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By Jason Pearce

Full Court Press

In a prior post, we discussed the topic of pyramiding.  This is where you take advantage of a winning trade by continually adding more and contracts or shares as a market trends in your favor.  The objective is to increase the size of your winning trades without a substantial increase in the risk on the trade.

First, we discussed an aggressive strategy of adding futures contracts just as soon as the open profits on a trade provide enough financing to do so.

Most traders initially learn about pyramiding this way.  As a matter of fact, I can recall a trading book that I read as a teenager that taught how to turn a $5,000 grubstake into $250,000 by simply following this easy path to “unlimited riches” while working a mere 15-20 minutes a day.

This is the absolute worst possible way to go about it.  It nearly always ends in tears.  The post explains why and shows a vivid example.

Next, a more sensible method was demonstrated.  This pyramiding method relies on the market’s price structure to determine where and when to pyramid a position.  There’s a delicate balance between pursuing profits and managing risks.  If you want to trade like a professional, this is the way to go.

In this post, we are going to touch on a couple of the more lesser-known pyramiding techniques.  These ideas will give you more options to work with.  This allows you to find and customize the pyramiding method that best suits your personal trading style.

Turtles, Pyramids, and Volatility

In full disclosure, what I know about Richard Dennis’ famous group of Turtles is only second-hand and third-hand knowledge.  When the Turtles were busy building their trading fortunes in the early 80s, I was busy doing my schoolwork, riding a BMX bike, and listening to my Def Leppard and Van Halen cassette tapes.

That being said, several of Dennis’ protégés have shared the secret sauce of the trading system that he taught them.  I feel like there’s enough information out there now that I can relay and comment on it.

The Turtles used volatility to determine their position sizes.  More fitting to out topic of discussion, they also used volatility to determine where they would add to their positions (i.e. pyramid).

They measured market volatility via the Average True Range (ATR), which is a tool that many professional traders still utilize today.  Specifically, they used the 20-day exponential moving average of the True Range as their volatility yardstick.

Once the Turtles bought a market on a breakout above a 20 or 55-day high, they would place their initial protective stops and then place order to buy more contracts at progressively higher prices.  These pyramid orders were designed to ramp the position size up as quickly as possible.

The 20-day ATR that they measured volatility with was referred to as “N”.  To pyramid, the Turtles would add to their long positions in intervals of ½ N higher as the market moved up.  So if the 20-day ATR of a particular market is 160 points, then ½ N is 80 points.

Importantly, the intervals were based on the actual fill prices.  So they would buy another round of contracts 80 points (½ N) higher than the last fill price.

The amount of entry points that a Turtle could take on one particular market was limited to four.  So after the initial breakout purchase was made (entry point #1), the position could be pyramided up to three more times at entry points #2, #3, and #4.

The protective sell stop for the contracts bought on the initial breakout was set at 2N below the entry price.  Also, the protective sell stop for each pyramided position was set at 2N below the entry price.  The thinking behind this is that the stop would be out of the way of random market swings since it’s double the average volatility of the last one month of trading (there’s typically twenty trading days in one month).

For example, if the 20-day ATR of a particular market is 160 points, then 2N is 320 points.  So the initial protective sell stop was place 320 points (2N) below the entry fill price.

Most of the time, when a new entry point was made, the protective sell stops on all units were raised to 2N below the most recent entry price as well.  The Turtles had a couple alternatives to this, but this was the standard method they used.

So there you have it: the pyramiding technique used by one of most famous and profitable trading group in the world.

Turtle Troubles

Before you take this Turtle pyramiding idea and apply it to your trading, there are a couple of potential drawbacks you should take into account.

First, recognize that the risk on the trade actually increases as more contracts are added.  Risk does not stay static or decrease the way that it does with the methodology we discussed in the prior post on using price structure to pyramid.

Suppose the 20-day ATR for gold is $13.00 and you went long a single 100/oz. futures contract at $1,240.00.  With the Turtle method, the initial protective sell stop would be set 2N or $26.00 below the entry price at $1,214.00.  This sets the initial risk at $2,600 on the trade.

If gold rallies ½ N higher ($6.50) you would purchase a second contract at $1,246.50.  The initial protective sell stop for this first pyramided contract would be set 2N ($26.00) below the entry price at $1,220.50.  Additionally, the protective sell stop for the initial purchase would also be raised to $1,220.50.

Here’s the rub: The risk on the pyramided contract is initially $2,600.  The risk on the initial contract, although reduced, is still $1,950.  So the total risk on the trade has now increased to $4,550.

Once you’ve extrapolated this out to the Turtle’s maximum position size of four entry points on the trade (the initial entry and three more pyramided entries), the total trade risk has jumped to $6,500.

That’s two and a half times the initial risk on the trade.

See the problem here?

Like I said, this is a potential drawback.  It doesn’t have to definitely be one.

If you know beforehand that the trade risk will increase as the pyramid is built, you could elect to initiate the trade with just a fraction of your maximum risk-per-trade.  Then as more contracts are added via the pyramid rules, your trade risk gets closer to your maximum risk-per-trade levels and finally reaches it when the last entry point is triggered.

In other words, you put a toe in the water and build up to your targeted maximum risk-per-trade as the market proves itself.  There’s certainly nothing wrong with a strategy of scaling into a position.  Many smart and successful traders do this.

A second potential drawback to this strategy is that the initial entry order and all three of the pyramid buy orders can get elected and filled all on the same day.

Worse yet, they could all be entered and then liquidated on the very same day!

If you’ve been trading for even a short length of time, you may have seen or even been caught in one of those “long bar” market spikes on the charts where prices rocket higher.  These sorts of moves happen on the downside as well.

As a matter of fact, the downside spikes seem to be more severe.  Anyone remember the Flash Crash?

One way you could offset this risk is to modify the pyramiding rules and limit it to one entry point per session.  That way, you will never be full loaded and then knocked right back out all in one fell swoop.

However, there is a potential downside to implementing a time limit rule like this.  If a market spike happens to be the start of a parabolic runaway move, you could miss significant chunks of the move and/or not get all the contracts you want.

There’s a tradeoff with everything in life, though.  You have to determine what is best for your own emotional makeup and capital risk.

Climbing Ladders

Now I’m going to show you a different twist on how to pyramid by incorporating both price structure and volatility.  I call this strategy a price interval ladder.  This is a method I’ve used many times, particularly with spread trade positions where I only track the closing prices, to build small positions into large positions.

You need to know up front that this pyramiding strategy is not something that I feel is compatible with a day trading or swing trading system.  (Why in the world are you day trading anyway?!)  This strategy is to be used in a campaign trade where you want to ride the trend for as long and as far as it will carry you.

In a nutshell, price interval ladders are evenly-spaced price points that are set in a market where contracts will be entered at progressively higher levels as the market advances.  Think of it as climbing a ladder and each higher price point interval is like a rung on that ladder.

The same set points of these price intervals are also where the protective sell stop levels will be trailed “up the ladder” until the market finally reverses trend and all contracts are liquidated.

Although the price interval ladders are based on price structure, it’s a different application than where we discussed trailing protective stops and adding after the market reactions against the trend.

Instead, we will measure the sizes of the countertrend moves in a trend.  Then the entry and exit points are set in price intervals that are larger than the size of the preceding countertrend moves.

The objective in spacing the intervals is to make them wide enough to be able to withstand any countertrend moves that are similar in size to what has already been occurring.

High-Tech Ladder

Let’s look at the NASDAQ 100 futures contract for an example of how a price interval ladder could have been applied during this run over the last few months.

In September and October of 2016, the NASDAQ 100 futures market prodded and poked at the 4,900 level a couple of times and stayed stuck in a trading range.

The election happened on November 8th and stock futures went absolutely nuts.  First it plunged to multi-month lows and then it rocketed back up to the highest level in several days.  The pullback from the preceding high in the all-session high was as much as 361 points.

At the end of the month, volatility had settled down.  The NASDAQ 100 had once again neared the 4,900 level and backed off one more time.

This time, the pullback was about 196.25 points in size.  This was larger than the 147-point pullback that the market experienced off the early October high, but not too different from the 207.75-point pullback that the market experienced off the August high.

In mid-December, the NASDAQ 100 finally cleared the 4,900 barrier.  With a breakout above the trading range and new all-time highs, anyone who looks at charts has to be bullish.  Therefore, let’s assume that a trader will want to get long.

We’ll be patient and wait for a bit of a pullback before jumping in.

The pullback finally occurred at the end of December when the market retraced 144.50 points from the December 27 record high of 4994.50.  Therefore, we can put in an order to buy a breakout to 5005.

Now let’s build a price interval ladder!

Due to the unusual volatility surrounding the election, we are going to disregard the pullback that occurred at that time.

With that in mind, the pullbacks that preceded the breakout ranged in size from 144.50 points to 207.75 points.  Therefore, we are going to set an interval ladder of 210 points to trade the NASDAQ 100.

This means that once the buy stop order at 5005 is filled, a protective sell stop will be placed at 4795.  Also, additional buy stop orders will be placed every 210 points higher at 5215, 5425, 5635, 5845, etc.

