Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 09/22/2023

This is a summary of links featured on Quantocracy on Friday, 09/22/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation Performance During the 2022 Bear Market [Allocate Smartly]

    As a whole, Tactical Asset Allocation (TAA) did not manage losses during the 2022 bear market as well as it has during previous downturns. Individual strategies varied and some did well, but a primary function of TAA is loss management, and any failure to do so is worth analyzing further. In this post, were going to break down the reason for some strategies poor performance in 2022. Heres
  • Quant Signal Trade-Offs in the Real World [Robot Wealth]

    I want to discuss a couple of simple trade-off considerations around quant trading signals that may not be obvious. Heres the price of some asset: Our main job is to predict how its likely to move. To do this, you use information about it that you think is predictive. And at any point in time: New information is appearing (trades, quotes, events, chatter). Old information that used to be

Quantocracy’s Daily Wrap for 09/20/2023

This is a summary of links featured on Quantocracy on Wednesday, 09/20/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Range-Based Volatility Estimators: Overview and Examples of Usage [Portfolio Optimizer]

    Volatility estimation and forecasting plays a crucial role in many areas of finance. For example, standard risk-based portfolio allocation methods (minimum variance, equal risk contributions, hierarchical risk parity) critically depend on the ability to build accurate volatility forecasts1. Multiple methods for estimating volatility have been proposed over the past several decades, and in this

Quantocracy’s Daily Wrap for 09/18/2023

This is a summary of links featured on Quantocracy on Monday, 09/18/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Analysis of Price-Based Quantitative Strategies for Country Valuation [Quantpedia]

    Value investing originated as an investment strategy in which investors try to beat the stock market by looking for stocks that trade at a price below their intrinsic value or book value. Value investors do not subscribe to the efficient-market hypothesis, which suggests that stock prices always reflect their intrinsic value. Instead, value investors believe stocks can be overvalued or undervalued
  • A New Wolf in Town? Pump-and-Dump Manipulation in Cryptocurrency Markets [Alpha Architect]

    Pump-and-Dump (P&D) schemes to manipulate the prices of cryptocurrencies are unlike the P&D schemes found in the equity market. They produce very large price distortions on the order of 65%, very large trading volumes of 13.5x the average, and generate very large profits to cryptocurrency manipulators. They target illiquid coins but only have temporary, short-term impact on prices. In
  • Don’t Convert to Convertible Bonds [Finominal]

    Convertible bonds are typically viewed as debt rather than equity instruments However, these are highly correlated to equities The diversification benefits are limited as these just represent diluted equity proxies INTRODUCTION Lets say youre the CEO of a small listed company that isnt doing well. The stock price of your company is depressed, so issuing equity would be highly dilutive.

Quantocracy’s Daily Wrap for 09/13/2023

This is a summary of links featured on Quantocracy on Wednesday, 09/13/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Seasonality of Bitcoin [Quantpedia]

    Seasonality effects, one of the most fascinating phenomena in the world of finance, have captured the attention of investors and researchers worldwide. Since these anomalies are often driven by factors other than general market trends, they usually dont correlate strongly with market movements, which can help reduce the portfolios overall risk. Following the theme of our previous article Are

Quantocracy’s Daily Wrap for 09/11/2023

This is a summary of links featured on Quantocracy on Monday, 09/11/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • There IS a low vol anomaly in SPY [Babbage9010]

    TL;DR There really is a low volatility anomaly in the SPY data; low volatility today predicts low volatility tomorrow and risk-adjusted returns are higher investing daily in the lower vol half of predicted market days. Same data, new analysis, better graphs and youll see it too. First up, a mea culpa. I misused my shallow understanding of stats::lag() in the last post and ended up
  • Momentum turning points and their impact on market cycles [Alpha Architect]

    The article investigates time-series (TS) momentum strategies and their performance in financial markets based on various speeds or lookback horizons. The study aims to understand the connections between different speeds of TS momentum, unobservable variables like trend, turning points, and noise levels in realized returns, and their impact on market cycles. Momentum Turning Points Goulding,
  • K-Nearest Neighbors Algorithm: Steps to Implement in Python [Quant Insti]

    Machine Learning (ML) has emerged as a powerful tool in the field of Artificial Intelligence, revolutionising various aspects of our lives. Whether it's recognising human handwriting or enabling self-driving cars, ML has become an integral part of our daily routines. With the exponential growth of data, the prevalence and importance of ML are only expected to increase in the coming years. ML
  • Fixed Income Factors II [Finominal]

    There are style factors like value and traditional fixed income factors like term premium The correlations of these factors has been low However, it is not clear which are better suited for a factor exposure analysis INTRODUCTION In our last research article, we compared fixed income factors from two asset managers, namely AQR Capital Management and Robeco, which highlighted different security

Quantocracy’s Daily Wrap for 09/09/2023

This is a summary of links featured on Quantocracy on Saturday, 09/09/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to backtest 2,000,000 simulations for the best exits [PyQuant News]

