Quant Mashup 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 x⃗ to the outcome or class labeling function f(x⃗ ) . One way to examine this is to understand how the distributions: p(xf) , the probability distribution of(...) 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.(...) 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(...) 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 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,(...) 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(...) What is Sequence Risk and Can Trend Following Help Reduce It? [Alpha Architect]What exactly is “sequence risk?” We’ll 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(...) 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(...) 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(...) 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(...) 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(...) Factor Investing in Singapore [Factor Research]Singapore’s 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(...) Research Review | 7 August 2020 | Gold [Capital Spectator]Is Gold a Hedge or Safe Haven Asset during COVID–19 Crisis? Md Akhtaruzzaman (Australian Catholic University), et al. May 15, 2020 The COVID–19 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(...) 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(...) 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 futures—delivering substantial(...) 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 can’t be defeated without future information(...) 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(...) Portfolio Optimisation with MlFinLab: Hierarchical Equal Risk Contribution [Hudson and Thames]Harry Markowitz’s 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(...) 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(...) 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 don’t(...) 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(...) 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(...) 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(...) 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(...) 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 it’s a huge area with a lot of problems we can attempt to solve, like text classification, translations or text generation In(...) Detailed Logging with a Low-Level CBT [Quant For Hire]Recently a student of my CBT course asked why he wasn’t seeing the usual output (including dates) when he selected AmiBroker’s “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 AmiBroker’s(...) 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(...) 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(...) 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(...) 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 Jack’s 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(...) 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(...) 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(...) 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(...) Weighting on a friend [OSM]Our last few posts on portfolio construction have simulated various weighting schemes to create a range of possible portfolios. We’ve then chosen portfolios whose average weights yield the type of risk and return we’d like to achieve. However, we’ve noted there is more to portfolio(...) 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(...) 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).(...) 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(...) The importance of testing different exits [Alvarez Quant Trading]When developing a strategy, exits are often not given a second thought. If you are creating a mean reversion, you may default to using Close greater than the 2-period RSI. If you are trading a trend strategy, you may default to trailing exit using 14-day ATR. You try a bunch of entry filters but(...) The secret sauce that makes Deep Learning frameworks so powerful [Quant Dare]Inside most of the Deep Learning frameworks that are available lies a powerful technique called Automatic Differentiation. If you ever encountered these words but don’t know what they mean or how this procedure works, this post is for you. In a previous post, we saw how to built a deep learning(...) A Simple Neural Network for Indicator Prognosis [Philipp Kahler]Technical indicators are the base of algorithmic trading. So wouldn’t it be nice to know tomorrows indicator value in advance? This article is about how to use a simple neural network to do so. Python and Tradesignal will be used to do the programming. A single linear neuron A single neuron /(...) EM Equities vs Debt: Same, Same, but Different? [Factor Research]Some EM asset classes are highly correlated, to the point they can almost be considered interchangeable EM equities and hard-currency government debt are highly correlated to US equities and bonds In crisis times, all EM exposure is sold off and fails to provide meaningful diversification benefits(...) What is Impact Investing? [Alpha Architect]Can we do impact investing that is both good for us and tastes better? In the past, if an investment had positive non-financial outcomes (positive impact), a return trade-off was expected. Today, some investors find that incorporating aspects such as diversity, stakeholders, and environmental(...) Machine Learning Model Validation [Only VIX]I just came across an excellent and highly relevant piece of research "A comparison of machine learning model validation schemes for non-stationary time series data" by Matthias Schnaubelt. Features like non-stationarity, concept drift, and structural breaks present serious modelling(...) Research Review | 17 July 2020 | Smart Beta Revisited [Capital Spectator]The Smart Beta Mirage Shiyang Huang (University of Hong Kong), et al. June 2020 We document sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are listed for investments. Adjusted by aggregate market return, the average return of smart beta indexes drops(...) ESG Scores and Price Momentum Are More Than Compatible [Quantpedia]Momentum in stocks is not only a key strategy in the many portfolios of practitioners, but it is also an attractive research topic for academics. The original idea behind momentum, is that past winner tend to perform well in the near future, and vice versa, past loser tend to underperform (Jegadeesh(...) Backtesting Basics: Four biases to know by heart [Auquan]In God we trust. All others must bring data. Backtesting is probably the single best method we have to quickly evaluate new trading strategies. However, if used incorrectly it can be our greatest weakness — guiding us on a false path to ruin. For the uninitiated, backtesting is the process where(...) Installing TensorFlow 2.2 on Ubuntu 18.04 with an Nvidia GPU [Quant Start]Earlier in the year we carried out our 2020 QuantStart Content Survey and Advanced Machine Learning & Deep Learning was voted the most popular topic. This article constitutes the first in a series on the topic of modern machine learning via deep learning as applied to systematic trading(...) Forex Intraday Seasonality [Dekalog Blog]Over the last week or so I have been reading about/investigating this post's title matter. Some quotes from various papers' abstracts on the matter are: "We provide empirical evidence that the unique signature of the FX market seasonality is indeed due to the different time zones(...) Finance Factors Coordination? Cascade Selection [Quant Dare]Currently, strategies based on premium factors are everywhere: from funds or ETFs built on ratios or statistics perfectly specified, trying to exploit specific factor premia, to boutique instruments more or less opaque that following one or more risk premia. In any case, one of the questions we may(...) Left Tail Risk and Left Tail Momentum [Alpha Architect]The positive trade-off between risk and expected return is the most fundamental concept in financial economics. Most investors are risk-averse. In order to hold higher-risk securities, they demand higher compensation in the form of higher expected returns. And risk-averse investors are more(...)