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Quantocracy’s Daily Wrap for 08/14/2020

This is a summary of links featured on Quantocracy on Friday, 08/14/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Feature Selection (2 / 3) [Tr8dr]

    As mentioned in the prior discussion feature selection (1/3), of primary interest is understanding the contribution of each feature in x to the outcome or class labeling function f(x ) . One way to examine this is to understand how the distributions: p(xf) , the probability distribution of feature f (without regard to label) p(xf|f(x)=y) , the feature distribution conditional on class label
  • Rebalance Timing Luck: The (Dumb) Luck of Smart Beta [Flirting with Models]

    We are proud to announce the release of our newest paper, Rebalance Timing Luck: The (Dumb) Luck of Smart Beta. Abstract Prior research and empirical investment results have shown that portfolio construction choices related to rebalance schedules may have non-trivial impacts on realized performance. We construct long-only indices that provide exposures to popular U.S. equity factors (value, size,

Quantocracy’s Daily Wrap for 08/13/2020

This is a summary of links featured on Quantocracy on Thursday, 08/13/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Feature Selection (1 / 3) [Tr8dr]

    I am often confronted with the problem of trying to reduce a high dimensional feature set to a, smaller, more effective one. Reducing dimension is important for machine learning models as: the volume of the search space grows exponentially at a minimum rate of 2d for binary categorical variables to a much higher exponential for continuous or n-ary categoricals. the joint-distribution of high
  • An Introduction to Digital Signal Processing for Trend Following [Alpha Architect]

    Digital signal processing (DSP), specifically the use of digital filters, is embedded in many indicators used by technical analysts to study and make trading decisions using time series of stock, bond, currency, commodity, and other financial asset prices. This analysis takes a look at several of the most commonly-used indicators from a DSP perspective to illustrate their properties and

Quantocracy’s Daily Wrap for 08/11/2020

This is a summary of links featured on Quantocracy on Tuesday, 08/11/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Best Machine Learning Algos for Landing a Top Hedge Fund Job in the 2020s [Auquan]

    Hedge Funds analyst roles represent some of the most fiercely contested roles in all of Finance (if not any industry). The work is incredibly varied and challenging, making the jobs the long term aim of many ambitious juniors from diverse backgrounds like Computer Science, finance, economics, Physics and so much more. This creates an intense competition for roles. In turn, the challenge becomes
  • Looking at 7-day Win Streaks [Quantifiable Edges]

    The recent rally has left the market short-term overbought by most measures. Short-term overbought often triggers some studies that suggest a downside edge, but when the overbought condition gets very strongly overbought, then those downside edges often disappear. And at some point, rather than strength leading to weakness, the strength will beget more strength. The strong move higher over the
  • What is Sequence Risk and Can Trend Following Help Reduce It? [Alpha Architect]

    What exactly is sequence risk? Well get more into the weeds of it, but for now, consider it the risk of loss when you can least afford it. Think of a client leaving their retirement party with their shiny new set of steak knives and then learning via the news that their enormous position in their employers stock has just dropped 50%. The authors of this paper look deeply into sequence

Quantocracy’s Daily Wrap for 08/09/2020

This is a summary of links featured on Quantocracy on Sunday, 08/09/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio Optimisation with MlFinLab: Estimation of Risk [Hudson and Thames]

    Risk has always played a very large role in the world of finance with the performance of a large number of investment and trading strategies being dependent on the efficient estimation of underlying market risk. With regards to this, one of the most popular and commonly used representation of risk in finance is through a covariance matrix higher covariance values mean more volatility in the

Quantocracy’s Daily Wrap for 08/08/2020

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

  • 10 Learnings from Open Source [Hudson and Thames]

    As many of you will know by now, Hudson & Thames is pivoting towards an open-core business model and away from our dreams of pure open source and the unlocking the commons. What follows is a very brief history of our learnings with open-source. Starting Out MlFinLab started as an ambitious project for Ashutosh and my (Jacques) Masters in Financial Engineering at WorldQuant University. We
  • Measures of market risk and uncertainty [SR SV]

    In financial markets, risk refers to the probability distribution of future returns. Uncertainty is a broader concept that encompasses ambiguity about the parameters of this probability distribution. There are various types of measures seeking to estimate risk and uncertainty: [1] realized and derivatives-implied distributions of returns across assets, [2] news-based measures of policy and

Quantocracy’s Daily Wrap for 08/07/2020

This is a summary of links featured on Quantocracy on Friday, 08/07/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What is the probability of profit of your next trade? (Introducing PredictNow.Ai) [EP Chan]

    What is the probability of profit of your next trade? You would think every trader can answer this simple question. Say you look at your historical trades (live or backtest) and count the winners and losers, and come up with a percentage of winning trades, say 60%. Is the probability of profit of your next trade 0.6? This might be a good initial estimate, but it is also a completely useless
  • Factor Investing in Singapore [Factor Research]

    Singapores stock market has unique features given its strong sector biases However, despite these, there were no structural factor exposures over time Like in other markets, investors can pursue factor investing to generate outperformance INTRODUCTION One of the stories of how Singapore received its name is about a Sumatran prince who came across a mythical beast called Janggi while hunting.
  • Research Review | 7 August 2020 | Gold [Capital Spectator]

    Is Gold a Hedge or Safe Haven Asset during COVID19 Crisis? Md Akhtaruzzaman (Australian Catholic University), et al. May 15, 2020 The COVID19 pandemic has shaken the global financial markets. Our study examines the role of gold as a safe haven asset during the different phases of this COVID19 crisis by utilizing an intraday dataset. The empirical findings show that dynamic conditional

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