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Quantocracy’s Daily Wrap for 03/08/2021

This is a summary of links featured on Quantocracy on Monday, 03/08/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Detecting Volume Breakouts [Financial Hacker]

    It is estimated that about 6000 different technical indicators have been meanwhile published, but few of them are based on volume. In his article in Stocks & Commodities April 2021, Markos Katsanos proposed a new indicator for detecting high-volume breakouts. And he tested it with a trading system that I believe is the most complex one ever posted on this blog. The VPN indicator calculates the
  • Autoregression: Model, Autocorrelation and Python Implementation [Quant Insti]

    Time series modelling is a very powerful tool to forecast future values of time-based data. Time-based data is data observed at different timestamps (time intervals) and is called a time series. These time intervals can be regular or irregular. Based on the pattern, trend, etc. observed in the past data, a time series model predicts the value in the next time period. The time series models
  • Low Volatility Factor Investing: Risk-Based or Behavioral-Based or Both? [Alpha Architect]

    The low-risk effect (aka low volatility) is based on the empirical observation that assets with low risk have high alpha. Specifically in this research, the effect is defined as the risk-adjusted return spread between low-risk and high-risk portfolios and not just low-risk stocks. Since the low-risk effect confounds traditional asset pricing models, various researchers have developed competing

Quantocracy’s Daily Wrap for 03/06/2021

This is a summary of links featured on Quantocracy on Saturday, 03/06/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • NER For Stock Mentions on Reddit (h/t @PyQuantNews)

    eddit has been at the epicenter of one of the biggest movements in the world of finance, and although it seemed like an unlikely source of such a movement its hardly surprising in hindsight. The trading-focused subreddits of Reddit are the backdrop for a huge amount of discussion about what is happening in the markets so it is only logical to tap into this huge data source. When

Quantocracy’s Daily Wrap for 03/04/2021

This is a summary of links featured on Quantocracy on Thursday, 03/04/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Does it make sense to change your trading behaviour in different periods of volatility? [Investment Idiocy]

    A few days ago I was browsing on the elitetrader.com forum site when someone posted this: I am interested to know if anyone change their SMA/EMA/WMA/KAMA/LRMA/etc. when volatility changes? Let say ATR is rising, would you increase/decrease the MA period to make it more/less sensitive? And the bigger question would be, is there a relationship between volatility and moving average? Interesing I
  • Momentum Factor Investing: What’s the Right Risk-Adjustment? [Alpha Architect]

    The momentum factor represents one of our core investment beliefs: buy winners. So when research presents itself that may contradict our beliefs it provides the opportunity to dig deeper and think harder about the factors we hold so dearly. Erik Theissen and Can Yilanci begin their paper by warming us up to the idea that momentum does outperform, and when measured on a portfolio level
  • Adding candlesticks to mean reversion setup [Alvarez Quant Trading]

    My preferred chart style is a candlestick chart but I have never investigated candlestick formations to see if they can help provide an edge in my trading. I recently ran into this blog post, Do Candlesticks Work? A Quantitative Test Of 23 Candlestick Formations, where he did his own investigation. Even better he shared the code for the formations in AmiBroker which would make it a lot easier. You

Quantocracy’s Daily Wrap for 03/02/2021

This is a summary of links featured on Quantocracy on Tuesday, 03/02/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Testing a Risk Premium Value Strategy [Allocate Smartly]

    This is a test of a Risk Premium Value strategy (RPV) that allocates to major US asset classes based on current risk premium valuations relative to historical norms. Readers will note the similarity between RPV and other related strategies, such as CXO Advisorys SACEVS. Backtested results from 1987 net of transaction costs follow (see backtest assumptions). Results are shown in two flavors:
  • Does Crowdsourced Investing Work? [Alpha Architect]

