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The Difference Between Beta And Delta And Why We Care

Beta is one of the classic measurements within the financial industry. It is one of the first measurements shown on Yahoo Finance, right under the bid-ask and earnings estimate. Participants use it as a general gauge of market-related risk associated with an investment. As a reminder, an investment with a Beta of 0.8 is generally supposed to participate in 80% of a market move. So if the market increases 10% the investment should move up 8% and in a down 10% environment it should move down 8%. If only it was so simple… Beta is so well known that most people have not reviewed the basics of its calculation in a while, nor do they remember its drawbacks – let’s do some Beta 101! Beta is essentially the slope of the best fit line between the investment being studied (one axis of the graph) and the market (the other axis of the graph). The Beta for both examples above are 1, suggesting that each security very closely follows the market. However, in practice these two Betas are very different. The graph on the left demonstrates that the investment and the market have historically moved in tandem, as the best fit line approaches each plotted point very closely (i.e., very high correlation). Thus, the Beta of 1 is meaningful and appears to be predictive of the future. The graph on the right demonstrates a relatively random relationship between the investment and the market (i.e., low correlation); by some coincidence, the “best fit line” happens to lead to a perfect Beta of 1, which of course is meaningless – there is no reason to expect the investment and the market to move in tandem in the future. This illustration demonstrates one of the major drawbacks with Beta. If correlation is low, Beta is not useful and can even be misleading. Another drawback of Beta is related to the traditional compliance disclosure that past results are no guarantee of future results – Beta is a formulaic calculation based on historical measurements, and thus not necessarily a great predictor of what is to come. Take a look at Chipotle’s (NYSE: CMG ) 1 year rolling Beta below for a factual yet comical illustration of this – over a 5 year period, Beta ranged from 0 to 1.4. This drawback is exacerbated by yet another, which is the need to decide the correct historical time period – how far back is “meaningful”? Chipotle’s Beta on Yahoo Finance is .45, while Google lists Beta at .6 for Chipotle. Which one is right? These drawbacks collectively create a conundrum for investors looking to shape a portfolio by relying upon Beta. Let’s now discuss Delta. Delta is a lesser known term that is related to options. Like Beta, it is a measurement of the expected exposure to a referenced security. This is however where the similarities end. Beta, as mentioned, is a best fit line calculation between a given investment and a reference security; the reference security is typically the market (e.g., S&P 500 index), though it doesn’t have to be. Delta measures the expected exposure of an option to its reference security (e.g., the Delta of Apple (NASDAQ: AAPL ) options compared with Apple stock). It is calculated based on a few widely known variables, including the price of the reference security, the time to expiration of the option, and the implied volatility (future expected volatility as priced by the marketplace) of the option. Based on the way Delta is calculated, the value is current . Meaning that if the delta for an option is .8, then there is a very high likelihood that the option value will increase by approximately .8 for a $1 movement in the referenced security. For a call option, which provides the clients the right to purchase a stock, delta is bounded between 0 and 1 (i.e., if a security changes price, a call option following that security will change in the same direction somewhere between 0% and 100% – since a call option’s Delta can’t be negative, it won’t change in the opposite direction, and since Delta can’t exceed 1, it won’t change more than the security did). For a put option, which provides the clients the right to sell a stock, delta is bounded between 0 and -1. As a measurement, Delta cannot be used as broadly as Beta, since it can only be used with an option and the security the option follows. However, where it can be used, Delta is highly predictive of future relative exposure. Let’s look at Delta in practice. A visual illustration of Call Delta vs. price of the reference security follows – y axis is delta, x axis is how far the reference stock is trading from the strike price. For this option, when strike [1] = current market price (0% on the chart), Delta is about 0.5. As can be seen from the chart, Delta for an option changes as the reference security moves away from the strike price in either direction – Delta approaches 1 when the option is sufficiently in the money (e.g., stock is up about 30% vs. strike price), and Delta approaches 0 when the option is sufficiently out of the money (e.g., stock is down about 30% vs. strike). The implied volatility of the reference stock will affect how quickly Delta of an option changes as will the amount of time left to expiration – both conversations for another time. Let’s see how Delta works in action, starting with a simple example of a call option