When at all possible, it is preferable to use the most liquid (actively traded) ETF for the specific index, sector, commodity, etc.. that you wish to trade. However, when a thinly traded ETF is the only option available, the use of limit orders may be a better option than market orders although there are pros and cons to each. For example, if a thinly traded ETF that you were looking to buy currently had a bid price of 10.40 and an asking price of 10.50, a market order to buy would most likely fill at or near the 10.50 price, possibly higher, depending on the number of shares you are purchasing. Let’s say you placed an order to buy 500 shares but there were only 200 shares being offered at the 10.50 ask price, then your first 200 shares should fill at 10.50 while the remaining 300 shares could fill at an even higher price due to slippage on the trade. With a spread of 10 cents, even if all of your shares filled at 10.50, you have immediately “lost” (on paper) about 1% on the trade just due to spreads alone as you would only get 10.40, possibly less, if you immediately sold those shares.

Therefore, the use of a limit order may be beneficial over a market order in this case. For example, one could place a limit order to buy the 500 shares at a price of 10.45, splitting the different between the bid & the ask price. The benefit to doing so would be that your order would only be filled at a price of 10.45 or better. However, there are two potential disadvantages to using a limit order in such a scenario: First, your order may or may not be filled. If you felt strong about entering this position, you risk that the price continues to move higher without your order filling and you must either decide to be comfortable not owning the position if it continues to move higher or to pull your limit order and “chase” the stock higher via another limit order or a market order.

The other potential pitfall of a limit order on a thinly traded stock or ETF would be a partial fill. In the example above, maybe your order to buy 500 shares at 10.45 is filled but only for 100 shares or less. If the order was a day order (good until the close of that trading session) and the remaining shares are not filled, then you will end up with a much smaller position that you originally wanted. Yes, a GTC order might fill the remaining shares in the coming days or weeks but with separate commission costs as most brokers will only aggregate fills, in calculating the total commission, on separate lots for a limit order if the fills on all lots occurred during the same trading session.

One final consideration regarding the liquidity of ETFs is that at times, ETFs that normally have large spreads due to low trading volumes can experience very tight spreads during periods of high trading volumes, such as a breakout in a sector or some news driven event that suddenly draws a lot of traders in. You may purchase that ETF with a market order noticing that the spreads are tight, only to find it hard to exit the position at a favorable price only a few days or weeks later after the volume surge has dried up. Therefore, it is best to know the history and average trading volume of the ETFs/ETNs that you plan to trade and account for any slippage or other liquidity issues that you might run into when formulating your trading plan.

ETF Tax Tutorial: Complete List Of ETFs That Issue A K-1

An Exchange Traded Product, or ETF, is a type of security that is derivatively-priced and which trades intra-day on a national securities exchange. Exchange Traded Products are derivatively-priced, where the value is derived from another investment instruments such as a commodity, currency, share price or interest rate. Generally, exchange traded products are benchmarked to stocks, commodities, indices or they can be actively managed funds. Exchange traded products include exchange traded funds (ETFs), exchange traded vehicles (ETVs), exchange traded notes (ETNs) and certificates.

The most popular exchange traded product is the exchange traded fund (ETF). These are securities that track an index, commodity or basket of assets. Exchange traded notes, on the other hand, are a type of unsecured, unsubordinated debt security. The value of an ETN can be affected by the credit rating of the issuer and not just changes in the underlying index. Exchange traded products have experienced huge growth since they were introduced. Different tax treatment applies to the various types of exchange traded products.

Because it trades like a stock, an ETF does not have its net asset value (NAV) calculated every day like a mutual fund does. By owning an ETF, you get the diversification of an index fund as well as the ability to sell short, buy on margin and purchase as little as one share. Another advantage is that the expense ratios for most ETFs are lower than those of the average mutual fund. When buying and selling ETFs, you have to pay the same commission to your broker that you’d pay on any regular order. One of the most widely known ETFs is called the Spider (SPDR), which tracks the S&P 500 index and trades under the symbol SPY.

Tonight I received the following inquiry on the UCO short-term trade idea posted earlier today:

Q: I understand the price deterioration on a leverage ETF….does same apply for Non-leveraged ones? I think USO would be an example of this?

My reply below speaks generically to the use of leveraged vs. non-leverage ETPs in general. USO and other ETPs (Exchange Traded Products such as ETFs, ETNs…. click here to learn more about ETPs) that track a single commodity or basket of commodities typically do so via futures contracts, which have their own unique issues that can lead to variations in the return of the underlying commodity (spot price) and the actual performance of the tracking ETP. Those issues are an entirely different & complex conversation by themselves and not discussed below.

A: Not really. The price decay on leveraged ETFs is due to simple math and for the most part, does not affect the non-leveraged ETFs. Most non-leveraged tracking ETFs are pretty much efficient, less the small operating costs that they all must occur. You could Google some articles that explain why the leveraged ETFs decay but essentially, it’s something like this:

If XYZ is a 2x ETF that tracks the ABC index and the index goes up 3% today, then XYZ goes up 6%. $100k in ABC is now worth $103k & XYZ is worth $106k. Tomorrow the index drops by 3%. ABC is now worth $99.91 (103 x 97%) while XYZ is worth $99.64 (106 x 94%). Essentially, the longer a leveraged ETF is held, the larger the decay, or under-performance of the actual underlying index or sector that the leveraged ETF is tracking as the math works against it. Obviously, the more leverage employed (e.g. 3x vs. 2x), the more pronounced and rapid is the decay. This phenomenon holds true equally for both long (bullish) and short (bearish) leveraged ETFs.