Every time a buy stop order is filled, the protective sell stop orders for all contracts will be placed 210 points lower than the most recent entry, which is one “rung” lower on the price interval ladder.  This process will carry on until the entire position is liquidated either by a sell stop getting triggered or a profit objective being met.

Here’s how this strategy would have worked out in 2017:

January 6, 2017 – NASDAQ 100 rallies to 5005 and fills buy stop order.  A protective sell stop order is placed 210 points lower at 4795 and a buy stop order to buy more is placed 210 points higher at 5215.

February 9, 2017 – NASDAQ 100 rallies to 5215 and fills buy stop order.  A protective sell stop order is placed 210 points lower at 5005 for both long contracts and a buy stop order to buy more is placed 210 points higher at 5425.

March 15, 2017 – NASDAQ 100 rallies to 5425 and fills buy stop order.  A protective sell stop order is placed 210 points lower at 5215 for all three long contracts and a buy stop order to buy more is placed 210 points higher at 5635.

May 1, 2017 – NASDAQ 100 rallies to 5635 and fills buy stop order.  A protective sell stop order is placed 210 points lower at 5425 for all four long contracts and a buy stop order to buy more is placed 210 points higher at 5845.

June 2, 2017 – NASDAQ 100 rallies to 5845 and fills buy stop order.  A protective sell stop order is placed 210 points lower at 5635 for all five long contracts and a buy stop order to buy more is placed 210 points higher at 6055.

June 12, 2017 – NASDAQ 100 declines to 5635 and elects the protective sell stop orders for all five contracts.  The trade results in a profit of 1,050 points, which is a 5-to-1 return on the initial risk.

The beauty of measuring the sizes of the countertrend moves in a particular trend is that it is relative to the current market conditions.  It works just as easily in currencies…and crude oil…and grains…and bonds…and any other market you can think of.  This is a robust strategy.

Ladder Modifications

Once you get the hang of this price interval ladder strategy, there are a couple of ways that a trader could build a better mousetrap and modify it.

First, the trailing exit stop or “lower rung” on the ladder can be trailed as the market makes new highs for the move without having to wait for the higher pyramid entry orders to get elected first.

Since the size of the countertrend moves off the highs were measured and the price intervals were placed in increments that are larger than the typical reaction, this is a smart trailing stop strategy that works to reduce risk at a faster pace.

Another modification is to update the size of the price intervals based on the most recent couple of countertrend moves.  If the pullbacks are getting bigger, the wider price intervals will provide more breathing room.

Conversely, if the pullbacks are getting smaller, the tightening price intervals will reflect that and reduce the risk on the trade.  This can have the positive effect of increasing the reward-to-risk ratio on a trade.

Know Your Limits

Do some noodling on these pyramiding ideas and figure out what sort of strategy makes the most sense to you and what gels with your own trading system/methodology.  Once you’ve decided on what you’re going to do, though, you’re homework isn’t complete.

You will still need to determine just how big you’re willing to build your pyramids.

Even though you’re trailing the protective stops as you pyramid a winning position, you still need to set a limit on how big you will go.  This is because there is no iron-clad guarantee that your protective stops will be executed and filled at the exact price of your order.  Price slippage –especially after a big run- tends to be the norm.

I’ve seen a reversal in the silver market only take twenty minutes to destroy one-third of a profit on a trade that took weeks of pyramiding to build…and that wasn’t even the final top for the market!  Traders beware.

Nasty slippage is not even the worst thing that can happen.

If a market suddenly makes a limit move against you, there’s no guarantee that your stop order will even be executed at all!  You could be stuck in a lock limit situation for days at a time.

This lock limit scenario is a worst case scenario.  It rarely happens.

But the fact that it’s possible means that you have to build it into your contingency plan.

It only takes one of those to put a trader out of business if the leverage is too high.  You’ve heard the story of what happened to those geniuses who ran Long Term Capital Management, haven’t you?  It was the leverage that killed ‘em, not their being wrong about the market.

So if you’re going to build pyramids, make sure they aren’t big enough to crush you when they occasionally topple over.


More Articles by Jason Pearce:

Building Pyramids for Asymmetric Trading Gains Part I

How Much Leverage is Appropriate in Your Account?

US Dollar: The New Bear Market?

Equities: US Against the World

Profiting From Failure: The Wash & Rinse Trade, Part II

Profiting From Failure: The Wash & Rinse Trade, Part I

How to Trade with Moving Averages, Part II

How to Trade with Moving Averages, Part I

Market Returns Do Not Equal Investment Returns with Leveraged ETFs

Is The Canadian Housing Market Bad for Canadian Banks?

2017: The Death Year for Stocks

Potential Bond Market Reversal Ahead

 

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By Jason Pearce

Reward vs Risk

George Soros once said, “It’s not whether you’re right or wrong that’s important, but how much money you make when you’re right and how much you lose when you’re wrong.”

His comments address the subject of the reward-to-risk ratio on a trade.  If the payoff of a winning trade is multiple times larger than the risk and subsequent loss on a losing trade, then you can net out a profit even if you have a lot more losing trades than winning trades.

This is why Paul Tudor Jones only takes a trade where he expects to get a minimum of a 5:1 reward-to-risk ratio.

Jones said, “Five to one means I’m risking one dollar to make five.  What five to one does is allow you to have a hit ratio of 20%.  I can actually be a complete imbecile.  I can be wrong 80% of the time, and I’m still not going to lose.”

Simple Math

To calculate the reward-to-risk ratio on a trade, you have to know where the position is being entered, where the initial protective stop is being placed, and where you expect the market to go if the trade is successful.

The difference between the entry price and the initial protective stop tells you the risk on the trade.

The difference between the entry price and the minimum price you expect it to get to if you’re right is the potential reward on the trade.

Just divide the potential reward amount by the initial risk amount and, voilà, you will get the targeted reward-to-risk ratio for the trade.

Building the Great Pyramids

Now that you know how to determine the reward-to-risk ratio on the trade, I want to discuss a strategy that one can use to potentially increase the reward side of that ratio for any given trade.

Unlike in poker, where you have to up the ante and increase the amount of money you must risk in order to stay at the table, this strategy can allow a trader to keep the initial risk size the same –in some cases, even lower the amount of risk on the trade- and capture even more of the upside of a winning trade.

What I’m talking about here is building a pyramid.  No, this is not some new MLM scheme like your dead-beat cousin Eddie is trying to get you to sign up for.  This is a legit way to ramp up your profits on a winning trade.

Pyramiding a position simply means that you continue to add more and more contracts or shares as the market moves in your favor.  You increase your position size as the trend proves itself and your profits grow.

No Averaging Down

It is important to understand that pyramiding a position is not like the traditional strategy of dollar cost averaging where you continue to add a predetermined amount to your investment in time increments like the guy who socks away $500 each month into his mutual fund portfolio.

It’s certainly not where you average down on a position and buy more and more shares of a sinking stock, either.

Quite the opposite.

In pyramiding, you only add to your position when you’re in a trending market that is moving in your favor.

Furthermore, when more contracts or shares are added, the protective stop orders for all the previously acquired contracts should be moving up as well in order to reduce/eliminate the risk on these contracts.  At least, that’s the right way to do it.  Otherwise, all you are doing is taking bigger risks with bigger positions.

From my point of view, adding more contracts without trailing the stops on the other positions is not pyramiding; it’s simply engaging in bad risk management.

Rookie Pyramid-Builder Mistake

Unfortunately, a lot of new commodity traders first learn about pyramiding with the worst application possible.  This is a financial nuclear meltdown just waiting to happen.

The novice trader might read a get-rich-quick trading book or talk to some sleazy broker that teaches them to buy a futures contract and add more just as soon as it has a big enough open profit to cover the margin for another contract.

This sort of pyramiding is the most aggressive way to apply the strategy…and the most incorrect way to do it!  So let’s go ahead and talk about this misapplication first and put it to rest.  Knowing what not to do is just as important for your trading success as knowing what to do.

Recipe for Disaster

The margin for a 5,000 bushel wheat futures contract is currently around $1,500.  This represents a price swing of 30 cents (5,000 bushels * 30 cents = $1,500).

Suppose a trader has $50k in his account and he buys a September wheat contract on a breakout at $5.40.  He could put in a buy stop order to buy another one when it rallies 30 cents to $5.70 as the initial contract purchased at $5.40 would show an open profit of $1,500 and provide the financing for an additional contract.

This all seems harmless at first.  A single contract with fifty grand to back it and one more contract when the market moves in the right direction.  But watch how crazy and how fast this can escalate…

The trader can place an order to buy another contract just 15 cents higher at $5.85 instead of 30 cents higher at $6.00.  This is because an additional 15-cent gain on two contracts is $1,500.

Or the trader could elect to be a little more patient and instead put in an order to buy two futures contracts at $6.00 instead of one at $5.85.

If the trader were to use the latter and more “conservative” choice, he could simply put in buy stop orders to double up every time the wheat market moves an additional 30 cents higher.

