The decision to take control of your financial future by trading the markets is exhilarating and liberating. But there are many decisions left to be made, including market selection and the desired holding period. The single most important decision may be trading style: How the trader will select and execute trades. The two most common methods are discretionary and mechanical, or system-generated.
Many traders struggle with discretionary trading because of its inherent flexibility and subjectivity, which provides too much room for emotion-driven decisions. Conversely, others struggle with using purely mechanical, automated systems because of their rigidity and complexity.
There is a third option that often is overlooked: Probability-based trading. With the widespread adoption of spreadsheet applications such as Excel and the proliferation of reliable, intraday data, traders can avoid many of the pitfalls of discretionary and systematic methodologies, while enjoying the advantages of each. Here, we’ll explore the pros and cons of these two approaches and demonstrate why a hybrid approach built around probability-based execution may be the optimal method for many retail traders.
The discretionary trader
The discretionary trader can make decisions based on fundamentals, technicals or a combination of both. He can make trade decisions based on the interpretation of price charts using indicators and price patterns but does not have hard and fast rules based on price action. This approach is appealing because it provides a sense of control that is attractive to many. Other benefits include:
- Easy to learn the basics
- Freedom and flexibility to adjust each trade as needed
- Appeals to the independent nature of many traders
Though the feeling of control attracts most traders, it is the randomness of success that entraps even the most astute individual. It is widely accepted that the vast majority of self-directed traders use discretionary techniques and that more than 90% of them fail. Many believe that it is because of poor money management. And while true, poor money management is often a byproduct of false expectations regarding the ease and speed of achieving consistent success.
With positive and perhaps naive expectations, the new trader easily confuses winning trades with skill, and losing trades with bad luck. Worse, the laws of probabilities can conspire to paint an extremely misleading picture.
For example, over the course of 50 trades, each with a 50% probability of winning, there is a 95% probability that a streak of at least four consecutive winning trades will occur. Furthermore, there is a 77% probability that a streak of at least five consecutive winning trades will occur. It’s these completely random streaks that confuse and mislead the trader into believing that his method is robust and that it is just a matter of time before he will be buying his first island.
Malcom Gladwell asserts in his book, "Outliers," that one common trait among elite performers in all fields of work is the accumulation of at least 10,000 hours of practice or effort. In trading years, assuming six hours a day and 250 trading days a year, it would take at least seven years to reach this milestone. However, the false confidence gained from random early success distorts expectations — often grossly and irreparably — causing the trader to trade more frequently and aggressively than he should.
Another problem with discretionary trading is a bias toward the most recent activity that overshadows many traders’ memories. This unconscious bias seduces them into trading setups that have perhaps worked well of late, but unknown to them, do not present a well-defined historical edge for all types of markets. With inflated expectations of continued success, the overly optimistic trader trades aggressively and beyond his skill level.
In reality, the path to riches is not easy for the discretionary trader. As the market conditions evolve and meander through varying phases of bullishness and bearishness, the trader’s results often will vary dramatically from feast to famine. All too often, the seductive ebbs and flows of the trader’s account end with total frustration, or worse, a margin call by his broker.
To summarize, the challenges of discretionary trading include:
- Difficult to discern excellence and skill from random results
- Recency bias can distort chart interpretation
- Emotions can interfere with proper execution
- It can take years to achieve consistent profitability
Of course, not all discretionary traders fail. Those who have the capital, confidence and commitment to learn to adapt their techniques to varying market environments ultimately can reap the rewards that most seek, but few attain. And some who do not achieve success will survive long enough to try a different approach: System trading.
