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Frequently Asked Questions

Dr K VIX Volatility Model
My profit/loss on VVM is lower than what the website shows. Please explain.

This report I sent out explains the differences:


The results table was consequently updated to reflect the changes. The live results began on June 27, 2016 as denoted by the **. I also created a graphic of VVM's buy/cash/sell signals shown near the top of the results section: https://www.virtueofselfishinvesting.com/market-timing-results 

VVM as noted is a volatile strategy. The recently announced +177.03% reflects returns from December 23, 2015 to the close of September 8, 2016. On Sept 9, I sent out an email 12 minutes after the open suggesting members take at least partial profits. This was when the model was still close to a +40% profit on its July 15 sell signal. Markets then got clobbered. The July 15 sell signal finished up 'only' +17.16% as shown in the results table. The table does not account for any partial profits that may have been taken earlier.

VVM then went to a rare VIX spike buy signal. For information on this rare signal, read https://www.virtueofselfishinvesting.com/faqs/answer/what-is-the-vix-spiking-strategy-also-known-as-vix-spike-buy-signal. Change is the only constant when it comes to markets. I have examined the last few days of trade from September 9-13, 2016 which are highly irregular and have pushed the model into record drawdowns given the extent of the moves, so VVM accounts and adjusts for this new data.

Consequently, the rule of buying back XIV on the original sell signal right after a VIX spike buy signal is closed out will no longer be automatic. Rebuying XIV will only take place if the market moves in a favorable direction. Financial bubbles continue to expand, thus markets are increasingly vulnerable to sudden sharp corrections. As always, inherent logic guides the course of any material changes made to the models.

Most recently, the rebuy strategy was adjusted so the model will never be sidelined again during uptrending markets.

Growing Pains

The model has gone through its share of growing pains that date back to when it first went beta in August 2015. It went to beta because the profits up until late August 2015 were substantial. But then the markets went into a highly unusual pattern which prompted the exchanges to set new trading rules against short selling since they blamed the crash in August 2015 on short sellers. Whether or not short sellers were to blame, VVM adjusted for these wild swings by introducing fail-safes which greatly reduced risk.

Meanwhile, the profit-taking and VIX spiking strategies have made substantial differences to VVM's performance by enhancing profits WHILE reducing risk, the best of both worlds. That said, the aberrant market action of August 2015 then recently from September 9-13, 2016 is illustrative of the highly manipulative environment of today's markets. 

Nevertheless, prior to integration of the profit-taking strategy, I would simply send out emails (which can be found in our VVM and MLR report archives) suggesting members might take at least partial profits since a fast +12% to 18% or more had been achieved on a buy signal (buying volatility). This continued to occur so I ultimately decided to create profit taking rules in context with the price moves on buy signals, since the returns would then be documented in the results table. Note, there is no profit taking rule on sell signals (selling volatility anticipating the market will move higher) since the market tends to take the stairs up and the elevator (or trap door these days) down. Thus it can undo a couple months worth of sell signal profits in just a few days. But again, rules should generally have inherent logic behind them since patterns, while they do not repeat, often rhyme because they are human nature on parade.

In conducting research, some adjustments which seem obvious in hindsight may be overlooked until testing is done in real-time which brings the model's algorithms to life. Indeed, all the effort can pay off handsomely. 

Published: Sep 15 2016, Modified: Oct 23 2016