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In this paper we consider two cases of pairs trading strategies: a conditional statistical arbitrage method and an implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a cointegration model, of pairs of stock prices. We show...
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We present a simple new methodology to allow for time-variation in volatilities using a recursive updating scheme similar to the familiar RiskMetrics approach. It exploits the link between exponentially weighted moving average and integrated dynamics of score driven time varying parameter...
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theoretical performance guarantees on the forecast capability of our procedure. To be precise, we show that we can forecast future … margin at the longer forecast horizons. Finally, we investigate the economic value of our forecasts in a portfolio selection …
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We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and Expected Shortfall, for a given volatility model. We obtain precise forecasts of the tail of the distribution of returns not only for the 10-days-ahead horizon required by the...
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conditional volatilities and correlations, the distribution for the innovations and the method of forecast construction. We find … smaller. The differences from the model, distribution and forecast choices are also smaller compared to temporal aggregation. …
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Chapter 1: Why do we forecast? -- Chapter 2: Regression Analysis and Forecasting Models -- Chapter 3: An Introduction …
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