Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 04/26/2017

This is a summary of links featured on Quantocracy on Wednesday, 04/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Academic Factor Exposure Versus Fund Factor Exposure [Alpha Architect]

    Tomorrow Ill be sitting with Pat OShaughnessy and Ben Johnson to discuss Straight Talk About Smart Beta. Here is a link to the big Morningstar event. In preparation for our discussion we were spitballing ideas and Ben brought up the concept of helping investors understand the similarity/differences between live factor funds and the academic factor portfolios often used for
  • The best investment strategy in Europe from 2000 to 2014 data driven [Quant Investing]

    What investment strategy would have given you the highest returns in Europe over the 13 year period from July 2000 to July 2014? In this article I summarised the masters thesis of Andreas Hennes (completed at Goethe University Frankfurt am Main on 14 September 2015) where he set out to test exactly that. Results and findings Before I get to all the details here are the summarised results:
  • Vix Blues, Large Close to Close Declines in Vix [Voodoo Markets]

    This monday, we were witnesses to a rather large decline in Vix. Taking a quick look at how often drops like this happen and how has Vix behaved after large single day drops 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates import scipy as sp import seaborn as sns import quandl
  • The Dividend Growth Myth [Meb Faber]

    A few weeks ago, I was sipping coffee, thumbing through Barrons as I do every weekend. Its a way in which I keep a pulse on whats going on in our space. Though I never consciously pay attention to ads, on that particular morning, one caught my eye a big full pager from Schwab, below. They were trumpeting their low-cost trading commissions in the ongoing fee compression in the

Quantocracy’s Daily Wrap for 04/25/2017

This is a summary of links featured on Quantocracy on Tuesday, 04/25/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Great Academic Finance Research Papers at WFA 2017 [Alpha Architect]

    There are several big academic finance conferences that attract the best research and the best researchers in one bullpen the AFA and the WFA meetings. We chatted about the AFA event last January (be sure to check that out). But now it is the WFAs turn. I attended the WFA a few years back in Lake Tahoe (along with my friend Gary Antonacci). We had a blast hobnobbing with the big academic

Quantocracy’s Daily Wrap for 04/24/2017

This is a summary of links featured on Quantocracy on Monday, 04/24/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why quants don’t pick stocks [Flirting with Models]

    Quant is a broad word with many job descriptions in finance. In asset management, a quant is someone who applies mathematical (usually statistical) techniques to analyzing the securities market, usually with an eye towards identifying investment opportunities. Quants rely on factors: systematic investment approaches that capture and explain the return difference between different cohorts of

Quantocracy’s Daily Wrap for 04/23/2017

This is a summary of links featured on Quantocracy on Sunday, 04/23/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Constrained by capital or why rounding down is bad for you [Quant Bear]

    Imagine this, you have backtested a strategy adhering to all the general rules: you did proper in/out of sample testing, you have stable parameters (if the strategy has any), you didnt overfit, you account for transaction costs and slippage, everything seems good and you are ready to deploy your strategy and earn you some money. But did you check for capital constraints in your backtest?

Quantocracy’s Daily Wrap for 04/22/2017

This is a summary of links featured on Quantocracy on Saturday, 04/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • “Alternative” Facts about Formulaic Value Investing [Alpha Architect]

    A new paper, Facts about Formulaic Value Investing, is making the rounds and professes to plunge a dagger directly into the heart of systematic value investors. Half of my inbox is filled with questions regarding this paper, since we are considered by some rightly or wrongly to be experts on systematic value investing. The implication from the research piece is that systematic

Quantocracy’s Daily Wrap for 04/21/2017

This is a summary of links featured on Quantocracy on Friday, 04/21/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Abnormal Returns Memberships (shout out to the inspiration for Quantocracy) [Abnormal Returns]

    I am excited to announce that Abnormal Returns now supports memberships. The most common compliment I get about Abnormal Returns is that it saves you time. We all well know that time is money. A great way to help keep Abnormal Returns an ongoing, independent entity is to contribute to its upkeep at the $25 or $75 level. Please note this is annual, recurring annual membership.* Monetizing Abnormal
  • K-Means in investment solutions: fact or fiction [Quant Dare]

    Weve spoken previously about different clustering methods many times: K-Means, Hierarchical Clustering, and so on. However, this field does not end here. In this post, I will try to find how K-Means clustering works in an investment solution. K-Means Clustering The K-Means algorithm partitions the points in a data set into clusters. This partition minimises the sum, across the clusters, of the
  • Analysis of Commodity Futures Returns Over the Last Decade [Quantpedia]

    Long-only commodity futures returns have been very disappointing over the last decade, leading some to wonder if it was a mistake to invest in commodities. The poor performance is the result of poor income returns and not of falling commodity prices. This observation may be surprising for many commodity investors who were not aware, who misperceived, they were making a bet on income returns,
  • Using the BayesOpt Library to Optimise my Planned Neural Net [Dekalog Blog]

    Following on from my last post, I have recently been using the BayesOpt library to optimise my planned neural net, and this post is a brief outline, with code, of what I have been doing. My intent was to design a Nonlinear autoregressive exogenous model using my currency strength indicator as the main exogenous input, along with other features derived from the use of Savitzky-Golay filter

Quantocracy’s Daily Wrap for 04/19/2017

This is a summary of links featured on Quantocracy on Wednesday, 04/19/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Modelling Treasury ETF Performance in an Era of Rising Rates [Allocate Smartly]

    US Treasuries and other interest rate sensitive instruments form the backbone of many asset allocation strategies. Investors are justifiably concerned about a future of rising interest rates and the potential impact on those instruments. In this post we model that impact on constant maturity Treasury assets like the ETF TLT, which tracks long-term (20+ year) US Treasuries. For brevity, Im going

Quantocracy’s Daily Wrap for 04/18/2017

This is a summary of links featured on Quantocracy on Tuesday, 04/18/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value and Momentum Investing in Frontier Stock Markets [Alpha Architect]

    Value and Momentum investing have been studied across many different markets and asset classes (Asness et al 2013) and have shown to be effective factors. A working paper, Frontier Stock Markets: Local vs Global Factors by Douglas W. Blackburn and Nusret Cakici examines Value and Momentum investing in Frontier Markets from 2005-2016. This paper is unique because prior research has focused on

Quantocracy’s Daily Wrap for 04/17/2017

This is a summary of links featured on Quantocracy on Monday, 04/17/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Simulation-Based Rebuttal to Research Affiliates (@RA_Insights) [Flirting with Models]

    Research Affiliates published a new piece of research exploring mutual fund returns over the last 25 years and the implied ability for managers to capture popular factor premiums published by the academic community. They argue that several factors accepted in academia may not be implementable after real life frictions (e.g. transaction costs, cost of shorting, missed trades, et cetera). Their
  • Swedroe Spotlight: Does Market Sentiment Help Explain Momentum? [Alpha Architect]

    Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. In 1997, Mark Carhart, in his study On Persistence in Mutual Fund Performance, was the first academic to use momentum, together with the three Fama-French factors (market beta, size and value), to explain mutual fund

Quantocracy’s Daily Wrap for 04/15/2017

This is a summary of links featured on Quantocracy on Saturday, 04/15/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Parallelized Random Portfolio Generation [Quant Bros]

    Generate an efficient frontier of random portfolios with custom constraints in R. Accelerate your project with the power of cloud computing using Techila Technologies solution in combination with Rs plyr functions. Source code included. The embedded source code below is available due to the generous sponsorship of Techila Technologies. ############################# # Set Environment
  • Demystifying Bollinger Bands [Milton FMR]

    How do we know if a price is right and when do we enter the trade ? Is the S&P 500 Index trading at 2355 for that day to high or to low. Should I buy or sell ? Proponents of the Bollinger Band say that this indicator can greatly improve your odds in being on the right side of the market. The purpose of the bollinger band is to help you decide when to make your move by illustrating the momentum