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Economic Forecasting
- in Agriculture.” International Journal of Forecasting
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Corn: Correlation-driven nonparametric learning approach for portfolio selection
- ACM Transactions on Intelligent Systems and Technology
, 2011
"... Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications. In this paper, we propose a novel learning to trade algorithm termed the CORrelation-driven Nonparametric learning strategy (CORN) for actively trading stocks ..."
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Cited by 6 (5 self)
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Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications. In this paper, we propose a novel learning to trade algorithm termed the CORrelation-driven Nonparametric learning strategy (CORN) for actively trading stocks, which effectively exploits statistical relations between stock market windows via a nonparametric learning approach. We evaluate the empirical performance of our algorithm extensively on several large historical and latest real stock markets, in which the encouraging results show that the proposed new algorithm can easily beat both the market index and the best stock in the market substantially (without or with small transaction costs), and also surpasses a variety of state-of-the-art techniques significantly.
Measuring the efficiency of the intraday forex market with a universal data compression algorithm
- Computational Economics
, 2009
"... Universal compression algorithms can detect recurring patterns in any type of temporal data – including financial data – for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable O ..."
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Cited by 5 (1 self)
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Universal compression algorithms can detect recurring patterns in any type of temporal data – including financial data – for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable Order Markov (VOM) model and use it to test of the weak form of the Efficient Market Hypothesis (EMH). The EMH is tested for 12 pairs of international intra-day currency exchange rates for one year series of 1,5,10,15,20,25 and 30 minutes. Statistically significant compression is detected in all the time-series and the high frequency series are also predictable above random. However, the predictability of the model is not sufficient to generate a profitable trading strategy, thus, Forex market turns out to be efficient, at least most of the time.
History of the Efficient Market Hypothesis
, 2011
"... A market is said to be efficient with respect to an information set if the price ‘fully reflects ’ that information set, i.e. if the price would be unaffected by revealing the information set to all market participants. The efficient market hypothesis (EMH) asserts that financial markets are efficie ..."
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Cited by 3 (0 self)
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A market is said to be efficient with respect to an information set if the price ‘fully reflects ’ that information set, i.e. if the price would be unaffected by revealing the information set to all market participants. The efficient market hypothesis (EMH) asserts that financial markets are efficient. On the one hand, the definitional ‘fully ’ is an exacting requirement, suggesting that no real market could ever be efficient, implying that the EMH is almost certainly false. On the other hand, economics is a social science, and a hypothesis that is asymptotically true puts the EMH in contention for one of the strongest hypotheses in the whole of the social sciences. Strictly speaking the EMH is false, but in spirit is profoundly true. Besides, science concerns seeking the best hypothesis, and until a flawed hypothesis is replaced by a better hypothesis, criticism is of limited value. Starting in the 16th century, this note gives a chronological review of the notable literature relating to the EMH. History of the Efficient Market Hypothesis
PREDICTABILITY OF STOCK PRICE BEHAVIOUR IN SOUTH AFRICA: A NON-PARAMETRIC APPROACH
"... The predictability of stock returns has been an important issue in the finance literature over the years. Investors who manage to predict stock returns successfully should realise excess returns above the normal profit. However, the efficient market hypothesis (EMH) supports the view that securities ..."
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The predictability of stock returns has been an important issue in the finance literature over the years. Investors who manage to predict stock returns successfully should realise excess returns above the normal profit. However, the efficient market hypothesis (EMH) supports the view that securities markets are extremely efficient in reflecting information about individual stocks
Putting a Price on Carbon – Econometric Essays on the European Union Emissions Trading Scheme and its Impacts
, 2013
"... Government ..."
Keywords Efficient Market Hypothesis · Universal prediction · Forex Intra-day trading · Variable Order Markov
, 2008
"... Abstract Universal compression algorithms can detect recurring patterns in any type of temporal data—including financial data—for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Varia ..."
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Abstract Universal compression algorithms can detect recurring patterns in any type of temporal data—including financial data—for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable Order Markov (VOM) model and use it to test the weak form of the Efficient Market Hypothesis (EMH). The EMH is tested for 12 pairs of international intra-day currency exchange rates for
Prediction of USD/JPY Exchange Rate Time Series Directional Status by KNN with Dynamic Time Warping AS Distance Function
"... Abstract--- Exchange rate prediction is a challenging topic in the recent decade. Various studies have been done to improve the prediction regarding the accuracy in terms of level error and directional status error. The aim of this paper is to introduce a methodology that uses KNN (K-nearest neighbo ..."
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Abstract--- Exchange rate prediction is a challenging topic in the recent decade. Various studies have been done to improve the prediction regarding the accuracy in terms of level error and directional status error. The aim of this paper is to introduce a methodology that uses KNN (K-nearest neighbors) and DTW (dynamic time warping) to improve the fluctuation prediction and to have better evaluation parameters in the literature of financial market forecasting, comparing to other researches. The study is done with USD/JPY(United States Dollar/Japanese Yen) exchange rate time series and the results show improvement of prediction regarding the direction of time series. USD/JPY exchange rates are gathered from 1971 to 2012 and are partitioned into 30 element segments regarding the monthly cyclic behavior of the time series. Then two different set of these 30 element segments are divided with 7:3 ratio and the KNN is used to find out the 3 nearest neighbors regarding the DTW as similarity function. By a chosen function introduced also in this research, the directional status of the last element is predicted and the prediction result is then compared with other results in the literature of exchange rate prediction.
Predicting Stock Returns Using a Variable Order Markov Tree Model
"... The weak form of the Efficient Market Hypothesis (EMH) states that the current market price fully reflects the information of past prices and rules out predictions based on price data alone. In an efficient market, consistent prediction of the next outcome of a financial time series is problem-atic ..."
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The weak form of the Efficient Market Hypothesis (EMH) states that the current market price fully reflects the information of past prices and rules out predictions based on price data alone. In an efficient market, consistent prediction of the next outcome of a financial time series is problem-atic because there are no reoccurring patterns that can be used for a reliable prediction. This research offers an alternative test of the weak form of the EMH. It uses a universal pre-diction algorithm based on the Variable Order Markov tree model to identify reoccurring patterns in the data, constructs explanatory models, and predicts the next time-series outcome. Based on these predictions, it rejects the EMH for certain stock markets while accepting it for other markets. The weak form of the EMH is tested for four international stock exchanges: the German DAX index; the American Dow-Jones30 index; the Austrian ATX index and the Danish KFX index. The universal prediction algorithm is used with sliding windows of 50, 75, and 100 consecutive daily returns for periods of up to 12 trading years. Statistically significant predictions are detected for 17 % to 81 % of the ATX, KFX and DJ30 stock series for about 3 % to 30 % of the trading days. A summary prediction analysis indicates that for a confidence level of 99 % the more volatile Ger-man (DAX) and American (DJ30) markets are indeed efficient. The algorithm detects periods of potential market inefficiency in the ATX and KFX markets that may be exploited for obtaining excess returns. 1.
