Diary Of A Professional Trader by Peter Brandt

Updated: May 25, 2021

Peter Brandt is a vastly experienced stock market trader and shares his knowledge in this trading book.


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In this video animation we look at the book - Diary of a Professional Commodity Trader - by Peter Brandt


Peter Brandt is the CEO of Factor LLC, a global trading firm he founded in 1980.

In 2011, Peter was named among the 30 most influential people in the world of finance.

With such vast experience, knowledge and credibility in the financial arena, we look to extract as many nuggets as we can from the book and Peter himself.


There is a clear message throughout this book that separates it from others, many trading books focus on trade identification, whereas Peter focuses on trade management and risk control.

He says;

“Consistently profitable commodity trading is not about discovering some magic way to find profitable trades.”

Peter suggests that the majority think trading is all about trade identification. That is why you’ll see them jump from indicator to indicator, looking for the holy grail system that will lead them to riches.

This is not the way a professional like Peter Brandt operates.

Peter understands that identifying a trade is perhaps only 10% of the process. The other 90% is managing the trade after you enter. And when it comes to management, he knows that the name of the game is risk control.


This clear message continues throughout the book and through Peter’s advice in general.

He say’s;

“Consistently successful trading is founded on solid risk management.”


Let’s look at some of Peter Brandt’s trading stats to see why trade management is so crucial.

Peter’s long-term win rate for individual trades is only around 30%. Which means 70% of the time his trade ends in a loss.

However, he is still able to turn these stats into excellent profits through risk management. The key is that the losses he takes are very small in comparison to the gains he makes on his winners. The mantra of cut your losses and let your winners run is paramount here.


Let us move to our analysis screen and run our Monte Carlo simulator. The simulator here has been developed to determine the likelihood of outcome based on the parameters we enter.

For example, here we have entered the expected win rate of 30%.

Here we have entered an expected win amount per winning trade of $1000 and an expected loss per losing trade of $200. This gives us a 5 to 1 win/loss ratio.

We are stating in this simulation that 365 trades have been placed per cycle.

We now run the simulation 500 times, and the data is presented to us.

We can see here that the green line shows us the highest expected return of $80,000 from 365 trades over 500 simulations and the red line shows us the least amount of expected return of $20,000.


On average, we can determine that a win rate of 30% and a win to loss ratio of 5 to 1, would return $50,000 over 365 trades from risking $200 per trade.

The key point here is that a low win rate can still return healthy profits if winners are allowed to run, only losing positions should be cut short.

To further emphasise Peter’s focus on risk management, we can see here the possible amount of losses in a row that could be seen from this strategy. Imagine if you were risking 3% of your account on each position, after 30 losses in a row you would have lost 90% of your account!

Peter Brandt understands these probabilities and the potential ‘risk of ruin’. He keeps his overall risk low and uses a large sample size for his edge to play out, which will eventually produce those healthy returns.

The 30 trade losing streak could look something like this if the risk is managed correctly. In the bigger picture it is just a blip.


Peter says;

“It is possible to be profitable over time even though the majority of trading events could be losers. “Process” will trump the results of any given trade or series of trades.”

It’s not easy psychologically to have 70% of your trades fail. But Peter is so focused on process.

Discipline to follow the same process each time, from selection and through the trade life cycle is paramount.

He knows that it’s not the next trade, or the next 20 trades, but the entire cycle that needs to play out. His emotions are not only steadied by years of experience, but also by a true understanding of his own strategy.


Peter experienced approximately 235 trades a year. Only 75 of those being profitable.


Only a third of those 75 winning trades will be responsible for the bulk of his profits that year. Most of his winning trades will match the cost of the losers. But the big winners that are allowed to run will significantly improve his profits.


Peter’s understanding of his strategy gives him the ability to continually execute through any market environment.

Strategies work in cycles, as does the market. They go through periods of major gains whilst also experiencing periods of drawdown. The idea is to remain disciplined and execute according to your strategy through these periods. If the strategy has a definitive edge, the net result (in the long run) should be positive, or in Peter’s account, very positive.

Peter says;

“I am constantly studying and analysing my trading performance for two major reasons: to determine if my trading plan is in sync with the markets and to determine if I am in sync with my trading plan.”


How many amateur traders would continue trading a system after a 10-trade losing streak, the answer is not many.


But if we look at our simulator once more, we can see that a system with a 50% win rate has the possibility of hitting many long losing streaks in a row.

Let us assume the full cycle for this strategy is 365 trades and we have a 2 to 1 win/loss ratio.

We can see here that we hit a losing streak of 10 in this cycle.


9 in this cycle.


And 8 in this cycle.

But despite these losing streaks, the overall trend and profitability is very good after completing each full cycle.


But finally let’s look at running 100 simulations of 365 trades, to see how many losing trades in a row were achieved.

We see this time we reached 14 losses in a row with a system that has a 50% win rate.

These simulations reinforce the point Peter makes, if you have found a statistical edge in the market, you must allow for a large sequence of trades to play out before discarding your system after a losing streak.

Losing streaks are inevitable, they must be expected and managed accordingly. Otherwise you may end up like many amateur traders that jump from system to system.


Peter is a chartist and therefore relies on price, but remember a chart is a footprint of where price has been and is not predictive of where price is going. However, a chart can leave clues in regard to placing a trade with the potential of offering a good risk/reward setup.

Peter explains that there’s nothing magical about chart patterns. He says he really has no idea where price is going. Charts are just used to develop a process. To establish targets, define risk, and determine broad direction. Nothing more.


Let’s look at a simple chart pattern that is not predictive but could leave clues as to where a stop loss could be placed in order to offer a limited risk position.

Peter has suggested that he likes the rectangle pattern and has a strong preference towards horizontal support and resistance lines, as shown here.

This example shows price increase and decrease over a period of time which allow for support and resistance lines to be determined, often this pattern indicates an equilibrium between supply and demand. A weekly chart could see such a pattern develop over the course of 10 to perhaps 50+ weeks, within a range of maybe 8-12%.

Often called a breakout, the market may eventually break the resistance and can indicate that the bulls have gained control. Sometimes supported by a large increase in volume.

Now, lets look at the clues the price has left for a potential stop placement.

Maybe here for a 5% loss?.


Or even here at the break point for a tighter stop loss of around 2%?


This is only a hypothetical example and merely demonstrates that price can form a structure, in which there could be a logical reason for placement of a stop loss.

Again, no prediction is being made about future price direction here, its all about managing losses to allow for the winners (when they come) to create a favourable risk/reward ratio in the longer term.


We have so far established that Peter’s philosophy is all about risk management, working with probabilities and using historical price structure to form opportunities for trade entry, as opposed to predicting future price.

But how does Peter suggest we manage a trade once we have entered?

Clearly his exit rule which is of paramount importance is the initial entry stop loss, thereafter it is all about allowing a winning trade to run until the point that the trade either moves against you, or your target price is achieved.

The rules offered in the book are numerous and some perhaps complex but clearly very effective.

A simple rule offered is; Use the same timeframe to manage the trade as you did to enter the trade, therefore if you entered the trade using the weekly chart, don’t try to justify the exit by using the daily or hourly chart.

A more complex rule suggested is the ‘trailing stop rule’, Peter prefers a trailing stop based on price action as opposed to a fixed percentage or dollar amount.

In summary, Peters exit rule here (taken from his book) is based on 3 metrics.