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Yield Curve Is Flattening But Which Spread Should I Trade?

There are many variations of the yield curve to trade, and it can be confusing which is the right one for your needs. So you may be wondering, which should I trade?

The answer is relatively simple, if you understand your personal capacity and tolerance for risk, and whether you are a long-term or short-term trader. Another consideration is a bit more practical, as some of the spreads may cost significantly more on a risk-return basis than others. So, this is your homework before you put your money to work.

The charts below show a bunch of different yield curve spreads involving the 2-year note as the front leg. Going clockwise, starting from the upper left chart, it includes the Ultra 30-year bond (3:1 ratio), the 5-year note (1:1 ratio), the 10-year note (2:1 ratio), and the 30-year bond (3:1 ratio). The chart also shows the range in price of the spread, with a high in March and a low in April of 2017.

So, from a risk perspective it’s clear that the spreads with bigger dollar ranges present more risk. These are the TUL and TUB spreads, which pair up the 2-year with the 30-year bond and ultra bond respectively. The TUL and TUB are also a bit more expensive to put on as well because there are more contracts necessary to execute the proper ratio trade, but the expense to return is much lower than the other two.

A large range would indicate more risk, depending upon the size of your account. A very large account would have greater flexibility, while a smaller account may be restrictive to certain spreads. Small accounts would find the TUT and TUF spreads more palatable.

The TUT and TUF spreads are also slower moving than the TUL and TUB, as they react more slowly to global macro events and changes in monetary policy. So, these spreads may be better for someone that is not as active a trader as others, or prefers position trading over swing trading styles.

The downward arrows indicate a flattening yield curve, so the appropriate strategy would be to short the spread. This means short the front leg, and go long the back leg. It’s a flattener trade when we have a downward sloping moving average. This simply implies that the front leg of the trade (2-year note) is weaker than the back leg, evaluated since the beginning of 2017. One can assume that longer term yields are falling faster than shorter term yields, and are likely to continue that way, so long as the trend is down.


So to sum it up, if you have a larger account and are a more active trader, then the TUL or TUB spreads may suit you. If you have a smaller account, or you prefer a trend trading style, then the TUT or TUF spread may be best for you.

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What Is The TUT Spread?

In a previous post on Yield Curve Trading I list all the popular yield curve spreads that institutional and professional traders watch. The TUT spread is the 2-year over the 10-year Treasury futures spread. It’s a pairs trade that’s the difference between the notional values of the two contracts (cash value of the contracts).

This spread is considered significant with regard to the shape of the yield curve, giving traders a clue as to where yields may be heading. The yield curve plots the yields of all the different maturity treasury products, from the 3-month to the 30-year. Economists use the shape of the yield curve to predict future economic conditions.

Is The Yield Curve Steepening or Flattening?

The basic strategy for yield curve trading is to determine whether the curve may steepen or flatten. This will provide you with the primary direction you want to trade. You go long the spread if you believe the curve will steepen, and short the spread if you believe it will flatten.

A steepening curve is one where long term yields are increasing faster than short term yields. And a flattening curve is one where short term yields are rising faster than long term yields. Keep in mind that the price of Treasury futures is inverse to yield.

How to Trade Steepeners and Flatteners

When you put on a steepener, you are going long the front leg of the spread (2-year) and short the back leg of the trade (10-year). Remember price is inverse yield, so you would be expecting the yield of the Front leg (2-year) to underperform the yield of the Back leg (10-year). So a steepener is used when you think longer term yields will be rising faster than shorter term yields.

When you put on a Flattener, you are going short the Front leg (2-year), and long the Back leg (10-year). You’re expecting shorter term yields to rise faster than longer term yields.

With a longer term notional chart of the TUT spread you can visualize the steepening and flattening of the yield curve. When trending up, the yield curve is steepening, and when trending down, it’s flattening..