    Historically, as Richard Thaler pointed out in his book Misbehaving, financial academics have looked at humans as Econs. An Econ, unlike a human, values everything down to a penny before they make a decision, knows all possible alternatives, weighs them accurately, and always optimizes. 1 In recent years weve moved away from thinking of humans as Econs. We are now left with the age-old

Quantocracy’s Daily Wrap for 03/01/2021

This is a summary of links featured on Quantocracy on Monday, 03/01/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Does X work, some brief thoughts and choose your adventure [Investment Idiocy]

    When I was a spotty teenager I was a walking nerd cliche. I liked computers; both for programming and games. I was terrified of girls. I was rubbish at nearly all sports*. And I played D&D (and Tunnels and Trolls, and Runequest). * Nearly all: Not, I'm not talking about the 'sport' of Chess: I was also rubbish at Chess and still am. But due to some weird anomaly I was a dinghy

Quantocracy’s Daily Wrap for 02/26/2021

This is a summary of links featured on Quantocracy on Friday, 02/26/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Nothing but (neural) net [OSM]

    We start a new series on neural networks and deep learning. Neural networks and their use in finance are not new. But are still only a fraction of the research output. A recent Google scholar search found only 6% of the articles on stock price price forecasting discussed neural networks.1 Artificial neural networks, as they were first called, have been around since the 1940s. But development was
  • VIX and More: The Evolution of the VIX (1) [VIX and More]

    Volatility is notorious for clustering in the short-term, mean-reverting in the medium-term and settling into multi-year macro cycles over the long-term. I have chronicled each of these themes in this space in the past. Apart from volatility, I have also taken great pains to talk about the movements of the VIX, which is one of the most famous instances of implied volatility and represents investor
  • A Robust Approach to Multi-Factor Regression Analysis [Quantpedia]

    Practitioners widely use asset pricing models such as CAPM or Fama French models to identify relationships between their portfolios and common factors. Moreover, each asset class has some widely-recognized asset pricing model, from equities through commodities to even cryptocurrencies. However, which model can we use if our portfolio is complex and consists of many asset classes? Which factors
  • Correlation and correlation structure (5) a new coefficient of correlation [Eran Raviv]

    This is the fifth post which is concerned with quantifying the dependence between variables. When talking correlations one usually thinks about linear correlation, aka Pearsons correlation. One serious limitation of linear correlation is that its, well.. linear. By construction its not useful for detecting non-monotonic relation between variables. Here I share some recent academic
  • The Forecasting Power of Value, Profitability, and Investment Spreads [Alpha Architect]

    Studies such as the 2019 paper Value Return Predictability Across Asset Classes and Commonalities in Risk Premia, have demonstrated that while it is difficult to time investments based on their value spreads 1 which weve covered occasionally here and here, value spreads do contain information on the returns to value strategies in individual equities, industries, commodities, currencies,
  • Research Review | 26 February 2021 | Inflation [Capital Spectator]

    The Increased Toxicity of the U.S. Treasury Security Market Scott E. Hein (Texas Tech University) January 2, 2021 This short research paper documents the fact that exclusively watching for rising yields on conventional U.S. Treasury securities to reflect increased inflationary fears in the U.S. is no longer appropriate. With the Federal Reserve seeking to keep short-term nominal yields near zero

Quantocracy’s Daily Wrap for 02/24/2021

This is a summary of links featured on Quantocracy on Wednesday, 02/24/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • SigCWGAN, a new generation GAN architecture for Time Series Generation [Quant Dare]

    As a continuation to our last post on Time Series Signatures and our running list of posts regarding GANs and synthetic data we now want to present the Signature Conditional Wasserstein GAN, shortened as SigCWGAN, a new GAN architecture presented in [1] that is specifically designed to generate time series of arbitrary length and dimensions. 2. Properties of the Signature The SigCWGAN wields the

Quantocracy’s Daily Wrap for 02/23/2021

This is a summary of links featured on Quantocracy on Tuesday, 02/23/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Accelerate Design of Multi-Factor Multi-Asset Models with Quantpedia Pro [Quantpedia]

