Quantocracy’s Daily Wrap for 10/06/2015

Weve tested 24 simple strategies for trading VIX ETPs on this blog (separate and unrelated to our own strategy). And while I cant speak for all traders, based on all of my readings both academic and in the blogosphere, the strategies weve tested are broadly representative of how the vast majority of traders are timing these products. Below Ive shown the September results of all 24

Since writing about my experience writing the CFA Level I exam in June, I have received many emails from people interested in finding out how to become a quant. To some extent, this post will answer that question. That said, this post is actually not about how to become a quant, it is about how to be a quant in whatever sector of the financial services industry you already work in. Being is quant

Any trading strategy can be broken down into a set of events and the reaction to those events. The reactions can get infinitely complex and varying but essentially strategy writing is quite simply put exactly that. The kind of events and their frequency would depend on the markets and the instruments on which this strategy would be working on however, broadly speaking most markets would have

This post will review the DIY Financial Advisor book, which I thought was a very solid read, and especially pertinent to those who are more beginners at investing (especially systematic investing). While it isnt exactly perfect, its about as excellent a primer on investing as one will find out there that is accessible to the lay-person, in my opinion. Okay, so, official announcement: I am

Back-testing of a trading strategy can be implemented in four stages. Getting the historical data Formulate the trading strategy and specify the rules Execute the strategy on the historical data Evaluate performance metrics In this post, we will back-test our trading strategy in R. The quantmod package has made it really easy to pull historical data from Yahoo Finance. The one line code below

I've had a request for the code used to do the optimisations in chapter 4 of my book "Systematic Trading" (the 'one-period' and 'bootstrapping' methods; there isn't much point in including code to the 'handcrafted' method as it's supposed to avoid programming). Although this post will make more sense if you've read the book, it can also

Modelling of financial markets is usually undertaken using stochastic process. Stochastic processes are collection of random variables indexed, for our purposes, by time. Examples of stochastic processes used in finance include GBM, OU, Heston Model and Jump Diffusion processes. For a more mathematically detailed explanation of Stochastic processes, diffusion and jump diffusion models, read this

Last month I tested random rebalancing strategies based on dates and found that searching for optimal points through time to reset asset allocation may not be terribly productive after all. Lets continue to probe this line of analysis by reviewing the results of randomly changing asset weights for testing rebalancing strategies. Ill use the same 11-fund portfolio thats globally

September 2015: Trend Following UP +4.64% YTD: +13.98% Third month in a row of the index producing a positive return. The YTD and 12-month figures well in the black (over 10% and 35% respectively) show that trend following has been a good strategy to invest or trade in these past market conditions. Below is the full State of Trend Following report as of last month. Performance is

How Do Investors Measure Risk? Jonathan Berk and Jules H. Van Binsbergen October 1, 2015 We infer which risk model investors use by looking at their capital allocation decisions. We find that investors adjust for risk using the beta of the Capital Asset Pricing Model (CAPM). Extensions to the CAPM perform poorly, implying that they do not help explain how investors measure risk. A Smart

Selecting the indicators to use is one of the most important and difficult aspects of building a successful strategy. Not only are there thousands of different indicators, but most indicators have numerous settings which amounts to virtually limitless indicator combinations. Clearly testing every combination is not possible, so many traders are left on their own selecting somewhat random inputs to

The index had a strong September, continuing the Summer uptrend started in mid-July. This has now resulted in the YTD performance returning to positive territory, after the Spring slump took the index from the Winter highs to negative performance. Lets see what Autumn (or Fall depending on where you live) has in store Please check below for more details. Detailed Results

Readers of Scotts Investments know I am a proponent of do-it-yourself investing solutions. I am also a big fan of Alpha Architect, so I was excited when I was asked to review a book which combines the best of both worlds, DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth (DIY). Authors Wes Gray, Jack Vogel, and David Foulke, all of Alpha Architect, split DIY into two