Quant Mashup Multi-Factor Long-Short Portfolios – how have they performed? [Alpha Architect]Multi-factor, long-short portfolios have provided significant portfolio diversification benefits by adding unique sources of risks that have historically produced premiums that meet the criteria Andrew Berkin and I established in our book “Your Complete Guide to Factor-Based Investing”—the(...) Slava Ukraini! Latest from Quantocracy contributor in Ukraine: MOVE Index [Only VIX]In the previous article I wrote about using VIX / MOVE index ratio as an indicator for SPX returns. Here is the google sheet for your reference and experiments. The ratio itself is very stable - in fact 11 years ago I wrote that VIX = EXP(-1.84+1.06*LN(MOVE)) As you can see the relationship has held(...) Probabilistic alpha and beta: quantifying an uncertain edge [Artifact Research]In finance, the performance of an asset is often quantified by alpha (the excess returns above a benchmark return) and beta (the volatility or risk of the asset relative to a benchmark). These metrics are estimated from historical data and are often based on only short track records. Even if a long(...) A Balanced Portfolio and Trend-Following During Different Market States [Quantpedia]What’s the performance of a balanced portfolio during rising rates? How does it behave when inflation is high? What about a combination of these market states? And how do trend-following strategies fare in such an environment? These and even more questions we will attempt to resolve in our(...) Alpha Vantage API Python Tutorial [Analyzing Alpha]This article explains how to call the Alpha Vantage API to retrieve stock market data in a Python application using the Python alpha_vantage library and the Python requests module. The documentation for the Python alpha_vantage client library is limited. It isn’t easy to understand the mapping(...) Do Poor YTD Results Mean Late December Rally Will Flop? [Quantifiable Edges]I’ve heard people saying recently that the typical 2nd half of December bullish tendency is unlikely to unfold this year. The theories suggest that the market is often up on the year. And people and institutions flush with profits tend to push it higher as the New Year approaches. There is also(...) Scale in Active Management - a look at its Diseconomies [Alpha Architect]Pastor, Stambaugh, and Taylor (2015) and Zhu (2018) provide significant evidence of decreasing returns to scale (DRS) at both the fund and industry levels. The authors examine the robustness of their inferences after Adams, Hayunga, and Mansi (2021) critique the above two studies. What are the(...) Zakamulin's Optimal Trend Following [Allocate Smartly]This is a test of a novel trend-following strategy from the paper Optimal Trend Following Rules in Two-State Regime-Switching Models by Valeriy Zakamulin and Javier Giner. These results aren’t as eye catching as many we track, but the paper contributes some important ideas to the study of tactical(...) Serverless architecture for crypto trading [Gautier Marti]I recently asked on LinkedIn about advice and opinions on infrastructure for collecting, storing, processing, and storing back derived data (features, signals) for some simple mid freq / stat arb trading strategies. I did not expect to receive so much feedback about infrastructure for trading data(...) MOVE Index and SPX returns [Only VIX]MOVE index (Merrill Lynch Option Volatility Estimate) was developed by Merrill Lynch to measure implied volatility of US Treasury markets. ML became a part of Bank of America in 2008, and then indexes were sold to ICE in 2019, so now the index is called "ICE BofAML MOVE Index" The index is(...) 100 Years of Historical Market Cycles [Quantpedia]Which assets perform best when rates are rising, and inflation is high? And what happens if rates are still rising but inflation is already falling? And what’s the impact of the business cycle? These are the questions that everyone is currently trying to answer. Today, we will start a longer(...) The Informativeness: Measuring the Homogeneity of a Universe of Assets [Portfolio Optimizer]In this post, I will describe a measure of the homogeneity of a universe of assets, called the informativeness, introduced by Brockmeier et al.1 in their paper Quantifying the Informativeness of Similarity Measurements. After quickly going through the associated mathematics, I will present two(...) Machine Learning and Emerging Market Stock Returns [Alpha Architect]More specifically, the paper differentiates between: Traditional linear models (ordinary least squares regression and elastic net) and Machine learning methods that allow for non-linearities and interactions (tree-based models such gradient boosted regression trees and random forest and neural(...) Experimental Design and Common Pitfalls of Machine Learning in Finance [Hudson and Thames]The first lecture from the Experimental Design and Common Pitfalls of Machine Learning in Finance series addresses the four horsemen that present a barrier to adopting the scientific approach to machine learning in finance. The second lecture focuses on a protocol for backtesting and how to avoid(...) CoinGecko API Python Tutorial [Analyzing Alpha]This article will show you how to access the CoinGecko API endpoints in Python to retrieve live cryptocurrency information. You will use the pycoingecko and the Python requests library to fetch data from CoinGecko API. The official CoinGecko API and pycoingecko libraries’ documentations lack(...) Beware of Spurious Factors [Eran Raviv]The word spurious refers to “outwardly similar or corresponding to something without having its genuine qualities.” Fake. While the meanings of spurious correlation and spurious regression are common knowledge nowadays, much less is understood about spurious factors. This post draws your(...) Myth Busting: Alts' Uncorrelated Returns Diversify Portfolios [Finominal]Alternatives with lower correlations to equities & bonds did not lead to greater diversification benefits Correlations