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Quantocracy’s Daily Wrap for 04/11/2022

This is a summary of links featured on Quantocracy on Monday, 04/11/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What’s the Best Factor for High Inflation Periods? – Part I [Quantpedia]

    In the past couple of weeks, we have done a few event studies, analyzing events that in one way or another resemble what is happening in the world today. At the beginning of March, we examined Factor Performance in Cold War Crises, and at the end of March, we brought you an article analyzing Nuclear Threats and Factor Performance. Today we are going to look into factor performance during high
  • Trend Following & Factor Investing – Unexpected Cousins? [Factor Research]

    Trend following and beta-neutral factor investing are considered diversifying strategies However, since 2009 their correlations to stocks moved in tandem Both strategies had related performance drivers and risk exposures INTRODUCTION Asset classes seem easy to distinguish at first. For example, stocks and corporate bonds provide different exposure to the capital structure of companies. However,
  • Find Your Best Market to Trade With the Hurst Exponent [Raposa Trade]

    After five consecutive years of drought, Northern Californians welcomed the heavy rainfall in the winter of 2016-2017. By February, however, the rain had led many to worry about the integrity of the Lake Oroville Dam. Officials evacuated over 200,000 residents who lived downstream of the dam along the Feather River and engineers opened the emergency spillway. Soon, however, a small crack in the
  • Shorting ETFs: A look into the ETF Loan Market [Alpha Architect]

    The growth of ETFs has been explosive (and we arent helping the matter via ETF Architect which facilitates low-cost high quality ETF white label services). At the end of 2020, there was roughly $5.4 trillion invested in ETFs in the United States, representing more than 25% of US market trading by daily volume in the recent decade (ICI Factbook, 2021). One of the many benefits of ETFs relative

Quantocracy’s Daily Wrap for 04/08/2022

This is a summary of links featured on Quantocracy on Friday, 04/08/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Guide to Obtaining Time Series Datasets in Python (h/t @PyQuantNews) [Machine Learning Mastery]

    Datasets from real-world scenarios are important for building and testing machine learning models. You may just want to have some data to experiment with an algorithm. You may also want to evaluate your model by setting up a benchmark or determining its weaknesses using different sets of data. Sometimes, you may also want to create synthetic datasets, where you can test your algorithms under
  • Is Sector-neutrality in Factor Investing a Mistake? [Alpha Architect]

    Firm characteristics such as size, book-to-market ratio, profitability, and momentum have been found to be correlated with expected returns. The predictive power of these characteristics may stem from their industry component, their firm-specific component, or both. For example, while the study Do Industries Explain Momentum, found that momentum in stocks stems from the industry component,
  • Simple Machine Learning Models on OrderBook/PositionBook Features [Dekalog Blog]

    This post is about using OrderBook/PositionBook features as input to simple machine learning models after previous investigation into the relevance of such features. Due to the amount of training data available I decided to look only at a linear model and small neural networks (NN) with a single hidden layer with up to 6 hidden neurons. This choice was motivated by an academic paper I read online

Quantocracy’s Daily Wrap for 04/06/2022

This is a summary of links featured on Quantocracy on Wednesday, 04/06/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Benford s Law and Strategy Selection [Alvarez Quant Trading]

    While talking to a trader, he mentioned an article in the December 2021 issue of Technical Analysis of Stocks & Commodities about Benfords Law. I had read the same article and was wondering how it could be applied to my trading. Benfords Law is often used to look for fraud. I am sure I am not committing fraud on myself. As we talked, we wondered whether this could help in selecting which
  • Transformers: is attention all we need in finance? Part II [Quant Dare]

    Using PyTorch to test the attention mechanism applied to time series forecasting. Introduction In the previous post we saw what Transformers are and how they work in its basic form. In this post we will develop one possible way to adapt the original design, which was created [1] to target NLP tasks, for time series applications. We will use PyTorch to implement some models and test the results

Quantocracy’s Daily Wrap for 04/04/2022

This is a summary of links featured on Quantocracy on Monday, 04/04/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why 90% of Backtests Fail [Financial Hacker]

    About 9 out of 10 backtests produce wrong or misleading results. This is the number one reason why carefully developed algorithmic trading systems often fail in live trading. Even with out-of-sample data and even with cross-validation or walk-forward analysis, backtest results are often way off to the optimistic side. The majority of trading systems with a positive backtest are in fact
  • Optimize Your Trading Strategy With Python And The Kelly Criterion [Raposa Trade]

