scholarly journals The Determinants of House Prices in Malaysia

2021 ◽  
Vol 2 (1) ◽  
pp. 1-18
Author(s):  
Hazmi Hamizan Mohd Zaki
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
House Prices ◽  
Consumer Price Index ◽  
Composite Index ◽  
Real Income ◽  
Macroeconomic Factors ◽  
Distributed Lag ◽  
Long Run ◽  
Nominal Interest Rates

This paper studied how house prices were affected by macroeconomic factors from Q1 2009 to Q4 2018. The short and long-run effects of real income, nominal interest rates, inflation rate and stock prices on house prices in Malaysia were examined with the autoregressive distributed lag (ARDL) of a restricted error correction model (ECM). It was discovered that the selected macroeconomic factors were cointegrated with house prices. Income, represented by real Gross Domestic Product (GDP), significantly affected house prices in the short and long-run. Inflation and interest rate, proxied by Consumer Price Index (CPI) and Overnight Policy Rate (OPR), respectively, affected house prices significantly in the long-run. The stock market, tracked by Kuala Lumpur Composite Index (KLCI), had no significant impact on house prices signifying no wealth effect. Through the findings of an inelasticity of demand and an undesirable result of monetary policies, this paper concluded that more effective solutions needed to be carried out to ensure affordability of house ownership in Malaysia.

scholarly journals The asymmetric responses of stock prices in US market

2021 ◽  
Vol 36 ◽  
pp. 01013
Author(s):  
Woan Lin Beh ◽  
Wen Khang Yew
Keyword(s):  
Interest Rates ◽  
Stock Prices ◽  
Price Index ◽  
Consumer Price Index ◽  
Composite Index ◽  
The United States ◽  
Macroeconomic Factors ◽  
Dow Jones Industrial Average ◽  
Short Run ◽  
Average Index

Machine learning and data analytics are so popular in making trading much more efficient by helping the investors to identify opportunities and reduce trading costs. Before applying suitable predictive modelling algorithms, it is crucial for investors or policymaker to understand the nature of the stock data properly. This paper investigates the dependency of macroeconomic factors against the stock markets in the United States using the nonlinear Autoregressive Distributed Lag (NARDL) approach. The analysis considered the Dow Jones Industrial Average Index, NASDAQ Composite Index, and S&P 500 Index. Macroeconomic factors in this country such as consumer price index, export, interest rates, money supply, real effective exchange rates, total reserves, and gold price are considered in this study. In the findings, the NARDL approach shows that the Dow Jones Industrial Average Index and S&P500 Index are having bi-directional positive asymmetric effects to each other in the short run. In short-run, increasing the consumer price index is found to have a negative effect on Dow Jones Industrial Average Index but with a positive effect on S&P500 Index. In conclusion, this study aids investors and other market participants in making a more efficient investment decision.

Real House Prices in the UK

2011 ◽  
Vol 216 ◽  
pp. F62-F68 ◽  
Author(s):  
Ray Barrell ◽  
Simon Kirby ◽  
Rachel Whitworth
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
House Prices ◽  
Consumer Welfare ◽  
Best Interests ◽  
Long Run ◽  
Nominal Interest Rates ◽  
Cyclical Pattern ◽  
Income Ratio ◽  
The Uk

The housing market plays a fundamental role in the economy, and its functioning affects both consumer welfare and economic stability, as the recent crisis has made clear. Research by Barrell et al. (2010) shows that house prices are a key determinant of financial crisis probabilities in OECD economies, and contribute significantly towards systemic banking risk. This must lead the regulator to assess carefully the role of the housing market in this relationship, and if necessary impose regulatory restrictions on the market so as to ensure it functions in a way that reflects the best interests of the economy. In this note we look at the evolution of real house prices in the UK, noting that they have a strong cyclical pattern. We then look at the factors that might affect the evolution of real house prices, and we estimate a dynamic equation describing those prices. After considering a wide set of factors, we demonstrate that there is little role for the supply of housing relative to the number of households. This may be because the ratio of these two variables has been relatively constant over the past thirty years. We show that real borrowing costs, real incomes and the loan-to-income ratio are significant factors determining the long-run path of real house prices, and that front loading problems from high short-term nominal interest rates affect the path of adjustment. Overvaluations can persist for years, and we would judge that real house prices are currently fundamentally overvalued by around 10 per cent. If loan-to-income ratios are reduced then the fundamental overvaluation will increase, and such a policy will put further downward pressure on real house prices.

scholarly journals Do Interbank Interest Rates Matter for Stock Prices at Nepal Stock Exchange?

