We show how the U.S. dollar as the dominant invoicing currency in international trade causes the U.S. monetary policy to have asymmetric monetary effects. We develop a model of two countries, U.S. and Japan. Households in both countries need to hold cash in advance to purchase consumption goods: The U.S. dollar can be used to purchase both countries' goods, while the Japanese yen can only be used to purchase Japan's goods. Under these constraints, an expansionary U.S. monetary policy leads to (1) a larger U.S. trade deficit, (2) larger foreign holdings of the U.S. dollar, and (3) an appreciation of the U.S. real exchange rate. In contrast, the Japanese monetary policy has none of these real effects. Beyond asymmetric monetary effects, our novel mechanism also explains the correlation between consumption and real exchange rate, and the connection between foreign economic growth and the demand for the U.S. dollar.
{"title":"Dominant Invoicing Currency and Asymmetric Monetary Effects","authors":"Zefeng Chen, Zhengyang Jiang, Timothy M. Mok","doi":"10.2139/ssrn.3086880","DOIUrl":"https://doi.org/10.2139/ssrn.3086880","url":null,"abstract":"We show how the U.S. dollar as the dominant invoicing currency in international trade causes the U.S. monetary policy to have asymmetric monetary effects. We develop a model of two countries, U.S. and Japan. Households in both countries need to hold cash in advance to purchase consumption goods: The U.S. dollar can be used to purchase both countries' goods, while the Japanese yen can only be used to purchase Japan's goods. Under these constraints, an expansionary U.S. monetary policy leads to (1) a larger U.S. trade deficit, (2) larger foreign holdings of the U.S. dollar, and (3) an appreciation of the U.S. real exchange rate. In contrast, the Japanese monetary policy has none of these real effects. Beyond asymmetric monetary effects, our novel mechanism also explains the correlation between consumption and real exchange rate, and the connection between foreign economic growth and the demand for the U.S. dollar.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114424170","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}
Pub Date : 2017-11-01DOI: 10.5089/9781484330173.001.A001
C. Casas, Federico J. Díez, G. Gopinath, Pierre-Olivier Gourinchas
Most trade is invoiced in very few currencies. Despite this, the Mundell-Fleming benchmark and its variants focus on pricing in the producer’s currency or in local currency. We model instead a ‘dominant currency paradigm’ for small open economies characterized by three features: pricing in a dominant currency; pricing complementarities, and imported input use in production. Under this paradigm: (a) the terms-of-trade is stable; (b) dominant currency exchange rate pass-through into export and import prices is high regardless of destination or origin of goods; (c) exchange rate pass-through of non-dominant currencies is small; (d) expenditure switching occurs mostly via imports, driven by the dollar exchange rate while exports respond weakly, if at all; (e) strengthening of the dominant currency relative to non-dominant ones can negatively impact global trade; (f) optimal monetary policy targets deviations from the law of one price arising from dominant currency fluctuations, in addition to the inflation and output gap. Using data from Colombia we document strong support for the dominant currency paradigm.
{"title":"Dominant Currency Paradigm: A New Model for Small Open Economies","authors":"C. Casas, Federico J. Díez, G. Gopinath, Pierre-Olivier Gourinchas","doi":"10.5089/9781484330173.001.A001","DOIUrl":"https://doi.org/10.5089/9781484330173.001.A001","url":null,"abstract":"Most trade is invoiced in very few currencies. Despite this, the Mundell-Fleming benchmark and its variants focus on pricing in the producer’s currency or in local currency. We model instead a ‘dominant currency paradigm’ for small open economies characterized by three features: pricing in a dominant currency; pricing complementarities, and imported input use in production. Under this paradigm: (a) the terms-of-trade is stable; (b) dominant currency exchange rate pass-through into export and import prices is high regardless of destination or origin of goods; (c) exchange rate pass-through of non-dominant currencies is small; (d) expenditure switching occurs mostly via imports, driven by the dollar exchange rate while exports respond weakly, if at all; (e) strengthening of the dominant currency relative to non-dominant ones can negatively impact global trade; (f) optimal monetary policy targets deviations from the law of one price arising from dominant currency fluctuations, in addition to the inflation and output gap. Using data from Colombia we document strong support for the dominant currency paradigm.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117179950","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}
Bitcoin volatility is known to be high, as is shown by comparing Bitcoin volatility to several currencies and to assets like stock, gold etc. This work attempts to extend this work by comparing Bitcoin volatility to volatility of currencies of least developed countries and other cryptocurrencies. Exchange rate and return data drawn from Bloomberg and covering March 2014 to March 2017 was analysed. It was found that Bitcoin volatility is still considerably higher than volatilities of currencies of least developed countries. Only five currencies were more volatile for more than 10% of the time span analysed.
