Volatility is a key metric in decision-making processes—such as limit order placement and market impact estimation—for execution algorithms. Therefore, understanding the estimation method becomes essential. 📢 In our latest article, we conduct an empirical analysis comparing the standard deviation of returns method to Parkinson's volatility calculation. Each method has its strengths, but which one leads to better execution outcomes? Read the article at the link below, to know more. https://lnkd.in/ex33C2Bx
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Read below a quick blog piece on which method to estimate volatility is superior when sample size is small.
Volatility is a key metric in decision-making processes—such as limit order placement and market impact estimation—for execution algorithms. Therefore, understanding the estimation method becomes essential. 📢 In our latest article, we conduct an empirical analysis comparing the standard deviation of returns method to Parkinson's volatility calculation. Each method has its strengths, but which one leads to better execution outcomes? Read the article at the link below, to know more. https://lnkd.in/ex33C2Bx
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Paper proposes an "Adapted Diversification Loss Index (ADLI) [for] market stress detection... using random matrix theory to evaluate multicollinearity among deep latent factors from an autoencoder-based asset pricing model." https://lnkd.in/e8ZXYiTy
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Check out this in depth discussion of Dow Theory with Trevor Neil FSTA MCSI ACI-UK and David Linton CEO of Updata happening live at 9AM Pacific time 12PM Eastern time. If you miss this one check out the full line up of upcoming live LSEG Academy courses at the link in the first comment. #LSEG #LSEGWorkspace #Data #Analytics #MarketData #DOWTheory #TechnicalAnalysis #LSEGLearningCenter #LSEGAcademy
Join this #TechnicalAnalysis webinar with Trevor Neil and David Linton as they discuss Dow Theory. They will look at short, intermediate, and long-term trends, market cycles, volume interpretation, momentum, and more. The session will help your technical analysis skills to be well-grounded. https://lseg.group/3GAdywI
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Mastering Moving Average Convergence Divergence Analysis: Master moving average convergence divergence analysis with strategies, signals, and advanced techniques for better trading!
Mastering Moving Average Convergence Divergence Analysis
stockaveragecalculator.org
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Mastering Moving Average Convergence Divergence Analysis: Master moving average convergence divergence analysis with strategies, signals, and advanced techniques for better trading!
Mastering Moving Average Convergence Divergence Analysis
stockaveragecalculator.org
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I propose an affine model of short rates that incorporates a random walk with stochastic drift. This framework enables my model to capture the behavior of monetary authorities in the short rate market, allowing for minor deviations while reacting strongly to deviations large enough to threaten production. Importantly, my model facilitates the derivation of closed-form bond prices, thereby providing an analytical solution for bond-option prices. I compare my model with nine standard short rate models found in the literature. Among these, five are single-factor models and four are multifactor models. Remarkably, my model outperforms all competing short rate models, including the constant elasticity of volatility, stochastic mean, and stochastic volatility models. Moreover, it yields interest rate forecasts consistent with common term structure priors and surpasses the performance of the naive random walk model. Additionally, my stochastic mean model can explain the unspanned risks documented in the literature. https://lnkd.in/diwfv6t6
An affine model for short rates when monetary policy is path dependent - Review of Derivatives Research
link.springer.com