One important factor to be aware of is that the more volatile the underlying (index, commodity or sector), the more pronounced and accelerated the decay will be. For example, in a perfect world, if the underlying were to go straight up every day without any down days, the leverage ETF would actually perform BETTER than expected. For example, if you put $100 in a 3x leverage long ETF and the underlying index went up 3% every day for 5 days straight, you would have nearly $116, not just $115. ($100 X 1.03 x 1.03 x 1.03 x 1.03 x 1.03 = $115.93). Of course, the markets aren’t perfect (even when lifted by the heavy hand of the Fed) so even in an decent uptrend, there are plenty of down days. Essentially, the more down days (or UP days when using leveraged short/bearish ETFs) and the larger the magnitude of these “down” days, the worse the decay will be over time.

When you trade a very volatile index, such as the gold miners or shipping stocks, the day to day percentage swings are often quite large and at times, extremely large. Therefore, NUGT (3x long gold mining ETF) will experience extensive decay or tracking error (when compared to GDX, the 1x or non-leveraged gold miners ETF). On the flip-side, an investment in a 2x leverage ETF for a relatively low volatility index during a fairly stable trend will still have some decay but quite minimal, at least over a relatively short period of time (weeks or even a few months).

Bottom line is that the leveraged ETFs, especially the 3x long & short and especially those tracking a commodity, sector or index experiencing high volatility such as crude oil as well as gold & silver mining stocks have been lately, are prone to the highest degree of price decay due to the combination of the leverage employed and the large back & forth price swings. As such, the leveraged ETFs are best used for intraday (in & out before the close) trades.

If one were bullish on, say, small cap stocks and wanted to take a large position with an expected holding period of 3-6+ months, they would most likely be better off buying $30k of IWM (1x Russell 2000) versus $15k of UWM (2x Russell 2000) or $10k of TNA (3x Russell 2000), particularly if the Russell 2000 Index traded sideways to lower over those 3-6+ months. Should the $RUT trade sideways in a choppy trading range for 6 months & end up exactly where it began, for the most part (plus dividends & minus operating expenses) the IWM trade would be flat while the UWM & TNA trades would almost certainly be at a loss.

Beta-Adjusted Position Sizing is a term that I use for to process of determining how much trading capital to deploy to each of my trades.  Beta is the term used in the financial markets to compare the price fluctuations of a security (stock, ETF, mutual fund, etc..) against it’s benchmark.  The most common benchmark used is the S&P500 although a stock’s beta can be measured against any specific index or benchmark (e.g. comparing SPG (Simon Property Group, a large REIT, to the DJ REIT sector).  However, for the purpose of determining my position size, I typically use the broad market (S&P 500 Index).

Take GDX for example.  Yesterday I had mentioned that fact that I completely disregard the big bullish engulfing candlestick put in on the daily chart since engulfing candlesticks are very common with the big price swings in GDX.  If you click to expand this chart, you will notice that the day to day swings are much larger than the daily moves in the SPX.  This gives GDX (forget about any correlations or lack thereof to the SPX for this purpose) a very high beta.

Another tool to use is the Average True Range (ATR) indicator on your charts but honestly, you should just be able to eyeball a chart and see how volatile any stock or ETF has traded in the past.  Most importantly, if you are looking at a stock in a pattern like a bullish falling wedge, you must realize that prices continue to be compressed as the wedge forms so don’t assume that lower volatility will continue going forward. On the contrary, falling wedge patterns are like coiled springs and once they trigger (break-out) then volatility often increases very sharply, very fast.

I don’t use any hard formula when determining my position size, maybe because I’ve been trading and investing for so many years that it becomes an automatic, especially as I often trade many of the same stocks repeatedly over time.  However, as a rookie trader or investor, I believe that it is critical to your success that you adjust your position size according to both the potential risk AND return (which ALWAYS go hand in hand).

For example, one of my recent trades was the CVM long set-up that was posted on Jan 12th (2012) while just breaking out of a nice falling channel.  CVM was a .34c stock back then which rule #1, DON’T USE FULL POSITION SIZES FOR PENNY STOCKS (sorry to yell, just wanted to make that clear).  The top of my final target zone was at .48c, or about 41% higher.  This trade hit that level just 3 days later (it actually stopped and reversed at .49c).  However, if that trade didn’t work out and the breakout failed, I would not have been surprised to see it drop 10%+ in no time flat.  Therefore, on a trade like that, being a low-priced stock with a volatile trading history, if you would normally put, say $10k into a SPY or GE trade, then you might only want to put $2500-$3k (maybe even less) into CVM.  Think of it this way, if you are looking at a potential gain of 40% on the trade, then $3k x 40% = $1,200 profit.  That is equivalent to a 12% gain on your $10k SPY trade (and when was the last time the SPY when up 12% in 3 days?)

Also make sure to beta-adjust your ETF trades, accounting not only for any leverage (2x or 3x long or short ETF’s) but also the sector.  That NUGT short that I have on right now is not only leveraged 3x against the gold miner sector but that sector itself is one of the most volatile sectors out there to boot.  Therefore, I not only lower the position size that I take on the trade but I also widen my stops considerably to account for both the leverage as well as the inherent volatility in the sector.  On a final note, it works the other way too.  For example, if I were to trade the TLT (long-term US gov’t bond ETF), then I might use about 1 1/2 times my usually position size in order to account for the lower than usual expected gains and volatility.