HangukQuant Research

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Attention Intensity as Contrarian Factor Tilt
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Attention Intensity as Contrarian Factor Tilt

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HangukQuant
Feb 05, 2023
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Attention Intensity as Contrarian Factor Tilt
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I am glad to annouce we have hit 2.5k readers! I have my fingers crossed for 5k by end of year :) We have decided to make available this week’s paper for all readers. The code appended is for paid subscribers.

We look at working with Google’s interest over time data, and construct some interesting signals. We also discuss important methods to deconstruct strategy exposure to classical factors, such as the Fama French approach. In the series of recent posts, such as the one below:

HangukQuant’s Newsletter
MANDATORY read: 30 Years of Evidence for (and against) Anomalous Returns from Cash Flow Statements in the United States and lessons on quantitative validation.
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2 years ago · 3 likes · 2 comments · HangukQuant

we have focused on training the reader’s analytical mind, and to recognise biases in how performance results can be introduced in available literature. This trains us to be more mindful of the consumption of financial literature. Additionally, such biases can easily creep into our quantitative approach and systematic construction in our personal portfolios. My hope is that readers apply the techniques learnt to their personal trading systems and question the validity of their own work, which can be a crucial, preventive wealth-saving exercise for your future. I hope that such works can also adjust expectations towards the reality of alpha research for the general public. One of our core goals is to bridge the gap in quantitative research between retail and institutional establishments, and a big part of that is in the delusional optimisim in which amateur traders view the attainment of persistent alphas.

Attention Intensity As Contrarian Factor Tilt
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On top of the previous features, our Russian Doll engine now supports computation and visualization of:

  • cumulative returns, log returns

  • maximum drawdown, rolling drawdown, rolling max drawdown

  • sortino, sharpe

  • mean, stdev, variance, skew, kurtosis of returns

  • cagr, rolling cagr, omega, calmar ratios

  • ulcer index

  • value at risk, expected shortfall

  • gain to pain ratios

  • weight bias

  • return density plots

  • one factor capm model with spx

  • one factor capm model with strategy constituents

  • fama french model with strategy constituents (daily resolution)

  • jensen’s alpha, treynor ratio

  • stochastic dominance of strategy

Due to significant volume in code additions, we decided to release a more comprehensive set of code files in the cbz folder attached. You can find:

  • aiohttp_wrapper.py: asynchronous sessioned request manager

  • alpha.py: Russian Doll implementation for backtester

  • data_master.py: control file for data services

  • eod_wrapper.py: implements eodhistoricaldata functionalities

  • equities.py: retrieves factor data and pricing data for equities

  • generic_wrapper.py: interacts with database and batches data requests

  • indices.py: retrieves pricing data for indices

  • performance.py: calculator for strategy performance measures and statistics

  • quant_stats.py: utility files for permutation testing, hypothesis testing and more

  • serp.py: interacts with SERP API to retrieve Google Data

  • strat.py: implementation of strategy and signal for paper discussed

  • yfinance_wrapper.py: implements threaded model for retrieving pricing data from Yahoo! Finance

CBZ folder of code files, paid readers:

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