Pravaha ◽  
2020 ◽  
Vol 26 (1) ◽  
pp. 165-170
Author(s):  
Rajesh Gurung
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Distributed Lag ◽  
Long Run ◽  
Auto Regressive ◽  
The Interest Rate ◽  
Bound Test

This study examines an auto-regressive distributed lag (ADRL) modeling approach to develop the relationship between the stock price and interest rate in the context of Nepal, using the monthly data for the period from July 1996 to January 2019. NEPSE Index in Nepal Stock Exchange Limited is used for the stock prices and interbank interest rate released in Quarterly Economic Bulletin of Nepal Rastra Bank is used for the interest rate. The bound test for co-integration and estimated negative coefficient of long-run regression results justified by the Error Correction Mechanisms (ECM) establishes a valid negative long-run association between the INTEREST and PRICE. This suggests important considerations for policies towards an interest rate stabilization for the stock price stability and further development of the stock market in Nepal.

scholarly journals How Does Stock Prices Respond to Various Macroeconomic Factors? A Case Study of Pakistan

2014 ◽  
Vol 1 (4) ◽  
pp. 25-30
Author(s):  
Ayaz Khan
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Correction Term ◽  
Macroeconomic Factors ◽  
Market Prices ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Long Run

Over the time everything flourished, at the same token the interrelationship among the stock market prices, returns and macroeconomic factors got attendance of the researchers in the field of finance and economics around the world. In this respect current study is an attempt to investigate the response of various macroeconomic factors (GDP, Money Supply, inflation, exchange rate and Size of firm) toward stock market prices in case of Karachi stock exchange over a period of 1971 to 2012. The study utilizes Autoregressive Distributed lag model (ARDL) technique. The results shows that in long run each factor significantly contribute to the stock price while in shot run some factors were significant while some were not but the error correction term shows significant convergence toward equilibrium. The findings of study suggest that for smoothness of stock market the current factors must be targeted.

International Real Estate Review

2019 ◽  
Vol 22 (3) ◽  
pp. 359-397
Author(s):  
Rose Lai ◽  
◽  
Robert Van Order ◽  
Keyword(s):  
Interest Rates ◽  
House Prices ◽  
Housing Prices ◽  
Shadow Banking ◽  
Explanatory Factors ◽  
Pooled Mean Group ◽  
Long Run ◽  
Nominal Interest Rates ◽  
Banking Activity ◽  
Growth Stocks

This paper studies the evolution of property values and the connections between shadow banking and property markets in China. We use Pooled Mean Group estimation to analyze Chinese house prices in 65 cities from 2007-2016, define the "fundamentals¨ of housing prices with the Gordon dividend discount model, and use lagged rents, prices, real and nominal interest rates, and shadow banking activity as short term explanatory factors. We find that the cities tend to share long run fundamentals and adjust relatively quickly to deviations from the fundamentals. We do not find bubbles; rather houses are like growth stocks with house prices rapidly chasing growing rents. More importantly, we find that house prices increase more quickly with the availability of shadow banking funds, which have grown rapidly.

scholarly journals MACROECONOMICS INDICATORS AND BANK STABILITY: A CASE OF BANKING IN INDONESIA

2016 ◽  
Vol 18 (4) ◽  
pp. 431-448
Author(s):  
Norzitah Abdul Karim ◽  
Syed Musa Syed Jaafar Al-Habshi ◽  
Muhamad Abduh
Keyword(s):  
Interest Rates ◽  
Commercial Banks ◽  
Banking Industry ◽  
Consumer Price Index ◽  
Islamic Banks ◽  
Bank Stability ◽  
Macroeconomic Factors ◽  
Long Run ◽  
The Stability ◽  
The Impact

This paper provides new empirical evidence of the bank stability in relation to the macroeconomic indicator of Indonesia. The bank stability is first calculated using Z-score, and then regressed using Autoregressive distributive lag (ARDL) model on the macroeconomic variables i.e. Gross Domestic Product (GDP) in US dollar, Interest rates (IR) in percentage and Consumer Price Index (CPI). To analyse further the long run relationship and the impact of bank stability, Cholesky standard deviation shock to the model, ARDL and Impulse Response Function (IRF) are used. These ARDL and IRF are carried out independently and repeated over data for three different models: (i) the commercial banks model, (ii) Islamic banks model, and (iii) the overall banking industry model. The empirical findings suggest long run relationship between the stability of commercial banks and macroeconomic factors. The findings also suggest the long run relationship between the stability of overall banking industry and macroeconomic factors. However, there is no evidence of long run relationship between the stability of Islamic banks and macroeconomics factors. Nevertheless, this finding is subject to the limitation of data, on the number of Islamic banks included in the test. The sample of Islamic banks was 5 banks from a total of 10 Islamic banks, due to insufficient data, as compared to the larger number of commercial banks taken into, as the sample.

