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2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.最新文献

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On generalized arbitrage pricing theory analysis: empirical investigation of the macroeconomics modulated independent state-space model 广义套利定价理论分析:宏观经济调节独立状态空间模型的实证研究
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196253
K. Chiu, L. Xu
{"title":"On generalized arbitrage pricing theory analysis: empirical investigation of the macroeconomics modulated independent state-space model","authors":"K. Chiu, L. Xu","doi":"10.1109/CIFER.2003.1196253","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196253","url":null,"abstract":"The inception of Markowitz's (1952) modern portfolio theory has also fuelled the development of asset pricing models for empirical finance, ranging from linear single-factor models like the capital asset pricing model to fairly complex multi-factor models such as the arbitrage pricing theory (APT). It is well-known in the literature of finance that APT could be used for modelling the underlying security returns generation process. We investigate a generalized version of the APT model, called the macroeconomics modulated independent state-space model, in terms of model specification adequacy as well as its performance on prediction. Empirical results reveal that the model is not only well-specified, but also superior to the temporal factor analysis model in stock price and index forecasting, thanks to its salient capabilities of modelling both short-term and long-term market dynamics.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123621969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Order selection of continuous time models: Applications to estimation of risk premiums 连续时间模型的顺序选择:在风险溢价估计中的应用
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196274
G. Basak, N. Chan, P. Lee
{"title":"Order selection of continuous time models: Applications to estimation of risk premiums","authors":"G. Basak, N. Chan, P. Lee","doi":"10.1109/CIFER.2003.1196274","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196274","url":null,"abstract":"This paper develops an order selection criterion for a continuous autoregressive (CAR) time series. Based on the quadratic variation consideration of a CAR(p) process, a new order selection criterion, the quadratic variation criterion (QVC) is proposed. It is shown that this new order selection criterion is consistent and provides an effective means to estimate the order of a CAR(p) model. Simulation studies suggest that the proposed method is efficient and outperforms other order selection criteria. The QVC is applied to select the order of the cumulative excess return process and the effect of the risk premium of a GARCH-M model when changing variance is taken into account.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121159305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Extraction of investment strategies based on moving averages: A genetic algorithm approach 基于移动平均线的投资策略提取:一种遗传算法方法
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196288
R. Jiang, K. Szeto
{"title":"Extraction of investment strategies based on moving averages: A genetic algorithm approach","authors":"R. Jiang, K. Szeto","doi":"10.1109/CIFER.2003.1196288","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196288","url":null,"abstract":"Investment strategies as rules for buy and sell are introduced as conditional statements involving inequalities of various moving averages. Different conditional statements on moving averages are represented as strings, encodable as chromosomes in an approach based on genetic algorithm. The data mining of good investment strategies corresponds to the extraction of rules that are fit in the sense of evolutionary computation. Three different kinds of moving averages (simple moving average, exponential moving average and adaptive moving average) of various durations have been used in the conditional statement involving the closing price of a given stock. The performance of a given investment strategy is evaluated using the rate of overall return in both the training set and the test set, thereby converting the problem of discovering good investment strategies to an optimization problem in combinatorics, which is solved with a genetic algorithm approach. Stock data from NASDAQ, including Microsoft, Intel, Oracle, and Dell are tested and comparisons of genetic algorithms with benchmark methods such as random walk, buy and hold, and exhaustive search are performed. Results show evidence of superior performance in genetic algorithm in term of the rate of overall return for the test set. Within the confine of limited data, all three moving averages show similar results for the four technology stock investigated.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131106699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Stock returns: momentum, volatility and interest rates 股票收益:动量、波动性和利率
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196285
Yue Fang, Sakae Wada, J. Moody
{"title":"Stock returns: momentum, volatility and interest rates","authors":"Yue Fang, Sakae Wada, J. Moody","doi":"10.1109/CIFER.2003.1196285","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196285","url":null,"abstract":"Various theories have been proposed to explain momentum in stock returns. We provide evidence in favor of risk-based explanations. Specifically, we construct self-financing market neutral portfolios that take long positions in past winners and short positions in past losers. We show that the return spreads between past winners and losers in the first year are driven primarily by high volatility stocks. Momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for volatility. We also show that momentum profits appear to be associated with economic cycles as proxied by the prime rate. The momentum strategies are substantially stronger during expansions than during recessions. This is mainly due to the relatively poor performance of past losers (rather than superior performance of the past winners) during expansions.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133961519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evidence for deterministic nonlinear dynamics in financial time series data 金融时间序列数据中确定性非线性动力学的证据
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196280
M. Small, C. Tse
{"title":"Evidence for deterministic nonlinear dynamics in financial time series data","authors":"M. Small, C. Tse","doi":"10.1109/CIFER.2003.1196280","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196280","url":null,"abstract":"Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128800357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A Monte-Carlo method for portfolio optimization under partially observed stochastic volatility 部分观测随机波动下投资组合优化的蒙特卡罗方法
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196269
Rahul Desai, Tanmay Lele, F. Viens
{"title":"A Monte-Carlo method for portfolio optimization under partially observed stochastic volatility","authors":"Rahul Desai, Tanmay Lele, F. Viens","doi":"10.1109/CIFER.2003.1196269","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196269","url":null,"abstract":"In this paper we implement an algorithm for the optimal selection of a portfolio of stock and risk-free asset under the stochastic volatility (SV) model with discrete observation and trading. The SV model extends the classical Black-Scholes model (1973) by allowing the noise intensity (volatility) to be random. The main assumption is that the portfolio manager has discrete access to the continuous-time stock prices; as a consequence the volatility is not observed directly. In this partial information situation, one cannot hope for an arbitrarily accurate estimate of the stochastic volatility. Using instead a new type of optimal stochastic filtering, and its associated particle method due to del Moral, Jacod, and Protter (1990), our algorithm, of the \"smart\" Monte-Carlo-type, approximates the new Hamilton-Jacobi-Bellman equation that is required for solving the stochastic control problem that is defined by the portfolio optimization question.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130761078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 18
FX trading via recurrent reinforcement learning 通过循环强化学习进行外汇交易
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196283
Carl Gold
{"title":"FX trading via recurrent reinforcement learning","authors":"Carl Gold","doi":"10.1109/CIFER.2003.1196283","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196283","url":null,"abstract":"This study investigates high frequency currency trading with neural networks trained via recurrent reinforcement learning (RRL). We compare the performance of single layer networks with networks having a hidden layer and examine the impact of the fixed system parameters on performance. In general, we conclude that the trading systems may be effective, but the performance varies widely for different currency markets and this variability cannot be explained by simple statistics of the markets. Also we find that the single layer network outperforms the two layer network in this application.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126088091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 63
Optimal trade execution of equities in a limit order market 限价订单市场中股票的最优交易执行
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings. Pub Date : 2003-03-20 DOI: 10.1109/CIFER.2003.1196284
R. Coggins, Adam Blazejewski, M. Aitken
{"title":"Optimal trade execution of equities in a limit order market","authors":"R. Coggins, Adam Blazejewski, M. Aitken","doi":"10.1109/CIFER.2003.1196284","DOIUrl":"https://doi.org/10.1109/CIFER.2003.1196284","url":null,"abstract":"The paper describes an approach for optimising trade execution in a limit order market. The way a trade is executed becomes important when the trade is a significant proportion of the day's turnover in a particular security. Under these circumstances limited liquidity leads to a significant transaction cost referred to as trade shortfall. We describe a method for calculating a trade execution plan which balances intra-day variations in the supply of liquidity against the risk of adverse future price movements. Our trade execution plans correspond to solutions of discrete time dynamic programming problems. This formulation admits the specification of transaction costs within a Value at Risk framework. The trade execution plans are derived and tested for three popular stocks on the Australian Stock Exchange (ASX). The performance of the plans is evaluated on an out of sample test set of the limit order book for each security and compared to three simpler trade execution strategies.","PeriodicalId":257544,"journal":{"name":"2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings.","volume":"48 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114027483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
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