Author Archives: Cesar Alvarez
Author Archives: Cesar Alvarez
I have done several posts about trading XIV & VXX. In these posts (here, here and here) I refer to using synthetic data before these ETFs started trading. I supported the use of the data due to the very high correlation of daily returns during the overlap period. With a correlation of .97, I thought great the data should be good to use for backtesting.
As anyone who pays attention to the market, the S&P500 is down nine days in a row. I had several people write me about this. I was talking to a trading friend over the weekend about this. Nine days down seems bad. Let us put this in a broader context. How far have we come down in those nine days? Only 3.07%. Now that got me thinking is 3.07% in nine days that bad?
I will be in Texas next week giving presentations. Click the links below for more details. I hope to see some readers there.
For more information see https://www.mta.org/event-registration/austin-chapter-meeting-featuring-cesar-alvarez/
For more information see http://www.afta-dfw.org/schedule.htm meeting #2.
In this short five minute video I will answer the following questions:
I was at a recent talk of the Northwest Traders and Technical Analysts group where they presented a VXX strategy with some huge return and drawdown numbers. Trading this would be very difficult. This got me thinking. If I had a strategy like this, how could I tame the numbers? Through the years, I have seen various ideas about how to do this but never looked into it. Searching the web one can find various volatility ETF strategies with very high returns and high drawdowns. I found one that looked interesting and had lots of potential for optimization and improvement. Then, I optimized the hell out of it searching for a variation with over 100% CAGR. I found one but I would never trade it because I over fit the data. I needed to something to work with.
In this short five minute video I will answer the following questions:
A reader sent this interesting link about Up/Down Capture. The great part about this article it is something I have intuitively known about my trading strategies but never tried to quantify. This was the bump I needed to investigate this concept. When the SPY moves up on average how much does my strategy profit? When the SPY moves down how much does my strategy lose? I had fun creating an interactive spreadsheet where you can change the numbers and see the results for your own strategy. This is one of the best spreadsheets I have done for the site.
To those on my new blog notification list, I sent out the opportunity to join me in a one hour webinar where people could ask me anything about trading. I had a ton of fun answering lots of great questions. See the bottom of the post for links to download the mp3 files of the webinars.
Some questions, I answered are:
In my last post I showed research on how optimization results can be mean reverting. Sometimes, my research keeps getting side tracked as I think of random ideas to look at. In this post, we look at the random walk my research took starting from my mean reverting optimization research. I will show how changing the start date can have a big change in the results, correlation of 1990’s to now, and random data and how it correlates.
Often one runs a optimization of a testing idea, then using some set metrics from these results, one picks a variation to trade. What often comes as a surprise to people, and myself the first time I saw this, is that your optimization runs are often mean reverting. What do I mean by this?