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Quantocracy’s Daily Wrap for 05/12/2021

This is a summary of links featured on Quantocracy on Wednesday, 05/12/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Getting historical data from MetaTrader [Thiago Marzagao]

    Getting historical intraday financial data can be a pain, especially for non-US markets. If you have deep pockets you can simply buy the data you need, but for retail investors the cost is prohibitive. If you want historical transaction-level data for the Brazilian stock market, for instance, TickData will sell it to you for about US$ 65000. Hard pass. What to do? I recently learned about an app
  • Strategy Backtesting in Mathematica [Jonathan Kinlay]

    This is a snippet from a strategy backtesting system that I am currently building in Mathematica. One of the challenges when building systems in WL is to avoid looping wherever possible. This can usually be accomplished with some thought, and the efficiency gains can be significant. But it can be challenging to get ones head around the appropriate construct using functions like FoldList, etc,
  • Different ranking methods for a monthly S&P500 Stock Rotation Strategy [Alvarez Quant Trading]

    Recently for my own trading, I have been researching rotational strategies on both the weekly and monthly timeframes. The most common indicator that I use for ranking stocks is Rate of Change (ROC) of the closing price. I read about using Rate of Change on the EMA to rank stocks. I liked a small twist on the idea and wanted to know how it compared to what I am using. Then this led me down another
  • A Decade of Cryptocurrencies [Grzegorz Link]

    It has been almost 11 years since the first official Bitcoin trades in July of 2010. It's price has experienced quite a run. Although controversial, cryptocurrencies have firmly taken hold of the current investing landscape, won hearts and minds of groups of investors, suggesting they are here to stay for longer than many have anticipated. As more data becomes available, it is interesting to
  • Value Investing Still Beats Growth Investing, Historically [Alpha Architect]

    A few weeks ago I saw comments on Twitter regarding the Russell 3,000 Value and Growth indices having approximately the same returns since inception. For example, here is Ben Johnson from Morningstar 1 As viewed from this tweet, and is born out in the data for the Russell indices, it appears that Value investing has no edge relative to growth investing over the past 40+ years! 2 So once again its
  • Estimating Fair Value For The 10-Year Treasury Yield [Capital Spectator]

    The world is awash in efforts to model a theoretical value for the stock market the CAPE ratio, for example. But while the equities hog much of the attention on this front, similar analytics for the worlds most important interest rate are no less valuable. How to begin? Not surprisingly, there are countless possibilities. Alas, time is short. Enter a model that generates a baseline estimate

Quantocracy’s Daily Wrap for 05/10/2021

This is a summary of links featured on Quantocracy on Monday, 05/10/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Copula for Statistical Arbitrage: C-Vine Copula Trading [Hudson and Thames]

    This is the sixth article of the copula-based statistical arbitrage series. You can read all the articles in chronological order below. In this series, we dedicate articles 1-3 to pairs-trading using bivariate copulas and 4-6 to multi-assets statistical arbitrage using vine copulas. Copula for Pairs Trading: A Detailed, But Practical Introduction. Copula for Pairs Trading: Sampling and Fitting to
  • Kalman Filter Techniques And Statistical Arbitrage In China’s Futures Market In Python [Quant Insti]

    Contrary to a more developed market, arbitrage opportunities are not readily realised which suggests there might be opportunities for those looking and able to take advantage of them. This project focuses on China's futures market using Statistical Arbitrage and Pair trading techniques. This article is the final project submitted by the author as a part of his coursework in Executive
  • Improving the Odds of Value Investing [Factor Research]

    The stock market volatility, skewness, and yield curve influence the performance of the value factor Investors require a certain market environment to buy troubled companies The key performance driver of the value factor is risk sentiment INTRODUCTION Ted Theodore first wrote about value versus momentum stocks way back in 1984, but almost 40 years later, there still is no real consensus among

Quantocracy’s Daily Wrap for 05/09/2021

This is a summary of links featured on Quantocracy on Sunday, 05/09/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 05/07/2021

This is a summary of links featured on Quantocracy on Friday, 05/07/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How I learned to stopped worrying and love the Bitcoin (future) [Investment Idiocy]

    For the last seven years since I started trading my own account I've pretty much kept the same set of futures markets: around 40 or so, with very occasional changes. The number is limited, as to trade more markets I'd need more capital. The set of markets I have is a compromise between getting a diversified portfolio, avoiding low volatility, not paying too much in trading costs, not
  • Accelerating Dual Momentum Redux: Longer History, Tempered Expectations [Allocate Smartly]

    This is a follow up to a strategy weve covered previously: Accelerating Dual Momentum (ADM) from EngineeredPortfolio.com. See our first test of ADM, which includes a description of the strategy rules and our own analysis of the strategy. Here weve extended our test by 20 years to include a less effective era for this strategy. Results from 1970 net of transaction costs follow. Read more
  • Risk Parity Asset Allocation [Quantpedia]

    This article is a primer into the methodology we use for the Portfolio Risk Parity report, which is a part of our Quantpedia Pro offering. We explain three risk parity methodologies Naive Risk Parity (inverse volatility weighted), Equal Risk Contribution and Maximum Diversification. Quantpedia Pro allows the design of model risk parity portfolios built not just from the passive market factors

