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Quantocracy’s Daily Wrap for 02/03/2024

This is a summary of links featured on Quantocracy on Saturday, 02/03/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to do interest rate analysis with multi-factor models [PyQuant News]

    Interest rates are the driving force behind the economy. They influence everything from the cost of purchasing a home to a companys decision on capital investments. Quants model how interest rate changes impact portfolios using principal component analysis (PCA). (They also do it for stock portfolios!) In todays newsletter, well look at how interest rate movements can be broken down.

Quantocracy’s Daily Wrap for 02/02/2024

This is a summary of links featured on Quantocracy on Friday, 02/02/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quantifying and Combining Crypto Alphas [Robot Wealth]

    In this article, Ill take some crypto stat arb features from our recent brainstorming article and show you how you might quantify their strength and decay characteristics and then combine them into a trading signal. This article continues our recent articles on stat arb: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat
  • How to Build a Systematic Innovation Factor in Stocks [Quantpedia]

    The aim of this article is multifold. It aims to answer the research question: does a portfolio consisting of top innovators outperform the S&P 500 index? To address this question, a strategy of investing long in top innovators according to their ranking is developed, and its performance is compared to that of the broad-based index. Based on the common belief that higher innovativeness carries
  • Trend to Passive Investing Negatively Affecting Active Funds [Alpha Architect]

    In our book, The Incredible Shrinking Alpha, Andrew Berkin and I identified four key trends that were increasing the hurdles for active managers in their quest to generate alpha: Academic research has been converting what was once alpha into beta (common factors that could be accessed at much lower costs through systematic funds such as index funds). The pool of victims (naive retail

Quantocracy’s Daily Wrap for 01/29/2024

This is a summary of links featured on Quantocracy on Monday, 01/29/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Replacing the 40 [Return Sources]

    The 60/40 portfolio (60 percent stocks, 40 percent bonds) has become such a classic, that for many investors, the word portfolio means 60/40 by default. Looking at the past few decades, its easy to see why this is the case. Stocks, (or at least U.S. stocks), have had outstanding performance. Since stocks are much more volatile than bonds, the vast majority of the returns to 60/40 come
  • Institutional portfolio managers – better at buying or selling? [Alpha Architect]

    What are the Research Questions? This paper examines the decisions of sophisticated market participants experienced institutional portfolio managers (PMs) and the authors ask the following questions: Is there a significant difference in performance between buying and selling decisions made by institutional PMs? Is there an asymmetric allocation of limited cognitive resources towards buying
  • Monte Carlo Simulations: Forecasting Folly? [Finominal]

    Financial advisors primarily use Monte Carlo simulations to forecast returns However, this methodology is flawed as it ignores the valuations of asset classes Using capital market assumptions is likely a better approach INTRODUCTION The Shanghai Composite Index (SSE) was booming in early 2015, and as it soared, legions of new investors rushed in to try their luck at securities speculation.

Quantocracy’s Daily Wrap for 01/28/2024

This is a summary of links featured on Quantocracy on Sunday, 01/28/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Join the Race: Quantpedia Awards 2024 Await You [Quantpedia]

    Hello everyone, Two weeks ago, we promised you a surprise, and now its finally time to unveil what we have prepared for you :). Our Quantpedia Awards 2024 aims to be the premier competition for all quantitative trading researchers. If you have an idea in your head about systematic/quantitative trading or investment strategy, and you would like to gain visibility on the professional scene, then
  • Ideas for Crypto Stat Arb Features [Robot Wealth]

    This article continues our recent articles on stat arb: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas In this article, Ill brainstorm some ideas for predictive features that you could potentially use in a crypto stat arb model. The ideas draw insights from recent discussions and market observations, but of course, you should do your own
  • Equity market timing: the value of consumption data [SR SV]

    The dividend discount model suggests that stock prices are negatively related to expected real interest rates and positively to earnings growth. The economic position of households or consumers influences both. Consumer strength spurs demand and exerts price pressure, thus pushing up real policy rate expectations. Meanwhile, tight labor markets and high wage growth shift national income from
  • Moving Average Distance and Time-Series Momentum [Alpha Architect]

    Because of the strong evidence, momentum continues to receive much attention from researchers. Out of the hundreds of exhibits in the factor zoo, one of just five equity factors that met all the criteria (persistent, pervasive, robust, implementable, and intuitive) Andrew Berkin and I established in our book Your Complete Guide to Factor-Based Investing was momentum (both cross-sectional
  • Quickly compute Value at Risk with Monte Carlo [PyQuant News]

    Value at risk (VaR) is a tool professional traders use to manage risk. It estimates how much a portfolio might lose, given normal market conditions, over a set time period. There are three ways to compute VaR: the parametric method, the historical method, and the Monte Carlo method. In contrast to the parametric and historical methods which are backward looking, Monte Carlo is forward looking. In

Quantocracy’s Daily Wrap for 01/24/2024

This is a summary of links featured on Quantocracy on Wednesday, 01/24/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mean Reversion vs Trend Following Through the Years [Alvarez Quant Trading]

    Something I am always thinking about is how the markets are behaving now vs the past few years vs several years ago. My edge on the strategies I trade depends on two main ideas. One, current market behavior is similar to what I tested on which is normally the last 5-10 years. Two, not too many others have found the same edge. Unfortunately for (2), more and more people are trading quant style and

