Macroeconomic Factors and Pakistani Equity Market

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.Financial Market, Pakistan, Stock Market

The Influence of Macroeconomic Factors on Stock Market Index (Study on Lq45 Index for August 2011–july 2016)

Penelitian ini bertujuan untuk mengamati pengaruh simultan dan parsial factor ekonomi makro yang diantaranya adalah harga minyak dunia, nilai tukar, tingkat inflasi dan tingkat suku bunga terhadap indeks LQ45. Penelitiаn ini menggunаkаn explаnаtory reseаrch dengаn pendekаtаn kuаntitаtif, dengаn 60 jumlаh sаmpel selаmа 10 periode indeks LQ45 pаdа Аgustus 2011 – Juli 2016. Dаtа yаng digunаkаn аdаlаh dаtа sekunder dengаn tipe dаtа time series. Аnаlisа yаng digunаkаn dаlаm penelitiаn ini аdаlаh аnаlisis deskriptif, inferensiаl stаtistik dаn regresi lineаr bergаndа. Hаsil penelitiаn menunjukkаn bаhwа 1) Vаriаbel ekonomi mаkro hаrgа minyаk duniа, nilаi tukаr, tingkаt inflаsi dаn tingkаt suku bungа memiliki pengаruh signifikаn secаrа simultаn terhаdаp indeks hаrgа sаhаm, indeks LQ45; 2) Vаriаbel hаrgа minyаk duniа tidаk memiliki pengаruh secаrа pаrsiаl terhаdаp indeks LQ45; 3) Vаriаbel nilаi tukаr memiliki pengаruh positif dаn signifikаn secаrа pаrsiаl terhаdаp indeks LQ45; 4) Vаriаbel tingkаt inflаsi tidаk memiliki pengаruh secаrа pаrsiаl terhаdаp indeks LQ45; 5) Vаriаbel tingkаt suku bungа memiliki pengаruh negаtive dаn signifikаn secаrа pаrsiаl terhаdаp indeks LQ45. Kata Kunci: Indeks LQ45, Harga Minyak Dunia, Nilai Tukar, Tingkat Inflasi, Tingkat Suku Bunga ABSTRАCT This research aims to observe the simultaneous and partial effect of macroeconomic factors which are world oil price, exchange rate, inflation rate and interest rate on LQ45 index. This reseаrch uses explаnаtory reseаrch аnd quantitative approach with the totаl of 60 samples for 10 periods of LQ45 index from Аugust 2011-July 2016. The dаtа collection method is using documentаtion with secondary time series dаtа. The аnаlysis method for this reseаrch is using descriptive аnаlysis, inferentiаl stаtistics аnd multiple lineаr regression. The results show thаt 1) The world oil price, exchаnge rаte, inflаtion rаte аnd interest rаte vаriаbles hаve а significаnt effect on LQ45 index simultаneously; 2) The vаriаble world oil price hаs no significаnt effect on LQ45 index pаrtiаlly; 3) The vаriаble exchаnge rаte hаs а positive аnd significаnt effect on LQ45 index pаrtiаlly; 4) The vаriаble level of inflаtion rаte hаs no significаnt effect on LQ45 index pаrtiаlly; 5) The vаriаble interest rаte hаs а negаtive аnd significаnt effect on LQ45 index pаrtiаlly

The Macroeconomic Determinants of Volatility in Precious Metals Markets

We investigate key macroeconomic factors that impact the price returns of precious metals markets. The markets investigated were gold, silver, platinum and palladium; whereas the macroeconomic factors accommodated business cycle, monetary environment and financial market sentiment factors. The key findings present limited evidence that the same macroeconomic factors jointly influence the volatility processes of the precious metal price series, although there is some evidence of volatility feedback between the precious metals. This finding lends weight to views that individual commodities are too distinct to be considered a single asset class or represented by a single index; a finding of considerable importance for portfolio managers and investors.