Let’s suppose our wheat trader gets “lucky” and catches a weather market in the grains where the market just shoots to the moon and makes hardly any pullbacks along the way.  That’s the sort of trade that fortunes are made of.  What happens if wheat rockets north of $8-per-bushel like it did in the summer of 2010?

The trader would have purchased one contract at $5.40, one additional contract at $5.70, two contracts at $6.00, four contracts at $6.30, eight contracts at $6.60, sixteen contracts at $6.90, thirty-two contracts at $7.20, sixty-four contracts at $7.50, and (gasp!) one hundred and twenty-eight contracts at $7.80.

That’s a total of two hundred and fifty-six wheat contracts that the trader is holding, folks.  I hope they’re not gluten-intolerant…

Oh, and when wheat touches eight dollars the account would be sitting on an open profit of $638,500.  What trader doesn’t dream of that?!

Jenga!

This nearly thirteen-fold increase in account size, brought about by an aggressive pyramiding strategy, is the siren song that lures the novice traders into the markets.  They only pay attention to the profit potential and hope to match Soros’ net worth with just a few trades with their $50k trading stake.

Here’s what they are not taking into account.  With two hundred and fifty-six wheat contracts on, every one-cent move in the price of wheat creates a profit or loss of $12,800 on their trading account and a mere ten-cent hiccup would rip an astronomical $128,000 from their account.

Notice what happened when wheat finally cracked the eight dollar mark in August of 2010: It rocketed to $8.41…and then promptly fell apart, like a high-stakes game of Jenga gone bad.

Wheat closed ‘limit down’ at a price of $7.25 3/4 that day.

From the day’s high to the close, this huge pyramided position dropped in value by $1,475,200.  (That’s nearly one and a half million dollars, just in case the commas aren’t registering in your brain.)

By the way, once wheat traded to $7.46 1/4 the account value hit zero.

By the day’s close of $7.25 3/4, the account was in a deficit to the tune of $261,900.  The trader is completely on the hook for this amount.

And that’s assuming he could have gotten out at the limit price.  If it was locked limit, the trader would have exited in the next trading session at an even worse price when the market gapped lower.

What?!

Although this is what the September wheat contract actually did in the summer of 2010, the pyramided trade is a theoretical example.  However, I can testify to the fact that scenarios like this can and do happen with alarming frequency.  I watched a trader run $20k into $100k in a matter of weeks and then crash it into a deficit of $20k in a matter of days.  It was accomplished during a good old-fashioned weather market in soybeans.

I also know of a mailman with a $50k net worth who ran a $25k account up to nearly $500,000…and then down into a deficit of nearly $1 million by aggressively pyramiding in the silver market this same way.

With a net worth of just $50k, it’s quite a burden to owe a clearing firm $1 million.

I could go on, but you should get the point by now.  This sort of aggressive pyramiding scheme that increases your account exponentially on the way up will decrease it even faster on the way down.  Don’t even think about it!

Trade Smart

A smarter and better way to build a pyramid is to wait for new entry setups to materialize in a market that you already have a position in.  In other words, you trade the market’s price structure.  This is not about calculating how much it takes to finance the next contract; it’s about waiting for the market to show you when and where to add to your position.

A very simple way to implement this is to trail the protective sell stops below each reaction low after a new high for the move is made.

You can also use the new high of the move as an entry signal for more contracts and place the protective sell stops below that same reaction low where the other stops are set.  That way, you’ve reduced you risk on all previously purchased contracts and you have a well-defined price structure pattern to add more.

The inverse works for short sales, of course.  After a market bounces and then hits a new low for the move, protective buy stops can be relocated to just above the bounce high and more contracts can be sold short.

There are two important rules you should adhere to:

First, only take new setups if the current position has an open profit.  You should never add to a position that’s currently a loser.  Even a breakeven trade has not earned the right to get bigger yet.

Second, wait until the initial protective stop has been moved enough to significantly reduce or even eliminate the initial risk on the trade.

That’s it.  Very simple to understand, very simple to and implement.  This is the KISS principle at its best.

Test Drive

As an example of pyramiding with market structure, let’s look at how this might have been applied to a short sale campaign trade in the July 2017 cocoa futures contract.  Keep in mind that one contract controls 10 metric tonnes of cocoa, so each tick ($1) is worth $10.

Also, let’s assume an account size of $100k where we’re behaving like reasonable traders and risking just one and a half percent (1.5%) of our equity per trade.  None of that crazy “pyramid-your-$10k-into-$1-million-in-two-months” garbage going on here.

We will cap the risk at $1,500 (that’s 1.5% of $100k) so that no losing trade or string of losers can ruin the account or take us out of the game.

Now, there are some who will say that you can’t make any real money when you’re risking such a small amount.  Like the saying goes, “No guts, no glory”, right?

Not when it comes to risk management and pyramiding.  Just watch and learn.

July cocoa made a double top last summer between the July and August highs of $3,077 and $3,069.   The lowest point between these two lows was the July 29th low of $2,800.  When this low was broken on September 9th, I think most technicians will agree that a short position could have been entered.

The initial protective buy stop order for this trade could be placed above the double top high of $3,077 or it could be placed above the bounce high that preceded the break at the September 7th six-session high of $2,907.

To keep things simple and low risk, let’s assume a short sale was initiated at $2,790 (ten ticks below the July 29th low) and the initial protective buy stop order was placed at $2,917 (ten ticks above the September 7th high).  This sets the initial risk on the trade at $1,270 per contract, which is a bit under our $1,500 risk target.

So here’s a price structure pyramiding plan that could have been implemented:

1 Once cocoa has bounced to at least a five-session high (this would be a one-week high since there are five trading days in a week) and then drops to a new low for the move, lower the protective buy stop for all contracts to ten ticks above the bounce high.

2 *After the protective buy stops on the prior contracts have been lowered, short another cocoa contract ten ticks below the most recent low for the move and place the initial protective buy stop ten ticks above the bounce high as well.

*There is a risk management contingency for the pyramided contracts: it can only be done as long as the total risk on all the prior positions are equal to or less than the initial risk on the trade and the new stop placement eliminates 50% or more of the open risk on the most recent contract added.

Here’s how the cocoa short sale campaign trade may have worked out:

September 19, 2016 – July cocoa rallies to a six-session high of $2,849.

September 29, 2016 – July cocoa drops to a one and a half year low of $2,693, breaking the prior low for the move at $2,729.  The protective stop on the initial short contract is lowered to $2,901 (ten ticks above the recent bounce high).  The risk is reduced to $1,110, which is not enough to allow for a new short contract.  Remember, the new protective stop placement has to cut at least half of the open risk on the most recent contract.

November 3, 2016 – July cocoa rallies to a nearly three-week high of $2,661.

November 4, 2016 – July cocoa drops to a three-year low of $2,539, breaking the prior low for the move at $2,585.  The protective stop on the initial short contract is lowered to $2,671 (ten ticks above the recent bounce high).  The initial contract entered at $2,790 now has a profit of +$1,190 locked in.

Also, a second contract is sold short at $2,575 (ten ticks below the most recent low for the move) and the initial protective buy stop for this contract is also set at $2,671 (ten ticks above the recent bounce high).  The initial risk on the second contract is $960.  Cumulatively, this locks in a net profit of +$230 on the entire trade.

November 21, 2016 – July cocoa rallies to a five-session high of $2,447.

December 2, 2016 – July cocoa drops to a new multi-year low of $2,334, breaking the prior low for the move at $2,363.  The protective stop on both short contracts is lowered to $2,457 (ten ticks above the recent bounce high).  The initial contract entered at $2,790 now has a profit of +$3,330 locked in and the second contract entered at $2,575 now has a profit of +$1,180 locked in.

Also, a third contract is sold short at $2,353 (ten ticks below the most recent low for the move) and the initial protective buy stop for this contract is also set at $2,457 (ten ticks above the recent bounce high).  The initial risk on the third contract is $1,040.  Cumulatively, this locks in a net profit of +$3,470 on the entire trade.

January 5, 2017 – July cocoa rallies to a six-session high of $2,244.

January 11, 2017 – July cocoa drops to a new multi-year low of $2,103, breaking the prior low for the move at $2,108.  The protective stop on all three short contracts is lowered to $2,280 (ten ticks above the recent bounce high).  The initial contract entered at $2,790 now has a profit of +$5,100 locked in, the second contract entered at $2,575 now has a profit of +$2,950 locked in, and the third contract entered at $2,353 now has a profit of +$730 locked in.

Note that a fourth contract was not sold short.  This is because the prior low for the move at $2,108 was not broken by at least ten ticks.

January 17, 2017 – July cocoa rallies to a six-session high of $2,240.

January 27, 2017 – July cocoa drops to a new multi-year low of $2,100, breaking the prior low for the move at $2,103.  The protective stop on all three short contracts is lowered to $2,257 (ten ticks above the recent bounce high).  The initial contract entered at $2,790 now has a profit of +$5,330 locked in, the second contract entered at $2,575 now has a profit of +$3,180 locked in, and the third contract entered at $2,353 now has a profit of +$960 locked in.

Once again, a fourth contract was not sold short because the prior low for the move at $2,103 was not broken by at least ten ticks.