Macroeconomic Factors and Pakistani Equity Market”

2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen
Keyword(s):  
Stock Market ◽  
Industrial Production ◽  
Stock Prices ◽  
Stock Price ◽  
Consumer Price Index ◽  
Reverse Causality ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Equilibrium Relationships

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.

scholarly journals Mobile Money Use: The Impact of Macroeconomic Policy and Regulation

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 51
Author(s):  
Lorna Katusiime
Keyword(s):  
Exchange Rate ◽  
Interest Rates ◽  
Financial Innovation ◽  
Macroeconomic Policy ◽  
Mobile Money ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Long Run ◽  
Short Run ◽  
The Impact

This paper examines the effects of macroeconomic policy and regulatory environment on mobile money usage. Specifically, we develop an autoregressive distributed lag model to investigate the effect of key macroeconomic variables and mobile money tax on mobile money usage in Uganda. Using monthly data spanning the period March 2009 to September 2020, we find that in the short run, mobile money usage is positively affected by inflation while financial innovation, exchange rate, interest rates and mobile money tax negatively affect mobile money usage in Uganda. In the long run, mobile money usage is positively affected by economic activity, inflation and the COVID-19 pandemic crisis while mobile money customer balances, interest rate, exchange rate, financial innovation and mobile money tax negatively affect mobile money usage.

scholarly journals INTEREST RATES, FISHER EFFECT AND ECONOMIC DEVELOPMENT IN TURKEY, 1989-2011

2016 ◽  
Vol 25 (2) ◽  
pp. 95-100
Author(s):  
Selahattin GÜR?? ◽  
Burak GÜR?? ◽  
Turgut ÜN
Keyword(s):  
Economic Development ◽  
Interest Rates ◽  
Test Validity ◽  
Threshold Cointegration ◽  
Fisher Effect ◽  
Empirical Results ◽  
Distributed Lag ◽  
Leading Indicator ◽  
Nominal Interest Rates ◽  
Fisher Hypothesis

This paper investigates the validity of the Fisher Hypothesis in Turkey coveringthe period 2003 – 2012. To test validity of Fisher Hypothesis, this paper uses anAutoregressive Distributed Lag test for threshold cointegration recently introduced in theliterature by Li and Lee (2010). The empirical results which are obtained from this paperindicate that Fisher hypothesis is valid for Turkey, meaning nominal interest rates wouldbe an important leading indicator for inflation.

Analisis Pengaruh Inflasi, Nilai Tukar Rupiah, dan BI-Rate terhadap Harga Indeks Saham Syariah Indonesia

2021 ◽  
Vol 4 (2) ◽  
pp. 47-56
Author(s):  
Fifi Afiyanti Tripuspitorini
Keyword(s):  
Exchange Rate ◽  
Interest Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Partial Least Square ◽  
Least Square ◽  
Stock Index ◽  
Macroeconomic Factors ◽  
Negative Effect ◽  
Monthly Period

Islamic investment is experiencing an upward trend from year to year. Many investors are starting to look at Islamic stocks. One of the Islamic stocks in Indonesia is the Indonesian Sharia Stock Index (ISSI). Investors must have many careful considerations to invest. One of the factors that may influence stock prices is macroeconomic factors. This study aims to determine how macroeconomic variables in the form of inflation, the rupiah exchange rate against the dollar, and Bank Indonesia interest rates can affect the ISSI stock price. This study uses a quantitative data approach. The data is obtained from the Sharia Stock Index (ISSI) in the monthly period January 2016 to December 2018.Meanwhile, data analysis used Partial Least Square (PLS) with the help of WarpPLS. The results showed that inflation and the rupiah exchange rate had no effect on the ISSI stock price. while the BI rate has a significant negative effect on the ISSI stock price.

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