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Quantocracy’s Daily Wrap for 12/23/2020

This is a summary of links featured on Quantocracy on Wednesday, 12/23/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Petra on Programming: Short-Term Candle Patterns [Financial Hacker]

    Japanese traders invented candle patterns in the 17th century. Some traders believe that those patterns are still valid. But alas, no one yet got rich with them. Still, trading book authors are all the time inventing new patterns, in hope to find one that is really superior to randomly entering positions. In the Stocks & Commodities January 2021 issue, Perry Kaufman presented several new
  • Twas 3 Nights Before Christmas: NASDAQ version [Quantifiable Edges]

    Ive posted and updated the Twas 3 Nights Before Christmas study on the blog here several times since 2008. The study will kick in at the close today (12/22). This year I will again show the Nasdaq version of the study. While all the major indices have performed well during this period, the Nasdaq Composite has some of the best stats.

Quantocracy’s Daily Wrap for 12/21/2020

This is a summary of links featured on Quantocracy on Monday, 12/21/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Monte Carlo option pricing – comparison of R and Julia languages [Mateusz Dadej]

    This example investigates the performance of R in comparison to Julia language. Additionally shows how to easily call Julia inside R code. With that being said, we will load JuliaCall library that enables us to do so. Alternatively, there is also XRJulia library available. library(JuliaCall) It is necessery to tell R where is Julia.exe stored, so the loaded library can communicate with it
  • Visualizing Correlations Among Dow 30 Stocks Via NetworkX [Machine Learning Applied]

    NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Using daily adjusted close data from 20201118 to 20201218 for Dow 30 stocks, we compute correlation coefficients, apply a threshold of 0.8 to find similar stocks, and produce two types of graphs with NetworkX. To compute correlation coefficients, we read in daily
  • Fed Model Improvement? [CXO Advisory]

    Is there a better way than the Fed model to measure relative attractiveness of equities and bonds. In his October 2020 paper entitled Towards a Better Fed Model, Raymond Micaletti examines seven Fed Model alternatives, each comparing a 10-year forward annualized estimate of equity returns to the yield of 10-year constant maturity U.S. Treasury notes (T-note). The seven estimates of future
  • Another miserable year for market forecasters [Mathematical Investor]

    Suppose, during a nightly TV weather broadcast, that a reporter presented forecasts by persons, with no credentials in mathematical meteorology, who based their analysis on eyeballing a few charts and graphs. If anyone took such amateur forecasts seriously, when a severe storm was approaching, rather than relying on the consensus of qualified scientists assisted by state-of-the-art supercomputer

Quantocracy’s Daily Wrap for 12/19/2020

This is a summary of links featured on Quantocracy on Saturday, 12/19/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bitcoin Mempool & Momentum [Tr8dr]

    I have been thinking about the recent institutional buying that has propelled the price of bitcoin to stratospheric levels; in particular considering how one might detect some of this interest early. Bitcoin and crypto in general is quite interesting in that at some level, due to the decentralized ledger, there is more transparency in this market than any other financial market. The majority of
  • Is Size a Useful Investing Factor or Not? [Alpha Architect]

    In his famous 1981 paper, The Relationship Between Return and Market Value of Common Stocks, Rolf Banz found that small firms have higher risk-adjusted returns than large firms. This was one of the first major challenges to the capital asset pricing model (CAPM) and market efficiency in general. However, its failure to generate statistically significant premiums post-publication has called

Quantocracy’s Daily Wrap for 12/18/2020

This is a summary of links featured on Quantocracy on Friday, 12/18/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • QQQ:IWM for Risk-on and GLD:TLT for Risk-off? [CXO Advisory]

    A subscriber asked about a strategy that switches between an equal-weighted portfolio of Invesco QQQ Trust (QQQ) and iShares Russell 2000 ETF (IWM) when the S&P 500 Index is above its 200-day simple moving average (SMA200) and an equal-weighted portfolio of SPDR Gold Shares (GLD) and iShares 20+ Year Treasury Bond ETF (TLT) when below. Also, more generally, is an equal-weighted portfolio of
  • Reinforcement Learning for Trading [Quant Dare]

    One of the most appealing areas of Artificial Intelligence is Reinforcement Learning, for its applicability to a variety of areas. It can be applied to different kinds of problems, in the present article we will analyze an interesting one: Reinforcement Learning for trading strategies. Reinforcement Learning We introduced Reinforcement Learning and Q-Learning in a previous post. In order to

Quantocracy’s Daily Wrap for 12/15/2020

This is a summary of links featured on Quantocracy on Tuesday, 12/15/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Explaining variance [OSM]

    Were returning to our portfolio discussion after detours into topics on the put-write index and non-linear correlations. Well be investigating alternative methods to analyze, quantify, and mitigate risk, including risk-constrained optimization, a topic that figures large in factor research. The main idea is that there are certain risks one wants to bear and others one doesnt. Do you want