January 30, 2017 – July cocoa drops to a new multi-year low of $2,088, breaking the prior low for the move at $2,103.  Therefore, a fourth contract is sold short at $2,093 (ten ticks below the most recent low for the move) and the initial protective buy stop for this contract is set at the same place as the others at $2,257 (ten ticks above the recent bounce high).  The initial risk on the fourth contract is $1,640.  Cumulatively, this locks in a net profit of +$7,830 on the entire trade.

February 16, 2017 – July cocoa rallies to a seven-session high of $2,060.

March 1, 2017 – July cocoa drops to a more than five-year low of $1,899, breaking the prior low for the move at $1,901.  The protective stop on all four short contracts is lowered to $2,075 (ten ticks above the recent bounce high).  The initial contract entered at $2,790 now has a profit of +$7,150 locked in, the second contract entered at $2,575 now has a profit of +$5,000 locked in, the third contract entered at $2,353 now has a profit of +$2,780 locked in, and the fourth contract entered at $2,093 now has a profit of +$180 locked in.

A fifth contract was not sold short.  This is because the prior low for the move at $1,901 was not broken by at least ten ticks.

March 2, 2017 – July cocoa drops to an eight and a half year low of $1,879, breaking the prior low for the move at $1,901.  Therefore, a fifth contract is sold short at $1,891 (ten ticks below the most recent low for the move) and the initial protective buy stop for this contract is set at the same place as the others at $2,075 (ten ticks above the recent bounce high).  The initial risk on the fifth contract is $1,840.  Cumulatively, this locks in a net profit of +$13,270 on the entire trade.

March 13, 2017 – July cocoa rallies to an eleven-session high of $2,023.

March 15, 2017 – July cocoa rallies to a multi-week high of $2,081.  This triggers the buy stop orders on all contracts at $2,075 and liquidates the entire position with a net profit of +$13,270 on the trade.

Price Structure Pyramid Performance

So how did this more conservative price structure pyramiding strategy affect the reward-to-risk ratio on the cocoa trade?

Well, the initial trade was entered at $2,790 with a risk of $1,270 per contract and the profit was +$7,150.  The profit was a little over five and a half times the initial risk, yielding a reward-to-risk of 5.6:1.

But…

The total profit on the trade was +$13,270 and the pyramiding and risk management rules made it so that the cumulative risk never exceeded the initial risk as more contracts were added.  That means the total trade risk was never more than the initial risk of $1,270.

So the +$13,270 profit was nearly ten and a half times the initial and maximum risk on the trade, yielding a reward-to-risk ratio of almost 10.5:1 in the $100k account.  That’s nearly double what the non-pyramided trade would have returned.

Consider the fact that the trade initially risked 1.27% and made a +13.27% return in six months without being hyper-aggressive.

Annualized, that’s a +26.54% return on the entire account with a single trade that risked about one and one-quarter of a percent.

Yes, Virginia, there really is a way to make good money on small risks!

Obviously, this cocoa pyramid trade is one of those best case scenarios.  They don’t all have this sort of outcome.  Most trades don’t.  But the example does show you the possibilities of what can happen when you take advantage of a sustained trend by pyramiding the smart way.

Many Ways to Win

In trading, there are many different paths to success.  Different timeframes, different setups, different entry signals, different kinds of systems, etc.

The same goes for pyramiding.

In this post, we discussed a wrong way to pyramid and one smart way to pyramid.

But this merely scratches the surface.

In the next post on the subject, we will discuss how volatility can be used for pyramiding.  I will also show you a different way to use price structure to build a pyramid.  Both of these pyramiding methods can be implemented in a systematic, rule-based manner.  So if you’re interested in learning how to potentially turning a single hit into a grand slam home run, stay tuned!


More Articles by Jason Pearce:

How Much Leverage is Appropriate in Your Account?

US Dollar: The New Bear Market?

Equities: US Against the World

Profiting From Failure: The Wash & Rinse Trade, Part II

Profiting From Failure: The Wash & Rinse Trade, Part I

How to Trade with Moving Averages, Part II

How to Trade with Moving Averages, Part I

Market Returns Do Not Equal Investment Returns with Leveraged ETFs

Is The Canadian Housing Market Bad for Canadian Banks?

2017: The Death Year for Stocks

Potential Bond Market Reversal Ahead

 

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by Brynne Kelly

July 24, 2017

What Does An ‘OIL GLUT’ really mean?

The terms “glut” and “oil” have become almost inseparable the past 18 months.  Fueled by an obsessive focus on inventory and production levels, it has become an easy narrative.

The Cambridge English Dictionary defines a ‘glut’ as:

A supply of something that is much greater than can be sold or is needed or wanted.

A glut is often associated with low prices, or an expectation of low prices.  An extreme example of a supply ‘glut’ can be seen in the electricity markets through real-time electricity prices.  Whereas most commodity markets exist with a storage system under-pinning them,  this is not the case for electricity markets (but for limited battery and hydro storage).  As a result, when power has been generated in excess of demand, market prices have to move low enough to clear this excess supply.  As a matter of fact, this market clearing price can even be less than zero (negative), meaning the producer has to PAY the consumer to take the product off their hands.  The negative price reflects the ‘cost’ the consumer incurred to accommodate that supply into their system.  Without a storage system in place, market regulations require utilities to hold enough generating capacity to cover the highest projected demand for the year plus a reserve margin.

A robust storage system helps to smooth day-to-day and seasonal differences in supply and demand and reduces traditional production capacity requirements.  In this way, storage acts as an alternative form of supply and demand by allowing product injections during times of over-production for use in times of under-production.  The natural gas market in the US is a good example of this.  Total natural gas production capacity exceeds total demand in the summer, but isn’t enough to meet total demand in the winter.  Using storage however, production can continue at a relatively stable level throughout the year, with excess being injected into storage in the summer for use in the winter.

Storage levels then become the ‘glut’ indicator, unlike the electricity market which doesn’t have a buffer between differences in supply and demand.  At the extremes, conventional storage systems either become too full to accommodate additional supply, or too low to accommodate projected future seasonal demand.  In either case, price signals emerge in an attempt to rectify the situation.

Perceived versus Real “Glut”

An inventory shortage or excess can be either perceived or real.  Real inventory issues show up in the spot market.  Perceived inventory issues are based on assumptions.  These assumptions are anticipated as threats to the spot market at some point in the future and are expressed via the futures market.  If these assumptions don’t manifest into the spot market over time, assumptions regarding the ‘future’ will ultimately be revised.  Think of flowers delivered on Valentine’s Day.  A month in advance, the market establishes a clearing price for flowers delivered exactly on February 14th.  There are even discounts offered for flowers delivered the day before or the day after February 14.  These are based on perceived value.  Come Valentine’s day, those who forgot to place their order and need flowers are now forced into the ‘spot’ market and may be willing to pay multiples of the original price for delivered flowers, or they may luck out and find an overzealous store stuck with too much delivery capacity.

With that in mind, let’s circle back to the aforementioned ‘glut’ in the oil markets.  The prevailing narrative is that there is too much supply for the current level of demand.  The evidence being used to support this narrative is inventory levels.  High inventory levels are perceived as a threat to the spot market.  As long as there is still room to fill conventional storage, producers have the option of storing their barrels or selling them.  In this way, spot prices are linked to futures prices.  In a perfect world, the difference (spread) between the spot price and the next futures price should reflect the cost of storage capacity.  Of course, the cheapest storage options will be used first.  As these fill up, spreads may widen to value the next most economic form of storage and so on.  This is why it has been traditionally assumed that a widening spread, or contango, may be signaling a market oversupply.  On the other hand, if spot prices are higher than futures prices, those with barrels in storage will withdraw stored barrels to capture a higher spot price and eliminate storage costs.

Take a look at the 1-month price spreads in WTI futures since the beginning of 2017:

At the beginning of the year, the front of the futures market was trading at a slight contango from one month to the next (the black line above).  However, starting with the Dec-17 contract, the market had moved into ‘backwardation’.  This market structure makes the decision to store barrels uneconomic and should have induced producers to sell their barrels into the spot market.  You can see that by June, the backwardation in the futures curve had been pushed back 3 months (the grey line) and by last week that backwardation was gone.

The effect of the shape of the term structure seems to have had the desired effect on inventories, as storage has been drawn down significantly since April:

Total Petroleum inventories have been reduced by over 50 million barrels since the beginning of April, 2017.  This is significantly higher than inventory withdrawals in the prior 3 years.  As a result, total inventory levels are now slightly below where they were at this time last year but still above levels of the prior 3 years:

Once the incentive to store barrels was reduced, they were instead pulled out of storage and moved to market.  Pulling over 50+ million barrels out and selling them into the market put pressure on the front of the futures curve relative to the back (seen in the chart below):

As a result, the December 2018 contract is now close to $2.00 over the December 2017 contract.  While that may sound like a lot, it’s just a little over $0.15 a month compensation to defer payment on your production.  Since the seller of oil doesn’t receive payment until after the oil is delivered, holding it in inventory doesn’t generate cash.  As a matter of fact, holding oil in inventory costs money (via the tank storage cost).  With all the news coverage this past year regarding the need for cash, it’s no surprise producers would rather sell now versus hold inventory.