Identification of macroeconomic factors in large panels

This paper presents a dynamic factor model in which the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of over-identifying loading restrictions, while the structural shocks are estimated following standard practices in the SVAR literature. Estimators based on the EM algorithm are developped. We apply this framework to a large panel of US monthly macroeconomic series. In particular, we identify nine macroeconomic factors and discuss the economic impact of monetary policy stocks. The results are theoretically plausible and in line with other findings in the literature. The first part of this paper uses quantitative methods to assess the success of party affiliation, personal interests and the economic profile of the constituencies in predicting voting behavior. Thanks to the detailed censuses of 1846 on agriculture, industry and population, it is possible to typify the economic make-up of the electoral districts in much more detail than in the British case. However, the analysis of roll-call voting proves that party affiliation and personal and constituency economic interests are insufficient to explain the shift towards free trade. The second part of the paper then discusses the role played by political strategy and ideas in the liberalization of corn tariffs, using a qualitative analysis of the debates on tariff policy. The large number of votes over a forty year period allows us to document the relationship between ideas and interests in a new way.Monetary policy, Business Cycles, Factor Models, EM Algorithm.

Macroeconomic factors and micro-level bank risk

The interplay between banks and the macroeconomy is of key importance for financial and economic stability. We analyze this link using a factor-augmented vector autoregressive model (FAVAR) which extends a standard VAR for the U.S. macroeconomy. The model includes GDP growth, inflation, the Federal Funds rate, house price inflation, and a set of factors summarizing conditions in the banking sector. We use data of more than 1,500 commercial banks from the U.S. call reports to address the following questions. How are macroeconomic shocks transmitted to bank risk and other banking variables? What are the sources of bank heterogeneity, and what explains differences in individual banks' responses to macroeconomic shocks? Our paper has two main findings: (i) Average bank risk declines, and average bank lending increases following expansionary shocks. (ii) The heterogeneity of banks is characterized by idiosyncratic shocks and the asymmetric transmission of common shocks. Risk of about 1/3 of all banks rises in response to a monetary loosening. The lending response of small, illiquid, and domestic banks is relatively large, and risk of banks with a low degree of capitalization and a high exposure to real estate loans decreases relatively strongly after expansionary monetary policy shocks. Also, lending of larger banks increases less while risk of riskier and domestic banks reacts more in response to house price shocks. --FAVAR,bank risk,macro-finance linkages,monetary policy,microeconomic adjustment

Macroeconomic Factors and Micro-Level Bank Risk

The interplay between banks and the macroeconomy is of key importance for financial and economic stability. We analyze this link using a factor-augmented vector autoregressive model (FAVAR) which extends a standard VAR for the U.S. macroeconomy. The model includes GDP growth, inflation, the Federal Funds rate, house price inflation, and a set of factors summarizing conditions in the banking sector. We use data of more than 1,500 commercial banks from the U.S. call reports to address the following questions. How are macroeconomic shocks transmitted to bank risk and other banking variables? What are the sources of bank heterogeneity, and what explains differences in individual banks’ responses to macroeconomic shocks? Our paper has two main findings: (i) Average bank risk declines, and average bank lending increases following expansionary shocks. (ii) The heterogeneity of banks is characterized by idiosyncratic shocks and the asymmetric transmission of common shocks. Risk of about 1/3 of all banks rises in response to a monetary loosening. The lending response of small, illiquid, and domestic banks is relatively large, and risk of banks with a low degree of capitalization and a high exposure to real estate loans decreases relatively strongly after expansionary monetary policy shocks. Also, lending of larger banks increases less while risk of riskier and domestic banks reacts more in response to house price shocks.FAVAR, bank risk, macro-finance linkages, monetary policy, microeconomic adjustment

Identification of macroeconomic factors in large panels.

This paper presents a dynamic factor model in which the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of overidentifying loading restrictions, while the structural shocks are estimated following standard practices in the SVAR literature. Estimators based on the EM algorithm are developped. We apply this framework to a large panel of US monthly macroeconomic series. In particular, we identify nine macroeconomic factors and discuss the economic impact of monetary policy stocks. The results are theoretically plausible and in line with other findings in the literature.

Identification of Macroeconomic Factors in Large Panels

This paper presents a dynamic factor model where the extracted factors and shocks are given a clear economic interpretation. The economic interpretation of the factors is obtained by means of a set of over-identifying loading restrictions, while the structural shocks are estimated following standard practices in the SVAR literature. Estimators based on the EM algorithm are developed. We apply this framework to a large panel of US monthly macroeconomic series. In particular, we identify five macroeconomic factors and discuss the economic impact of monetary policy shocks. The results are theoretically more plausible than those implied by standard SVAR models and indicate a significant role for monetary policy shocks in macroeconomic dynamics.Monetary policy, Business Cycles, Factor Models, EM Algorithm.