Quantocracy’s Daily Wrap for 12/14/2020

This is a summary of links featured on Quantocracy on Monday, 12/14/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Value Factor s Pain: Are Intangibles to Blame? [Factor Research]

    The rise of intangibles has been increasingly used as an argument for the poor performance of the value factor However, this idea is not supported by data The type of market environment is marginally more useful for explaining the value factor performance INTRODUCTION Great storytelling may be the most powerful human skill. Empires have been built by lone individuals whose enthralling narratives
  • December Opex Week Historically Bullish [Quantifiable Edges]

    I have written many times over the years about the bullish tendency of the market during opex week in December. I used to refer to it as The Most Wonderful Week of the Year. And it wasup until 2018. So below is an updated look at the stats and profit curve for owning SPX from the close of the Friday before December opex to the close on December opex. SPX Dec opex week performance bullish
  • Inflation and precious metal prices [SR SV]

    Theory and plausibility suggest that precious metal prices benefit from inflation and negative real interest rates. This makes gold, silver, platinum, and palladium natural candidates for hedges against inflationary monetary policy. Long-term empirical evidence supports the inflation-precious metal link. However, there are important qualifications. First, the equilibrium relation between consumer

Quantocracy’s Daily Wrap for 12/11/2020

This is a summary of links featured on Quantocracy on Friday, 12/11/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Active vs Passive: Smart Factors, Market Portfolio or Both? [Quantpedia]

    We would like to present our newest own-research about factor allocation and passive versus active strategies clash. However, respecting our blog format, this version is largely shortened and we invite you to read the full version. Introduction In the equity market, there are two types of investing: active and passive. The aim of passive investors is to track the market with all the ups and
  • Using Probability Cones to Test for Strategy Death [Alvarez Quant Trading]

    The most common question I get is how do you determine that a strategy is no longer working. It is also the question that I dont have a good answer for. I have written several posts about this: Trading the Equity Curve, How to turn off a strategy using historical volatility, Broken Strategy or Market Change. During his How to detect a failing trading strategy presentation, Kevin Davey discusses
  • Buying Quality: Is the Juice Worth the Squeeze? [Alpha Architect]

    Investing is never easy, but some times are easier than others. Buying US government bonds at 10%+ yields when inflation was steadily decreasing in the 1980s was probably less worrying than buying them today at negative real yields. In todays world, bonds may have largely lost their income-generating purpsose, although they still constitute a large proportion of investors portfolios. What is

Quantocracy’s Daily Wrap for 12/09/2020

This is a summary of links featured on Quantocracy on Wednesday, 12/09/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Evolving Thoughts on Data Mining [Robot Wealth]

    Several years ago, I wrote about some experimentation Id done with data mining for predictive features from financial data. The article has had several tens of thousands of views and nearly 100 comments. I think the popularity of the article lay in its demonstration of various tools and modeling frameworks for doing data mining in R (it didnt generate any alpha, so it cant have been
  • Real-time growth estimation with reinforcement learning [SR SV]

    Survey data and asset prices can be combined to estimate high-frequency growth expectations. This is a specific form of nowcasting that implicitly captures all types of news on the economy, not just official data releases. Methods for estimation include the Kalman filter, MIDAS regression, and reinforcement learning. Since reinforcement learning is model-free it can estimate more efficiently. And

Quantocracy’s Daily Wrap for 12/04/2020

This is a summary of links featured on Quantocracy on Friday, 12/04/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dynamic trend following [Investment Idiocy]

    As most of you know I have a regular(ish) gig talking on the Top Traders Unplugged systematic investor podcast, every month or so with Niels Kaastrup-Larsen and Moritz Seibert. Anyway on the most recent episode we got chatting about whether open or closed equity should matter when trading a position. More broadly, should your history of trading a position affect how you trade it now, or is it only

Quantocracy’s Daily Wrap for 12/03/2020

This is a summary of links featured on Quantocracy on Thursday, 12/03/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Maximizing the Rebalancing Premium [Invest Resolve]

    This short article investigates the rebalancing premium that investors may expect from risk parity portfolios. It is offered as an appendix to the paper, Risk Parity: Methods and Measures of Success. We define rebalancing premium as the difference between the compound return on a portfolio, and the weighted average compound returns produced by the underlying investments in a portfolio. We
  • Profitability Factor Details: Taxable Income is Tied to Future Profitability and Returns [Alpha Architect]

    Robert Novy-Marxs 2013 paper The Other Side of Value: The Gross Profitability Premium not only provided investors with new insights into the cross-section of stock returns but also helped further explain some of Warren Buffetts superior performance. Novy-Marx built upon a 2006 paper, Profitability, Investment, and Average Returns, by Eugene Fama and Kenneth French, who showed