Days of Supply

Oil inventories are often expressed as “Days of Supply”.  This is essentially total inventories divided by daily demand.  Over the past 10 years, we have gone from just under 25 days of supply to a little over 30 days as production has increased and demand has flattened (as seen below).

This assumes oil inventories can transported to refineries to be processed as they are withdrawn.  I use ‘days of supply’ to put the phrase ‘inventory glut’ into perspective.  Is just over a month’s worth of crude oil held in inventory to meet our current demand needs something you would consider excessive?  Since we still rely on imports for over half of our crude oil needs in the US, this doesn’t scream ‘excess’ to me.  But, as in any business, holding inventory is expensive and it’s a delicate balance to determine the optimal balance between margin and cost.  Assuming there are decent margins to be made, it would be logical to assume more inventory would be held at low prices versus high prices.

What is The Signal?

As Nate Silver discussed in his book “The Signal and the Noise” (2012), we seek to extract signals and eliminate noise when building models with historical data to
predict the future.  However,  while the final outcome of an event is subject to influences that will repeat themselves in a foreseeable way in the future, it is also subject to a great deal of noise that will not repeat itself in the future in a predictable manner.

I believe the ‘signals’ we have been receiving from the oil market have moved from ‘price’ signals to ‘volatility’ signals.

Increased production and storage capacity in the US have reset oil prices from $90 to $45 in the past 2 years. As a result, production costs have been targeted and optimized.  What remains is a larger, more efficient system with a lower convenience yield that may be less prone to significant price moves in either direction.

However, low volatility also makes it more difficult to justify new assets as it reduces projected returns (all other things being equal).  With long lead-times to build new assets like pipelines and export infrastructure, a sustained period of low volatility will have impacts not realized for many years in the future.

 

 

 

 

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July 5, 2017

Understanding The “Mexico Deal”

 

So, you’ve heard about this large oil transaction that has the potential to move markets and wanted to know more?  In the article below, I use this transaction as a means to delve in to the structure of the type of trading group that might participate in this deal. From there, I then take a deeper look at the transaction itself and the complex hedging decisions those that participate might face.  With this information, you will learn where to look for any related trading opportunities.

We know that several years ago the Mexican government implemented an annual crude oil hedging program as part of their budget process.  Their intent is to protect the oil revenue defined in their yearly budget through the purchase of put options.

Recently, knowledge of this deal has received more press and it is now widely anticipated as a transaction large enough to move markets.  To understand the process that occurs from deal negotiation through deal closing, let’s first take a look at the structure of the trading desk.

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Trading desk structure

To understand how large deals like this unfold, it’s helpful to understand the different roles on a large integrated trading desk, specifically the trader and the marketer roles.

You may have noticed that many of the large banks and integrated energy companies out there have what they call their “Trading and Marketing” group.  That’s because they are actually two distinct functions that depend on each other to make money.

Trading and Marketing roles defined

The trading desk manages a portfolio of risk exposure, executing strategies to capture anticipated market moves.  They are usually governed by Value at Risk (VAR), Volume, and Credit limits.  VAR is a common measure of how much a portfolio might lose (gain) given normal market conditions for a given confidence interval (probability) and liquidation period.  It is a measure of market risk.

When working inside a large institution where capital constraints like margin are monitored at the corporate level, it’s more relevant to assign VAR limits at the individual trader or desk-level rather than assign margin limits.

In addition to VAR limits, traders or trading groups are often assigned volume limits.  These volume limits are often assigned the total portfolio level, the individual market level, or both.  The rationale for volume limits is to prevent position size from impacting the liquidity-portion of the VAR calculation, among other things.  It’s not an exact science, and in my career I have certainly run up against assigned volume limits before my VAR limits.

The introduction of central clearing has simplified portfolio credit risk in listed products, however, it is still an issue for non-listed products.  There is still a vast world of over-the-counter (OTC) transactions with non-standard terms, non-standard durations, non-standard grades and variable volume requirements.  These transactions are enabled by direct credit agreements negotiated between counter-parties in the deal.  As a result, corporate or portfolio-level credit exposure limits by counterparty are established to ensure exposure to a particular counterparty doesn’t exceed collateral agreements.

The marketing desk in a trading business usually focuses on originating non-standard transactions directly with another counterparty.  Typically a marketer within an energy trading group might be assigned a region of the US and work to build relationships with both producers and consumers within that region.  For example, they may have an industrial client that is looking to buy 800 Mmbtu’s of natural gas delivered to their plant location via pipeline in southern Alabama.  This is not the standard 10,000 Mmbtu exchange-traded natural gas future.  Since the marketing role is to originate business directly with customers, versus take risk, the marketer will bring the terms of the deal to their internal trading group for them to quote a price.

There can be a lot of discourse between the trading and marketing groups regarding deal valuation.  Marketers generally don’t manage market risk, they manage relationships. They are primarily measured on the amount and quality of the deals they close.  Conversely, a trader is measured on the returns they generate from the portfolio they manage.  Once a deal is closed, it is transferred to the trading desk to manage.  Some groups establish a ‘transfer price’ at which the deal is moved into the trading ‘book’ from the marketing ‘book’ in an attempt to capture any value (a marketer’s negotiation skills) added to the sales/purchase price over and above the trader’s quoted price. Ultimately, the more deals the group as a whole gets a look at the more they are aware of what is going on in the market, which is valuable information.

It would be reasonable to assume that the opportunity to participate in the Mexican hedge deal originated through the marketing group and the relationships they have created over the years.  It’s also reasonable to assume that these marketers work closely with their internal trading desks regarding the terms of the deal so that their traders can establish a market price at which they are willing to transact.

Why do I assume this?  Deals like the Mexican oil hedge require a lot of contracts with specific negotiated terms (credit, margin, legal, etc).  This requires a lot of time, which is something that traders on a desk don’t usually have.  This is clearly a deal done directly between two counter-parties, contains non-standard terms (if it was a simple put option on WTI futures, it could be executed via the exchange) and its contract language would have to be carefully monitored and updated each year.

The benefit of being a Market-Maker

Market-making on a trading and marketing desk, as described above, refers to the internal process of the traders providing market prices to the group’s marketers on deal opportunities they originate from their customers.  Once the marketer has obtained a price from their trading desk and established how long that price is good for (1 hour, 1 day, etc.) they submit them to the customer.  Often times it is unknown how many other companies the customer is soliciting markets from.  Because markets are submitted directly to the customer, they are not public which makes for a distorted feedback loop.  You generally have no idea what prices your competition gave to the customer, but can only assume that if you didn’t win the deal, you did not provide the best price.

Over the years, I have worked with marketers and participated in pricing long-term, non-standard deals.  In most cases the counterparty needs either variable volumes, obscure delivery points or an illiquid grade of product.  The counterparty has often reached out to several companies to ensure they are getting competitive prices.  This is why an active trading desk is needed as part of an overall group.  Being active in the physical and financial markets every day gives traders the knowledge needed to understand market dynamics and the performance risk they are being asked to ‘price’.

One thing is for sure:  the fewer market-makers and the less liquid the product being priced, the more opportunity there is for adding larger premiums to your markets.

It’s fairly common for markets to have large annual or seasonal transactions that occur due to regulatory requirements, hedging or procurement. Some of these transactions are governed by regulatory rules regarding the type of counterparty that can participate.  These rules are typically related to the size and credit-worthiness of the participants.  Limitations on the number of participants limits the amount of competition and increases price mark-ups (mark-downs).

Which brings me back to the annual hedge by the Mexican government, as the above speaks to the rumored ‘large fees’ made by those that qualify to make markets for this deal.  I believe “large fees” relates to how wide one can make their market.

Due to the size of this deal, and the potential pay-outs, Mexico is interested in dealing with counter-parties that are well collateralized with the ability to pay out large sums in the future should their option go ‘in-the-money’. There is nothing worse than having a winning trade on your books only to have your counterparty go bankrupt or become unable to pay (as happened to many when Enron filed for bankruptcy).

Electricity Market Example

To illustrate that deals like this occur across all industries, let’s take an example from the electricity market that I am familiar with.  The electricity market is regional with listed futures contracts for major pricing hubs within each region.

There are two main listed futures for each pricing hub:  On-peak and Off-peak think high-sulfur and low-sulfur crude oil grades).  In the eastern time-zone, On-peak contracts cover the 16 hours (7 AM-10 PM) on each week-day of the month. The Off-peak contract covers the 8 hours (10 PM-7 AM) on each week-day of the month and also the entire 24 hours for each weekend and holiday in a month.  The volume for each of these contracts is, for the most part, 50 MW/hr multiplied by the number of On or Off-peak hours in each month.

An electricity marketer communicates with many different types of customers to originate a deal (large industrial users, builders of new generation, etc.) When a customer is looking to transact, they provide the terms of what they are looking for and the deadline for prices to be submitted.  In this example, let’s say that the customer is a large industrial company that is growing and needs to purchase additional electricity to cover that growth.  Their plant is located in Pennsylvania and they provide the following estimated usage curve indicating how much they are looking to buy each hour:

The customer has requested a fixed price quote (given this usage curve) for a 5 year term.  The volume of the futures contracts traded in the market are for 50 MW/hr blocks, while the volume the customer needs per hour varies throughout the day. Hedging this deal using futures contracts will leave the trader with excess during some hours and shortages in others.