Quantocracy’s Daily Wrap for 01/22/2024

This is a summary of links featured on Quantocracy on Monday, 01/22/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A General Approach for Exploiting Statistical Arbitrage Alphas [Robot Wealth]

    Last week, I wrote a short article about statistical arbitrage trading in the real world. Statistical arbitrage is a well-understood concept: find pairs or baskets of assets you expect to move together, wait for them to diverge, and bet on them converging again. Simple enough. But making it work, especially at scale, is a little more complicated. A somewhat old-school approach takes pairs of
  • Easily compare investment strategies [PyQuant News]

    Portfolio optimization is a balance between maximizing returns and minimizing risk. While it might sound easy, its actually very difficult compare investment strategies. First, we have to accurately forecast future returns and risk. Then, we have to use tricky optimization models to build the portfolios subject to our constraints. Not to mention come up with a strategy that works! Most
  • Outperforming Cap- (Value-) Weighted and Equal-Weighted Portfolios [Alpha Architect]

    Popular benchmarks in academic research studies to evaluate the performance of investment strategies are cap-weighted (market-, or value-weighted), and equal-weighted portfolios. Capitalization-weighted portfolios are used because they are the simplest and cheapest to implement, representing the total market with little to no rebalancing costs. Equal-weighted portfolios have produced higher
  • Trend Following in Bear Markets [Finominal]

    Short-only trend following in stocks generated consistent losses across markets However, combining the strategy with an equities portfolio generated diversification benefits Like other hedging strategies it would be difficult to execute this strategy over the long-term INTRODUCTION Trend following is likely the most researched investment strategy. The folks at AQR have backtested the framework

Quantocracy’s Daily Wrap for 01/19/2024

This is a summary of links featured on Quantocracy on Friday, 01/19/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dr. Keller & Keuning s Simple Variation of Hybrid Asset Allocation [Allocate Smartly]

    This is a test of the simple variation of Dr. Keller and Keunings strategy from their paper Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA). Weve covered the balanced version of HAA previously. It has become one of the more popular strategies on our platform, and members have asked us to add this simpler-to-execute variation as well.

Quantocracy’s Daily Wrap for 01/18/2024

This is a summary of links featured on Quantocracy on Thursday, 01/18/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Exploration of CTA Momentum Strategies Using ETFs [Quantpedia]

    Commodity Trading Advisor (CTA) funds are commonly associated with managed futures investing in futures and options, and are a subset of the broader hedge fund universe[1]. Beyond commodities, they have the flexibility to venture into other assets, including interest rates, currencies, fixed income and equity indices. Most of the CTA strategies are trend-following in nature. Trend-following

Quantocracy’s Daily Wrap for 01/17/2024

This is a summary of links featured on Quantocracy on Wednesday, 01/17/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Can You Trade Only The “Best” Trend Signals? [Return Sources]

    Trend following is a relatively simple strategy, at least at the concept level: buy when prices go up, and sell when they go down. The main way that trend followers differentiate themselves is the timeframe over which they measure whether the price has gone up or down. For example, one manager might follow short term trends, like one month price moves. Another might use long-term trends, like
  • Adaptive Asset Allocation Extended [Foss Trading]

    This post extends the replication from the Adaptive Asset Allocation Replication post by running the analysis on OOS (out-of-sample) data from 2015 through 2023. Thanks to Dale Rosenthal for helpful comments. The paper uses the 5 portfolios below. Each section of this post will give a short description of the portfolio construction and then focus on comparing the OOS results with the replicated

Quantocracy’s Daily Wrap for 01/16/2024

This is a summary of links featured on Quantocracy on Tuesday, 01/16/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Quant_rv_MV5_big, and a milestone [Babbage9010]

    The same multi-vol quant strategy we all love, but now with 2000+ vol signals to choose from. quant_rv is a daily SPY strategy that uses realized volatility measures of SPY to predict days of lower volatility ahead, that in turn predict positive returns. In the net, quant_rv wins by very modest improvements to the SPY win ratio and by modest improvements to the average win size relative to the
  • Advanced FX carry strategies with valuation adjustment [SR SV]

    FX forward-implied carry is a popular ingredient in currency trading strategies because it is related to risk premia and implicit policy subsidies. Its signal value can often be increased by considering inflation differentials, hedging costs, data outliers, and market restrictions. However, even then, FX carry is an imprecise and noisy signal, and previous research has shown the benefits of
  • 46 awesome books for quant finance, algo trading, and market data analysis [PyQuant News]

    One of the most common questions I get: What books should I read for quant finance, algorithmic trading, and market data analysis? And one of my favorite hobbies is collecting books on the subject. 46 awesome books for quant finance, algo trading, and market data analysis 46 books for quant finance, algo trading, and market data analysis. Books for quant finance, algorithmic trading, and market
  • Getting Value Exposure from Non-Value Funds [Finominal]

    The factor betas of value-focused ETFs range dramatically Non-value-focused funds can have high betas to the value factor However, these often come with large unintended bets INTRODUCTION While some investors are die-hard believers in value investing, others regard this more opportunistically and only occasionally seek exposure to this investing style. Perhaps cheap stocks have been outperforming,