Exchange Rate, Exchange Rate Volatility and Stock Prices: An Analysis of the Symmetric and Asymmetric Effect Using ARDL and NARDL Models Article Swipe
La Ode Saidi
,
Abd. Azis Muthalib
,
Pasrun Adam
,
Wali Aya Rumbia
,
La Ode Arsad Sani
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.14453/aabfj.v15i4.11
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.14453/aabfj.v15i4.11
This article examined the symmetric and asymmetric effects of the IDR/USD exchange rate and its volatility on stock prices using the monthly time series data of the IDR/USD exchange rate and the Indonesian composite stock price index from January 2006 to July 2019. The data were analyzed using ARDL and NARDL models. The results showed that in the short term, the IDR/USD exchange rate has a symmetry effect on stock prices, while volatility lacks such a symmetric influence. However, these two variables asymmetrically affect stock prices, Furthermore, in the long term both the exchange rate and the volatility lack symmetric and asymmetric influence on stock prices.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.14453/aabfj.v15i4.11
- OA Status
- diamond
- Cited By
- 10
- References
- 30
- Related Works
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- OpenAlex ID
- https://openalex.org/W3189306821
All OpenAlex metadata
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https://openalex.org/W3189306821Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.14453/aabfj.v15i4.11Digital Object Identifier
- Title
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Exchange Rate, Exchange Rate Volatility and Stock Prices: An Analysis of the Symmetric and Asymmetric Effect Using ARDL and NARDL ModelsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-01-01Full publication date if available
- Authors
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La Ode Saidi, Abd. Azis Muthalib, Pasrun Adam, Wali Aya Rumbia, La Ode Arsad SaniList of authors in order
- Landing page
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https://doi.org/10.14453/aabfj.v15i4.11Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.14453/aabfj.v15i4.11Direct OA link when available
- Concepts
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Economics, Volatility (finance), Exchange rate, Stock exchange, Econometrics, Stock (firearms), Monetary economics, Finance, Engineering, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
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10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 3, 2023: 3, 2022: 3Per-year citation counts (last 5 years)
- References (count)
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30Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.both | 91 |
| abstract_inverted_index.data | 24, 44 |
| abstract_inverted_index.from | 37 |
| abstract_inverted_index.lack | 98 |
| abstract_inverted_index.long | 89 |
| abstract_inverted_index.rate | 12, 29, 63, 94 |
| abstract_inverted_index.such | 74 |
| abstract_inverted_index.term | 90 |
| abstract_inverted_index.that | 55 |
| abstract_inverted_index.time | 22 |
| abstract_inverted_index.were | 45 |
| abstract_inverted_index.2019. | 42 |
| abstract_inverted_index.NARDL | 50 |
| abstract_inverted_index.index | 36 |
| abstract_inverted_index.lacks | 73 |
| abstract_inverted_index.price | 35 |
| abstract_inverted_index.short | 58 |
| abstract_inverted_index.stock | 17, 34, 69, 84, 104 |
| abstract_inverted_index.term, | 59 |
| abstract_inverted_index.these | 79 |
| abstract_inverted_index.using | 19, 47 |
| abstract_inverted_index.while | 71 |
| abstract_inverted_index.affect | 83 |
| abstract_inverted_index.effect | 67 |
| abstract_inverted_index.prices | 18 |
| abstract_inverted_index.series | 23 |
| abstract_inverted_index.showed | 54 |
| abstract_inverted_index.IDR/USD | 10, 27, 61 |
| abstract_inverted_index.January | 38 |
| abstract_inverted_index.article | 1 |
| abstract_inverted_index.effects | 7 |
| abstract_inverted_index.models. | 51 |
| abstract_inverted_index.monthly | 21 |
| abstract_inverted_index.prices, | 70, 85 |
| abstract_inverted_index.prices. | 105 |
| abstract_inverted_index.results | 53 |
| abstract_inverted_index.However, | 78 |
| abstract_inverted_index.analyzed | 46 |
| abstract_inverted_index.examined | 2 |
| abstract_inverted_index.exchange | 11, 28, 62, 93 |
| abstract_inverted_index.symmetry | 66 |
| abstract_inverted_index.composite | 33 |
| abstract_inverted_index.influence | 102 |
| abstract_inverted_index.symmetric | 4, 76, 99 |
| abstract_inverted_index.variables | 81 |
| abstract_inverted_index.Indonesian | 32 |
| abstract_inverted_index.asymmetric | 6, 101 |
| abstract_inverted_index.influence. | 77 |
| abstract_inverted_index.volatility | 15, 72, 97 |
| abstract_inverted_index.Furthermore, | 86 |
| abstract_inverted_index.asymmetrically | 82 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.93950884 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |