Quantocracy

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Quantocracy’s Daily Wrap for 10/03/2017

This is a summary of links featured on Quantocracy on Tuesday, 10/03/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hiking Mountains, Gladly, To Honor The Fallen [Alpha Architect]

    Landon Thomas Jr. recently wrote an article in the New York Times regarding our participation in the recent March for the Fallen Event. Landons article was well-written and provided a compelling narrative. However, much of the attention of the article was focused on Alpha Architect and my personal story, which we genuinely appreciate. But I was one of many There were 500+ alongside us on the
  • Capital Raising for Early Stage Quant Fund Managers – Part I [Quant Start]

    This is the first in a two part series of articles written by Frank Smietana, an expert guest contributor to QuantStart. In this article Frank takes a look at how early-stage quantitative hedge fund managers can go about looking to secure their first institutional allocation of capital. Please be aware that since this article discusses capital allocation, the article (and any information accessed
  • Suggestion of a New Currency Factor Model [Quantpedia]

    We examine the ability of existing and new factor models to explain the comovements of G10-currency changes. Extant currency factors include the carry, volatility, value, and momentum factors. Using a new clustering technique, we find a clear two-block structure in currency comovements with the first block containing mostly the dollar currencies, and the other the European currencies. A factor

Quantocracy’s Daily Wrap for 10/02/2017

This is a summary of links featured on Quantocracy on Monday, 10/02/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Olympics: Q3 2017 [Factor Research]

    2017 is on track for a good year for factor exposure as most factors are positive Quality, Growth, and Momentum are headed for the winners podium Value is negative across regions, giving up all of last years gains INTRODUCTION We present the performance of six well-known factors on an annual basis for the last 10 years and the first three quarters of 2017. Its worth mentioning that not all
  • TAA vs buy and hold in overvalued markets (CAPE > 30 edition) [Investing For A Living]

    Personal note: Sorry for the long delay from posting. I had a death in the family this summer, a big overseas family wedding, and Ive been working on getting my newsletter released, which Ill announce in a later post. Now, Im back. I was thinking this morning that with the increasing talk of market valuation, bubbles, etc. it would be a good time to revisit my post on TAA vs buy and hold
  • Analyzing the FDIC Dataset [Jonathan Kinlay]

  • The Frustrating Law of Active Management [Flirting with Models]

    In an ideal world, all investors would outperform their benchmarks. In reality, outperformance is a zero-sum game: for one investor to outperform, another must underperform. If achieving outperformance with a certain strategy is perceived as being easy, enough investors will pursue that strategy such that its edge is driven towards zero. Rather, for a strategy to outperform in the long run,
  • When Months Finish At A High [Quantifiable Edges]

    urn of the month will often trigger some seasonal studies. The study below looks at performance after times that SPY has closed a month at the highest closing price of the month. 2017-10-02 image1 The numbers across the board are fairly compelling. Trades may want to keep this in mind as we enter October.
  • Academic Research Insight: Volatility Wisdom of Social Media Crowds [Alpha Architect]

    Title: VOLATILITY WISDOM OF SOCIAL MEDIA CROWDS Authors: Ahmet K. Karagozoglu and Frank J. Fabozzi Publication: Journal of Portfolio Management, Winter 2017 (version here) What are the research questions? Using raw tweets from Twitter and StockTwits (Trader Mood Data from PsychSignal) a minute-by-minute social media sentiment signal is constructed for numerous financial instruments and used

Quantocracy’s Daily Wrap for 10/01/2017

This is a summary of links featured on Quantocracy on Sunday, 10/01/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in September (Now Adjusted for Timing Luck) [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help you follow these strategies in
  • Smart Portfolios from @InvestingIdiocy [Reading the Markets]

    Robert Carver, author of Systematic Trading, has turned his attention to the thorny problem of portfolio construction. In Smart Portfolios: A Practical Guide to Building and Maintaining Intelligent Investment Portfolios (Harriman House, 2017) he deals with such topics as how to blend assets with different levels of risk, the reasons that forecasting returns is so difficult, and how to calculate

Quantocracy’s Daily Wrap for 09/30/2017

This is a summary of links featured on Quantocracy on Saturday, 09/30/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Calibrating Financial Models using a Non-Parametric Technique [Top of The Bell Curve]

    Traditionally, asset returns have been modeled using diffusion processes. Diffusion processes assume that the sample path of the process being modeled is continuous. However, empirical evidence suggests that there are jumps that occur in asset returns, such as those that occurred during the financial crisis of 2008. The presence of jumps has implications in derivative pricing and asset allocations

Quantocracy’s Daily Wrap for 09/29/2017

This is a summary of links featured on Quantocracy on Friday, 09/29/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Kelly Criterion Does It Work? [QuantStrat TradeR]

    This post will be about implementing and investigating the running Kelly Criterion that is, a constantly adjusted Kelly Criterion that changes as a strategy realizes returns. For those not familiar with the Kelly Criterion, its the idea of adjusting a bet size to maximize a strategys long term growth rate. Both https://en.wikipedia.org/wiki/Kelly_criterionWikipedia and Investopedia have

Quantocracy’s Daily Wrap for 09/28/2017

This is a summary of links featured on Quantocracy on Thursday, 09/28/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • VIX and Trend-Following, the Killer Combo? [Alpha Architect]

    Some things in life are naturally made for each other. Some examples include the following: Peanut Butter and Jelly Starsky & Hutch Value and Momentum So my ears perked up when the idea of combining VIX levels and Trend Following started making the rounds on finance twitter. Like any geek, I was eager to start testing the idea, knowing ahead of time that there is a major overfitting hurdle to
  • Are Short Out-of-the-Money Put Options Risky? Part 2: Dynamic Case [Relative Value Arbitrage]