Just as demand varies by hour, so do prices (as illustrated in the graph below).

You can see that using the standardized futures contract as a hedge would leave the trading book with excess length during the hours of the day that prices tend to be the lowest, and with shortages with during the hours of the day that prices tend to be the highest.

The trader will factor this into their model when crafting their offer price.

Here are a few basic hedging scenarios that might take place if they win the deal and it ends up in the trading book (as a sale to the industrial customer):

  • Buy a 50 MW block of on-peak futures (7 AM-10 PM, Mon-Fri) and stay short the off-peak hours (nights and weekends),
  • Buy a 50 MW block of both On and Off-peak futures which makes the net position fairly flat during on-peak hours, but net long during off-peak hours,
  • Do nothing – it’s a nice compliment to the trader’s overall bearish positioning and view that futures prices are headed lower

Of course, there are other options besides using futures contracts.  This deal may be somewhat offsetting to an existing position already in the trading book (in which case the trader might have an incentive to offer a better price to the customer because it relieves some headaches and locks in some profit).  The trader could also utilize a combination of options, however, options on electricity futures that settle against the hourly price averages are fairly expensive due to the higher volatility of hourly prices versus daily.

Other factors that affect hedge activity relate to corporate-imposed risk limits (volume and VAR limits).  Some deals are large enough that they would cause the trading portfolio to exceed their risk limits, if not hedged immediately.  Of course, you can see from the example deal above that it’s not always possible to hedge ALL of the risks immediately in some deals (like the variable hourly volumes and prices).  However, if the size of the new deal is enough to put the portfolio over volume or VAR limits,action must be taken immediately using liquid futures.  Post-mortem analysis will determine what net risk is left in the portfolio to manage (i.e. basis, location, quality, volume, etc.).

This is when a trader assesses their ‘net risk’.  Ending up long basis (spread) as a result of hedging is still a trade.  Would you buy that basis (go long) regardless?  If not, sell basis.

Deconstructing the Mexican deal:

Using the knowledge of the overall dynamics reviewed above, let’s look at how that might apply to the Mexican deal.

We know that roughly 95% of the crude oil that Mexico sells to the US is Maya heavy crude for use by Gulf Coast refiners.  Pemex (Mexico’s state-owned petroleum company) calculates their sales as a derivative of other market prices.   Their current formulas are:

Since over 95% of Mexico’s crude oil sales to the US are of Maya crude, that’s the formula we will look at for this analysis.  Maya’s value in the Gulf Coast is  indexed to a basket of 3 crude oil grades and 1 fuel oil grade, plus a constant (K) commonly called the K-factor.  This constant is updated monthly and posted on their website (found here) as seen below:

There are a lot of moving parts, each having different sets of price influences and drivers.  Also interesting to note,  WTI is not used directly in any of these formulas.  This is what Pemex states on their website regarding their pricing formulas:

First, let’s use what we have learned so far to evaluate the deal that was done for 2017 (the deal runs annually from Dec 1 – Nov 30).

Deal Assumptions: 

(see August 29, 2016 WSJ article)

 

 

 

The term of the deal has historically been 12 months running from December to the following November.  Using all of this information, it’s fairly straight-forward to pull together a back of the envelope analysis of the 2017 performance of $38.00 options against the market:

I pulled monthly posted prices (for US delivered Maya crude) from the EIA website for the beginning of 2017 and used the Pemex formula for the balance of the year.  It doesn’t appear that any of these puts would be in the money.  Given that market prices are only modestly above the strike, this is not great news for Mexico since they are net long oil. The premium they paid would be much easier to stomach if oil prices had moved much higher.  Cashing in on their puts is not actually the goal here since this is basically catastrophe insurance.  Any ‘gain’ derived from this insurance really just represents an overall loss of revenue on their total oil production.

With that in mind, take a look at Maya oil prices in the chart below:

With the Pemex formula and the futures curves for each of the 4 benchmarks, you can get a feel for 2018 Maya ‘futures’.  What strike level, if any, will they consider for next year?

For reference, futures curves can be seen in the table below:

For those who are more ‘visual’, here are the futures curves as of July 5, 2017:

The unknown in the calculations above for future terms (besides movements in outright price) is the Pemex published “K-factor”.  I used the posted K-factor for June 2017 (shown earlier) as a constant for the balance of the year and 2018.  While Pemex is responsible for setting the K-factor, it seems to be loosely correlated to the LLS/Brent spread.

Analyzing the Risks to the Market Participants in the Annual Mexican Hedge Deal

A recent Bloomberg article shed a lot of light onto this transaction.  One thing the Bloomberg author noted was that changes in bank regulations may be impacting post-deal activities:

Putting aside that a bank may have multiple trading groups and portfolios that ‘take the other side’ of any hedges they transact, I will focus on the market risk that a single portfolio involved in this deal might face rather than the corporate-level net portfolio.

We know that in the past the options purchased by the Mexican Government are primarily based on the underlying price of Maya, and to a lesser-extent, Brent.  I will assume that would again be the case for 2018.

As already mentioned, we know that Maya’s price is derived as a percentage of WTS, High sulfur fuel oil (HSFO), LLS and Dated Brent prices plus the variable constant set by Pemex.  This gives us the ability to understand the risks the seller of these options will need to lay-off once the deal is done.

Primary price exposure:

  • WTS
  • USGC HSFO
  • LLS
  • Dated Brent

Secondary price exposure created as a result of hedging (since it’s highly unlikely the seller can equally offset their exposure using Maya futures):

  • WTI/Brent Spread
  • LLS/Brent Spread
  • Brent/Oman Spread
  • USGC LSFO
  • Dated Brent/Brent Futures
  • Light/Heavy Crude Oil Spread
  • WTS/Canadian Heavy Spread
  • Etc.

For example, if risk were entirely laid-off using WTI futures the book is now exposed to any significant change in WTI’s relationship to Brent.  Another risk the seller of the options might incur relates to the expiration differences between monthly and average price options (it’s been noted that the deal is comprised of a basket of Asian, or average-price options).  To the extent that European or American options are purchased as a hedge, the option seller will still have to manage the difference between hedges using monthly strikes and the average of daily Index postings that are used to settle Asian options.

Looking at the market risks identified above, you get a sense of how complicated a hedge strategy could become.  Any unexpected shift-change in the relationship of the hedge contract to the underlying products used to price Maya (i.e. WTI suddenly trading at a premium to Brent) could seriously impact the hedge effectiveness.

It’s unlikely that there is a deep, liquid market for over-the-counter Asian options on Mayan Crude.  Therefore, hedging this deal will require the use of a mix of more liquid futures and options markets.  Determining the optimal mix of products to use is an art and a science.  The ‘art’ being any market bias regarding price direction and spreads.  The ‘science’ being the use of statistical tools and models.

How would you decide to hedge this trade?  Two statistical tools that are often used when evaluating effective hedge markets are ‘correlation’ and ‘r-square’.  Correlation measures the strength and the direction of a linear relationship between variables.  R-square measures the proportion of the fluctuation of one variable that is predicted from another variable(s).

Shown below are two simple correlation tables for the markets used in the Maya pricing formula (based on 2 different sets of historical price data):

 

In both time series, one thing that stands out is the high correlation between Maya and LLS oil price moves.

Since WTI and Brent are the two most liquid futures contracts, I went on to include historical WTI prices in the mix (even though WTI isn’t specifically included in the Maya price formula) and ran correlations again, using the same two historical time periods:

With the addition of WTI, we reveal a high correlation between WTI and WTS (which is a main component in the Maya price formula).

 

 

 

Price correlations provide useful insight.  To get more specific however, the R-square coefficient is used to define the usefulness of those correlations.  R-square is a measure of how much the variance of ‘y’, or in our case “Maya”, is explained by the model of continuous predictors “x” (in our case WTI, Brent, LLS, WTS, HSFO)

R-square outputs (using the same historical time series as presented in the correlation matrix) are shown below:

Each bar represents the historical price series used as well as which “index” variable is being compared to Maya.  For example, the first blue bar on the far left is the R-square of Maya and LLS prices using historical prices from 2015 through 2017.

Notice the difference in the results of the two historical time series used.  Specifically, the decline in the r-square of Maya vs HSFO (labeled R^2 HSFO above) in recent years.

This is obviously one of the problems with using historical time series data.  The changing nature of spread relationships can be significant and render older data useless.  Two years ago, heavy crude oil was pricing significantly below lighter grades, however, those relationships have changed with the OPEC cuts that started last year (which took the production of heavier grades off the market raising their price relative to lighter grades).

We could go on and on using various statistical models, but you get the idea.  The point is to get a sense of how those involved in the deal may look to hedge.  With both LLS and Brent showing the highest correlation and therefore, r-square values with respect to Maya, WTI may not be the hedge of choice.  With WTI as one of the more depressed light grades in the market lately, using it as a hedge leaves the portfolio essentially “long” Brent and LLS (the result of selling puts on Maya crude) and short WTI.