{"title":"Evolution of Bitcoin - Volatility Comparisons with Least Developed Countries’ Currencies","authors":"Dr. Jochen Kasper","doi":"10.2139/ssrn.3052207","DOIUrl":"https://doi.org/10.2139/ssrn.3052207","url":null,"abstract":"Bitcoin volatility is known to be high, as is shown by comparing Bitcoin volatility to several currencies and to assets like stock, gold etc. This work attempts to extend this work by comparing Bitcoin volatility to volatility of currencies of least developed countries and other cryptocurrencies. Exchange rate and return data drawn from Bloomberg and covering March 2014 to March 2017 was analysed. It was found that Bitcoin volatility is still considerably higher than volatilities of currencies of least developed countries. Only five currencies were more volatile for more than 10% of the time span analysed.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114939881","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}
Attempts to accurately measure the monetary velocity or related properties of Bitcoin have often attempted to either directly apply definitions from traditional macroeconomic theory or to use specialized metrics relative to the properties of the Blockchain such as bitcoin-days destroyed. In this paper, it is demonstrated that beyond being a useful metric, bitcoin-days destroyed has mathematical properties that allow one to calculate the average dormancy (time since last use in a transaction) of the bitcoins used in transactions over a given time period. In addition, transaction volume and average dormancy are shown to have unexpected significance in helping estimate the average size of the pool of traded bitcoins by virtue of the expression Little's Law, though only under limited conditions.
{"title":"Bitcoin Average Dormancy: A Measure of Turnover and Trading Activity","authors":"Reginald D. Smith","doi":"10.2139/ssrn.2992404","DOIUrl":"https://doi.org/10.2139/ssrn.2992404","url":null,"abstract":"Attempts to accurately measure the monetary velocity or related properties of Bitcoin have often attempted to either directly apply definitions from traditional macroeconomic theory or to use specialized metrics relative to the properties of the Blockchain such as bitcoin-days destroyed. In this paper, it is demonstrated that beyond being a useful metric, bitcoin-days destroyed has mathematical properties that allow one to calculate the average dormancy (time since last use in a transaction) of the bitcoins used in transactions over a given time period. In addition, transaction volume and average dormancy are shown to have unexpected significance in helping estimate the average size of the pool of traded bitcoins by virtue of the expression Little's Law, though only under limited conditions.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114892422","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}
We jointly re-specify the relative purchasing power parity (RPPP) and uncovered interest rate parity (UIP) conditions as the (log) ratio of stochastic discount factors by inverting the market price of risk formula. Our empirical model provides new insights, which show that violations to UIP and RPPP both stem from the existence of a risk premium in exchange rates and from observed market return differentials being a noisy statistic of the markets' expected return differentials in our re-specified model. Using an integrated macro-microstructure framework for expected market return differentials improves our model fit and the validity of UIP and RPPP.
{"title":"Differential Risk Premiums and the UIP Puzzle","authors":"Rita Biswas, Louis R. Piccotti, Ben Z. Schreiber","doi":"10.2139/ssrn.2990363","DOIUrl":"https://doi.org/10.2139/ssrn.2990363","url":null,"abstract":"We jointly re-specify the relative purchasing power parity (RPPP) and uncovered interest rate parity (UIP) conditions as the (log) ratio of stochastic discount factors by inverting the market price of risk formula. Our empirical model provides new insights, which show that violations to UIP and RPPP both stem from the existence of a risk premium in exchange rates and from observed market return differentials being a noisy statistic of the markets' expected return differentials in our re-specified model. Using an integrated macro-microstructure framework for expected market return differentials improves our model fit and the validity of UIP and RPPP.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128390182","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}
Carry trading is one of the most popular currency trading strategies. The aim of this paper is to apply and analyze the approach described in Baz et al. (2015) by utilizing the G10 currency cross rates and the 3-month Libor rates. The carry trading strategy is well documented and widely used by several types of market participants. In a first step, the strategy is tested with generated data based on the CHF/USD currency pair and the carry signal is being analyzed. In a second step, the strategy was applied to a basket of 45 currency pairs consisting of all the possible combinations between the G10 currencies. The outcome shows that carry trading can be protable if traded under the right market conditions, which are stable interest rates and an appreciation of the traded currency cross rate. The Deutsche Bank Currency Harvest Index, which is a similar implementation of a carry trading strategy outbids the approach by Baz et al. (2015) for the analyzed time period.