    Retail traders almost always have small trading accounts. To get the returns they're after, traders frequently take on leverage – often times imprudent amounts in highly levered FOREX accounts that can be levered 50-100x! Retail equity brokers are a bit more conservative with maximum leverage ratios of 2-3x. Leverage is a dangerous thing to play with – and we don't recommend
  • Gaining an Edge via Textual Analysis of FOMC Meetings [Alpha Architect]

    How investors understand and use central bank communications, aka FEDSPEAK, is oftentimes cryptic and difficult to analyze. This study attempts to provide some clarity to this issue by applying textual analysis to both high-frequency price and communication data, to focus on episodes whereby stock price movements are identifiable and on investors reactions to specific sentences communicated by
  • Factor Olympics Q1 2022 [Factor Research]

    Factor volatility was low despite the significant geopolitical and economic turmoil in Q1 2022 Value is the clear winner with double-digit gains Quality stocks underperformed, but only moderately INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10 years. Specifically, we only present factors where academic research supports the existence of
  • Equity convexity and gamma strategies [SR SV]

    Equity convexity means that a stock outperforms in times of large upward or downward movements of the broad market: its elasticity to the market return is curved upward. Gamma is a measure of that convexity. All else equal, positive gamma is attractive, as a stock would outperform in market rallies and diversify in market stress. However, gamma is not observable, changeable, and needs to be

Quantocracy’s Daily Wrap for 04/01/2022

This is a summary of links featured on Quantocracy on Friday, 04/01/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mean-Variance Optimization: Well Diversified (Near) Efficient Portfolios [Portfolio Optimizer]

    One well-known stylized fact of the Markowitzs mean-variance framework is that, irrespective of the quality of the estimates of asset returns and (co)variances, efficient portfolios are concentrated in a very few assets1. From a practitioners perspective, this has always been a problem12. In this blog post, I will describe a solution proposed in Corvalan3, which is to replace efficient
  • Nuclear Threats and Factor Performance – Takeaway for Russia-Ukraine Conflict [Quantpedia]

    The Russian invasion of Ukraine and its repercussions continue to occupy front pages all around the world. The battle situation is very dynamic, but it seems that Ukraine holds ground very well and is even able to execute strong local counter-offensives against Russian forces. Thats definitely not a situation that president Putin had expected when he started his special operation.

Quantocracy’s Daily Wrap for 03/31/2022

This is a summary of links featured on Quantocracy on Thursday, 03/31/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Are Stock Market Bubbles Identifiable? [Alpha Architect]

    We can define an investment bubble as an irrational strong price increaseimplying a predictable strong decline. The efficient market hypothesis (EMH) implies both the absence of bubbles and that the future return is unpredictable. In his Nobel Prize lecture, the father of the EMH, Eugene Fama stated: The available research provides no reliable evidence that stock market price declines are
  • Yield Curve Inversions and SPX Returns [Quantifiable Edges]

    There has been a lot of talk recently about yield curve inversions and whether that means a recession is on the way, and how soon? And if there is a recession, will there also be a bear market? I decided to forget about economic forecast and just look at how the SPX did after a curve inversion. I looked at both the 2yr/10yr and the 3mo/10yr combinations. For the study I used Norgate Data, and
  • Mutual Fund Returns vs Investor Returns [Quant Dare]

    It is well known that we investors are full of biases when making investment decisions (loss-aversion, trend-chasing, ), but what is the real impact of these biases on our performance? In this post we will try to answer this question quantitatively, and we will also compare the average investor returns with the average mutual funds returns. Do you want to know how good is the investors

Quantocracy’s Daily Wrap for 03/28/2022

This is a summary of links featured on Quantocracy on Monday, 03/28/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Which Articles Should You Read on SeekingAlpha.com? [Alpha Architect]

    One of the most established tenets in social psychology science states, When considering what content to share in their social interactions, people primarily contemplate what impressions their sharing could create among receivers and whether those impressions are consistent with who they are or desire to be. ( mainly they want to be liked and seen as competent). It is defined in scientific
  • Building a Diversified Portfolio for the Long-Term [Factor Research]

    Most diversifying strategies fail to provide diversification benefits when most needed We build a diversified portfolio via trend, multi-factor, and long volatility An equal-weighted approach to asset allocation is not worse than more complex approaches INTRODUCTION At FactorResearch, we have published more than 200 research articles on investing, which included diverse topics ranging from
  • Positive $SPX Seasonality After the 4th Friday in March [Quantifiable Edges]