Said another way, the trader who has hedged with WTI has now made a market call on the Brent/WTI spread.  Selling put options (i.e. to the Mexican government) creates ‘length’ in a portfolio.  Think of this length as being related to Brent and LLS (and also WTS and HSFO).  Selling WTI futures to reduce

this length leaves the portfolio with a spread, namely long the Brent/WTI spread or long the LLS/WTI spread.

The knowledge of how such a large deal may be hedged can lead to trading opportunities.  For example, if I believed the initial hedges might be placed in the most liquid markets such as WTI, I might expect the Brent/WTI spread to widen in response to heavier-than-normal WTI futures selling.  Therefore, it might pay to go long that spread before hedging begins. The trader responsible for hedging this deal might also do the same hoping to pull some more profit out of the market from trading positions.  You can extrapolate this concept to High vs Low sulfur fuel oil, Gulf coast vs New York harbor spreads, etc.  My point is that outright price movement isn’t the only outcome here, and you might be well-served to look at how the various spread relationships are behaving.

Since the initial move in spreads after the OPEC cuts last year, the entire oil complex has remained closely linked.  A break-out move in any of these spread relationships might be a signal that significant hedging volume has entered the market.  Pay close attention.  Anyone who has significant volume to sell in the market might hit those that are less liquid first to ensure they can get some sales off before the market senses what’s coming.  Since selling pressure in WTI and Brent can pull the entire complex down with it, one trick traders use is to sell or go short some off the less obvious markets (WTS, HSFO, etc.) beforehand in hopes of capturing additional profit created by said hedge activity.

Just as spreads may widen, or prices may go lower when large selling pressure comes in to the market, remember that the counterparties that were directly involved in the deal may be left with significant spread risk in their book that will need to be managed.  Unexpected changes in price relationships can be exacerbated in the market as a result.

Bottom-line, there is more to this deal than meets the eye.  A simple expectation of lower prices due to hedging activity may not be the only market opportunity!

 

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By Jason Pearce

The Two-Edged Sword

Archimedes made a great statement about the power of leverage when he said, “Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.”  That’s a great quote…until it gets misapplied to the arena of speculation.  Context is everything.

If you’re gonna talk about the advantage of using leverage in the financial markets, you would be irresponsible if you didn’t address a subject that’s intrinsically linked to it: risk.  If you want to learn the correct way to use leverage, you need to consider more than just the potential gains that leverage can bring.  You have to consider the potential losses.

The pros know that the winners take care of themselves.  It’s the losers that have to be managed.  The problem is, too much leverage can make the losing trades unmanageable even if you’re actively protecting yourself with stop orders.  Leverage is the how the markets provide a trader with more than enough rope to hang himself.

Leverage Levels

Currently, a stock brokerage firm will allow customers to trade with leverage of 2-to-1.  This is done by providing a margin loan to the trader.  If a trader has $100,000 on deposit, the brokerage firm will loan him up to $100,000 and allow him to buy $200,000 worth of equities.

So a stock trader with margin could double his money on a stock that increases in value by 50%…and just as easily wipe out his stake if the price of the stock was cut in half.

Many people believe that trading commodities is far riskier than trading stocks.  What?!  Trading corn is riskier than trading Tesla?!  This notion was likely brought about by the fact the available leverage for commodity trading is significantly higher than the leverage for stocks. So the belief is half right; commodity trading can be risker, but that’s because of the leverage available, not the instrument being traded.

That margin requirement to trade a futures contract is often around 5% of the value of the underlying contract.  For instance, the E-mini S&P 500 is currently worth around $120,000.  The initial margin requirement is $5,500, which is just 4.5% of the contract’s value.  This would allow a futures trader to potentially leverage his account at a level of 20-to-1 where $100,000 on deposit can control as much as $2 million worth of futures contracts.

At a level of 20-to-1, a fully margined commodity account would make a fortune on a modest price increase.  The other side of that coin is that the trader could also be completely wiped out on a 5% adverse move in price.

Forex trading reaches a whole different level of leverage…and insanity.  Those sleazy online “bucket shops” that are always trying to sucker the public into currency trading offer traders leverage of 50-to-1…and 100-to-1…and sometimes even 200-to-1.

Just think about that in dollar terms.  A $100,000 deposit in a forex account could control $5 million, $10 million, or even $20 million worth of currency.

At 100-to-1 leverage, it only takes a 1% change in price to double you money or lose it all.  What could possibly go wrong?

Too Much of a Good Thing

Just as leverage can amplify investment gains, it also amplifies invest losses.  This is why you never see professional traders and money managers taking full advantage of the leverage being offered.

It’s also why you’ve never heard of a professional trader racking up a month or even a year with a +1,000% return.  To knock it out of the park like that, you’d have to take way too much risk.

As a matter of fact, one professional trader I know gets very concerned if he makes too much money over a certain period of time!  His thinking is that he must be taking on too much risk or using too much leverage if the gains are accruing that quickly.

Professional traders make their trades based on probabilities.  But they manage risk based on possibilities.  If it’s possible for profits to snowball quickly, then it’s possible for losses to snowball quickly as well.  To keep a losing streak from turning into an avalanche you’ve got to put limits on the amount of leverage used.

Bond Bubble Blowup

C.S. Lewis wrote, “Experience: that most brutal of teachers. But you learn, my God do you learn.”  I’ve had the pleasure of having Professor Experience personally tutor me when I attended the University of Hard Knocks.  My major was in What Not to Do When Trading.

Let me first say that mean reversion works…eventually.  But if you’re going to make a bet on it and hold on, the trick is to make sure your position is small enough to survive the waiting period.  The more leverage involved, the less staying power you have.

When I was a wise old trader in my twenties, I picked a fight with the bond market.  Confidence and hubris was running high because I’d just come off of a couple of successful trade campaigns in the grain market and the Japanese yen.  And now that the Treasury market was running away to record highs, I put them in the crosshairs and went short.

T-bonds were around 124-00 at the time, which is a value of $124,000 per contract.  So initially, I went short one contract for every $20k in account equity and figured I could safely hold a contract with a $20k cushion and ride out the storm without needing a protective stop.  Based on the contract value, I was leveraged at 6-to-1.

T-bonds just kept ripping higher and posted a record string of daily gains.  Three weeks after I went short, I experienced an intraday drawdown of a little over $5,500 per contract.  Perversely, my losses were ratcheting higher by the day while the probabilities of a reversal also increased.

But don’t confuse probable with possible.

The six-figure open loss caused me emotional turmoil.  My $20k cushion shrank to $14,500 per contract.  I was down, but not out.  But I now had a bond contract value of $129,500 with a cushion of $14,500, raising the leverage to nearly 9-to-1.

Out of the Frying Pan

I called up another “professional” trader I knew in order to get his take on things.  He asked me about my conviction on the trade.  I told him I was still bearish and bonds just had to crash after a run-up like this!  Somehow, an old floor trader saying popped up: “When in trouble, double”.

So I did.  Seriously, I was already bleeding with a six-figure loss and then I proceeded to double my exposure by selling more contracts short at 128-24 ($128,750 value).  By doing so, my equity cushion was suddenly $15,250 for every two contracts.  Two contracts at that price are worth $257,500.  That spiked the leverage on the position to nearly 17-to-1.

As you would expect, Treasuries only accelerated from there.  The market posted daily gains and even some new all-time highs for several consecutive trading days.

When my trading accounts were just a stone’s throw away from a margin call, I finally tapped out.  I lost about $9k for each initial short contract and another $4,250 for each ‘add-on’ short contract.  My attempt at The Big Short wiped out two-thirds of my equity ($13,250 for every $20k), meaning a total loss of several hundred thousand dollars on the books.

Oh, and it gets even better…

As fate would have it, I covered all of those short positions just one day before the final record high was set!  Bonds tanked the very next day and started the multi-month decline I was anticipating…but without me in it.

There are a lot of lessons to learn from this story: Don’t bet the farm on one big trade, don’t fight the trend, don’t trade without protective stops (or at least options to hedge), don’t depend on the opinions of others, etc.

But one lesson I want to bring highlight right now is that of using too much leverage.

Had I stuck with the original (flawed) plan, which was a fully leveraged position of 6-to-1, I would have still had to endure a wicked drawdown.  But I would have never been forced to choose between liquidating or meeting a margin call.

By adding to a losing position and tripling my leverage to nearly 17-to-1, my protective buffer of equity was removed.  I had no more wiggle room when the trade went further against me and I had to get out.

Bottom line: the amount of leveraged used was the only difference between being able to weather a major drawdown until I could eventually get out with a profit or being forced out early with major losses.

Miscalculating Risk

I stated earlier that too much leverage can make the losing trades unmanageable.  A lot of times, this is due to the false sense of security that protective stops can bring.  You may think you know what your risk on a trade is, but sometimes you can be wrong.  Very wrong.

Suppose Sensible Sam is watching the soybean market and he thinks it’s about to take off.  He has $100,000 in his account and wants to risk three percent of his equity on a soybean trade.  That means he’ll have to put a protective stop order in the market to knock him out if the market moves against him by $3,000.

