This is a summary of links featured on Quantocracy on Monday, 08/21/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
-
Accounting for Autocorrelation in Assessing Drawdown Risk [Flirting with Models]Under a simple model of asset prices, expected returns and volatilities can be used to calculate expected maximum drawdowns over a given timeframe. However, these expected drawdowns do not line up with the drawdowns investors have experienced. Simple models have underestimated drawdown risk in equities, low volatility equities, and income strategies, and overestimated historical drawdown risk in
-
Making Python massively parallel (and burgers) [Cuemacro]I like burgers. I suspect I start most of my blog articles with a similar sentence. Most burgers are sufficiently large, such that a single burger will suffice for a meal. However, occasionally you get burger sliders, mini burgers of different flavours, which are also easier to share. It is an obvious point that a plate of burger sliders is likely to end up getting finished quicker than a single
-
Modeling Volatility and Correlation [Jonathan Kinlay]In a previous blog post I mentioned the VVIX/VIX Ratio, which is measured as the ratio of the CBOE VVIX Index to the VIX Index. The former measures the volatility of the VIX, or the volatility of volatility. A follow-up article in ZeroHedge shortly afterwards pointed out that the VVIX/VIX ratio had reached record highs, prompting Goldman Sachs analyst Ian Wright to comment that this could signal
-
Academic Research Insight: Abusing ETFs [Alpha Architect]What are the research questions? By studying the trading data (provided by a German brokerage house) of a large (6,949) group of individual self-directed investors over the period from 2005-2010, the authors attempt at answering:(1) Do ETFs provide performance benefits to individual investor portfolios? If not, what are the reasons? Does investors heterogeneity (specifically, overconfident
-
Smart Beta vs Factors in Portfolio Construction [Factor Research]SUMMARY Investors seek smart beta products for risk reduction However, smart beta products are effectively long-only products with full equity risk Only factor products, i.e. long-short portfolios, offer true diversification benefits and downside protection INTRODUCTION FTSE Russells 2017 Smart Beta Investor Survey showed that the Nr 1 objective for evaluating smart beta strategies was for risk