    There are some bullish forces kicking in the next few weeks. For one, the week after the 4th Friday in March has been a strong one over the last 24 years. (Not as much before that.) We can see this in the study below, which I showed in this weekends subscriber letter. Positive SPX seasonality after 4th Friday in March That is an encouraging looking curve and bullish stats. Traders may want to

Quantocracy’s Daily Wrap for 03/27/2022

This is a summary of links featured on Quantocracy on Sunday, 03/27/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using requests and BeautifulSoup in Python to scrape data [Wrighters.io]

    The amount of data available on the internet is quite staggering. It is often quite easy to do a quick search and click through to view data on a website. However, if you want to actually use that data in your analysis, you have to be able to fetch it and convert it into a format that is usable. The creators and owners of the websites, however, may not want you do this. They might prefer that you
  • Top N Crypto-Assets by MarketCap for Backtesting Purposes in Python [Quant at Risk]

    A quantitative research over the construction of a perfect crypto-portfolio can be based on a number of crypto-assets. The selection of them is of paramount importance. If you are able to build the right portfolio, stick to it, or successfully manage its composition in time (e.g. through the method of rebalancing), the final PnL coming from your management can be worth every dollar invested in all
  • 5 Economic Indicators That Matter To Investors [Decoding Markets]

    Recently, I grabbed a book from my library that had been standing there for the past 10 years. Its called Guide to the 50 Economic Indicators That Really Matter. Its one of the few books that describe concrete trading strategies that are still relevant. Its also a great read to brush up on knowledge about economic indicators. Lets talk about some of them. Indicators Matter In a typical

Quantocracy’s Daily Wrap for 03/26/2022

This is a summary of links featured on Quantocracy on Saturday, 03/26/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 2022 Democratize Quant Conference Recap and Materials [Alpha Architect]

    We recently hosted our Democratize Quant Conference (sign up here for updates). This post is a recap of what we heard and some resources we can make available to the public. Democratize Quant 2022 Agenda/Outline Session 1: State of the Asset Management Industry (with a focus on the ETF aspect) Dave Nadig presented on the current state of the ETF business and much more! Slides Here is what I
  • Hedging cash flows [Quant Dare]

    Currency hedging is a powerful tool, offering foreign investors access to new opportunities, providing returns very similar to those of local ones. However, it also has some disadvantages to consider. In this post we will explain how passive hedging could transform the original currency risk problem into a different one: dealing with the cash flows from hedging. Going back to the equation for the
  • Can Investment Flows Affect Prices? Yep. [Alpha Architect]

    Traditional finance theory suggests that stocks prices always reflect their fair market values based on publicly available information. Or in academic parlance, the semi-strong form efficient markets hypothesis serves as the null. What are the implications of this hypothesis? Well, the hypothesis suggests that the only reason a stock price will move is due to a shift in fundamentals (either

Quantocracy’s Daily Wrap for 03/22/2022

This is a summary of links featured on Quantocracy on Tuesday, 03/22/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Finding Alpha on the Internet (Part 3) [Derek Wong]

    We continue the series by replicating using as much data and code as provided in the source material. We create a three-state Gaussian Mixture Model and fit it so S&P500 data. I examine the output and give feedback about my coding replication and data sourcing along the way. Then I try to apply a proxy for adding economic data as a featureprevious posts Part 1 and Part 2. Disclaimer: Not
  • Hacking 1-Minute Cryptocurrency Candlesticks: Capturing Binance Live Data [Quant at Risk]

    There is no question about how profitable the trading of cryptocurrencies can be. If you create an algorithmic strategy and stick to it, you can capture a +10% PnL wave sometimes even twice a day for a selected asset. Unfortunately, the opposite is true, too! The crypto-risks seem to follow the same patterns. But, lets be optimistic from the beginning. In this mini-series of articles, we will
  • Intraday Stock Index Forecasting [Jonathan Kinlay]

    In a previous post I discussed modelling stock prices processes as Geometric brownian Motion processes: To recap briefly, we assume a process of the form: Where S0 is the initial stock price at time t = 0. The mean of such a process is: and standard deviation: In the post I showed how to estimate such a process with daily stock prices, using these to provide a forecast range of prices over a
  • What Can We Learn from Insider Trading in the 18th Century? [Quantpedia]

    Directors, board members, and large shareholders are just some of those who might have non-public material information about their firm. Even though this information could be easily used to profit by trading their own stocks (stocks of the company they hold information about), this behavior is strictly prohibited. This is but one aspect of insider trading. There are two different possible