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Quantocracy’s Daily Wrap for 06/04/2022

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

  • Short-term Momentum [Alpha Architect]

    Momentum, the tendency of past winner stocks to outperform past loser stocks over the next several months, is one of the most well-documented and well-researched asset pricing anomalies. In the asset pricing literature, momentum is generally defined over the short-, medium- and long-term in the following manner: Short-term reversals are defined as the prior months (t 1) return. Medium-term

Quantocracy’s Daily Wrap for 06/02/2022

This is a summary of links featured on Quantocracy on Thursday, 06/02/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Evaluating Data Coverage with Tiingo [Quant Start]

    In this article we will be introducting Tiingo, a data and stock market tools provider. Founded in 2014 Tiingo aims to empower its users by providing good, clean and more accurate data. They offer OHLCV data for 82,468 Global Securities, 37,319 US & Chinese Stocks 45,149 ETFs & Mutual Funds. They also have an intraday feed through partnership with IEX. In addition, they have fundamental
  • Options Hedging & Leveraged ETFs in Market Swings [Alpha Architect]

    Not long ago, GameStop stock rose like crazy in only a few hours with the effects of broker-dealer options hedging spurred by retail investor buying pressure. And from February to March 2020, options trading activity was also pointed to as a contributor to stock swings in the Covid-19 selloff. The market dropped 30% and then recovered quickly over the following weeks. It has been documented that

Quantocracy’s Daily Wrap for 05/31/2022

This is a summary of links featured on Quantocracy on Tuesday, 05/31/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trending Fast and Slow [Allocate Smartly]

    This is a test of a tactical strategy from the paper Trending Fast and Slow. It trades the S&P 500 by switching between fast and slow momentum based on market volatility. The strategy would have kept pace with the S&P 500, while significantly reducing the worst drawdowns. Backtested results from 1954 follow. Results are net of transaction costs see backtest assumptions. Learn about

Quantocracy’s Daily Wrap for 05/30/2022

This is a summary of links featured on Quantocracy on Monday, 05/30/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • An introduction to accessing financial data in EDGAR, using Python [Wrighters.io]

    Some sources of financial data can be expensive or difficult to find. For example, some is only available from exchanges or vendors who charge a hefty fee for access. However, the financial industry is also heavily regulated, and one of its main regulators provides free access to its data. The (U.S. Securities and Exchange Commission)[https://www.sec.gov] (known as the SEC), has the mission of
  • Introduction and Examples of Monte Carlo Strategy Simulation [Quantpedia]

    The Monte Carlo method (Monte Carlo simulations) is a class of algorithms that rely on a repeated random sampling to obtain various scenario results. Monte Carlo simulations are used to predict the probability of different outcomes when it would be difficult to use other approaches such as optimization. The main aim is to create alternative scenarios, which account for possible risk and help with
  • Duration volatility risk premia [SR SV]

    Duration volatility risk premium means compensation for bearing return volatility risk of an interest rate swap (IRS) contract. It is the scaled difference between swaption-implied and realized volatility of swap rates changes. Historically, these premia have been stationary around positive long-term averages, with episodes of negative values. Unlike in equity, simple duration volatility risk
  • Biotech Stocks: High Idiosyncratic Risks, High Alpha? [Factor Research]

    Most technological change today is an evolution rather than a revolution. Naturally, it is great to have a mobile device that allows instant access to the global knowledge depository, entertainment, shopping, and so on, but most of these innovations have been predicted decades ago by science fiction authors. Reading such novels actually makes human progress seem awfully slow. Human colonies

Quantocracy’s Daily Wrap for 05/27/2022

This is a summary of links featured on Quantocracy on Friday, 05/27/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 100-Years of Multi-Asset Trend-Following [Quantpedia]

    Trend-following strategies have gained extreme popularity in the recent decade. Almost every asset manager utilizes trend following, or momentum, in some form whether consciously or subconsciously. We at Quantpedia are convinced that each and every strategy has to be scrutinized thoroughly before its put into use. This is one of our motivations why we will introduce to you our framework for
  • Strategies to Mitigate Tail Risk [Alpha Architect]

    Investors care about more than just returns. They also care about risk. Thus, prudent investors include consideration of strategies that can provide at least some protection against adverse events that lead to left tail risk (portfolios crashing). The cost of that protection (the impact on expected returns) must play an important role in deciding whether to include them. For example, buying