and then graduating to an options portfolio: Chart #1 is the classic shape of a call with time still left to maturity [2] . If the reference security declines below the strike, the loss is limited to the price paid for the option while if the reference security increases the call participates with the gains. Chart #2 shows the previous graph of Delta based on the relative value of the referenced stock vs. strike price. Using the data in Chart #2, one can predict relatively accurately how much the price of the call will increase and decrease based on an increase or decrease in the price of the reference security. Between the two charts, understanding ultimate exposure as well as relative exposure on a daily basis is very straightforward. For example, if the reference stock increased from 0% to 2%, the option should increase about 1% (Delta is about 0.5 for that range). However, if the reference stock increases from 30% to 32% (a 2% increase in total), the option value should increase about 2% (Delta is about 1 for that range). Now that we have the basics, let’s explore what happens when we combine options. Selling a “put spread” means we sell a put at a given strike and limit our downside by buying a put at a lower strike price – the lower the second strike price, the wider the spread, and the greater our risk (though the more premium we collect for taking that risk). Let’s discuss the maximum exposure of the spread. If we covered ourselves 12.5% below where we sold the first put, our maximum exposure can at most be 12.5%. If the market declines -25% by expiration, then the put we sold would be worth -25% and the put we bought would be worth +12.5%, for a net loss of 12.5%. On the other hand, if the market finishes flat or positive, our value is 0, since both the put we sold and the put we bought are worth 0. Can we figure out the Delta of the combined two option positions? Of course we can! A put spread is simply one long put and one short put so we can calculate the Delta of each and subtract. Below is a chart of the combined Deltas: Because we have two offsetting options, the Delta never goes to 1. Why? When the market is down significantly, the Delta for both puts is -1, so our long put and our short put result in a net Delta of -1 – (-1) = 0. This intuitively makes sense, because we know that once the market is down significantly more than -12.5%, it doesn’t matter if it’s down -30% or -40%, both puts are gaining value equally. If the market is up significantly, Delta for both puts is 0, bringing us back to a combined delta of 0. The above chart shows the combined Deltas with 4 months to go prior to the options expiring. As we mentioned earlier, both time to expiration and volatility have an effect on delta – following is an example of how time affects Delta. The following chart is an illustration of the same 12.5% put spread with 2 weeks left to maturity. As can be seen, a large Delta exposure is concentrated around the center of the spread with almost no delta once either put is surpassed. At any given point in time, the overall Delta can be calculated to give an accurate expectation of the price movement relative to the reference security. Now that we all have a deeper understanding of Beta and Delta, I would like to bring this all back to crafting investment strategies. A large component of the investing public looks to Beta as a guide in making investment decisions. However, for the reasons we’ve mentioned, Beta can be an ineffectual tool in portfolio planning. A product with a low historical Beta may exhibit a future decline far greater than the market for any number of reasons. As I’ve written about before, Funds and investment products often show a murky future, leaving a public averse to ambiguity unsatisfied with their investment options. So-called defensive strategies and tactical plays often seem to work for a period of time and abruptly stop working, leaving investors holding the bag (Contact me for many such examples). In the hands of an experienced user, option strategies are uniquely able to provide a strong level of transparency along with tangible levels of risk and reward. There are a growing number of strategies in the market that look to take advantage of options. For example, our Exceed Investments products are engineered to take advantage of the unique qualities of options in providing a more defined and controlled exposure to the market. In the same way that Delta provides a more mathematically true approximation of the future than Beta does, defined outcome investing can offer a level of predictability unattainable in traditional equity investing. [1] Strike is the value where the owner of a call has the contractual right to buy the stock and where the owner of the put would have the contractual right to sell the stock. For example, if Apple was trading $200 and the strike of the call was $195, the owner could exercise and buy at $195. If the strike of the call was $205, the owner would not exercise because they can simply buy it on the open market. (For reasons beyond the scope of this article, owners typically wait to expiration to exercise) [2] Options are term based, with a specific maturity date. In that sense, they are similar to bonds. As such, there is a level of premium attributable to the value prior to maturity. Again a topic for another time.