Trading with the Proper DV01 Ratio

When trading the TUT, as when trading any of the yield curve trades using futures, you need to be aware of what the proper weighting is for the Front and Back legs. This is because you need to remove the price risk associated with the futures contract due to the non-linear relationship between price and yield. To do this we need to find out how much a contract changes in price for each basis point in yield. This is called the Dollar Value of One Basis Point or DV01. Once we have the DV01 of each contract we can divide one by the other to get the ratio. This will be the weighting, or ratio between the front and back legs.

The calculation for DV01 is a bit involved. You can use a spread sheet and devise your own calculator, or you can use one that the CME Group provides here.

The goal of the ratio is to create relatively equal sided trades in terms of yield. It’s similar to options trading where you attempt to make your trade delta neutral. In this case we can see that the DV01 for the 2-year is approximately 1/2 that of the 10-year DV01 ($37.04 and $78.90 respectively). So it will take two 2-year contracts for each 10-year contract to create a Dollar Value neutral trade.

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Dollar Value Hedging Treasury Futures

When we speak of hedging, what we’re really talking about is a pairs trade, where we go long one asset and short another. We hedge to take advantage of several key aspects of Treasury futures. The most important is the edge we get by eliminating the directional aspect of price (minimizes risk) and focusing instead on yield direction. This is important, because the fluctuations of price are very difficult to trade, but the direction of yield is simple due to the slow moving Federal Reserve monetary policies.

The problem we face as traders is how to isolate yield from price of the individual treasury futures contracts. The way we do that is by translating the dollar value of the treasury instrument to the yield. This is called the DV01, or dollar Value of One Basis Point (of yield). So, by calculating the DV01 of each side of the hedge, we can then divide one by the other to get a ratio, and this ratio will represent the relative size of each side of the trade, and we can round that number to give us the ratio of contracts on either side of the trade.

This process requires a formula, which is nicely represented as an Excel formula, making it super simple to calculate the DV01, and thus the ratio we are looking for. This ratio changes over time depending on the price and yield on the treasury instruments. So periodically we have to check this ratio to update the position sizes we take with trades, to make sure we are trading changes in yield and not price.

Here’s a diagram that shows the non-linear inverse relationship between price of a bond and yield. As the price of a bond goes down, the yield goes up in an accelerated fashion, when the price of a bond goes up, the yield goes down in a decelerated way. This shape creates a situation called convexity, which refers to the shape of the curve. The tangent line is an approximation of the price at maturity, called duration.

Calculating the DV01

There are two well known ways to calculate the DV01 of a treasury instrument (bill, note or bond). The first is to measure price sensitivity over a small incremental change in the security’s yield. The second way is using the treasury security’s modified duration. The duration method can be complicated, so we will focus on the yield sensitivity method, which is relatively simple.

The yield sensitivity method is accomplished by finding the difference between two absolute prices of the same treasury instrument over one basis point (bp) change in yield. Here’s the formula:


Using Excel’s PV function we can create a relatively simple tool to calculate DV01 of both sides of the pairs trade. All you have to do is input the current yield of the respective Treasury instruments. Below is a sheet that calculates the hedge ratio for the Notes over Bonds (NoB) trade. If you are interested in obtaining this Excel sheet, contact me and I will share it with you.


The hedge ratio rounds up, so the proper hedge of the 10-year Note vs the 30-year Bond is 2 to 1. So, using this ratio in your trade analysis removes the risk of trading non-linear price movements and instead trading only differences in yield. If you are interested in learning more about trading the yield curve I’m offering a course and mentoring program under the Learn tab

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Yield Curve Trading

Yield Curve trading using futures has been the bread and butter of large institutions and professional traders for decades. This type of spread trading offers excellent returns and hedging opportunities in one of the most liquid markets in the world, US Treasuries.

In our opinion, broader adoption to this type of trading into the retail market has been hampered due to the lack of intuitive, easy to use tools. Spreads by their very nature are difficult to understand because of the moving parts. But the strategies most traders use are quite simple and super-reliable.

We offer custom trading tools that make it simple to execute spread trades with futures using the TradeStation platform. The tools are intuitive and easy to use, allowing the trader to take full advantage of the strategies employed by professionals. Check out our course on Trading the Yield Curve, to get these tools, along with one-on-one training and mentoring.

