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Quantocracy’s Daily Wrap for 08/06/2020

This is a summary of links featured on Quantocracy on Thursday, 08/06/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quantamental: How to Create a Google Style News Recommender for Your Stocks [Auquan]

    This article is accompanied by a Google Colab notebook, which contains all the code and additional mathematical details. You can find the notebook here: https://links.quant-quest.com/KGNotebook What Will You Learn in This Article? In this article we will explore how you can automatically identify relevant news about a company, using a technology called knowledge graphs (KGs). You will be able to
  • Cross-Asset Signals and Time-Series Momentum [Alpha Architect]

    In their paper Time Series Momentum, published in the May 2012 issue of the Journal of Financial Economics, Tobias Moskowitz, Yao Hua Ooi and Lasse Pedersen documented significant time-series momentum (trend) in equity index, currency, commodity and bond futuresdelivering substantial abnormal returns with little exposure to standard asset pricing factors and performing best during extreme

Quantocracy’s Daily Wrap for 08/04/2020

This is a summary of links featured on Quantocracy on Tuesday, 08/04/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Buy / Sell Imbalance [Tr8dr]

    It is fairly easy to recognize price momentum with price-based indicators ex-post or with lag. Price based momentum signals tend to have lag issues in recognizing the start and end of a price move as there is a tradeoff between noise and lag [1] that cant be defeated without future information (due to principles from signal processing). [1] For those interested see impulse-response and the
  • Creating Anti-Fragile Portfolios [Factor Research]

    Most asset classes are bets on economic growth Diversified endowment-style portfolios are essentially short volatility Long volatility strategies can be used to create anti-fragile portfolios LONG OR SHORT VOLATILITY? In what by now seems like a galaxy far far away, I once worked as an equity derivatives intern at Credit Suisse First Boston in London. As at other investment banks, the team had

Quantocracy’s Daily Wrap for 08/02/2020

This is a summary of links featured on Quantocracy on Sunday, 08/02/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio Optimisation with MlFinLab: Hierarchical Equal Risk Contribution [Hudson and Thames]

    Harry Markowitzs Modern Portfolio Theory (MPT) was seen as an amazing accomplishment in portfolio optimization, earning him a Nobel Prize for his work. it is based on the hypothesis that investors can optimize their portfolios based on a given level of risk. While this theory works very well mathematically, it fails to translate to real-world investing. This can be mainly attributed to two

Quantocracy’s Daily Wrap for 08/01/2020

This is a summary of links featured on Quantocracy on Saturday, 08/01/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to learn Python for finance [Cuemacro]

    The question I get asked most is, what is your favourite burger joint? The answer.. well, youll have to ask me! The second question I get asked a lot, particularly in recent months, is how can I learn Python if Im working in finance? I will endeavour to answer that question, updating and adding to articles Ive written before. If you work in finance there are lots of good reasons to learn

Quantocracy’s Daily Wrap for 07/31/2020

This is a summary of links featured on Quantocracy on Friday, 07/31/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • I like to MVO it! [OSM]

    In our last post, we ran through a bunch of weighting scenarios using our returns simulation. This resulted in three million portfolios comprised in part, or total, of four assets: stocks, bonds, gold, and real estate. These simulations relaxed the allocation constraints to allow us to exclude assets, yielding a wider range of return and risk results, while lowering the likelihood of achieving our

Quantocracy’s Daily Wrap for 07/30/2020

This is a summary of links featured on Quantocracy on Thursday, 07/30/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Boundary corrected kernel density [Eran Raviv]

    Density estimation is now a trivial one-liner script in all modern software. What is not so easy is to become comfortable with the result, how well is is my density estimated? we rarely know. One reason is the lack of ground-truth. Density estimation falls under unsupervised learning, we dont actually observe the actual underlying truth. Another reason is that the theory around density
  • The Effectiveness of Selected Crisis Hedge Strategies [Quantpedia]

    During past months we made a set of articles analyzing the performance of equity factors and selected systematic strategies during coronavirus crisis. These articles were short-ranged with data only from the start of the year 2020, which is enough for the purpose of the quick blog posts, but very short-sighted to see the nature of these strategies. Therefore, we expanded the time range by 20
  • Why ML in Finance is Hard (3 / 4) [Tr8dr]

    Following on from the prior post, want to discuss the problem of sample independence. Many machine learning models in finance deal with timeseries data, where samples used in training may be close together in time and not be independent of one another. There are very few features in finance that do not make use of lookback periods, for example: almost all technical indicators (SMA being the most
  • Is Systematic Value Dead??? [Alpha Architect]

    There is a large body of academic research demonstrating that the value premium has been persistent over long periods, pervasive across asset classes (stocks, bonds, commodities, and currencies) and also across and within industries, countries, and regions, robust to various fundamental metrics, and is implementable (survives transactions costs). In addition, there are intuitive risk- and

Quantocracy’s Daily Wrap for 07/29/2020

This is a summary of links featured on Quantocracy on Wednesday, 07/29/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Connecting to the Interactive Brokers Native Python API [Quant Start]

    Interactive Brokers has always been a popular brokerage with systematic traders. Initially this could partially be attributed to the fact that IB provided an Application Programming Interface (API) that allowed quants to obtain market data and place trades directly in code. Many competing brokerages took some time to develop their own APIs, allowing IB to gain a reasonable early-mover advantage in
  • Introduction to NLP: Sentiment analysis and Wordclouds [Quant Dare]

