Reconsidering the Relationship between Oil Prices and Industrial Production: Testing for Cointegration in some of the OECD Countries

This paper investigates the effects of crude oil prices on the industrial production for some of the OECD countries. According to it, the empirical results sign that there is statistical meaningful short term causality from crude oil price to industrial production in all countries except France. In France however, causality is from industrial production to oil price in short run. The error correction mechanism is run for US. The causality is from oil price to industrial production in long run for US. These results show us that oil prices do affect industrial production index. Another interesting finding that, similar results were observed for oil exporting and importing countries such as Saudi Arabia and Iran as well. This situation is important that firm sensitivity towards oil price shows a similarity among the countries

THE EFFECT OF CONFİDENCE FACTOR ON USED OF BANK CREDİT BY FIRMS

Capital structure is complex areas of financial decision making due to its interrelationship with macroeconomic değişkens. In this study for Turkey, the relationship between confidence factor and the usage of bank credit is investigated with cointegration analysis and error-correction mechanism. Real sector confidence index is used for domestic country and international VIX is for outside country. The period includes 106 month and 8 years for 2000 and 2008. Monthly data is obtained from yahoo, IFS and CBTR. According to the results of the analysis, there seems to be a causality from real sector confidence index to bank credit. Besides, It is not found causality from VIX to bank credit.Bank credits, confidence, Johansen co- integration, VAR model, Error correction

A Micro Based Study on Bank Credit and Economic Growth: Manufacturing Sub-Sectors Analysis

This study examines the relationship between bank credits and performance and growth of manufacturing sub-sectors. Industrial Production Index was used for a different approach as a dependent variable. Indications of the autoregressive distributed lag (ARDL) bound co-integration test support the theory that bank credits are more effective than loan rates on industrial production of sub-sectors. Moreover, the increase in bank credit leads to the rise of industrial production in all the sub-sectors, except Machinery. According to the Toda Yomamato causality test results, there are different degrees of causalities in means of the importance of bank loans for industrial production. On the other hand, in all sub-sectors except machinery and chemical sub-sectors, causality relations were observed at different grades beginning from loan interest rates to industrial production. As a result, this study concludes with the evidence of supply leading hypothesis via the financial sector leads and causes economic growth

Performance Evaluation of the Hedge Funds Established in Turkey

WOS: 000507235400016The aim of this study is to evaluate the performance of the hedge funds in Turkey. Hedge funds, which are quite new to Turkish financial markets, are examined and the performance of the funds that have been founded in Turkey starting from 2008 are analyzed. Analyzed hedge funds, which are in total of 22 funds, are the ones that we have the data for a period of 36 months (2014-2017). The mean returns of the funds and the risks they take are calculated with the use of Istanbul Stock Exchange (BIST100) as a market indicator. Moreover, Data Envelopment Analysis (DEA) has been applied in order to measure the performance of the funds. According to the results, 91% of the funds have been found to have positive monthly geometric return on average. When it comes to the results of DEA, which has been done with 2 different models called BCC and CCR models, the first model has found 55% of the funds efficient whereas the latter has found 41% of them efficient

What drives green betas? Climate uncertainty or speculation

[EN] Examining green equity sectors including geothermal, wind, solar, bioclean, and clean energy within a DCC-MIDAS framework, we show that green betas are predominantly driven by speculative sentiment in technology stocks rather than climate uncertainty. We argue that the lottery-like features of green assets, whose values are highly tied to the success of new technologies, result in a negative risk-mispricing relationship driven by technology speculation. Further economic analysis shows that a forward-looking investment strategy conditional on technology sentiment yields improved risk-adjusted returns for passive equity investors, par-ticularly following the 2016 Paris Agreement. Our findings establish a new speculation-based channel for characterizing the systematic risk of green assets.Polat, O.; Demirer, R.; Eksi, IH. (2024). What drives green betas? Climate uncertainty or speculation. Finance Research Letters. 60. https://doi.org/10.1016/j.frl.2023.1048706

How Does Transparency Affect Bank Risk and Performance? Evidence from Turkey

Purpose: The main objective of this study is to investigate the effect of transparency on the performance of banks, which are among the most important units of the financial sector. Methodology: The Generalized Method of Moments (GMM) analysis was applied using the annual data from 22 deposit banks operating in Turkey. Four models related to profitability, credit risk, deposits, and stock returns were established by calculating a transparency score derived on the basis of 106 criteria for each year and for each bank. Findings: According to the GMM results, it was observed that transparency, credit risk, and profitability were negatively correlated, while stock returns had a positive relationship. Research limitations: There are not enough public-traded banks, especially in the stock returns section. Although this research has the largest sample size among the studies conducted to date, all banks in Turkey could not be included in its scope. Value: The analysis reveals the importance of reporting and sharing information from banks. Banks should set a transparency criterion, and a transparency score should be established using the researched criterion

Predicting House Prices Using DMA Method: Evidence from Turkey

The aim of this study is to analyze the dynamics of the housing market in Turkey’s economy and to examine the impact of variables related to housing prices. Preferred by many international housing investors, Turkey hosts profitable real estate investments as one of the developing countries with a shining housing market. This study applies the dynamic model averaging (DMA) methodology to predict monthly house price growth. With the increasing use of information technologies, Google online searches are incorporated into the study. For this purpose, twelve independent variables, with the Residential Property Price Index as the dependent variable, were used in the period January 2010–December 2019. According to the analysis results, it was observed that some variables, such as bond yields, the level of mortgages, foreign direct investments, unemployment, industrial production, exchange rates, and Google Trends index, are determinants of the Residential Property Price Index

Effect of levosimendan and predictors of recovery in patients with peripartum cardiomyopathy, a randomized clinical trial

Levosimendan is a promising new inodilator agent but its effectiveness in peripartum cardiomyopathy (PPCM) has not been tested in a clinical trial. The authors sought to evaluate the effect of levosimendan therapy and to determine the predictors of clinical outcome in patients with PPCM