Financial Conditions Index Research Articles

Probabilistic Quantile Factor Analysis

This article extends quantile factor analysis to a probabilistic variant that incorporates regularization and computationally efficient variational approximations. We establish through synthetic and real data experiments that the proposed estimator can, in many cases, achieve better accuracy than a recently proposed loss-based estimator. We contribute to the factor analysis literature by extracting new indexes of low, medium, and high economic policy uncertainty, as well as loose, median, and tight financial conditions. We show that the high uncertainty and tight financial conditions indexes have superior predictive ability for various measures of economic activity. In a high-dimensional exercise involving about 1000 daily financial series, we find that quantile factors also provide superior out-of-sample information compared to mean or median factors.

Asymmetric dependency among US national financial conditions and clean energy markets

This paper examines the relationship between the US National Financial Conditions Index (NFCI) and the clean energy industry using quantile and frequency connectedness, cross-quantile, and wavelet quantile correlation (WQC) techniques. Results reveal (a) a stronger dependence between the NFCI and clean energy under bullish market states. Moreover, the total connectedness between the NFCI and clean energy mostly exhibits time-varying characteristics. In particular, clean energy has a greater spillover effect than the NFCI. (b) Dynamic frequency total connectedness at extreme quantiles provided a more comprehensive view of structural shocks in financial markets, and major crises, such as COVID-19, significantly amplified this connectedness. Overall, the WilderHill Clean Energy Index and the NASDAQ OMX Renewable Energy Index demonstrate substantial potential for hedging financial conditions. (c) The cross-quantile correlation results revealed an asymmetric dependency, demonstrating a sustained significant positive relationship between the NFCI and clean energy index (CEI) across the relative higher quantiles and middle quantiles. The WQC showed that the NFCI and specific CEIs tended to exhibit the strongest positive correlations in nonextreme quantiles and lower frequencies. These results can be of considerable interest to various financial market participants.

IFCI-SA: International financial conditions index for South American economies

The Russian invasion of Ukraine in early 2022, triggered a wave of risk aversion in the global financial markets. In contrast to previous events, South American emerging economies experienced limited impact to this more restrictive global financial environment. To measure the financial conditions of these economies over time, we propose an International Financial Conditions Index for South American economies (IFCI-SA), built from a parametric factor model. This index includes standard variables provided by the literature, along with sovereign debt risk premia and the most relevant commodity prices for the region. We use our model and index to: (i) discuss South American financial conditions from 2007 to 2024; (ii) explain the impact of a particular global event like the Russo-Ukrainian war; (iii) decompose risk premia movements into global and domestic shocks; and (iv) test its forecasting capabilities.

Financial Conditions Index: A Guide to Monetary Policy for Selected WAMZ Countries

Financial Conditions Index: A Guide to Monetary Policy for Selected WAMZ Countries

Evaluating Australia's financial conditions: A comparative analysis and extension of a dynamic factor model index

AbstractThis article investigates the unique financial conditions in Australia in the wake of COVID‐19, a subject of critical importance given the recent unprecedented economic events such as the fastest rate rises since the 1990s and the presence of persistently high inflation. This study aims to contribute to the literature by examining the speed of interest rate changes and its implications on financial conditions, particularly in an environment characterised by negative real interest rates. The research aims to extend and refine the financial conditions index (FCI) developed by the Reserve Bank of Australia by incorporating a momentum variable to capture the speed of interest rate changes. A dynamic factor model is utilised to investigate 73 data series across nine main categories, constructing the FCI on a quarterly basis. The results indicate that rapid interest rate changes significantly impact financial conditions, holding significant weights within the model, thus requiring careful policy considerations.