One of the benefits of trading yield curve spreads besides the incredible liquidity and reliable strategies, is the margin offsets, or discounts, making the cost of executing a yield curve spread trade very small relative to the capital you put to work. This allows the trader flexibility to be risk savvy, yet carry sufficient leverage to achieve impressive returns on capital.

The Yield Curve as a Leading Indicator

Since the late 1980’s there has been significant research done across the industry and within the Federal Reserve that documents the empirical regularity that the slope of the yield curve reliably predicts future real economic activity. For example, every recession has been preceded by a flattening of the yield curve.

The slope of the yield curve is primarily influenced by the central banks’ monetary policy and inflation expectations. The Fed will raise rates to cool down heated economies, and lower rates to provide stimulus. So, steep yield curves reflect periods of stimulus, and flat curves reflect periods of tight monetary policy.

A practical way to model this is with yield curve spreads, like the difference between the 10-year bond and 3-month bill treasury rates, to calculate the probability of a recession in the US 12 months in advance. The spread makes a low approximately 12 months prior to a recession. This chart goes all the way back to 1959.

We can also model this using futures spreads like the TUT, or 2-year vs 10-year notes. Here’s a chart going back to the beginning of 2006, notice how well it correlates to the same period in the 10-year vs 3-month chart above, predicting the recession in 2009.

Yield Curve Strategies

The primary strategies employed by most professionals to determine the direction of the yield curve trade, look at whether the curve is steepening or flattening. A steep yield curve is the normal, healthy orientation of the curve, it occurs most often. The curve flattens usually as a consequence of the Federal Reserve policies, including rate hikes and liquidation of the balance sheet. These are policies that are employed in an attempt to cool down an exuberant market.

When we say go long the spread, like the TUT spread, we mean go long the shorter maturity leg (Front Leg) and short the longer maturity leg (Back Leg). The Front Leg is ALWAYS named first in the spread, so the TUT is the 2-year vs the 10-year note spread. So when we go long the TUT, we are long the 2-year and short the 10-year. We only go long when the yield curve is in a steepening mode, and we only take shorts when the yield curve is in a flattening mode.

Execution Risks

The risk in the yield curve strategy is measured using the DV01 (dollar value of a basis point), so you would calculate the DV01 of both the Front and Back Legs of the spread and find the ratio, this will determine the approximate ratio of contracts to use in the trade.

The CME Group does this calculation for you, and displays these ratios as a reference to traders on their website. The proper risk adjusted ratio to use for the TUT spread is 2:1, or two 2-year contracts for every one 10-year contract.

There are many other related yield curve trades using the various maturities, and each has an associated risk measure and recommended ratio of Front to Back Leg position size. By using this ratio, you more or less eliminate movement of the spread due to price, and isolate instead the movement of yield. Here are the popular yield curve trades using treasury futures and TradeStation symbols and the calculated DV01 ratio as of April 2017.

Spread Name Front Leg Back Leg CME Ratio
TUF 2YR (TU) 5YR (FV) 1:1
TUT 2YR (TU) 10YR (TY) 2:1
TUB 2YR (TU) 30YR Bond (US) 3:1
TUL 2YR (TU) 30YR Ultra Bond (UB) 3:1
FYT 5YR (FV) 10YR (TY) 3:2
FOB 5YR (FV) 30YR Bond (US) 3:1
FOL 5YR (FV) 30YR Ultra Bond (UB) 3:1
NOB 10YR (TY) 30YR Bond (US) 2:1
NOL 10YR (TY) 10YR Ultra Bond (TEN) 3:1
BOB 30YR Bond (US) 30YR Ultra Bond (UB) 3:1


Is The Yield Curve Flattening or Steepening

So, the strategy is simple, you go long the spread when the yield curve is steepening, and short when it’s flattening. But how can you tell if the yield curve is steepening or flattening? A steepening curve is the predominant situation, in other words, long term rates are usually higher than shorter term rates, probably 70% of the time. But occasionally, when the Fed is attempting to reel in a market because of over inflation concerns, they might increase short term rates, causing the yield curve to flatten.

