Technical analysis based on high and low stock prices forecasts: evidence for Brazil using a fractionally cointegrated VAR model

After the East Asian crisis in 1997, the issue of whether stock prices and exchange rates are related or not have received much attention. This is due to realization that during the crisis the countries affected saw turmoil in both their currencies and stock markets. This paper studies the non-linear interactions between stock price and exchange rate in Malaysia using a two regimes multivariate Markov switching vector autoregression (MS-VAR) model with regime shifts in both the mean and the variance. In the study, the Kuala Lumpur Composite Index (KLCI) and the exchange rates of Malaysia ringgit against four other countries namely the Singapore dollar, the Japanese yen, the British pound sterling and the Australian dollar between 1990 and 2005 are used. The empirical results show that all the series are not cointegrated but the MS-VAR model with two regimes manage to detect common regime shifts behavior in all the series. The estimated MS-VAR model reveals that as the stock price index falls the exchange rates depreciate and when the stock price index gains the exchange rates appreciate. In addition, the MS-VAR model fitted the data better than the linear vector autoregressive model (VAR).

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The representative household's demand for money in a cointegrated VAR model

Econometrics Journal ◽

10.1111/1368-423x.00044 ◽

2000 ◽

Vol 3 (2) ◽

pp. 162-176 ◽

Cited By ~ 9

Author(s):

Thórarinn G. Pétursson

Keyword(s):

Var Model ◽

Demand For Money ◽

Cointegrated Var

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A time-varying approach to analysing fiscal policy and asset prices in South Africa

Journal of Financial Economic Policy ◽

10.1108/jfep-01-2013-0003 ◽

2014 ◽

Vol 6 (1) ◽

pp. 46-63 ◽

Cited By ~ 5

Author(s):

Rangan Gupta ◽

Charl Jooste ◽

Kanyane Matlou

Keyword(s):

Fiscal Policy ◽

Stock Prices ◽

Asset Prices ◽

Marked Change ◽

Var Model ◽

Time Varying ◽

Content Type ◽

Vector Autoregressive ◽

Time Varying Parameter ◽

The Impact

Purpose – This paper aims to study the interplay of fiscal policy and asset prices in a time-varying fashion. Design/methodology/approach – Using South African data since 1966, the authors are able to study the dynamic shocks of both fiscal policy and asset prices on asset prices and fiscal policy based on a time-varying parameter vector autoregressive (TVP-VAR) model. This enables the authors to isolate specific periods in time to understand the size and sign of the shocks. Findings – The results seem to suggest that at least two regimes exist in which expansionary fiscal policy affected asset prices. From the 1970s until 1990, fiscal expansions were associated with declining house and slightly increased stock prices. The majority of the first decade of 2000 had asset prices increasing when fiscal policy expanded. On the other hand, increasing asset prices reduced deficits for the majority of the sample period, while the recent financial crises had a marked change on the way asset prices affect fiscal policy. Originality/value – This is the first attempt in the literature of fiscal policy and asset prices to use a TVP-VAR model to not only analyse the impact of fiscal policy on asset prices, but also the feedback from asset prices to fiscal policy over time.

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FORECASTING HARGA SAHAM MENGGUNAKAN METODE SIMPLE MOVING AVERAGE DAN WEB SCRAPPING

Jurnal Ilmiah Matrik ◽

10.33557/jurnalmatrik.v21i3.726 ◽

2019 ◽

Vol 21 (3) ◽

pp. 234-241

Author(s):

Dessy Tri Anggraeni

Keyword(s):

Stock Prices ◽

Stock Price ◽

Moving Average ◽

Technical Analysis ◽

Secondary Market ◽

A Value ◽

Price History ◽

The Difference ◽

Absolute Percent Error ◽

Error Method

Abstract: The fluctuative of stock prices in a secondary market provide the possibility for investors/traders to gain profits through the difference in stock prices (capital gain). In order to obtain these benefits, it is necessary to analyze before buying shares, through fundamental and technical analysis. One of several methods in Technical Analysis is Simple Moving Average Method. This method can be used to predict (forecast) stock prices by calculating moving average of the stock price history. Historical stock prices can be obtained in real time using the Web Scrapper technique, so the results is more quickly and accurately. Using the MAPE (Mean Absolute Percent Error) method, the level of accuracy of forecasting can be calculated. As a result, the program was able to run successfully and was able to display the value of forecasting and the level of accuracy for the entire data tested in LQ45. Besides forecasting with a value of N = 5 has the highest level of accuracy that reaches 97,6 % while the lowest one is using the value of N = 30 which is 95,0 %.

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The effect of ambiguity on the UK stock market: evidence from a new empirical approach

Investment Management and Financial Innovations ◽

10.21511/imfi.14(4).2017.12 ◽

2017 ◽

Vol 14 (4) ◽

pp. 133-147

Author(s):

Run Qing Tan ◽

Viktor Manahov ◽

Jacco Thijssen

Keyword(s):

Stock Market ◽

Stock Returns ◽

Stock Prices ◽

Linear Models ◽

The Other ◽

Var Model ◽

Market Returns ◽

Stock Market Returns ◽

Bid Ask Spread ◽

The Uk

This study developed a new ambiguity measure using the bid-ask spread. The results suggest that the degree of ambiguity has an impact on the daily UK stock market returns, but ambiguity does not cause changes in the returns. This implies that UK stock prices or returns cannot be predicted using variation in the degree of ambiguity through linear models, such as the VAR model, which was used in the study. The two sets of results in the study show that the degree of ambiguity from the previous two days might affect stock market returns. The authors observe that an increase in the degree of ambiguity two days ago is associated with a positive premium required by the investors. On the other hand, the degree of ambiguity tends to be affected by its past five-day values. Thus, the degree of ambiguity seems to persist for five days until investors update their priors. The intuition behind the result is that the degree of ambiguity can affect the returns of the UK stock market and UK stock market returns can in turn have an impact on the degree of ambiguity. The authors also observe that the degree of ambiguity does not seem to predict stock market returns in the UK when one applies linear models. However, this does not mean that there is no non-linear relationship between the degree of ambiguity and stock market returns or stock returns.

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Analisis Teknikal Harga Saham Waskita Karya Tahun 2017 dengan Metode ARIMA

Jurnal Ilmiah Akuntansi dan Keuangan ◽

10.32639/jiak.v7i1.187 ◽

2018 ◽

Vol 7 (1) ◽

pp. 122-126

Author(s):

Wahyuni Windasari

Keyword(s):

Key Words ◽

Stock Prices ◽

Stock Price ◽

Historical Data ◽

Arima Model ◽

Security Analysis ◽

Technical Analysis ◽

Price Movement

AbstractAs an investor needs to do an analysis before making a decision either in selling or buyingshares. Security analysis consist of two types of analysis, namely tecnical analysis andfundamental analysis. Technical analysis to test wheater historical data will predict stock pricesas a consideration to buy or sell an investment's instrument. One type of technical analysis isthe ARIMA method. In this research uses daily stock price of WSKT Tbk during 1 Januariâ€“10Oktober 2017 to predict stock prices the few days. The best ARIMA model to describe WSKTstock price movement is MA(4), with MAE predict data is 480.25.Key words : forecasting, ARIMA, technical analysis, stock prices.

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