A general framework for predicting returns from multiple currency investments

Christou, Costas; Swamy, P. A. V. B.; Tavlas, George S.

doi:10.1016/s0165-1889(97)00116-4

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…Under this assumption, (1) may not provide an adequate approximation to the "true" model (Swamy and Tavlas 2001). 12 It follows from the specification of a time-varying coefficient (TVC) model below that the conditions that the coefficients of (4a) are constant and E[u i,t |E i,t−s−1 ] = 0 for all s ≥ 0, may imply misspecifications in (4a) (Swamy and Tavlas 1994;Christou et al 1998). 13 Siregar and Rajan (2004) obtained similar results in their study of Southeastern Asian economies.…”

Section: Estimation Methodsmentioning

confidence: 99%

Some Further Evidence on Exchange-Rate Volatility and Exports

Hondroyiannis

Swamy

Tavlas³

et al. 2008

Rev. World Econ.

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Section: Estimation Methodsmentioning

confidence: 99%

Some Further Evidence on Exchange-Rate Volatility and Exports

Hondroyiannis

Swamy

Tavlas³

et al. 2008

Rev. World Econ.

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“…For a similar view, see Friedman and Schwartz (1991). Christou, Swamy and Tavlas (1998) provide a formal analysis of the use of out-of-sample predictability as a criterion for model evaluation. 6 This discussion focuses on key changes in the economic and financial environment that might bear directly on money-demand behaviour.…”

Section: Financial Deregulationmentioning

confidence: 99%

“…For a similar view, see Friedman and Schwartz (1991). Christou, Swamy and Tavlas (1998) provide a formal analysis of the use of out‐of‐sample predictability as a criterion for model evaluation.…”

mentioning

confidence: 99%

Empirical Modelling of Money Demand in Periods of Structural Change: The Case of Greece*

Brissimis¹,

Hondroyiannis²,

Swamy³

et al. 2003

Oxf Bull Econ Stat

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This paper examines the behaviour of the demand for money in Greece during 1976Q1 to 2000Q4, a period that witnessed many of the influences that cause money-demand instability. Two empirical methodologies, vector error correction (VEC) modelling and second-generation random coefficient (RC) modelling, are used to estimate the demand for money. The coefficients of both the VEC and RC procedures support the hypothesis that the demand for money becomes more responsive to both the own rate of return on money balances and the opportunity cost of holding money because of financial deregulation. In general, both procedures also support the hypothesis that the income elasticity of money demand declines over time as a result of technological improvements in the payments system and the development of money substitutes, which lead to economies of scale in holding money.*We are very grateful to a referee for insightful comments on an earlier version of this paper. We also wish to thank Stephen Hall and Lawrence Klein for helpful comments. The views expressed are the authors' own and should not be interpreted as those of their respective institutions. JEL Classification numbers: C20, E41.OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 65, 5 (2003) 0305-9049 605

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“…Joy (2011) nustatytos neigiamos koreliacijos tarp aukso kainos ir dolerio kurso iškelia klausimą dėl valiutų įtraukimo į investicinį portfelį. Nagrinėjant mokslinius darbus, susijusius su valiutų įtraukimu į investicijų portfelį, reikia pastebėti, kad daugiausia jų yra nukreipta į apsaugą nuo valiutų kursų svyravimo turint tarptautinį investicijų į kitus aktyvus (dažniausiai akcijas) portfelį (pvz., Hamza et al 2007;Roon et al 2003;Tee 2009;Kim 2012;Walker 2008), taip pat į investicijų skirtingomis valiutoms efektyvumo vertinimą (pvz., Christou et al 1998), tačiau straipsnių, kuriuose būtų tiriamos valiutų, kaip investavimo priemonių, derinimo su kitais aktyvais viename portfelyje galimybės, nepavyko rasti.…”

Section: Lentelė Prekių Investicinių Savybių Moksliniai Tyrimaiunclassified

Investicijų portfelio sprendimai

Žilinskij¹,

universitetas²

2012

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nuokrypis nuo numatytos tikėtinos investicijų grąžos; CML-kapitalo rinkos tiesė (angl. capital market line); RFR-nerizikinga palūkanų norma (angl. risk free rate); OC-sandorių sąnaudos (angl. operation costs); APG-APB "Apranga"; CTS-AB "City service"; IVL-AB "Invalda"; LNA-AB "Linas Agro Group"; PTR-AB Panevėžio statybos trestas; SAB-AB Šiaulių bankas; x TEO-AB TEO LT; UKB-AB Ūkio bankas; SMA-paprastas slankusis vidurkis; WMA-svertinis slankusis vidurkis; EMA-eksponentinis slankusis vidurkis; ARMA-autoregresinis slankusis vidurkis; ANN-dirbtinis neuroninis tinklas (angl. Artificial neural network); HMM-paslėptasis Markovo modelis (angl. Hidden Markov Model); PSO-dalelių masės optimizavimas (angl. Particle Swarm optimisation); NLICA-nelinijinė nepriklausomų komponentų analizė; SVR-paramos vektorių regresija; GBM-geometrinis Browno judėjimas; HCSOM-Hybrid Cohonen Self Organising Map; MAFE-vidutinė absoliutinė prognozavimo paklaida; FE-prognozės paklaida; AFE-absoliuti prognozės paklaida; MSE-vidutinė kvadratinė paklaida; RMSE-šaknis iš vidutinės kvadratinės paklaidos; MAPE-vidutinė absoliuti procentinė paklaida; MAD-vidutinis absoliutus nuokrypis; TIC-Theil'o nelygybės koeficientas; RMAE-santykinė vidutinė absoliuti paklaida; NMSE-normalizuota vidutinė standartinė paklaida; POCID-krypties pokyčio prognozė; ARV-vidutinis santykinis neatitikimas; AA-Alcoa Inc.

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A general framework for predicting returns from multiple currency investments

Cited by 10 publications

References 29 publications

Some Further Evidence on Exchange-Rate Volatility and Exports

Some Further Evidence on Exchange-Rate Volatility and Exports

Empirical Modelling of Money Demand in Periods of Structural Change: The Case of Greece*

Investicijų portfelio sprendimai

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