Volatility-Based Positioning and Trade Diversification
November 23, 2018 / Ole Urfels
Diversification is one of investors’ most important and well-known concerns. However, for traders, the basic notion of diversification (holding a portfolio of uncorrelated positions) is not suitable for most cases. Still, there are many other lesser-known ways to diversify that traders can employ. For example, traders focusing on only one security can diversify by trading systems to achieve a stable average return across all these strategies. Similarly, traders utilizing only one strategy should diversify across multiple markets. Although the former approach is certainly worth discussing, this article will focus on the latter approach as applied by the Turtle Traders and how they achieved diversification over markets, how their approach can be generalized to benefit a broader base of traders and, finally, which types of traders may benefit from the described method.
The Turtles were a group of traders trained by and working for Richard Dennis, starting around 1983, that traded using a rule-based system primarily in the futures markets. These traders, without specific prior knowledge and training, reaped enormous profits. Their approach normalized the dollar volatility of a position by adjusting the position size based on market volatility. This resulted in a similar dollar volatility across all traded markets so that a typical move in any of the traded markets resulted in the same dollar return. To determine their position size, the Turtles used Equation 1 below. One unit was their initial position in the trade and their stop was placed at two times the 20-day Average True Range (ATR(20)).
The terms and implications of Equation 1can be understood as follows. One percent of the account size is the risk measure used for position sizing. The ATR(20) is the average of the true ranges over the past 20 days, where the true range is the highest of the following: the current high less the current low, the absolute value of the current high less the previous close, and the absolute value of the current low less the previous close. This definition of “daily range” takes the common occurrence of a gap (price jump) at the market opening into account. In theory, the ATR is similar to a Moving Average. However, the difference is that a Moving Average considers a single value path while the ATR considers a range path from which the trader is estimating the current volatility. To manage trade risk, the Turtles used a stop of two times the ATR(20), which coincides with 2% of their account size.
Following this, as long as each market behaved relatively constant in its volatility, the Turtles could trade their strategy in markets with different volatilities while expecting similar dollar returns from each market. This meant they were able to diversify over many markets and did not have to fear being overexposed to one particular market on an absolute dollar basis. This procedure made sure that winners in one market would offset losers in another
Equation 1. Turtles’ position size.
For less rule-based and more discretionary traders, similar position sizing models can be derived by utilizing the general idea behind the Turtles’ approach. This will be referred to as discretionary position sizing (DPS), where the position sizing methodology is arbitrary compared to the standard Turtles’ approach. Firstly, traders need to determine the account risk they are willing to put up for each trade. This will commonly be between 0.5% and 3% of account size. Secondly, traders need to measure the trade risk, that is, the dollar value of the protective stop which defines the maximum amount that can be lost during the trade. Thirdly, traders divide the account risk by the trade risk to arrive at the position size. The following are such formulae for stock and forex trades:
Equation 2. Stocks position size.
Equation 3. Forex position size.
(1: The unit of the pip value (lot, mini lot, micro lot) will determine the unit of Amount of Lots.)
The DPS approach also leads to a volatility-based position sizing and thus strategy diversification over markets. The premise lies in the assumption that protective stops are placed at significant levels like swing highs or swing lows indicating former short-term volatility. In low volatility markets, these significant levels will be closer together than in high volatility markets, when measured in points. Although these characteristics are generally true, two inherent issues need to be mentioned.
First, in very low volatility environments, the position size could easily build up to a great amount of the account equity. Since the protective stop still represents the account risk (e.g. 1%) this should not be of too much concern. However, a multi-position strategy would not be tradeable with this approach, because one position can already occupy all free margin. Thus, traders need to adjust these measures to fit their strategy.
The second inherent problem, trading highly priced securities, further illustrates the issue. Imagine a trader that is willing to risk $1000 wants to buy a stock trading at $100. The stop is placed at $98 leading to a $2 stop-value. From Equation 2 given above, the trader should buy (1000$ / $2) 500 shares resulting in an overall stop-value of $1000. However, 500 shares will cost ($100 * 500) $50,000. Assuming a risk factor of 1% the account size of the trader is ($1000 / 0.01) $100,000. This means one position takes up 50% of the trader’s account. A share trading at $300 with a stop-value of $2 could not be traded ($300 * 500 = 150,000), and the system breaks down in the same way as with some very low volatility markets.
To summarize so far, in an environment with decent volatility, a volatility-based position-sizing approach will give traders good diversification opportunities across different markets. This will lead to better performance because all markets can now be viewed as a diversified portfolio of a single strategy. Most important, each trade has the same dollar-effect in each market. However, traders need to be wary of special market situations like low volatility and highly priced securities, where the approach needs to be adjusted to fit the trading strategy.
Given these points, the method works best to minimize volatility and losses for traders that are looking to enter short-term positions and do not manage a full, active portfolio. Every single position entered can be seen as 1% punt (assuming the stop-loss is at 1% from the above example). This activity clearly defines the worst-case number of times one can enter the market before going bust and functions as a rough way of risk management. For example, with a 1% account risk, a 90% drawdown would result after a whopping 229 failed trades in a row.
In addition, the DPS method works especially well for contra traders. These traders have no real capital and thus have to measure their risk very closely since they are only given a limited credit capacity for a limited time period. Thus, with no delivery and full leverage, the strategy’s strong risk management is most favorable since in contra trading there is no concept of “paper losses” after servicing the profit/loss balance.
In conclusion, diversification is not only a key to long-term investment, but it is also important and applicable to short-term trading. When using a single strategy, traders should diversify their system across multiple markets. The Turtles used a very rule-based approach, utilizing the 20-day-ATR as a volatility measure to normalize their dollar return in different markets while at the same time only risking 2% of their account size on each trade. This approach can be generalized for less rule-based trading, by determining short-term volatility through significant price levels that are commonly used as protective stop levels, while only risking a fixed percentage of equity per trade. Two caveats arise from this method. First, low volatility environments lead to large trade sizes that can take up all free margin. Second, trading highly priced stocks also result in large position sizes per trade, again taking up free margin. Thus, this method works best for traders that are entering short-term positions and are not considering a full active portfolio suck as contra traders, who are especially concerned with risk management due to their trading style. Altogether, traders can highly benefit from reviewing their position sizing methodology, since it can turn a good but unprofitable strategy into a profitable one.