often break when markets crash Better metrics are required to measure the diversification potential of alternatives INTRODUCTION Alternative investments accounted for $13(...) Volatility scaling: is it useful for factor timing? [Alpha Architect]The research summarized here is built upon a documented risk management strategy applied to factor investing (Barroso and Santa-Clara, 2015; Moreira and Muir, 2017). The idea was to overlay a scaled volatility measure designed to change risk exposures and hopefully produce higher Sharpe ratios. That(...) Managed Futures and Trend Following - Inside the Black Box [Light Finance]It goes without saying that 2022 has been a difficult year across markets. Investors have had to contend with an inflationary bear market for which the traditional playbook has proven woefully inadequate. NASDAQ and high yield debt, the darlings of yesteryear, have fallen from grace with few(...) The Size Effect: Does it vary in accordance with monetary policy? [Alpha Architect]The size effect was first documented by Rolf Banz in his 1981 paper “The Relationship Between Return and Market Value of Common Stocks,” which was published in the Journal of Financial Economics. After the 1992 publication of Eugene Fama and Kenneth French’s paper “The Cross-Section of(...) Research Review | 9 Dec 2022 | Valuation Analysis [Capital Spectator]Preference for dividends and stock returns around the world Allaudeen Hameed (National University of Singapore), et al. November 2022 We find strong international evidence favoring dividend payout as a salient stock characteristic affecting expected stock returns. We find that dividend-paying stocks(...) Building a Raspberry Pi Cluster for QSTrader Using SLURM - Part 5 [Quant Start]In the previous article we created a virtual environment and installed QSTrader on all our secondary nodes. We then carried out a test of the sixty forty strategy across all secondary nodes to make sure our installation had been successful. Now that we have successfully paralellised QSTrader we can(...) Volume and Mean Reversion [Alvarez Quant Trading]Overall, I have had very little success integrating volume into any of my strategies. Either volume would have no predictive value or if it did, using it reduced the number of trades too much to be worthwhile. It has been a long while since I have looked into this and I had some new ideas. The Rules(...) Why I prefer probabilistic forecasts - hitting time probabilities [Sarem Seitz]Probabilistic forecasts are a more comprehensive way to predict future events compared to point forecasts. Probabilistic forecasts involve creating a model that predicts the entire probability distribution for a given future period, providing insight into all likely outcomes. This allows for the(...) Doubling Down: Double Deep Q-networks for trading [Quant Dare]In previous posts, we have seen the basic RL algorithm, Deep Q learning (DQN). We have also seen it applied, using Neural Networks as the Agent, to an investment strategy. We finally even used it for a cryptocurrency investment strategy. This time, we will implement a slightly more advanced(...) Investing in Deflation, Inflation, and Stagflation Regimes [Alpha Architect]Spikes in inflation and fear of stagflation prompted this study which answers the following question: 1. How do risk premiums and investment strategies behave across inflationary regimes like periods of high inflation, deflation, or stagflation? What are the Academic Insights? By utilizing the(...) Are Alternative ETFs Good Diversifiers? [Finominal]Alternative products with uncorrelated returns do not necessarily provide diversification benefits Out of 10 alternative ETFs, only one product improved the Sharpe ratio of a 60/40 portfolio Correlations should be regarded carefully in fund selection INTRODUCTION Given the demise of the traditional(...) Vol-of-Vol for Crypto-Derivative Products [Quant at Risk]In quantitative finance, the Volatility of Volatility (also referred to as Vol-of-Vol or VoV) is an important parameter for pricing various derivative products (e.g. Volatility Dispersion Swaps) and its correct estimation is frequently desired. VoV is usually a single number treated an an input(...) How Much Are Bitcoin Returns Driven by News? [Quantpedia]The main theme of these days in the crypto world is unmistakenly clear, it’s the mayhem connected with the collapse of the FTX empire, insolvencies of various lenders, and questions about underlying holdings in GBTC OTC ETF and reserves of exchanges and Tether (or other stablecoins as well). With(...) Trend Following and Relative Sentiment: Complementary Factors [Alpha Architect]Trend following (time series momentum) is one of the most well-documented and well-known factors in investing, demonstrating persistence, pervasiveness, robustness, and implementability (survives transaction costs). Lesser well-known is relative sentiment—an indicator that measures the positions,(...) Weekly rebalancing Sector ETFs using Structural Entropy [Pravin Bezwada]Based on previous article Structural Entropy, this article attempts to test the performance of a long short strategy on US sectors using structural entropy. Ideally it should use liquid US sector futures but since data is unavailable (not for free), it uses ETFs as proxy. The assumption in previous(...) Slava Ukraini! Latest from Quantocracy contributor in Ukraine: VIX and Expected Range [Only VIX]Continuing on trying to fight disinformation about VIX. Everyone knows that VIX index the square root of the expected 30-day variance, and if we drop mathematical precision - 30 day expected volatility of S&P index. Scott Bauer, on CBO's website - "the VIX Index tells us the level of(...) Binance API Python Tutorial [Analyzing Alpha]This tutorial explains how to call Binance API endpoints in Python using the python-binance library and the Python requests function. The Binance API provides extensive documentation on how to call its various endpoints. Furthermore, multiple online blogs explain how to