套息交易是最流行的货币交易策略之一。本文的目的是通过利用G10货币交叉利率和3个月Libor利率，应用和分析Baz等人(2015)中描述的方法。套息交易策略被多种类型的市场参与者充分记录并广泛使用。第一步，使用基于瑞郎/美元货币对生成的数据对策略进行测试，并对利差信号进行分析。第二步，将该策略应用于一篮子45对货币，包括十国集团(G10)货币之间所有可能的组合。结果表明，如果在合适的市场条件下进行套利交易，即稳定的利率和交易货币交叉汇率的升值，套利交易是有利可图的。德意志银行货币收获指数(Deutsche Bank Currency Harvest Index)是套息交易策略的类似实施，在分析的时间段内优于Baz等人(2015)的方法。
{"title":"A Statistical Analysis of Carry Trading","authors":"Siro Fritzmann, David Jaggi, Joerg Osterrieder","doi":"10.2139/ssrn.2993902","DOIUrl":"https://doi.org/10.2139/ssrn.2993902","url":null,"abstract":"Carry trading is one of the most popular currency trading strategies. The aim of this paper is to apply and analyze the approach described in Baz et al. (2015) by utilizing the G10 currency cross rates and the 3-month Libor rates. The carry trading strategy is well documented and widely used by several types of market participants. In a first step, the strategy is tested with generated data based on the CHF/USD currency pair and the carry signal is being analyzed. In a second step, the strategy was applied to a basket of 45 currency pairs consisting of all the possible combinations between the G10 currencies. The outcome shows that carry trading can be protable if traded under the right market conditions, which are stable interest rates and an appreciation of the traded currency cross rate. The Deutsche Bank Currency Harvest Index, which is a similar implementation of a carry trading strategy outbids the approach by Baz et al. (2015) for the analyzed time period.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122143839","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}
We present a model of the foreign exchange market with 2 types of investors: cash-constrained carry traders, and short-sighed boundedly rational technical traders. We show that the interactions between both agents explain several of the well-documented puzzles of the exchange rate. In particular, the model provides a theoretical base for the fact that currencies of high interest rate countries tend to crash, sometimes without a clear fundamental trigger.
{"title":"The Special FX Market","authors":"Louis Raffestin","doi":"10.2139/ssrn.2979978","DOIUrl":"https://doi.org/10.2139/ssrn.2979978","url":null,"abstract":"We present a model of the foreign exchange market with 2 types of investors: cash-constrained carry traders, and short-sighed boundedly rational technical traders. We show that the interactions between both agents explain several of the well-documented puzzles of the exchange rate. In particular, the model provides a theoretical base for the fact that currencies of high interest rate countries tend to crash, sometimes without a clear fundamental trigger.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125307404","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}
One of the daunting problems in international finance is the weak explanatory power of existing theories of the nominal exchange rates, the so-called “foreign exchange rate determination puzzle”. We propose a continuous-time model to study the impact of order flow on foreign exchange rates. The model is estimated by a newly developed econometric tool based on a time-change sampling from calendar to volatility time. The estimation results indicate that the effect of order flow on exchange rates is more than doubled compared with the traditional econometric estimations. The normality tests of the distribution of regression residuals confirm our application of the new econometric tool.
{"title":"Martingale Regressions for a Continuous Time Model of Exchange Rates","authors":"Zi‐Yi Guo","doi":"10.2139/ssrn.3013803","DOIUrl":"https://doi.org/10.2139/ssrn.3013803","url":null,"abstract":"One of the daunting problems in international finance is the weak explanatory power of existing theories of the nominal exchange rates, the so-called “foreign exchange rate determination puzzle”. We propose a continuous-time model to study the impact of order flow on foreign exchange rates. The model is estimated by a newly developed econometric tool based on a time-change sampling from calendar to volatility time. The estimation results indicate that the effect of order flow on exchange rates is more than doubled compared with the traditional econometric estimations. The normality tests of the distribution of regression residuals confirm our application of the new econometric tool.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130237057","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}
This paper explores whether the exchange rate effects of macro news are time- and state-dependent by analyzing and comparing the relative influence of US and Japanese macro news on the JPY/USD rate before, during, and after the Global Financial Crisis. A comprehensive set totaling 40 time-stamped US and Japanese news variables and preceding survey expectations along with 5-minute indicative JPY/USD quotes spanning the 1 January 1999 to 31 August 2016 period facilitate our analysis. Our results suggest that while US macro news are now more important than before the Crisis, the influence of Japanese macro news has waned to the point of near-irrelevance. These findings are of particular importance to exchange rate modeling of the New Era.
