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Quantocracy’s Daily Wrap for 08/07/2018

This is a summary of links featured on Quantocracy on Tuesday, 08/07/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Warning: Stock and Bond Correlation Assumptions are Regime Dependent! [Alpha Architect]

    It aint what you dont know that gets you into trouble. Its what you know for sure that just aint so. attributed to Mark Twain. Mark Twain had some great insights. The quote above can apply to just about every aspect of life, including investing. This axiom is particularly relevant when one is making simplifying assumptions because you are implicitly stating that you know something
  • July 2018 Trend Following [Wisdom Trading]

    July 2018 Trend Following: DOWN -1.98% / YTD: -7.85% Please find this months report of the Wisdom State of Trend Following. Performance is hypothetical. Chart for July: Wisdom State of Trend Following – July 2018 And the 12-month chart: Wisdom State of Trend Following 12 months – July 2018 Below are the summary stats: Horizon Return Ann. Vol. Last month -1.98% 17.37% Year To Date -7.85% 15.7%
  • State of Trend Following in July [Au Tra Sy]

    Slightly positive month for the State of Trend Following, with the YTD slightly negative. Please check below for more details. Detailed Results The figures for the month are: July return: 0.57% YTD return: -2.19% Below is the chart displaying individual system results throughout July: StateTF July And in tabular format: System July Return YTD Return BBO-20 0.62% 8.33% Donchian-20 0.77% 6.03%

Quantocracy’s Daily Wrap for 08/06/2018

This is a summary of links featured on Quantocracy on Monday, 08/06/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mean Reversion and Bond ETF Returns [Flirting with Models]

    In July 2016, we argued that bond investors should be quick to celebrate the strong returns they had realized year-to-date. The combination of a defined maturity and known coupon rate creates a gravitational pull for bond returns. Using a global bond ETF universe, we develop a simple model to forecast future 1-year returns. The model suggests that mean reversion is a strong forecaster of future
  • Momentum Variations [Factor Research]

    The simplicity of the Momentum factor can be intellectually challenging Various alternative Momentum versions highlight remarkable similar return profiles The robustness is an attractive characteristic of the investment strategy INTRODUCTION What do selfies, the Kardashians, Crocs, blue cheese, and Boris Johnson have in common? They all rank within the top 50 things that split the opinion of
  • An Extensive Test of Market Timing Strategies in the Gold Market [Quantpedia]

    While the literature on gold is dominated by studies on its diversification, hedging, and safe haven properties, the question When to invest in gold? is generally not analyzed in much detail. We test more than 4,000 seasonal, technical, and fundamental timing strategies for gold. While we find large gains in economic terms relative to the buy-and-hold benchmark for several strategies, the
  • Getting Down To Business! [System Trader Success]

    In the previous parts of this 3-part article (see part 1 and part 2), I introduced you to algo trading, and then discussed features of algo trading, along with advantages and disadvantages. Algo trading can definitely help you compete with the big boys, but it is not automatically a supertrader creator. There is no easy way to trade, and algo trading is no exception. Rest assured there

Quantocracy’s Daily Wrap for 08/05/2018

This is a summary of links featured on Quantocracy on Sunday, 08/05/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 08/04/2018

This is a summary of links featured on Quantocracy on Saturday, 08/04/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What variance swaps tell us about risk premia [SR SV]

    Variance swaps are over-the-counter derivatives that exchange payments related to future realized price variance against fixed rates. Variance swaps help estimating term structures for variance risk premia, i.e. market premia for hedging against volatility risk based in the difference between market-priced variance and predicted variance. The swap rates conceptually produce more accurate estimates
  • Mutual fund performance and survivorship bias [Mathematical Investor]

    As we have noted in previous Mathematical Investor blogs (see this blog for instance), surprisingly few mutual funds beat their respective benchmark (typically some market index). Even fewer consistently beat their benchmarks year after year. A new report from S&P Dow Jones sheds light on this phenomenon. It tabulates, for each year from 2001 through 2017, the percent of mutual funds in

Quantocracy’s Daily Wrap for 08/03/2018

This is a summary of links featured on Quantocracy on Friday, 08/03/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Conference: Financial Revolution – Sentiment Analysis, AI and Machine Learning – Oct 30, 2018, Zurich

    Artificial Intelligence is deemed to be the main driver of the 4th Industrial Revolution. IDC predicts that investment in AI will grow from $12bn in 2017 to $57.6 by 2021, while Deloitte Global predicts the number of machine learning pilots and implementations will double in 2018 compared to 2017. As a result, companies from every industry have been spurred on to seize the trend and innovate
  • A Q&A Discussion with Vanguard Researchers on the “Fair Value CAPE Ratio” [Alpha Architect]

    As everyone whos been invested for the last ten years knows, post-financial crisis stock returns have been incredible. The chart below highlights the total returns for the S&P 500 Index, the MSCI EAFE Index, the MSCI EEM Index, and the MSCI ACWI Index. The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually
  • Tactical Asset Allocation in July [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies, net of transaction costs. 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

Quantocracy’s Daily Wrap for 08/01/2018

This is a summary of links featured on Quantocracy on Wednesday, 08/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • RSI2 Strategy: Double returns with a simple rule change [Alvarez Quant Trading]