The big question in terms of flattening or steepening is, what’s the time frame you are trading in? If you are trading very short term, by that I mean similar to a swing trader, where trades are open for a couple days to a couple weeks, then your idea of steepening or flattening may be very different from someone trading long term, like a position trader.

I trade short term, so I want a measure that effectively captures the general direction of the yield curve, so that the choice of whether to go long or short, is for the most part coincident with the direction of the yield curve. This will give me the best probability of a successful trade, kind of like trading with the trend, the trend is you friend. So, I use the TUT or TUB spread weekly chart, and add a 2 line moving average, where the fast line is set to 25 and the slow line set to 30. I then look for cross overs to determine when the yield curve is changing direction.

The TUB spread covers almost the entire yield curve, where the TUT spread covers only a portion of the shorter term yields. You may have to experiment with this to find the best indicator. If you are a NOB trader, then maybe you are only interested in the upper end of the curve, so the FOB might be a better choice.

If the moving average slope is not very big, then you might want to hold on to the current strategy of steepening or flattening. Also, depending upon your entry strategy, it might make sense to favor either steepening or flattening. You’ll have to do the back testing to determine your own rules. I have developed a large set of conditions based on about a decade of trading yield curve spreads, along with detailed, multi-time frame analysis.

Here’s an example of using a notional chart of the FOB with 2 moving averages to determine the strategy to employ.

There are many ways to determine when to switch strategies. There are also effective sub strategies that layer on top of the steepening/flattening strategy that are very effective as well. One example might be trading only US economic reports and fading the move, or trading with the direction of the move.

If you would like to learn how to trade the yield curve, and obtain our tools that make trading it simple and intuitive, then click here to sign up for our one-on-one training and mentoring program.

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Statistical Arbitrage Basic Strategy

Statistical Arbitrage is a pairs or spread trading strategy, predominately used by hedge funds, investment banks, and professional traders. The strategy involves tracking the difference in notional value between two highly correlated instruments, like Silver and Gold futures, or the NoB spread, which is a trade between the 10 year and 30 year treasury futures contracts. The notional value is the actual cash value of a futures contract. Statistical Arbitrageurs trade the notional difference of the pair. Here is how you calculate the notional value of a futures contract, and then the notional difference between a trading pair:

Notional Value = Current Price x Big Point Value

Notional Difference A & B = Notional A - Notional B

There are three key features in this strategy. The first is that when the difference in value between a trading pair changes in a statistically significant manner, perhaps due to some market shock, there is a high probability that that change will regress back to an average or statistical mean value. There are mathematical proofs that show the probability of regressing back to the mean is 75%. Second, futures have tremendous leverage, presenting an opportunity for high return on capital. And third, most futures brokers provide a substantial discount on the total margin of a pair due to perceived reduced risk, this means pairs trades use much smaller amounts of trading capital, so more flexible risk management can be employed.[/vc_column_text]

This is a classical regression to the mean strategy, where the difference between prices is tracked, rather than just a single price. The pairs must be highly correlated assets. So, if ABC is positively correlated with CBA, and suddenly ABC is up 20 points, while CBA is down 20 points, we can assume this price dislocation is an unusual and a temporary condition, that will eventually revert back to a mean. Profit is derived from taking a position during that regression by going long the under performing asset, and short the over performing one. As they regress, profit is realized.

When selecting pairs to trade, it can be very important to draw on fundamentals, as well as statistics, to help identify relationships between two instruments. Start by pairing one instrument in a particular sector or industry with an equal dollar value and correlated instrument, typically in the same sector or industry. Look for instruments that are not only highly correlated, but also trade with good liquidity, can be easily shorted, and with minimal slippage. Example pairs might include futures contracts for Gold and Silver, Crude Oil and Gasoline, Treasury Notes and Bonds.

When selecting pairs to trade, it can be very important to draw on fundamentals, as well as statistics, to help identify relationships between two instruments. Start by pairing one instrument in a particular sector or industry with an equal dollar value and correlated instrument, typically in the same sector or industry. Look for instruments that are not only highly correlated, but also trade with good liquidity, can be easily shorted, and with minimal slippage. Example pairs might include futures contracts for Gold and Silver, Crude Oil and Gasoline, Treasury Notes and Bonds.