5 Costly ETF Mistakes You Can Easily Avoid

ETFs are becoming increasingly popular with investors due to their low cost, transparency, easy tradability and tax efficiency. The ETF revolution has made it possible for individual investors to get a convenient, diversified access to almost any investment strategy in virtually any corner of the investing world. Retail investors now have access to many investment opportunities that were earlier available only to sophisticated, high net worth individuals. Despite their widespread use, there are many misconceptions regarding ETFs leading to costly errors, which can be easily avoided. This article aims to help investors avoid some of those mistakes and become more successful ETF investors. Buying an ETF above Its NAV ETFs usually trade at fair prices, i.e. close to their intrinsic values or aggregate values of their holdings. But at times certain ETFs’ prices deviate from their NAVs and they can trade at a premium or discount to their NAVs. If you buy an ETF (or an ETN) when it is trading at a premium, you can incur losses if you sell after the premium crashes. The popular oil ETN, the iPath S&P Crude Oil Total Return Index ETN (NYSEARCA: OIL ), was trading at an almost 50% premium over its NAV for some time earlier this year. In fact, Barclays had issued a notification warning investors about ETN premiums. As expected, the premium plunged after some time, making investors vulnerable to unexpected losses. Investors should make sure to check the previous day’s closing indicative value on the sponsor’s website. They can also check the intraday indicative value on Yahoo Finance using the ticker for the ETF and adding “^” and “-IV” at the beginning and end. So, for OIL ETN, the ticker for intraday indicative value is ^OIL-IV. Avoiding Low Volume ETFs Many investors confuse low trading volumes with the liquidity of an ETF and some even avoid newer ETFs, which may have better strategies but low trading volumes, in favor of older, more popular products with higher trading volumes. ETFs are different from stocks in this area and their trading volume should not be interpreted like stock trading volume. The liquidity of an ETF is not determined by its trading volume but by the liquidity of underlying shares (ETFs’ holdings). At the same time, low volume does usually lead to wider bid-ask spreads, which add to the trading costs. So, these ETFs are not suitable for frequent trading. And it does make sense to use limit orders while trading in low-volume ETFs. Using Market Orders during Volatile Markets The market mayhem on Monday, August 24, last year (ETF Flash Crash) left some harsh lessons for ETF investors. Many ETFs fell 20% or more and some as much as 30%-45% that morning, even though their underlying stocks had not declined so much. Large dislocations in ETFs’ prices were seen not only in smaller ETFs but in some very large and popular ETFs such as the Guggenheim S&P Equal Weight ETF (NYSEARCA: RSP ) and the Vanguard Consumer Staples ETF (NYSEARCA: VDC ). While these discrepancies lasted only for a short period of time, none of the trades executed during that time were canceled. There were many factors that caused ETFs’ pricing problems. But the biggest mistake that ETF investors could have avoided was using “market orders” during those turbulent market conditions. Investors who had left a sell market order or a sleeping stop-loss sell order for one of the ETFs that had severe distortion in pricing probably saw their orders hit at worst possible prices, much below fair values. Ignoring the Contango Impact on Commodity ETFs While some commodity ETFs, mainly those tracking precious metals hold the physical commodity, most commodity ETFs use futures contracts to track the price of commodities due to high storage costs. These futures contracts are required to be rolled over when they are close to expiration. At times, futures price of the commodity is higher than the spot price – known as “contango” – which results in losses at the time of rolling over the contracts. Contango affects the performance of ETFs since the futures contracts’ return will be lower than spot price returns of the commodity. A recent article in WSJ highlighted this issue in the performance of ETFs that track the performance of oil using futures, including the PowerShares DB Oil ETF (NYSEARCA: DBO ), the United States Oil ETF (NYSEARCA: USO ) and OIL. While US crude futures were down about 20% through February 22 this year, oil funds fared much worse. Always Buying Currency Hedged International ETFs Currency hedged ETFs have been quite hot in the past couple years as the US dollar surged against most other currencies. By hedging out the currency exposure, through currency hedged ETFs, investors get access to pure equity returns in international markets. Investors should also remember that often stocks and currencies move in the same direction. That is, if an economy strengthens, its stock market as well as the currency will perform well. In such cases of positive correlation, hedging will actually work against investors. However in some cases, particularly in cases of export oriented economies, stocks and currencies have shown a negative correlation historically. That’s why currency hedged Japan funds performed so well in the recent past. That said currency hedging is not always a good idea. Take the example of Japan ETFs – while currency hedged products like the WisdomTree Japan Hedged ETF (NYSEARCA: DXJ ) outperformed the unhedged ones like the iShares MSCI Japan ETF (NYSEARCA: EWJ ) over the past couple years, as the yen weakened against the dollar, they have underperformed over the past 2-3 months, as the Japanese currency rebounded, thanks mainly to its safe-haven status and worse-than-expected stimulus measures announced by the BOJ. Original Post

Dual ETF Momentum March Update

Scott’s Investments provides a free “Dual ETF Momentum” spreadsheet which was originally created in February 2013. The strategy was inspired by a paper written by Gary Antonacci and available on Optimal Momentum. Antonacci’s book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk , also details Dual Momentum as a total portfolio strategy. My Dual ETF Momentum spreadsheet is available here and the objective is to track four pairs of ETFs and provide an “Invested” signal for the ETF in each pair with the highest relative momentum. Invested signals also require positive absolute momentum, hence the term “Dual Momentum”. Relative momentum is gauged by the 12 month total returns of each ETF. The 12 month total returns of each ETF is also compared to a short-term Treasury ETF (a “cash” filter) in the form of the iShares Barclays 1-3 Treasury Bond ETF (NYSEARCA: SHY ). In order to have an “Invested” signal the ETF with the highest relative strength must also have 12-month total returns greater than the 12-month total returns of SHY. This is the absolute momentum filter which is detailed in depth by Antonacci, and has historically helped increase risk-adjusted returns. An “average” return signal for each ETF is also available on the spreadsheet. The concept is the same as the 12-month relative momentum. However, the “average” return signal uses the average of the past 3, 6, and 12 (“3/6/12″) month total returns for each ETF. The “invested” signal is based on the ETF with the highest relative momentum for the past 3, 6 and 12 months. The ETF with the highest average relative strength must also have an average 3/6/12 total returns greater than the 3/6/12 total returns of the cash ETF. Portfolio123 was used to test a similar strategy using the same portfolios and combined momentum score (“3/6/12″). The test results were posted in the 2013 Year in Review and the January 2015 Update . Below are the four portfolios along with current signals: Return Data Provided by Finviz Click to enlarge As an added bonus, the spreadsheet also has four additional sheets using a dual momentum strategy with broker specific commission-free ETFs for TD Ameritrade, Charles Schwab, Fidelity, and Vanguard. It is important to note that each broker may have additional trade restrictions and the terms of their commission-free ETFs could change in the future. Disclosures: None