    We hinted in the past few blogs that we were preparing a small surprise. And now its time to unveil what we have been cooking during the previous several months. Quantpedias main mission is to help with the discovery of new ideas for systematic trading strategies. Our users can quickly identify the most promising quant research papers for studying. However, once a handful of Quantpedia ideas
  • 3 ways traders kill trading strategies w/ Rob Carver of @InvestingIdiocy [Better System Trader]

    Ever built an angelic trading strategy that performed heavenly in a backtest, only to find its a devil in live trading? Well there are some very specific sins traders make when building trading strategies that destine them (the strategies that is) to a miserable life of soul-sucking underperformance, endless torment and an untimely death. Nobody wants to see their strategies suffer
  • How useful are Moving Averages – Backtest Results [Milton FMR]

    How can we know if moving averages are effective? Can a moving average tell us whether a trend will continue or not? Is the golden cross really useful in predicting trend reversals? What about predicting bear markets with a moving average crossover? First of we start by defining what a moving average is and what it is used for. Basically, it is a statistic that captures the average change in a
  • The Risk and Returns to Private Debt Investments [Alpha Architect]

    The subject of private debt and its associated performance characteristics has not been covered sufficiently in the academic literature. Relatively few research articles have attempted to characterize the returns and risk on the types of private debt strategies available to investors. This is true, in spite of the position private debt holds as the dominant source of capital for private firms in

Quantocracy’s Daily Wrap for 02/22/2021

This is a summary of links featured on Quantocracy on Monday, 02/22/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sparse Mean-reverting Portfolio Selection [Hudson and Thames]

    Buy low, sell high. One cannot find a more succinct summary of a mean-reversion trading strategy; however, single assets that show stable mean-reversion over a significant period of time such that a mean-reversion trading strategy can readily become profitable are rare to find in markets today. Even if such gems were found, celebrating the discovery of the gateway to easy money could prove
  • The R&D Premium: Is it Risk or Mispricing? [Alpha Architect]

    Asset pricing models are important because they help us understand which factors explain the variation of returns across diversified portfolios. However, models are not like cameras that provide a perfect picture of the world. If models were perfectly correct, they would be laws, like we have in physics. Instead, models are engines that advance our understanding of how markets work, and prices are
  • Understanding the disposition effect [SR SV]

    Investors have a tendency to sell assets that have earned them positive returns and are reluctant to let go of those that have brought them losses. This behavioural bias is called disposition effect and is attributed to loss aversion and regret avoidance. It has been widely documented by empirical research. The prevalence of the disposition effect is a key motivation behind trend following

Quantocracy’s Daily Wrap for 02/17/2021

This is a summary of links featured on Quantocracy on Wednesday, 02/17/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Finance Database GitHub (h/t @PyQuantNews)

    As a private investor, the sheer amount of information that can be found on the internet is rather daunting. Trying to understand what type of companies or ETFs are available is incredibly challenging with there being millions of companies amd derivatives available on the market. Sure, the most traded companies and ETFs can quickly be found simply because they are known to the public (for example,
  • Identifying Anomalies in Capital Markets: Accrual Anomaly [Milton FMR]

    Since the financial crisis in 2008 the number of anomaly related academic papers exploded and has grown so quickly that it is impossible to keep up with the full scope of research. To accommodate the need of an overview in this interesting research field we will summarize the most prominent market anomalies and present our findings in a series of articles. We start our series with the accrual
  • Copula for Pairs Trading: Strategies Overview [Hudson and Thames]

    This is the third article of the copula-based statistical arbitrage series. You can read the previous two articles: Copula for Pairs Trading: A Detailed, But Practical Introduction. Copula for Pairs Trading: Sampling and Fitting to Data. Introduction Systematic approaches of pairs trading gained popularity from the mid-1980s. Gatev et al (2006) examined the profitability of a distance-based