Determining how well a pair of assets are correlated is important to determining the viability of pair.  Remember, pairs with a high degree of historical correlation have strong regressive tendencies (75% or higher). This presents an incredible edge to traders.

A correlation coefficient is a statistical method that measures how well the price of a pair of assets moves relative to each other tick by tick. The more they move together, the higher the correlation coefficient. Values of the correlation coefficient range from -1 to +1; with a value of +1 representing a perfect positive correlation (two instruments move in the same direction every tick), a value of 0 representing no correlation, and a value of -1 meaning perfect negative correlation (When two instruments move in perfect inverse to one another).

Correlations of 0.75 or above are often used as a benchmark for Statistical Arbitrage traders. Correlation less than 0.5 is generally looked upon as a weak correlation. Factors that can weaken correlation between a pair over time include supply and demand factors, politics, interest rates, economic growth, environmental factors, etc.

To tell whether a divergence is worth placing a trade, we need to measure the move using a statistical tool. The Z-Score is often used for this, it is a measure of a price movement relative to its mean or average price. Specifically, the Z-Score is calculated by taking the the difference between the current price and the average price, and then dividing that by the standard deviation of the current price over a specific period of time. We calculate the Z-Score this way:

Z-Score = (price - Avg( price, length)) / StdDev(price, length)

A common trading strategy is to watch over bought and over sold conditions on the Z-Score when it exceeds plus or minus 1.5 to 2 standard deviations. For example; one would short the pair if the Z-Score moved above +2 standard deviations, and go long should it fall below -2 standard deviations.

Standard deviation is a statistical concept that shows how a specific set of prices are spread around an average value. Statistically, in a normal bell curve distribution of prices; 68% of prices should fall within +/- one standard deviation of the mean, 95% of prices should fall within +/- two standard deviations of the mean, and 99.75% of prices should fall within +/- three standard deviations of the mean.

Through back testing and optimization strategies, trading opportunities can be found when the notional value diverges “X” number of standard deviations from the mean. You may further find that adding filters or price sizing strategies will further improve the probability of a successful trade.

Technical analysis, fundamental analysis, or a combination of the two can be used to find trading opportunities. Fundamental factors could include major economic events, long-term trends, monetary policy, growing seasons, etc. Technical analysis might involve one or more of the following; statistical measures, analyzing chart patterns, moving averages, stochastic, RSI’s, commercial indicators, etc.

Pairs trading with statistical arbitrage is a great market-neutral strategy for high probability returns with reduced risk, but it’s necessary to have access to quality tools to model your opinions and execute the trades accurately and consistently. Also, finding a rock solid premise for trading a pair is important. In fact, the best pairs trades are ones that adhere to a fundamental condition of the pairs, or the market they are in. These conditions might determine exclusive trade direction, execution times, seasonality, or any number of domain-specific reasons that can make trading that pair extraordinary.

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Why Trade Futures Over Stocks – Restrictions

Have you ever been locked out of trading because of a trading violation? Maybe your broker claimed you were a patterned day trader?

Or have you missed an opportunity due to short selling restrictions? Perhaps shares weren’t available to short? This happens a lot with small priced stocks, but can even happen with big stocks like Tesla or Apple.

Let’s look at minimum account size.

You don’t want to be tagged as a patterned day trader. A pattern day trader is someone who executes 4 or more round trip trades in stocks or ETFs within a week.

For example, you bought AAPL in the morning and then sold it a few hours later, and then the next day you shorted SPY and bought it back that same day. If you do that 4 times in the span of a week, you will be tagged a patterned day trader and your broker will shut you down and not allow you to take any new positions for 90 days…and there’s nothing you can do about it.

There is a way around this…you need to have a minimum of $25,000 in your brokerage account. Then the pattern day trader rules are lifted.

A futures trader isn’t required to meet this minimum account size. In fact, as long as you maintain the minimum margin for your positions, you can trade as frequently as you like at a size suitable to your trading needs.