    This post is the continuation of the previous one on the riskiness of OTM vs. ATM short put options and the effect of leverage on the risk measures. In this installment were going to perform similar studies with the only exception that from inception until maturity the short options are dynamically hedged. The simulation methodology and parameters are the same as in the previous study. As a
  • Craftsmanship Alpha [Quantpedia]

    Successful investing requires translating sound investment concepts into actual trading strategies. We study many of the implementation details that portfolio managers need to pay attention to; such choices range from portfolio construction to execution. While these kinds of decisions apply to any type of investment strategy, they are particularly important in the context of style investing.
  • What Kind of Asset Is Bitcoin? [CXO Advisory]

    Does Bitcoin behave like some other asset class? To investigate, we calculate daily and monthly return correlations between Bitcoin and each of 34 exchange-traded products encompassing eight used in Simple Asset Class ETF Momentum Strategy (SACEMS), 24 considered in SACEMS Portfolio-Asset Addition Testing plus SPDR Bloomberg Barclays 1-3 Month T-Bill (BIL) and Powershares DB US Dollar

Quantocracy’s Daily Wrap for 09/27/2017

This is a summary of links featured on Quantocracy on Wednesday, 09/27/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • High Frequency Trading III: Optimal Execution [Quant Start]

    In this article series Imanol Prez, a PhD researcher in Mathematics at Oxford University, and an expert guest contributor to QuantStart outlines the basics of high-frequency trading. In this article Imanol uses the theory of stochastic optimal control to optimally execute a large trade order. It is well known that when a large order is trying to be executedeither a sell or buy orderthe
  • Calculate monthly returns with Pandas [Quant Dare]

    Calculating returns on a price series is one of the most basic calculations in finance, but it can become a headache when we want to do aggregations for weeks, months, years, etc. In python the Pandas library makes this aggregation is very easy to do, but if we dont pay attention we could still make mistakes. Assuming that we want the return of the whole month, and we are not interested, for

Quantocracy’s Daily Wrap for 09/25/2017

This is a summary of links featured on Quantocracy on Monday, 09/25/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Addressing Low Return Forecasts in Retirement with Tactical Allocation [Flirting with Models]

    The current return expectations for core U.S. equities and bonds paint a grim picture for the success of the 4% rule in retirement portfolios. While varying the allocation to equities throughout the retirement horizon can provide better results, employing tactical strategies to systematically allocate to equities can more effectively reduce the risk that the sequence of market returns is
  • Quality Factor: Zero Alpha for Most Investors? [Factor Research]

    SUMMARY Its difficult to rationalise why there should be excess returns from high quality stocks The Quality factor needs to be constructed beta-neutral to achieve positive returns Exposure to the Quality factor is an attractive hedge for an equity-centric portfolio INTRODUCTION The concept of investing into the Quality factor is an odd one as its difficult to rationalise why investors
  • Global Diversification Works for Multi-Factor Portfolios [Quantpedia]

    The benefits of country diversification are well established. This article shows that the same benefits extend to equity factors, such as value, size, momentum, investment, and profitability. Specifically, country factor portfolios reflect both common variation, which we define as the global factor, and local variation. On average, a US investor could enjoy a 30% reduction in portfolio volatility

Quantocracy’s Daily Wrap for 09/22/2017

This is a summary of links featured on Quantocracy on Friday, 09/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Timing Investigation: Interest Rates, Value Spreads, and Factor Premiums [Alpha Architect]

    Now that the Federal Reserve has begun the process of raising interest rates, and has announced their intention to begin to unwind their policy of quantitative easing (reducing the amount of bonds in their portfolio, either by selling holdings or allowing holdings to mature), investors may be concerned about the impact of rising interest rates on factor premiums. Wei Dai, senior researcher at
  • Downloading Historical Data Using Oanda’s API and R [Dekalog Blog]

    It has been about 5 months since my last blog post and in this time I have been working away from home, been on summer holiday and spent some time mucking about on boats, so I have not been able to devote as much time to my blog as I would have liked. However, that has now changed, and this blog post is about obtaining historical data. Many moons ago I used to download free, EOD data from

Quantocracy’s Daily Wrap for 09/21/2017

This is a summary of links featured on Quantocracy on Thursday, 09/21/2017. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Option Chain Extraction For NSE Stocks Using Python [Quant Insti]

    We are back again with another post on Python. Our last post, Basic Operations on Stock data using Python was well received and we are glad to see the number of likes & shares for the post on various quant trading and Python forums. Keep them coming! Financial market data is a very critical element of a trading system. Be it historical or live data, you need data for various purposes
  • Trinity Portfolio (Lite) from @MebFaber [Allocate Smartly]

    This is a test of the Trinity Portfolio from Meb Faber and Cambria Investments, so named for the three key elements of the strategy: (1) a globally diversified mix of assets, (2) a tilt towards the value and momentum factors, and (3) exposure to momentum and trend-following. Weve titled our test Trinity Lite because weve made some not insignificant changes to Fabers original model
  • Seven Habits of Highly Ineffective Quants [CXO Advisory]

    Why dont machines rule the financial world? In his September 2017 presentation entitled The 7 Reasons Most Machine Learning Funds Fail, Marcos Lopez de Prado explores causes of the high failure rate of quantitative finance firms, particularly those employing machine learning. He then outlines fixes for those failure modes. Based on more than two decades of experience, he concludes that: