This is a summary of links featured on Quantocracy on Saturday, 08/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!
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Multivariate volatility forecasting [Eran Raviv]Last time we showed how to estimate a CCC and DCC volatility model. Here I describe an advancement labored by Engle and Kelly (2012) bearing the name: Dynamic equicorrelation. The idea is nice and the paper is well written. Departing where the previous post ended, once we have (say) the DCC estimates, instead of letting the variance-covariance matrix be, we force some struc
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Introduction to Monte Carlo Analysis Part 2 [Quants Portal]Markov Chains, Central Limit Theorem and the Metropolis-Hastings In the previous article I gave a generic overview of Monte Carlo as well as introduced importance sampling. We now dive deeper by giving strict definitions of some of the widely used and yet misunderstood or rather commonly neglected concepts due to its perceived importance. There after we explore the Metropol
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Steady Vol & Big ‘O’ Sharpe [John Orford]Big 'O' Sharpe changes backtest starting dates day by day until the lowest Sharpe is found. When strategies rebalance on periodic basis it turns out that such very small changes cause very large differences in results. Big 'O' Sharpe is the pessimistic grumpy brother of the happy-go-lucky Sharpe ratio. On the plus side if you do get a good Big 'O' Sharpe number
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Multiscale Noisy-Rational-Expectations Equilibrium [Alex Chinco]1. Motivation Evolutionarily Slow. In modern financial markets, people simultaneously trade the exact same assets on vastly different timescales. For example, a Jegadeesh and Titman (1993)-style momentum portfolio turns over half its holdings once every 6 months. By contrast, Kirilenko, Kyle, Samadi, and Tuzun (2014) estimate that high-frequency traders (HFTs) reduce half