Technically Speaking, July 2012

This is a summary of a presentation by Greg Bender, CMT and Brian Barry, CMT that was part of the 2012 Annual Symposium on April 19th – 20th, 2012 in New York City.

Brian spoke about the applications of technical analysis in algorithmic equity trading. Greg discussed ways to analyze market sentiment using the VIX, new implied volatility benchmarks and tradable products.

Brian began the presentation with an overview of the increasingly complex decision process that traders face. At the macro level, traders must decide what and when to trade. They must then decide how to trade, a decision that requires traders to select an execution algorithm.

Some traders use scheduled algorithms, which include VWAP (volume weighted average price) and TWAP (time weighted average price). VWAP is defined as the ratio of the value traded (price * volume) to total volume traded over a particular time frame, and is usually defined for one day.  VWAP is often used as a trading benchmark by investors who want to execute orders with minimal market impact. TWAP is a trading execution strategy that attempts to execute an order evenly over a specified time frame. As an example of the differences between the two, a VWAP order might have 40 percent of the trade executed in the first half of the day and the rest in the second half, while a TWAP trade would be executed evenly throughout the trading day. VWAP trading would result in a smile-shaped curve during the trading day with more volume being seen near the open and close than in the middle of the trading day while the TWAP trade would be seen as a flat line.

Other trading algorithms include POV (Percentage of Volume) which Brian described as a way to slice the order quantity by the participation rate in the market. Liquidity seeking algorithms execute trades by sending orders to the exchange or dark pool with the most liquidity for that security.

Implementation shortfall algorithms are opportunistic strategies that seek to balance risk and use unscheduled orders to try to obtain an execution price that is better than the midpoint of the arrival price (the bid and ask at the time the order arrives).

Trade execution then require decisions on where to route the order to (exchanges, dark liquidity pools, or other venues), what size order to send, and when to seek execution. Some traders will pursue a passive algorithm based on these factors while others will pursue an aggressive approach. Some traders may prefer to use dark pools while others will favor lit exchanges. Technical analysis can help with all of these decisions.  Brian presented a chart of Microsoft (MSFT), using ten-minute bars. The chart showed MSFT with its VWAP and in the lower panel of the chart is an indicator showing the current premium or discount of the price to VWAP. Brian pointed out that MSFT has a tendency to revert to its VWAP.

To take advantage of this tendency, he presented the example of a client that comes in around noon and wants to trade MSFT which is sitting below its VWAP. Knowing that MSFT has a tendency to revert to its VWAP, Brian would recommend that the trade be executed with TWAP to avoid getting caught in this mean reversion when the volume increases at the end of the day and MSFT is likely to be above the VWAP based on the reversion idea. The TWAP algorithm would execute the trade on a straight line rather than seeing the majority of the trade executed at the edge of the smile that volume creates near the close.

In another example, Brian presented the case of a client looking to buy Wells Fargo (WFC) as its price is advancing along a trend line. He would suggest that the client use a POV strategy as long as the trend line holds and then switch to a VWAP strategy while price is under the trend line. This will weight the order more towards the end of the day if price falls and the volume smile will ensure most of the trade gets executed at the lower price if WFC declines.

After another example, Brian turned the presentation over to Greg, who is also an execution consultant at Bloomberg. Greg is on the derivatives side while Brian is an equity market specialist. Greg discussed some of the tools available to traders looking to take advantage of changes in volatility. Hedge funds, other institutional traders and retail investors are driving triple digit growth in volatility trading over the past several years and the liquidity in these markets is helping traders execute their strategies.

VIX is a statistical gauge of the implied volatility of the components of the S&P 500. As an example of implied volatility, he cited Apple (AAPL) which was trading at about $600. In a low volatility environment, a $610 call on AAPL has no intrinsic value and could trade near $1 or $2. In high volatility environments, the same call might be worth $9 or $10 which indicates that implied volatility is high.

As a statistical gauge, VIX is not directly tradable. Futures, options, and Exchange Traded Notes (ETNs) are available to trade, but they are derived from VIX so there are pricing differences between each of them.

Because implied volatility is an estimate of the standard deviations of returns estimated by the market and is also a function of time, the “Rule of 16” applies. There are 256 trading days in a year and the square root of 256 is approximately 16. When the VIX is 16, that means traders are handicapping a 1 percent move in the S&P 500 on 2 out of every 3 days. Traders are concerned about the third day, when the price moves beyond that range. This rule allows traders to quickly spot if implied volatility is high or low. That means traders can use this rule to help develop trading strategies.

VIX futures are tradable and are an estimate of the future implied volatility while the spot VIX, a theoretical value, is the commonly quoted index. That means the ETNs will not trade exactly in line with the spot quote or the futures. There are other factors that influence the pricing in ETNs like the credit quality of the issuer. Each tradable will need to be understood because they will behave differently.

There are also VIX indexes available for individual stocks and other tradables like gold and oil. There are opportunities available in this market, Greg noted. Buy-writes or covered call strategies might be profitable to sell when volatility is high relative to the index. This idea is shown in the chart below with AAPL’s volatility being high and rising relative to the VIX in the NASDAQ 100. That creates an opportunity for option writers. Goldman Sachs (GS) is a bellwether for financial stocks and is shown in the bottom half of the chart below.

VIX products are also available for traders in the credit markets and they are available on stock market sectors, among other things. Pairs trades and intermarket trading strategies could be developed for any of these ideas. Spread curve analysis is also possible, as shown in the next chart.

VXZ and VXX are volatility ETNs. When this futures curve is above zero, it implies that volatility is likely to increase. For the ETNs themselves, this relationship has a large impact on returns. When the spread is greater than zero, the futures are in contango, the roll yield on the contracts will be negative and if the contango market conditions continue, these products will eventually go to zero. This could be a useful idea for traders to explore.

VIX and trading algorithms are an area that traders may be able to exploit and could be one of the new frontiers in technical analysis.