    If youve been a reader of this newsletter for a while, or a student of Getting Started With Python for Quant Finance, youll recognize this statement: Backtests are not a way to brute force optimize parameters to maximize a performance metric. Doing that leads to overfitting and losses. But optimization does play an important part in building trading strategies. Today, well see how. How to
  • Equity versus fixed income: the predictive power of bank surveys [SR SV]

    Bank lending surveys help predict the relative performance of equity and duration positions. Signals of strengthening credit demand and easing lending conditions favor a stronger economy and expanding leverage, benefiting equity positions. Signs of deteriorating credit demand and tightening credit supply bode for a weaker economy and more accommodative monetary policy, benefiting long-duration

Quantocracy’s Daily Wrap for 09/08/2023

This is a summary of links featured on Quantocracy on Friday, 09/08/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Price data from Yahoo Finance in R the Easy Way [Robot Wealth]

    Traders typically have many ideas for trading strategies more than they can ever implement in practice! Therefore its useful to be able to move quickly in the early research phase. You want to disprove things as quickly as possible so that you can move onto the next thing. Obviously there is immense value in reliable and easy data access. You dont want to be wrangling large data sets
  • Stock-bond correlation and its lessons for investors [Alpha Architect]

    The correlation between stocks and bonds should be a critical component of any asset allocation decision, as it impacts not only the overall risk of a diversified multi-asset class portfolio but also the risk premia one should expect to receive for taking risk in different asset classes. The problem for investors is that the correlation between stocks and bonds fluctuates extensively across time

Quantocracy’s Daily Wrap for 09/07/2023

This is a summary of links featured on Quantocracy on Thursday, 09/07/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Financial Distress Factors: Altman Z-Score and Interest Coverage Ratio [Quant Rocket]

    Are rising interest rates straining balance sheets and increasing the risk of bankruptcies? This article investigates two financial distress factors, the Altman Z-Score and interest coverage ratio, to see if distress is on the rise and how it impacts stock returns. This post is part of the fundamental factors series, which explores techniques for researching fundamental factors using Pipeline,
  • Code Walkthrough for the Alpha Simulator (for Programming Beginners) [Hanguk Quant]

    As we advance into our third year on this blog – its dawning upon me that many of the readers are getting left behindthe biggest concern by far is the complexity of the current Russian Doll model and not being sure how to proceed with using the statistical suite presented therein, together with the formulaic alphas. Although I was intending to further take the Russian Doll to have integrated

Quantocracy’s Daily Wrap for 09/05/2023

This is a summary of links featured on Quantocracy on Tuesday, 09/05/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Testing TrendYCMacro from Durian and Vojtko of @Quantpedia [Allocate Smartly]

    This is a test of the TrendYCMacro strategy from the paper Avoid Equity Bear Markets with a Market Timing Strategy from urian and Vojtko of Quantpedia. The strategy combines trends in price, the slope of the yield curve and key economic indicators to switch between US equities and cash. Backtested results from 1927 follow. Results are net of transaction costs see backtest assumptions.
  • Short Term Signals – can they produce meaningful alpha? [Alpha Architect]

    Short-term return anomalies are generally dismissed in the academic literature because they seemingly do not survive after accounting for market frictions. In this research, short-term factors are taken seriously, and the authors argue the standard parameters may not apply to short horizons. The authors ask: Do the standard assumptions regarding estimates for trading costs,

Quantocracy’s Daily Wrap for 09/02/2023

This is a summary of links featured on Quantocracy on Saturday, 09/02/2023. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Investment Factor: does it impact returns? [Alpha Architect]

    Over the long term, low-investment firms have outperformed high-investment firms. This finding has led to the investment factor (CMA, or conservative minus aggressive) being incorporated into the leading asset pricing modelsthe four-factor q-theory model (market beta, size, investment, and profitability), the Fama-French five-factor model that adds value, and the Fama-French six-factor model
  • Autocorrelation in Trading: A Practical Python Approach to Analyzing Time Series Data [Quant Insti]

    Autocorrelation is a statistical concept that measures the correlation between observations of a time series and its lagged values. It is commonly used in various fields, including trading for technical analysis, to identify patterns, trends, and relationships within data. Autocorrelation helps analyse the dependence between past and present values and provides insights into the persistence or
  • How to use HDF5 for advanced, ultra fast market data storage [PyQuant News]

    If theres one thing algorithmic traders cannot get enough of, its data. The data that fuels our strategies is more than just numbersits the lifeblood of our decision-making processes. And having data available locallyor at least within your controlis a big part of that. In todays newsletter, well use the ultra-fast HDF5 file format to store data for research and analysis.
  • Research Review | 31 August 2023 | Financial Crises [Capital Spectator]

    Predicting Financial Crises: The Role of Asset Prices Tristan Hennig (International Monetary Fund), et al. August 2023 We explore the early warning properties of a composite indicator which summarizes signals from a range of asset price growth and asset price volatility indicators to capture mispricing of risk in asset markets. Using a quarterly panel of 108 advanced and emerging economies over