Margin Restrictions

As an equity trader, you can only trade up to 4X your maintenance margin on an intra-day basis. So, if you have $30,000 buying power in your account, you can only trade up to a value of $120,000.

Exceed this amount, and margin calls may further limit your buying power and ability to trade.

In futures that same margin may allow you to trade a much larger notional value. For example, if you wanted to buy e-mini S&P 500 futures, you’d post initial margin for each contract, currently $4,750.

So, with $30,000 you could buy 6 contracts, which would allow you to control over $650K of notional value at the current index prices (12/9/2016). And you’d still have some buying power left.

That’s quite a difference in the amount you could control; $120k for equities, and $650k for futures. But let’s make something clear, nobody is saying go out there and maximize your available buying power, but it becomes clear that you can do a lot more with less by trading futures over stocks.

Shorting is a Huge Differentiator

Probably the biggest issue with equity traders these days is shorting a stock, that’s because there must be shares available to trade, and there are many reasons why shares may not be available to trade.

I had to shut down a robotic trading system that traded the wildly popular company Telsa, because there were many instances that the system couldn’t short the stock, because the broker didn’t have shares to short.

In comparison, a futures trader doesn’t have these problems. You can short any futures contract as easily as you can go long. In some cases, the government may even establish an uptick rule, preventing you from shorting a stock all together. This would never happen with futures.

And finally, when a trader shorts a stock, they need an uptick before you can short, which means if the market is falling sharply, a stock trader may never get a chance to enter a short position.

So, why miss out on another opportunity because of restrictions. The clear winner here is futures.

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2 Trading Myths Debunked

On the face of things, these 2 myths seem logical, but they are not. And once you learn why, you will have a whole new appreciation for volatility and how to use it to your advantage.

MYTH #1 if your strategy consistently loses 70% of the time, all you have to do is switch your orders, and buy, when you would normally sell. Then you would be a 70% winner.
MYTH #2 If markets are random, just flip a coin to decide when to buy or sell, heads you buy, tails you sell. You’ll be right 50% of the time.

Both of these sound correct from a statistical point of view, however each of these myths is not taking into account some very important information that is present with every trade you make.

Ok, let’s suppose you’re trading Apple and your strategy calls for a 10 cent stop loss. We can see from this price chart from yesterday (October 14th) that any trade with a 10 cent stop loss would have been stopped out on a regular basis. That’s because Apple’s price ranges 30-40 cents throughout the day.

We can see this by looking at the Average True Range (ATR) indicator, which measures volatility and is an excellent way to get a handle on setting an appropriate stop. The ATR was very high in the morning, then settled out later in the day…this is quite typical.

Screen SharingScreenSnapz358

The ATR was at a peak of about 33 around 10:30 AM, then finally settled to about 20 for the remainder of the day. The value of the ATR is in cents, measured as an average range using the previous 14 bars.

Now let’s consider the coin flip myth. While it’s true that a trade taken anywhere during the day has approximately a 50% chance of going up or down, when you add in the 10 cent stop, and consider the amount of volatility, that 50% chance goes down to 0%.

Now, if you were to widen your stop to be something close to the ATR, then we would start approaching that 50% theoretical rate of choosing the right direction. And the wider we make it, the closer we get. So, by having a tight stop loss, you may think you are controlling risk, when in fact you are guaranteeing that your trade is going to lose nearly all the time.

Even if we took on myth #2, and switch our buy and sell orders, that pesky volatility, and out tight stop loss, would give us pretty much the same result, a big losing trade, one after the other. Even if the trade was perfectly timed.

So, what’s the solution?

You need to know where volatility is at all times. Not only will it tell you where your stop needs to be, but it will also clue you into an appropriately sized position. In general, higher volatility means wider stops and smaller positions, and low volatility is the opposite, smaller stops and larger positions.

These dynamic adjustments will move you closer to the trading sweet spot.

As far as myth #2 is concerned, the coin flip…volatility is only one of the factors you must consider. You would have to time your trades perfectly to gain an edge, a random trade simply wouldn’t cut it. If you go long at the daily peaks, you’re gonna suffer.