call the Binance API using a(...) Replicating a CTA via Factor Exposures [Finominal]Strategies can be copied by recreating them from scratch or using factor exposures CTAs can be replicated via factor exposure analysis by utilizing only 4 asset classes Not a perfect replication, but surprisingly good given the limited input INTRODUCTION Our two most recent research articles focused(...) Identifying the drivers of the commodity market [SR SV]Commodity futures returns are correlated across many different raw materials and products. Research has identified various types of factors behind this commonality: [i] macroeconomic changes, [ii] financial market trends, and [iii] shifts in general uncertainty. A new paper proposes to estimate the(...) Creating a CTA from Scratch - II [Finominal]CTAs pursue trends across asset classes, regardless if long or short 2022 is exceptional as CTAs have more short positions than during the GFC No single long bond index position remains, fixed income is one big short INTRODUCTION In our last research article (read Creating a CTA from Scratch – I)(...) Option Momentum: does it work? [Alpha Architect]Several studies show momentum works in global equities, corporate bonds, currencies, and commodities. This paper asks the following research question: Does momentum work within option markets? What are the Academic Insights? By focusing on the returns of delta-neutral straddles (from 1996 to 2019)(...) Why bother with unbiasedness? [Quant Dare]For every quantity to be estimated (estimand), there’s a plethora of ways to estimate it (estimators). This raises the question of what properties we should be looking for so as to make a sensible choice. Often highlighted as one of such properties is unbiasedness, which we will discuss below with(...) Trend-Following Rules in Two-State Regime-Switching Models [Alpha Architect]Academic research on trend-following investing has almost exclusively been focused on testing the profitability of various trading rules. Most of these rules are based on moving averages of past prices. The most popular is the Simple Moving Average (SMA). Less commonly used types of moving averages(...) Active manager bias – is it the same as for individual investors? [Alpha Architect]The empirical research on the ability of actively managed funds, including such studies as the 2002 paper “Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses” by Russ Wermers, has found that they do have the ability to identify(...) Reviewing Patent-to-Market Trading Strategies [Quantpedia]The following article is a short distillation of the research paper Leveraging the Technical Competence of a Stock for the Purpose of Trading written by Rishabh Gupta. The author spent a summer internship at Quantpedia, investigating the Patent-to-Market (PTM) ratio developed by Jiaping Qiu, Kevin(...) New Quant Podcast: So, you want to be a Quant? [Quant at Risk]Here is the first episode in a new series of podcasts entitled Break into Finance. We will be talking about what it takes to launch your career in finance, what does it mean to become a quant, and where to start. Any questions welcomed! Beyond linear II: the Unscented Kalman Filter [Quant Dare]The Unscented Kalman Filter allows to deal with nonlinear systems in a different way than the Extended Kalman Filter. Find how it works in this post. This is not the first time we talk about the Kalman Filter (and it probably won’t be the last); I recommend you check this and this posts to(...) If you're so smart, how come you're not Sam Bankman-Fried? [Investment Idiocy]There has been a very interesting discussion on twitter, relating to some stuff said by Sam Bankman-Fried (SBF), who at the time of writing has just completely vaporized billions of dollars in record time via the medium of his crypto exchange FTX, and provided a useful example to future school(...) Impact of Dataset Selection on the Performance of Trading Strategies [Quantpedia]We have previously mentioned that not all models (such as CAPM) that work well for developed markets (DM, such as the U.S. and Europe) are suited to be applicable in other world parts. The following article is a short analysis that shows that investing in Emerging Markets (EM) has its peculiarities.(...) Creating a CTA from Scratch [Finominal]CTAs have become popular again given their positive returns in 2022 However, they are typically difficult to grasp given their ever-changing portfolios Building a CTA from scratch is not complicated and reduces the opaqueness INTRODUCTION 2022 has been a long year of disappointments for investors.(...) Industry and factor momentum: is there a theoretical foundation? [Alpha Architect]This post is the second and final portion of the review on momentum published on Momentum literature. The seminal article on momentum was published by Jegadeesh and Titman in 1993. Although the Jegadeesh article foreshadowed much of the research on cross-sectional and time series momentum at the(...) A Simple Approach to Market-Timing Strategy Replication [Quantpedia]In previous articles, we discussed the ideas behind portfolio replication with market factors and presented Quantpedia’s approach to Multi-Factor Regression. Additionally, we examined the methods of market factor data extension used in construction of our historic factor universe we utilize to(...) Top 7 blogs on Sentiment Trading | 2022 [Quant Insti]“The intelligent investor is a realist who sells to optimists and buys from pessimists.” - Benjamin Graham Sentiment Trading strategies work on market sentiment and the trends around them. The strategies are often determined by the price and value of an asset that may fluctuate. Market(...) Macro factors of the risk-parity trade [SR SV]Risk-parity positioning in equity and (fixed income) duration has been a popular and successful investment strategy in past decades. However, part of that success is owed to a supportive macro environment, with accommodative refinancing conditions and slow, disinflationary, or even deflationary(...)