The systematic trader
Though discretionary trading is the more common approach of self-directed traders, there is another option. Systematic trading is just as it sounds: Using a programmatic system to create entry and exit signals. The advantages for the trader are many:
- Minimizes emotion-driven mistakes
- Visibility of historical results promotes more realistic expectations regarding trade frequency, win rate, profit expectancy and drawdowns
- Eliminates the baby-sitting of trades
- Appeals to the mathematically and engineering-inclined
However, there are challenges and disadvantages, too:
- Difficult to create robust, profitable systems without extensive market experience
- Requires significant programming skills or expensive outsourcing of these efforts
- Difficult to program for the myriad of unique, real-world scenarios
- Over-optimized systems can set unrealistic expectations and under-perform expectations
- Can be difficult to follow and execute signals when market conditions become volatile
Further, discretionary decisions are not completely eliminated. Ultimately, there are many subjective decisions required to program an entire trading system, including: Selection criteria, entry timing and technique, exit criteria for targets as well as stops, position sizing, etc.
Most systematic traders will allow at least some minor discretion, such as not acting on a signal in front of a report or if volatility spikes. Discretionary traders will look at much of the same technical information as the systematic trader but will weigh all that information before making a decision on a trade, rather than creating rules that generate trade signals based on the information.
The probability trader
So what exactly is a probability-based trader? This is an individual who uses historical data to assist, but not necessarily control, all elements of the trade decision including selection, entry and exit criteria. In essence, it’s a blend of both discretionary and system trading that maximizes the advantages of each, while minimizing the disadvantages of both.
Benefits of probability trading include:
- Compensates for lack of trading experience
- Excellent check and balance for discretionary decisions
- Minimizes emotion
However, all methods have drawbacks, and probability trading is no different:
- Requires years of historical data
- Requires significant spreadsheet or programming skills, or access to third-party data
- Can be difficult to interpret conflicting data
Let’s take a look at a real-world example of a typical trade conducted by the author (a former discretionary trader).
On Jan. 3, 2011, the first day of the New Year, the E-mini S&P 500 futures contract gapped up big (it opened well above the previous day’s closing price) and did not retrace back to its prior day close (it did not fill its gap). By the end of the day, it had closed at a 28-month high (see "Unfilled gap"). The bull market continued to rip to the upside, and shorts were paying the price.
It is a cliché, but one that is followed by many traders, that all gaps are filled. A discretionary trader could act on this impulse and develop a strategy that assumes the market would fill that gap.
Thankfully, the author had not faded this gap due to it showing poor historical results based upon similar price patterns, market conditions and seasonality. Of similar gap setups, only 53% had filled or finished profitable by the end of the day. Based on our research of gaps, the odds of a profitable trade, if targeting gap fill and using a reasonable size stop, were less than 40%."
On the next day, Jan. 4, the ES gapped up again, this time a little over four points, and was poised to open near the prior day’s high. The commentators and guests on the major financial networks were warning everyone to be careful shorting this raging bull market. But unlike the prior day, the historical data suggested otherwise.
Calculations based off of pattern recognition and seasonality indicated an average win rate of 81% when entering at the open, with a five-point stop loss and targeting the prior day’s closing price.
A quick calculation showed excellent profit expectancy ratio based on our 81% confidence (0.81 x 4 points) – (0.19 x 5 points) = +2.3 points. Though the author did not feel good about this setup, the historical data was too compelling to ignore, and a market order was submitted at precisely 9:30 am EST with a five-point stop. The target price was hit 25 minutes later as the gap filled for a fast, easy 4-point profit (see "Filled and profitable").
The point is not that this was a profitable trade, but rather that the decision to enter the trade, as well as the location of the stop and target, all were guided by probabilities based upon historically similar setups.
Another significant advantage of using historical probabilities to guide decision-making is that the data can be used in conjunction with important technical levels and proven discretionary techniques. For example, if the data suggest a five-point stop, and this would place it one or two ticks in front of a key level such as the daily pivot, then the stop can be adjusted slightly in a manner that increases the odds of success without significantly changing the profit expectancy for the trade.
Clearly, there is no right or wrong style for trading the markets — it is a highly personal decision and one that should be tailored for each individual’s personality, trading experience and objectives. The difference between discretionary and systematic is more one of scale than absolutes. However, combining the simplicity and flexibility of discretionary trading with system-generated probabilities can provide the best of both worlds.
Scott Andrews is a private trader and founder of MasterTheGap.com. You can reach him at firstname.lastname@example.org.