So, one way you can overcome this is to measure momentum, in an attempt to find the peaks and valleys of price action. Of course you’ll never be perfect, pin pointing the exact bottoms and tops of pivots is virtually impossible. So, what do you do?

Let price come to you, and except the fact that you are going to lose some trades.
Use momentum to get you somewhere in the ball park for timing your entry, and ATR to adjust your stop and position size.
You also have to accept that when you settle on some value for momentum, you might not hit an extreme during the day, and thus there will be no trade setups. That can be frustrating, but you have to suck it up and take it. On the other hand, there will be days when the market simply goes nuts, and runs straight up or down, and you never find a spot to enter, or you enter what your indicator says should be a top, but then it just continues going up.

Again, you need to come to grips with the fact that you can’t win every trade. You may not even be able to win 50% of the trades you take. So, long as your winning trades make more money than your losing trades, you’ll make money. But that’s easier said than done.

Is ATR the only way to measure volatility?

The ATR measures volatility in terms of price action, but that’s only part of the available information that makes up the volatility of a security. Let’s face it, using 14 bars before you can determine where volatility is can make your trading choices always behind the gun, lacking real time info.

Another way to assess volatility is through liquidity. You measure liquidity in terms of the size and frequency of limit orders placed by other traders waiting to take your trade. This is a far more complex topic that I will leave for another email. But let’s just say that there’s a direct correlation between the amount of liquidity and the amount of volatility.

At least now, you have a new understanding of volatility, and some ways to use it, and hopefully a new found skepticism. Sometimes things that seem logical, are missing key bits of information. Do your homework, and preserve your capital at all costs, before you chase myths that promise easy profits.

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How Trade Size Impacts Returns

I have often said that if you want to make money trading, then reduce your size. And this is true, as most of us tend to over-leverage. But simply reducing your size isn’t the most effective strategy…how much you reduce it, and the way you size your positions can have significant impact to your returns as well.

So, here I’m going to examine the effect of different trade size strategies that you can employ in your trading that may make your road to riches a bit more enjoyable.


Most books tell you your position size should depend on the amount of risk you want to take, in other words, size your position based on how much you can tolerate losing. And in my experience, that’s probably going to be the end result…losing that amount of money. If we would just step off that band wagon of managing risk, and start thinking more in terms of managing our winners, we would be far better off.

There are lot’s of ways to control the size of you position, I’m going to examine four, and they are:

The trading strategy we will use should be inconsequential, so let’s make it super simplistic, we’ll use a counter trend model employing the Relative Strength Index (RSI) to detect overbought and oversold conditions. This is perhaps the most popular indicator in every chartists heads, and the one most often referred to by the talking heads on CNBC. Of course that’s no ringing endorsement, but we’ll go with it!

In our strategy we’ll only look at long trades, and use the daily timeframe of the SPDR S&P 500 ETF (SPY) going back to October 25th, 1995, that should provide enough data points to make this exercise relevant. We will start with $100k of initial capital to establish a baseline for comparison. I have also included slippage and commission so that the results more closely reflect real life conditions.

Here’s the basic strategy:

Indicator Action Input Value
Buy Rule RSI(2) Crosses below 30
Sell Rule RSI(2) Crosses above 70
Share Size Strategies using a basic RSI trading strategy
Share Size Strategies using a basic RSI trading strategy

Fixed Share Amount
This is a non-risk based method that buys 500 shares of SPY for every trading signal given by the strategy.

fixed shares perf

fixed share stats

fixed shares annual

fixed share equity

Fixed Dollar Amount
This is the second non-risk based method that invests $100,000 of SPY for every trading signal given by the strategy.

fixed dollar perf

fixed dollar stats

fixed dollar annual

fixed dollar equity

Fixed Fractional
The fixed-fractional method is one of two formulas that we examined that incorporates a risk component into the denominator of the trade-size calculation. In this formula, the risk component is decided as a point amount that you would be comfortable risking on a trade. In this test we risked 2 percent of the capital in each trade. Some call this method compounding.