    I think one of the most interesting areas in the data analysis field is Natural Language Processing (NLP). These last years this discipline has grown exponentially and now its a huge area with a lot of problems we can attempt to solve, like text classification, translations or text generation In this post, I will show one of the simplest ways to approach to text processing. Im going to focus
  • Detailed Logging with a Low-Level CBT [Quant For Hire]

    Recently a student of my CBT course asked why he wasnt seeing the usual output (including dates) when he selected AmiBrokers Detailed Log option and ran a backtest that utilizes a low-level CBT. The answer is that much of the Detailed Log output comes from AmiBrokers ProcessTradeSignals method, which isnt used in a low-level CBT. However, its fairly straightforward to add your
  • Are Asset Class Correlations At A New Permanently High Plateau? [Capital Spectator]

    The coronavirus crisis reordered many things in economics and finance and you can add asset correlations to the list. After markets crashed in March, followed by a strong (so far) rebound, asset classes have continued to move with an unusually deep and broad degree of unison. High, or at least higher return correlations arent unusual around periods of severe market corrections. The question is

Quantocracy’s Daily Wrap for 07/27/2020

This is a summary of links featured on Quantocracy on Monday, 07/27/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why ML in Finance is Hard (part 1) [Tr8dr]

    I have used machine learning in trading strategies over the past 10 years. However my use of ML has often played a relatively small role in the overall design and success of the strategies. I use ML in specific signals or strategy sub-problems where the data / problem setup tends to have a robust statistical solution. This is as opposed to the Nirvana scenario where fundamental features and
  • Seasonality Factor [Dual Momentum]

    Our first look at calendar influences was in analyzing the best time during the month to execute dual momentum trades. Studies here, here, and here show that stocks perform best early in the month. This is when institutional investors make changes to their portfolios. Prices then are most representative of their true value. Here are the Sharpe and Sortino ratios for our Global Equities Momentum
  • Relative Skewness: A New Risk Factor? [Alpha Architect]

    In the search for more and better factors, this article examines the cross-sectional relationship between historical skewness (see Jacks post here) and the returns on a robust set of assets and documents the premium for taking on skewness risk. The authors construct long/short portfolios across four global asset classes including equity indices, government bonds, commodities, and currencies
  • Global Macro: Masters of the Universe? [Factor Research]

    The alpha of global macro funds has been shrinking consistently over time However, correlations to equities & bonds were low on average, offering diversification benefits Capital allocators have been cautious on the strategy in recent years INTRODUCTION He-Man and the Masters of the Universe was a popular TV cartoon show in the 1980s, where a handsome Prince Adam was battling the evil Skeletor
  • Nowcasting for financial markets [SR SV]

    Nowcasting is a modern approach to monitoring economic conditions in real-time. It makes financial market trading more efficient because economic dynamics drive corporate profits, financial flows and policy decisions, and account for a large part of asset price fluctuations. The main technology behind nowcasting is the dynamic factor model, which condenses the information of numerous correlated

Quantocracy’s Daily Wrap for 07/24/2020

This is a summary of links featured on Quantocracy on Friday, 07/24/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Petra on Programming: The Compare Price Momentum Oscillator [Financial Hacker]

    Vitali Apirine, inventor of the OBVM indicator, presented another new tool for the believing technical analyst in the Stocks & Commodities August 2020 issue. His new Compare Price Momentum Oscillator (CPMO) is based on the Price Momentum Oscillator (PMO) by a Carl Swenlin. So we got another indicator with an impressive name but has it any use? Lets check.
  • Weighting on a friend [OSM]

    Our last few posts on portfolio construction have simulated various weighting schemes to create a range of possible portfolios. Weve then chosen portfolios whose average weights yield the type of risk and return wed like to achieve. However, weve noted there is more to portfolio construction than simulating portfolio weights. We also need to simulate return outcomes given that our use of
  • Introduction to Artificial Neural Networks and the Perceptron [Quant Start]

    In this article we begin our discussion of artificial neural networks (ANN). We first motivate the need for a deep learning based approach within quantitative finance. Then we outline one of the most elementary neural networks known as the perceptron. We discuss the architecture of the perceptron and its ability to function as a supervised linear classifier, using step function based activation

Quantocracy’s Daily Wrap for 07/23/2020

This is a summary of links featured on Quantocracy on Thursday, 07/23/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • My NAAIM Webinar [Quantifiable Edges]

    Last week I had the honor of being a guest speaker for the National Association of Active Investment Managers (NAAIM)) webinar series. The topic I discussed was Quantifiable Edges for Active Investing. That recording is now available to view on the NAAIM website (email registration required). And if you are an investment manager, you may also want to learn more about NAAIM.
  • Fundamental Momentum, the Carry Trade, and Currency Returns [Alpha Architect]

    Momentum in prices is the tendency of assets that have performed well recently (such as over the prior year) to outperform assets in the same asset class that have performed poorly over the prior year. For a more thorough review of momentum check out this post by Wes Gray. This phenomenon has been found to exist not only in stocks all around the globe, but in bonds, commodities, and currencies as