    While playing around with a 2 period RSI (Relative Strength Index) mean reversion strategy, I came up with a very simple rule change with a much larger impact on the results than expected. I doubled the compounded annual growth rate and cut the maximum drawdown in half. That never happens. In my optimization runs the best CAR went from lows 10s to the low 20s with this rule change. The
  • Consistent Momentum [Sutherland Research]

    Its been some time since I last posted so what better way to start than by quantifying and exploring a momentum strategy that was first introduced to me by the good guys at Quantpedia (www.quantpedia.com). If you havent heard of this site before, then I encourage you to check it out. For a nominal fee you get access to an incredible array of trading strategies that have been sourced and
  • Momentum Solutions for Retirement [Dual Momentum]

    As the surge of boomer retirements continues, commentators have given new thought to what safe withdrawal rates are for retirement accounts. The topic is especially significant given two additional factors. First, retirement balances are shockingly low for boomers (Ghilarducci 2015)[1]. Second, market fundamentals do not suggest that either bonds or equities will generate reliably strong rates of

Quantocracy’s Daily Wrap for 07/30/2018

This is a summary of links featured on Quantocracy on Monday, 07/30/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Measuring Process Diversification in Trend Following [Flirting with Models]

    We prefer to think about diversification in a three-dimensional framework: what, how, and when. The how axis covers the process with which an investment decision is made. There are a number of models that trend-followers might use to capture a trend. For example, trend-followers might employ a time-series momentum model, a price-minus moving average model, or a double moving average
  • Factors: Shorting Stocks vs The Index [Factor Research]

    Most factor investing research is based on long-short stock portfolios Investible risk premia strategies often feature a short index position Trade-off between theoretical alpha and implementation costs & efficiency INTRODUCTION Amundi, a French asset manager, was the first institution to launch a European multi-factor ETF that was market neutral, the Amundi ETF iSTOXX Europe Multi-Factor
  • Finance Journals Rarely Publish Articles with low T-stats [Alpha Architect]

    Coined by Rosenthal in 1979, the term file drawer problem refers to the notion that journal editors are biased toward accepting articles that include statistically significant results over those with nonsignificant results. The competition for increasing the citation count and improving journal impact numbers is considerable and primarily driven by the fact that articles with significant results
  • Review: Quantpedia.com [Throwing Good Money]

    Quantpedia contacted me a few months ago and asked if Id be interested in reviewing their site on my blog. Im always looking for new ideas for trading systems, so I said sure! (Disclosure: they provided me with free account access during the review period.) Quantpedia.com is an aggregator and interpreter of academic papers on trading and financial research. An encyclopedia of
  • Predictability of Betting-Against-Beta Factor [Quantpedia]

    The leverage aversion theory implies that returns to the betting-against-beta (BAB) strategy are predictable by past market returns: An outward shift in investors' aggregate demand function simultaneously increases market prices and increases the expected future BAB return. I confirm the prediction empirically and find that the BAB strategy performs better in times when and in countries where

Quantocracy’s Daily Wrap for 07/29/2018

This is a summary of links featured on Quantocracy on Sunday, 07/29/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market intraday momentum [Eran Raviv]

    I recently spotted the following intriguing paper: Market intraday momentum. From the abstract of that paper: Based on high frequency S&P 500 exchange-traded fund (ETF) data from 19932013, we show an intraday momentum pattern: the first half-hour return on the market as measured from the previous days market close predicts the last half-hour return. This predictability, which is both
  • Seasonalities: Bad Period for Stocks? [Quintuitive]

    I just finished the implementation of another approach to finding repetitive calendar behaviour, and was quite surprised that the only short period for stocks, has just began. What are the odds of this?

Quantocracy’s Daily Wrap for 07/28/2018

This is a summary of links featured on Quantocracy on Saturday, 07/28/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Understanding Stock Price Range Forecasts [Jonathan Kinlay]

    Range forecasts are produced by estimating the parameters of a Geometric Brownian Motion process from historical data and using the model to project a large number of sample paths for the stock price over the coming month and year. For example, this is a range forecast for Netflix, Inc. (NFLX) as at 7/27/2018 when the price of the stock stood at $355.21: $NFLX As you can see, the great majority of
  • The dangerous disregard for fat tails in quantitative finance [SR SV]

    The statistical term fat tails refers to probability distributions with relatively high probability of extreme outcomes. Fat tails also imply strong influence of extreme observations on expected future risk. Alas, they are a plausible and common feature of financial markets. A summary article by Nassim Taleb reminds practitioners that fat tails typically invalidate methods and conventions

Quantocracy’s Daily Wrap for 07/27/2018

This is a summary of links featured on Quantocracy on Friday, 07/27/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Simple Hedging System With Time Exit [Relative Value Arbitrage]

    This post is a follow-up to the previous one on a simple system for hedging long exposure during a market downturn. It was inspired by H. Krishnans book The Second Leg Down, in which he referred to an interesting research paper [1] on the power-law behaviour of the equity indices. The paper states, We find that the distributions for t 4 days (1560 mins) are consistent with a power-law