{"title":"The Exchange Rate Effects of Macro News after the Global Financial Crisis","authors":"Yin-Wong Cheung, Rasmus Fatum, Yohei Yamamoto","doi":"10.24149/gwp305","DOIUrl":"https://doi.org/10.24149/gwp305","url":null,"abstract":"This paper explores whether the exchange rate effects of macro news are time- and state-dependent by analyzing and comparing the relative influence of US and Japanese macro news on the JPY/USD rate before, during, and after the Global Financial Crisis. A comprehensive set totaling 40 time-stamped US and Japanese news variables and preceding survey expectations along with 5-minute indicative JPY/USD quotes spanning the 1 January 1999 to 31 August 2016 period facilitate our analysis. Our results suggest that while US macro news are now more important than before the Crisis, the influence of Japanese macro news has waned to the point of near-irrelevance. These findings are of particular importance to exchange rate modeling of the New Era.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121794677","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}
Three different classes of data mining methods (k-Nearest Neighbour, Ridge Regression and Multilayer Perceptron Feed-Forward Neural Networks) are applied for the purpose of quantitative trading on 10 simulated time series, as well as real world time series of 10 currency exchange rates ranging from 1.11.1999 to 12.6.2015. Each method is tested in multiple variants. The k-NN algorithm is applied alternatively with the Euclidian, Manhattan, Mahalanobis and Maximum distance function. The Ridge Regression is applied as Linear and Quadratic, and the Feed-Forward Neural Network is applied with either 1, 2 or 3 hidden layers. In addition to that Principal Component Analysis (PCA) is eventually applied for the dimensionality reduction of the predictor set and the meta-parameters of the methods are optimized on the validation sample. In the simulation study a Stochastic-Volatility Jump-Diffusion model, extended alternatively with 10 different non-linear conditional mean patterns, is used, to simulate the asset price behaviour to which the tested methods are applied. The results show that no single method was able to profit on all of the non-linear patterns in the simulated time series, but instead different methods worked well for different patterns. Alternatively, past price movements and past returns were used as predictors. In the case when the past price movements were used, quadratic ridge regression achieved the most robust results, followed by some of the k-NN methods. In the case when past returns were used, k-NN based methods were the most consistently profitable, followed by the linear ridge regression and quadratic ridge regression. Neural networks, while being able to profit on some of the time series, did not achieve profit on most of the others. No evidence was further found of the PCA method to improve the results of the tested methods in a systematic way. In the second part of the study, the models were applied to empirical foreign exchange rate time series. Overall the profitability of the methods was rather low, with most of them ending with a loss on most of the currencies. The most profitable currency was EURUSD, followed by EURJPY, GBPJPY and EURGBP. The most successful methods were the linear ridge regression and the Manhattan distance based k-NN method which both ended with profits for most of the time series (unlike the other methods). Finally, a forward selection procedure using the linear ridge regression was applied to extend the original predictor set with some technical indicators. The selection procedure achieved limited success in improving the out-sample results for the linear ridge regression model but not the other models.
{"title":"Forecasting Foreign Exchange Rate Movements with k-Nearest-Neighbour, Ridge Regression and Feed-Forward Neural Networks","authors":"Milan Fičura","doi":"10.2139/ssrn.2903547","DOIUrl":"https://doi.org/10.2139/ssrn.2903547","url":null,"abstract":"Three different classes of data mining methods (k-Nearest Neighbour, Ridge Regression and Multilayer Perceptron Feed-Forward Neural Networks) are applied for the purpose of quantitative trading on 10 simulated time series, as well as real world time series of 10 currency exchange rates ranging from 1.11.1999 to 12.6.2015. Each method is tested in multiple variants. The k-NN algorithm is applied alternatively with the Euclidian, Manhattan, Mahalanobis and Maximum distance function. The Ridge Regression is applied as Linear and Quadratic, and the Feed-Forward Neural Network is applied with either 1, 2 or 3 hidden layers. In addition to that Principal Component Analysis (PCA) is eventually applied for the dimensionality reduction of the predictor set and the meta-parameters of the methods are optimized on the validation sample. In the simulation study a Stochastic-Volatility Jump-Diffusion model, extended alternatively with 10 different non-linear conditional mean patterns, is used, to simulate the asset price behaviour to which the tested methods are applied. The results show that no single method was able to profit on all of the non-linear patterns in the simulated time series, but instead different methods worked well for different patterns. Alternatively, past price movements and past returns were used as predictors. In the case when the past price movements were used, quadratic ridge regression achieved the most robust results, followed by some of the k-NN methods. In the case when past returns were used, k-NN based methods were the most consistently profitable, followed by the linear ridge regression and quadratic ridge regression. Neural networks, while being able to profit on some of the time series, did not achieve profit on most of the others. No evidence was further found of the PCA method to improve the results of the tested methods in a systematic way. In the second part of the study, the models were applied to empirical foreign exchange rate time series. Overall the profitability of the methods was rather low, with most of them ending with a loss on most of the currencies. The most profitable currency was EURUSD, followed by EURJPY, GBPJPY and EURGBP. The most successful methods were the linear ridge regression and the Manhattan distance based k-NN method which both ended with profits for most of the time series (unlike the other methods). Finally, a forward selection procedure using the linear ridge regression was applied to extend the original predictor set with some technical indicators. The selection procedure achieved limited success in improving the out-sample results for the linear ridge regression model but not the other models.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116774856","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}
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