click here to download the following code in a Word document.
In this code, we size trades based on average range and big point value. We also add a parameter for a start date. Assume we started trading a channel breakout system on Jan. 2, 2011. We do not allow multiple entries in the same direction; thus, if we take all the trades, we are only testing the first n-day high or n-day low to place the trades. If we just started trading on a given date, we could take a new buy on the third or fourth breakout, which never has been tested. This creates problems because starting our trading on Jan. 2 could lead to secondary entries that have not been tested.
Therefore, the correct way is to trade a system alongside a clone system. The clone takes all signaled trades while the original system takes the real trades allowed after a given date. The clone system is used to filter these real trades as follows:
- If the clone system is long on our start date, we do not allow any
real long trades until the clone system goes flat or short. - If the clone system is short on our start date, we do not allow any
real short trades until the clone system goes flat or long.
Doing this means that we only take the new trades and the first signals that have been tested. This approach is termed "sync technology."
If we do not adopt this approach, then we have one of two options. We have to use simple money management, which can be calculated manually, or we assume the risk of taking secondary untested signals that could lose money.
Sync technology is so important that it has become a standard operating procedure that I generically implement on any system I employ. We also address another issue. Because of money management, we must decide what to do if a trade’s initial signal is skipped and we later decide to allow the trade. This would give us the same secondary signal problem we have when we just started trading. We easily can resolve this by applying the sync technology rules to these trades.
Spreading the risk
Many commodity trading advisor (CTA) programs trade a single trend-following strategy on a basket of markets. This is why the Barclay CTA index produces the number it does, as follows:
From January 1980
Compound Annual Return 11.60%
Sharpe Ratio 0.42
Worst Drawdown 15.66%
Correlation vs. S&P 500 0.01
Correlation vs. U.S. Bonds 0.11
Correlation vs. World Bonds 0.00
This gives us a minimal acceptable return (MAR) of 0.74 and a Sharpe ratio of 0.42. These results don’t look that good, but they are better than the average because of survivorship bias of the index. CTAs that perform badly are removed from the index.
The problem is that all commodities correlate during times of major events, so the correlation risk is greater than implied. To really diversify, you must combine multiple systems of different core logic, such as combining a trending strategy for a commodity basket with an arbitrage system for Treasury bonds or a countertrend stock index approach. Developing multiple system trade plans, in which each system can trade a basket of markets, creates money management strategies that are so complex that a computer is required for implementation. You also might want to allow different allocation units between the systems.
Balance and rebalancing
Let’s compare a system that uses volatility-based money management (dynamic margin) and its trade plan to a second system that automatically exits 50% of any position that reaches 20% of the account value. If only one contract is owned, it will exit the complete position. This can be done with the code shown in "Quick exit" (below).
Click here to download the following code in a Word document.
Here are the results:
Compound Annual Growth Rate
Normal 17.84%
Using Rebalance rules 19.21%Percent Maximum Drawdown
Normal 20.96%
Using Rebalance rules 19.04%Sharpe Ratio
Normal 0.7636
Using Rebalance rules 0.8558MAR
Normal 0.8513
Using Rebalance rules 1.0089
The rebalancing approach can improve the growth rate and lower drawdown. We improved both the Sharpe ratio and MAR significantly by exiting a few trades with these windfall profits. Rebalancing is a good tool for trend-following methodologies, as many times you will give up half of the open position profits on a trade.
This sensible exit approach is one of many that today’s modern trading system analysis tools allow us to test. Other examples include:
a) Stop trading if you lose N% in a given month.
b) Stop trading if you make N% in a given month.
c) Rank market by ADX and only take trades of top trending markets.
d) Rank market by other measures and only take trades of top trending markets.
e) Balance risk on long/short positions; for example, skip trades in times when the majority of signals are on one side of the market.
f) Balance risk by sector.
These ideas are just a starting point for what you can test. ADX filter is a good example of an area ripe for further study. Consider allowing a signal if the market is in the top N, ranked by ADX, and one of the top two ranked active orders of the day. For example, if the maximum number of positions is five, and we have three of these with active entry orders in the top five, we only would allow the top two to get filled.
We also could consider exiting the trades when a market drops out of the top N, where N is maximum number of positions. Research shows that the quality of trades is better and winning percentage can reach 60% or more using this type of ADX screening filter. The problem is this filter tends to reduce overall returns.
Death and taxes
Many traders prefer trading commodities because of the leverage. For most of us, futures have another advantage over stocks, however. Futures also have preferential tax treatment. The taxation of commodities is different from those of stocks in terms of time factor, as shown in "Tax time." As an example, suppose the total gains for a trade are $50,000 (X), the position is held for less than a year and you are in the 35% tax bracket. The results are shown in the second table in "Tax time."
Commodities tax $11,500 ($7,000 + $4,500)
Stock tax $17,500
Commodities savings $6,000
Of course, tax laws are subject to change, and you should consult a qualified accountant or tax adviser to discuss your specific situation. You also need to determine whether a futures contract comes under Section 1256 of the Internal Revenue Code. Section 1256 includes all regulated futures contracts. A regulated futures contract is one traded on a qualified domestic commodities exchange. Regulated futures contracts also can include futures contracts traded on a non-U.S. exchange, but not all futures contracts available for trade that are listed on non-U.S. exchanges are afforded 60-40 tax treatment. These exchanges have to be designated by the U.S. Secretary of the Treasury as a qualified board or exchange.
The bottom line is taxes do affect performance. Further, performance depends on the distribution of returns.
Unless you’re a professional trader, you can’t deduct more than $3,000 in losses per year, so if you have large losses, you can’t write them off. This could reduce performance greatly and even make a winning strategy lose money on a tax-adjusted basis.
Modern trading technology allows us to address real-life issues. These include managing existing trades, distinguishing original signals from secondary signals, money management in concert with multiple-market and trading system portfolios, and taxes. All of these issues are critical to the proper assessment of a complete trading approach.
So much more goes into your ultimate trading success than trading signals. Indeed, the argument can be made that trading signals are the least important element of a trade plan. Today’s tools finally permit us to paint a full picture of potential profits before we risk real money, and that is an edge that has been worth the wait.
Murray A. Ruggiero Jr. is the author of "Cybernetic Trading Strategies" (Wiley). E-mail him at ruggieroassoc@aol.com.