Quantocracy’s Daily Wrap for 05/06/2021

This is a summary of links featured on Quantocracy on Thursday, 05/06/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • U.K. Value Factor – The 200+ Year View [Two Centuries Investments]

    One year ago, I wrote about the U.S. Value factor and what I found by extending its history back in time before 1926. In summary, I wrote that Values drawdown in March 2020 was normal and likely close to its bottom. Without the insights from the extended history, Value had appeared dead given it had crossed the previous all-time maximum drawdown. As far as factor timing goes, I was close
  • Text-Based Factor Investing [Alpha Architect]

    This is the first part of a series of guest posts by Kai Wu, the CIO & Founder of Sparkline Capital. The Factor Zoo As readers of Alpha Architects blog, youre certainly familiar with factor investing. Factors are quantifiable firm characteristics that explain cross-sectional stock returns. While some factors merely explain risk (e.g., industry), others are also associated with positive

Quantocracy’s Daily Wrap for 05/05/2021

This is a summary of links featured on Quantocracy on Wednesday, 05/05/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Resurrecting the Value Premium [Alpha Architect]

    The dramatic underperformance of value stocks as defined by the HmL (the return on high book-to-market stocks minus the return on low book-to-market stocks) since 2017 has led many to question the existence of the value premium. The recent drawdown has been by far the largest ever experienced. From January 2017 through August 2020, the Fama-French small value research index produced a total return

Quantocracy’s Daily Wrap for 05/03/2021

This is a summary of links featured on Quantocracy on Monday, 05/03/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quant Minds Online Virtual Conference, May 24-28. Save 10% with this link. [Quant Minds]

    Mid-year learning and knowledge sharing for the quant finance community A week of 5 precision-engineered digital summits, laser-focused on the most innovative research. Choose the days that matter to you. Meet the quants finding solutions to the same problems you face.
  • 60/40 Portfolios Without Bonds [Factor Research]

    Bonds have become less useful in asset allocation given low to negative expected returns Liquid alternative strategies can be used to replace bonds From a historic perspective, long volatility strategies would have been especially attractive INTRODUCTION John Maynard Keynes famously asked, when the facts change, I change my mind what do you do, sir?. If this question was directed at
  • Macro information waste and the quantamental solution [SR SV]

    Financial markets are not macro information efficient. This means that investment decisions miss out on ample relevant macroeconomic data and facts. Information goes to waste due to research costs, trading restrictions, and external effects. Evidence of macro information inefficiency includes sluggishness of position changes, the popularity of simple investment rules, and the prevalence of

Quantocracy’s Daily Wrap for 05/01/2021

This is a summary of links featured on Quantocracy on Saturday, 05/01/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Timing Using Aggregate Equity Allocation Signals [Alpha Architect]

    When it comes to predicting long-term equity returns, several well-known indicators come to mindfor example, the CAPE ratio, Tobins Q, and Market Cap to GDP, to name a few. Yet there is another indicator without nearly as high of a profile that has outperformed the aforementioned indicators significantly when it comes to both forecasting and tactical asset allocation. That indicator, known
  • Research Review | 30 April 2021 | Interest Rates & Yield Curves [Capital Spectator]

    Forecasting Bond Risk Premia using Stationary Yield Factors Tobias Hoogteijling (Robeco Asset Management), et al. April 12, 2021 The standard way to summarize the yield curve is to use the first three principal components of the yield curve, resulting in level, slope and curvature factors. Yields, however, are non-stationary. We analyze the first three principal components of yield changes, which

Quantocracy’s Daily Wrap for 04/28/2021

This is a summary of links featured on Quantocracy on Wednesday, 04/28/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Copula for Statistical Arbitrage: Stocks Selection [Hudson and Thames]

    This is the fifth article of the copula-based statistical arbitrage series. You can read the previous four articles with the first three focusing on pairs-trading: Copula for Pairs Trading: A Detailed, But Practical Introduction. Copula for Pairs Trading: Sampling and Fitting to Data. Copula for Pairs Trading: A Unified Overview of Common Strategies. Copula for Statistical Arbitrage: A Practical
  • Reducing data dimensionality using PCA [Quant Dare]

    One common problem when looking at financial data is the enormous number of dimensions we have to deal with. For instance, if we are looking at data from the S&P 500 index, we will have around 500 dimensions to work with! If we have enough computing power, we will be able to process so much data, but that will not always be the case. Sometimes, we need to reduce the dimensionality of the

Quantocracy’s Daily Wrap for 04/27/2021

This is a summary of links featured on Quantocracy on Tuesday, 04/27/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Site: GANs and Synthetic Market Data (h/t @thodoha) [Mark Best]

    I have been thinking a lot about risk lately. The liquidity injections from the FED are pushing risk assets higher and higher. There seem to be bubbles in nearly every speculative assets. The main concern long term would be rising rates at the same time as a falling dollar suggesting there is no longer a market for US debt. Recently however rates have been rising which is causing concern that the
  • Learning the Exit (part 2) [Tr8dr]

    As described in my prior post Learning the Exit (part 1), I have a model that indicates mean reversion entries with ~81% accuracy, however I did not have a good approach in handling the exit. While 81% of MR signals had a minimum profit of 25% (of prior amplitude), the mean profit available was 150%, pointing to a larger profit opportunity to be had if can better handle the exit. I have found it