fixed fractional perf

fixed fractional stats

fixed fractional annual

fixed fractional equity

Percent Volatility
The percent-volatility method was our second risk-based trade-size formula. The risk component in this formula was once again in the divisor, but this time it is computed from the security’s (SPYs) average true range. So as the volatility of the security increases, we take a smaller trade size and as volatility decreases we take a larger trade size. We risked 2 percent of the capital in each trade and divided it by the average true range, times an ATR multiple.

percent vol perf

percent vol stats

percent vol annual

percent vol equity

Analysis of Different Strategies

We focused on two types of trade-size methods in this paper. The fixed-fractional and percent-volatility methods each incorporate an element of risk into the divisor. As we mentioned earlier, as the risk element grows (shrinks) in size, the position would be smaller (larger). The other trade-size approaches we analyzed were two non-risk-based techniques: the fixed-share amount and fixed-dollar amount. In the fixed-share approach, we invested 500 shares per trade, and in the fixed-dollar amount, we invested $25,000 per trade. These values did not change over the time period tested.

The main purpose of this paper was to compare trade-size methods that incorporate risk to methods that do not. Risk is a vital concept and can be addressed through different modes of portfolio management. With respect to position size, risk can be a personal dollar-amount preference, as was the case with fixed-fractional formula, or it can be a characteristic (average true range) of the security, as was the case with the percent-volatility formula. One factor that distinguishes the fixed-fractional formula from the percent-volatility formula is that the percent-volatility formula is a dynamic type of position sizing; the trade size adjusts as the volatility of the security increases or decreases. The fixed fractional is dependent on your personal risk preference in terms of dollars per trade. Both the fixed-share and fixed-dollar methods use a static trade size and do not consider any type of risk in the calculations.

The performance impact these trade-size methods had on the RSI strategy positively favored fixed fractional and percent volatility over the fixed-share and fixed-dollar trade sizes.

  • The fixed-fractional and percent-volatility methods had the highest annual returns of 5.51% and 6.05% when compared to the fixed-share and fixed-dollar methods, which only had annual returns of 3.30% and 2.06%.
  • The net profit values of the fixed-fractional formula (Net Profit: $174,414) and percent-volatility formula (Net Profit: $204,017) were also greater than the fixed-share method (Net Profit: $83,600) and fixed-dollar method (Net Profit: $42,217).
  • The fixed-fractional and percent-volatility methods also had the best risk-adjusted returns, with Sharpe ratios of .13 and .17. The fixed-share and fixed-dollar amount methods had negative Sharpe ratios of .09 and .01, although their total return and annual returns were positive for the period tested.


The fixed-fractional and percent-volatility methods only scrape the surface in terms of what is possible in developing trade-size formulas. For example, we could have easily modified the fixed-fractional method to have a dynamic risk amount in the denominator of the formula that adjusts to levels of percentage drawdown that the strategy experiences. Good money management is acknowledged as an important part of strategy trading. Through creative thinking and an understanding of how a risk component can affect the size of a position and, in effect, the performance of the strategy, one can experiment with this area of money management to help improve the risk-and-reward statistics of a trading strategy.

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How To Analyze Gaps for Profitable Trade Strategies – Part 1

Gaps are a popular pattern for market technicians to analyze and from which to profit. The reason is that gaps are easy to identify, and the specific characteristics of a gap are easy to quantify. This means we can apply statistical analysis on the various aspects of a gap to determine if there is opportunity.

But before we get into the strategies around gaps, we must understand exactly what a gap is, and how we can deconstruct them so that we can identify an edge.

Basically there are two types of gaps; gap ups and gap downs. Don’t confuse this with bullish or bearish, because we won’t know whether the market is bullish or bearish until the post gap analysis. And there are odds associated with a post bullish or bearish move, based on the gap characteristics.

We will develop a gap language so that we can easily communicate the type of gap, and that language is very precise. That’s what this video is all about. Once we have the language down, we can then model a strategy that reflects these gap aspects and backtest scenarios, so that we can identify statistically probable trades.