Quantocracy’s Daily Wrap for 05/25/2022

This is a summary of links featured on Quantocracy on Wednesday, 05/25/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Extending Historical Daily Commodities Data to 100 years [Quantpedia]

    Finding a high-quality data source is crucial for quantitative trading strategies. Also, having a long history is beneficial. Fama & French, for example, offer free historical data for stocks and a variety of factors. However, it is very hard to get good-quality and free data for other asset classes. For this reason, we have already examined how to extend historical daily bond data to 100
  • Hierarchical clustering: explanation and classification [Quant Dare]

    Clustering algorithms are one of the main techniques in the field of unsupervised learning. In the machine learning context, we understand by unsupervised learning the process of analyzing and identifying patterns in unlabeled datasets. Unsupervised learning algorithms observe similarities and differences in input data in order to discover hidden patterns or data groupings. As their name suggests,

Quantocracy’s Daily Wrap for 05/24/2022

This is a summary of links featured on Quantocracy on Tuesday, 05/24/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Performing Value Strategies – Part 1 [Quantpedia]

    Value strategies attempting at determining a fair value of an asset are one of the first-ever employed strategies in the markets. We all know about Benjamin Graham and Warren Buffet that are one of the best known examples of Value pioneers. Since then, however, Value strategies have evolved enormously. Value strategies have become a cornerstone of almost every factor portfolio, due to their
  • Risk Parity & Rising Rates [Factor Research]

    Risk parity strategies have become available via mutual funds and ETFs, but portfolio construction varies Rising interest rates are seen as a threat and recent performance was disappointing However, rising correlations between stocks and bonds would be more concerning INTRODUCTION Risk parity has been challenged ever since the worlds central banks have brought interest rates to approximately

Quantocracy’s Daily Wrap for 05/22/2022

This is a summary of links featured on Quantocracy on Sunday, 05/22/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Value Investing: Headwinds, Tailwinds, and Variables [Alpha Architect]

    n my past life as a rower, I spent a lot of time figuring out which way the wind was blowing: Would it be a headwind and slow things down? Or would it be a tailwind and shorten the race? But a tailwind that went against the current could cause choppy waterwhich would slow things back down. Variables affect other variables and things can get confusing, quickly. Investing is no different. A

Quantocracy’s Daily Wrap for 05/19/2022

This is a summary of links featured on Quantocracy on Thursday, 05/19/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend Following: Timing Fast and Slow Trends [Alpha Architect]

    Momentum, the tendency of past winner stocks to outperform past loser stocks over the next several months, is one of the most well-documented and well-researched asset pricing anomalies. In our book Your Complete Guide to Factor-Based Investing, Andrew Berkin and I presented the evidence of a premium that has been persistent across long periods of time, pervasive around the globe and across
  • How to Increase Factor Definition Robustness [Quant Dare]

    When dealing with factors information is important to go to the detail and get insight about how the factor is built. Ratios combination improves robustness. When we read papers or studies about the Factor Premium of different factors we almost always come across with the problem of how to define those factors: If we talk about Value Factor, we read in many papers that the factor is measured by
  • Can You Predict Cryptocurrencies? [Decoding Markets]

    The Nobel price laureate physicist Niels Bohr once said, Prediction is very difficult, especially if its about the future. This quote captures the reality in the markets rather accurately. Is Bitcoin breaking through the 50k mark this year? Or even the 100k mark? Will Ethereum outperform Solana between now and the end of the year? Will Bitcoin close higher or lower by the end of the week?

Quantocracy’s Daily Wrap for 05/18/2022

This is a summary of links featured on Quantocracy on Wednesday, 05/18/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Extending Historical Daily Bond Data to 100 Years [Quantpedia]

    Finding a good data source with quality data and long history is one of the greatest challenges in quantitative trading. There definitely are some data sources with very long histories. However, they tend to be on the more expensive side. On the other hand, cheap or free data usually lacks quality and/or has shorter time frames. This article explains how to combine multiple data sources to create
  • SPX and Gold Momentum Portfolio [Alvarez Quant Trading]

    Given the current rise in inflation, there has been a lot more interest in assets that do well during these times. Gold is one asset that is frequently brought up as an inflation hedge. I have also seen more lately about combining these two into a portfolio. Testing Notes The test range is from 1970 to 2021 using $SPX (S&P 500 Index) and @GC (Gold London PM Fix) from Norgate Data. A couple