Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 13 of 13 for “"back-testing"”.
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Optimized Forecasting of Dominant U.S. Stock Market Equities Using Univariate and Multivariate Time Series Analysis Methods
… Bivariate-PCA structures are applied in a back-testing environment to evaluate economic significance and robustness of the methods. Initial results of back-testing yielded similar results to those from earlier independent testing. Inconsistent performance across test intervals inspired the …
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Development and Implementation of a New National Warning System for Potato Late Blight in Great Britain
… of the Smith Period was examined using a back-testing analysis with a historical national-scale, longitudinal outbreak dataset and corresponding weather data. ROC analysis revealed significant regional variation in the ability of the Smith Period to forecast outbreaks. A series of …
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Refining Value-at-Risk estimates: An Extreme Value Theory Approach
… Value-at-Risk models commonly used by banks. Back-testing results following Kupiec (1995) unconditional coverage test, Christoffersen (1998) independent and conditional coverage test, Basel traffic light test, Santos and Alves (2012) new independent test, Dowd (2002) bootstrap back-test, and …
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Low volatility alternative equity indices
… construction. The empirical results from back-testing these portfolios show significant outperformance when compared with their market capitalization weighted equity benchmark counterpart (ALSI). In addition, a further analysis of this study delves into the construction of the low …
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Financing methods that drive innovation in biotech and pharmaceuticals : the meagfund [sic] IPO model
… for the mispricing of an IPO. We examine a back-testing of ten years examining a long only strategy and later also look at a case study of Monashee Investment Management that currently most closely resembles the megafund IPO model.
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Memory Vs Momentum - Exploring Momentum Strategies With The Hurst Exponent
… applied to the past stock price data, and the back testing results show that there is a U-shaped relationship between the strategy returns and Hurst exponent. This paper also builds on earlier model of a rule-based naïve trading strategy using Hurst exponent as a signal. The strategy generates …
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Estimating value at risk and expected shortfall: a kalman filter approach
… patterns required to predict future values. Back-testing results (in which the number of times VaR or ES forecasted too low a value to cover the following day's market loss is compared with the prescribed confidence level) indicate that the Kalman filter is a reliable and robust contender in …
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An online learning algorithm for technical trading
… trading strategies that can survive historical back-testing as well as form an overall aggregated portfolio trading strategy from the set of underlying trading strategies implemented on daily and intraday Johannesburg Stock Exchange data. The resulting population time-series are investigated …
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Profitability in Sports Betting: A Case Study of Men's Tennis
… returns. Through statistical simulations and back-testing, we find that it is possible to generate positive expected profits at sustainable levels of risk, with both formal and informal strategies. Interestingly, we also establish that building a successful strategy does not necessarily …
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A semantic Bayesian network for automated share evaluation on the JSE
… of the decision model was validated through back testing and measured using return and risk-adjusted return measures. The model was found to provide superior returns and risk-adjusted returns for the evaluation period from 2012 to 2018 when compared to selected benchmark indices of the JSE. …
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A generic optimisation framework for reinforcement learning in the foreign exchange market
… multi-seed training, rolling-window back-testing, and the execution of non-parametric statistical tests—in order to quantify and comparatively analyse the performance of deep reinforcement learning candidate agents, thereby ultimately guiding the user's selection of a suitable …
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Data-driven models for uncertainty and behavior
… sets for robust optimization using hypothesis testing. The approach is flexible and widely applicable, and robust optimization problems built from our new data driven sets are computationally tractable, both theoretically and practically. Optimal solutions to these problems enjoy a strong, …
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Semiparametric Bayesian Approach using Weighted Dirichlet Process Mixture For Finance Statistical Models
… propose a new model evaluation approach called back testing return (BTR) particularly for GARCH. This BTR approach produces model evaluation results which are easier to interpret than marginal likelihood and it is straightforward to draw conclusion about model profitability by applying this …