So Sensible Sam goes long three 5,000 bushel soybean futures contracts at $9.98 and places a protective sell stop at $9.78, which is twenty cents ($1,000 per contract) below his entry price.  Although he’s risking just three percent of his equity, Sensible Sam is moderately leveraged at about 1.5-to-1 because he has actually purchased $149,700 worth of soybeans ($9.98-per-bushel x 15,000 bushels = $149,700) with his $100k account.

Along comes Gunslinger Gary.  He’s also looking at the same soybean market and wants to get in on the action.  He’s been burned before by risking way too much of his equity, but he still wants to capitalize on the expected move in beans.

Gunslinger Gary has a brilliant idea: buy a ton of contracts and set a really tight protective stop.  Perhaps he is even going to follow Sensible Sam’s lead and risk just three percent of his $100,000 account…but that’s where the similarities stop.

Gunslinger Gary buys twenty 5,000 bushel soybean futures contracts at $9.98 and places a really tight protective sell stop at $9.95, which is just three cents ($150 per contract) below his entry price.  Theoretically, he’s only risking three percent of his equity.  However, trouble is brewing because Gunslinger Gary is leveraged at 10-to-1.  He has actually purchased $998,000 worth of soybeans ($9.98-per-bushel x 100,000 bushels = $998,000) with his $100k account.

Maybe Gunslinger Gary’s protective stop placement actually makes sense because he’s using intra-day charts to time a quick exit.  That’s not what I’m concerned about.  But we can’t escape the fact that he’s substantially more leverage than Sensible Sam.

Let’s forget about the best-case scenario where beans go ripping higher right after these guys get in.  Consider what happens if the market drops instead.

What if Gunslinger Gary’s protective stop is elected and he gets three-cent slippage on the fill?  He’ll lose $6k instead of $3k.  That’s double what he thought the risk was.

Or what if he manages to stay in the trade but an adverse crop report hammers the beans down 20 cents in the afterhours market where slippage is even greater or beans gap down in the morning (if he’s using pit-session stops only)?

In this scenario, Sam would also get knocked out of his three soybean contracts and suffer the $3k loss.  But good ol’ Gunslinger Gary would get murdered.  The 20-cent loss on his twenty soybean contracts would cost him a whopping $20,000.  That one trade would wipe out one-fifth of his account.

Although I used a hypothetical scenario to show the damage that leverage can inflict on a losing trade, don’t think for one moment that it’s not a plausible scenario.

Ask anyone who’s ever traded grains in the summer or had a position on when a crop report came out and you’ll hear tales about the market instantly moving limit.  Sometimes, the market will even move lock limit.  If you’re on the wrong side of that move, it means you can’t even get out at the market price!

Currently, the CME set the limit for soybeans at 70 cents ($3,500 per contract).  That limit amount can get raised by 50% in a heartbeat.

The takeaway here is that leverage is just as important –maybe even more so- than protective stop placements when calculating your true market risk.  Yes, you should have protective stops.  But you should also have leverage limits.  Leverage is like medicine: a little bit can help you…but too much will kill you!

Highly-Leveraged Is Relative

Most traders have heard the famous story about how George Soros “broke the Bank of England” by betting against the British pound back in 1992.

Soros’ right-hand man, Stanley Druckenmiller, was the one that pitched Soros the idea of shorting Sterling.  Druckenmiller said that Soros taught him to “go for the jugular” when you have a very strong conviction on a trade and to ride a profit with huge leverage.

Obviously, the plan worked.  They made over $1.5 billion on that trade.

Now, what many people don’t know is the size of that leverage on the trade.  Druckenmiller suggested to Soros that that they put 100% of the fund in the trade.  Soros disagreed.  He said they should have 200% in the trade.

Having 200% means leverage of 2-to-1.  That’s not 10-to-1 or 20-to-1 like a lot of novice commodity traders use and it’s certainly not 50-to-1 or 100-to-1 like the snake oil FX brokers tell the public they can use, either.

Druckenmiller said in one interview that the leverage at Quantum (Soros’s hedge fund) rarely exceeds 3-to-1 or 4-to-1.  So if one of the best traders in history doesn’t go beyond 4-to-1 leverage, why the heck would a lesser trader think that going 10-to-1 or more is a good idea?

Do keep in mind that just because they leveraged 2-to-1 does not mean that they were risking the entire amount.  Soros is known for taking a quick loss without regret if the market proves him wrong.

Market Wizard Wisdom

Larry Hite is one of the Market Wizards interviewed Jack Schwager’s famous book.  On the subject of leverage, he said that, “…if you leverage more than 3-to-1 that you are a loser. Because we found that if you did 3 to 1 you would have, even with perfect knowledge, you could go down a third.”

So here we’ve got yet another successful trader with several decades of performance to back his reputation, and he’s telling traders that the maximum leverage that they should consider is 3-to-1.

There are only two reasons I can think of that a person would use higher leverage than what the pros use: ignorance or greed.  And once you are made aware of the risk of using high leverage, you can no longer claim ignorance for your excuse.

Protect Yourself

Brokerage firms want you to use the available leverage.  The more you trade, the more commissions they make.  Don’t think for a minute that they’re going to step in and tell you that you’re taking too much risk.

Sure, the brokerage firms will issue margin calls.  But that’s not about protecting you; it’s about protecting them.  Brokerage firms don’t mind if you are burning through your trading capital.  “Churn and burn, baby.”  It’s just when the flames get too close by putting them at risk of a potential deficit that they’ll step in and tell you to wire more money to your trading account or liquidate your positions.

Surely, the good ol’ US government is protecting you, right?  Well, consider this: The SEC just approved the launch of a 4x leverage ETF.

I wrote in a prior post about how leveraged ETFs are constructed as an easy way to the poorhouse.  You can be right on the underlying market and still lose money.  That’s the effect that double and especially triple leverage ETFs can have.

But now the government is going to allow us to trade in quadruple leverage ETFs?!  Maybe it would be more accurate to re-label these genius derivatives as WTFs

The point is that nobody is going to be as careful about protecting your capital as you are.  To be successful, a trader and investor must be proactive and accept personal responsibility.  Part of this includes understanding and setting limits on leverage.

It Can Get Worse

Do you have a trading system that you’ve back-tested over decades of data?  Have you tested it on out of sample data as well?  Have you run a Monte Carlo simulation on it, too?  That’s good.  You’ve done your homework.

I’m sure you also remembered to factor in commissions and slippage in order to get a better feel for real world trading.  You now know what sort of worst case drawdown would’ve occurred, which can help you determine your comfort level for the amount of leverage you’ll use to trade it.  Time to get trading.

Not so fast!

The well-respected trader Peter Brandt said, “A trader’s worst drawdown is the one yet occur.”

Consider that fact that the worst drawdown in your back-testing record or even your real-time track record got that title by being even worse than all the prior drawdowns that preceded it.  That means it’s possible that another drawdown can come along and steal that title at some point.

All records were made by breaking another record.   That can be both a good thing and a bad thing.  On the subject of drawdowns, it’s definitely a bad thing.

Storm Prep

One simple way that a trader can build a protective buffer is to prepare for a drawdown that’s double the size of the biggest one to date.  This means adjusting your risk-per-trade to a level that will allow you to endure such a losing streak.

Furthermore, you may want to calculate what your entire portfolio risk is.  This means looking at the effect of a worst-case-scenario where every position in every sector of your account gets stopped out with slippage.  This drawdown is your Portfolio Meltdown Level.  It rarely, if ever, will happen.  But you still need to be prepared for the possibility of it occurring.

Does that Portfolio Meltdown Level make you sick?  Well, it’s a good thing that you’re calculating it then!  You just discovered that you’ve been taking too much risk…and you’re lucky enough to have not found out from experience.  Dial the Portfolio Meltdown Level back down to your comfort level.  Figure out what you want to set for your maximum risk level for each trade, for each sector, and for your entire portfolio.

Preparing a worst-case scenario defense plan also means reigning in the amount of leverage used.  Just because you have protective stops in for your positions, doesn’t mean your maximum expected risk level is guaranteed.  If some of the rock stars of the trading world think the maximum leverage they should use is 3-to-1 or 4-to-1, then perhaps you should consider adopting these levels as your maximum leverage limits as well.

We don’t know when the storm will hit, but we do know that it’s inevitable that it will happen someday.  Your job as a trader is to make sure that you are taking the necessary precautions to survive it.  Remember that your probabilities of trading survival are inversely correlated to the levels of leverage that you use.


More Articles by Jason Pearce:

US Dollar: The New Bear Market?

Equities: US Against the World

Profiting From Failure: The Wash & Rinse Trade, Part II

Profiting From Failure: The Wash & Rinse Trade, Part I

How to Trade with Moving Averages, Part II

How to Trade with Moving Averages, Part I

Market Returns Do Not Equal Investment Returns with Leveraged ETFs

Is The Canadian Housing Market Bad for Canadian Banks?

2017: The Death Year for Stocks

Potential Bond Market Reversal Ahead

 

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