Forecasting Consumer Price Index with Federal Open Market Committee Sentiment Index

AbstractThe Federal Open Market Committee (FOMC) is a component of the Federal Reserve System responsible for overseeing open market operations. The FOMC meets roughly eight or more times per year to assess the economy of the United States. After each meeting, the FOMC releases a statement to the press outlining its assessment of the US economy and its monetary policy stance. The sentiment of these statements may have an influence on the US economy and financial markets. Using sentiment and correlational analyses, this research examines how the sentiment of these statements affects the US economy and financial markets by analyzing how FOMC statement sentiment is correlated with the Consumer Price Index (CPI), the National Financial Conditions Index (NFCI), and the Adjusted National Financial Conditions Index (ANFCI). We find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the US City Average CPI value associated with the month before and the month after the statement's release. We also find that there is no evidence to suggest there exists a correlation between an FOMC statement's sentiment and the NFCI value associated with the week before or the week after the statement's release. However, we do find evidence to suggest that there is a moderate negative correlation between an FOMC statement's sentiment and the ANFCI value associated with the week before and the week after the statement's release. We also found that out of the three models we tested (linear regression, vine copula regression, and Gaussian copula regression), the Gaussian copula regression model performs the best when forecasting the CPI and the ANFCI. Additionally, we find that when forecasting CPI values, the models that include FOMC statement sentiment are more accurate than the models that exclude FOMC statement sentiment.

Finansal Koşullar Endeksi ile Ekonomik Büyüme ve Net Sermaye Girişi Arasındaki İlişkinin İncelenmesi: Türkiye İçin Nedensellik Analizi

The global economic crisis, which had a devastating effect worldwide with the bankruptcy of Lehman Brother's investment bank in the United States of America in 2008, revealed that countries should indicate risks and take precautions accordingly. In this sense, the importance of the Financial Conditions Index (FCI), which was created by considering the monetary policy instruments of the country's central banks and various macroeconomic and financial variables as a whole, has also increased. FCI, the index that has taken place in the literature since the 1990s, with the growth of countries, has been investigated in empirical studies conducted after the global economic crisis. In this study, the related index is calculated using Principal Component Analysis (PCA), and the data generated is analyzed with growth and net capital inflow items. According to the results of the related analysis, while there is bidirectional causality between FCI and real gross domestic product (GDP) growth, one-way causality was found between FCI and net capital inflow. The index created accordingly is the Granger cause of the net capital inflow.

Financial Condition Indices in an Incomplete Data Environment

Abstract We construct a Financial Conditions Index (FCI) for the United States using a dataset that features many missing observations. The novel combination of probabilistic principal component techniques and a Bayesian factor-augmented VAR model resolves the challenges posed by data points being unavailable within a high-frequency dataset. Even with up to 62 % of the data missing, the new approach yields a less noisy FCI that tracks the movement of 22 underlying financial variables more accurately both in-sample and out-of-sample.

Financial system stability in Indonesia and its relationship with economic growth before and during the Covid-19 pandemic

The purpose of this study is to assess the condition of financial system stability in Indonesia both before and during the Covid-19 pandemic and to look at its relationship with economic growth. This study develops six sub-sector groups described in 19 indicators in order to assess the condition of the financial system. Quarterly data for 6.5 years from Quarter I 2016 to Quarter II 2022 was evaluated. To assess the condition of the financial system, this study uses a composite index approach with the normalized max-min method. The correlation analysis method is used to assess the relationship between the index of financial system conditions and economic growth. The results showed that during the pandemic, there was a more significant increase in pressure on financial conditions than before the pandemic. The financial system instability index during the pandemic in the second quarter of 2020 was 3 times higher than the average and more than 5 times higher than the same quarter in 2019. In addition, the relationship between the financial condition index and economic growth is at 0.77 (strong category). The implication is this research can provide insight to the government, financial institutions, and the public regarding the condition of financial system stability before and during the Covid-19 pandemic. This research suggests that the government should control credit restructuring policies during the pandemic and strengthen financial institutions. This research has limitations in terms of objects that only include conventional financial institutions. Further studies can use other objects such as Islamic financial institutions.

Forecasting the Trend of Macroeconomic Variables in Terms of Financial Conditions Index in Iran: TVP-FAVAR Approach

Forecasting the Trend of Macroeconomic Variables in Terms of Financial Conditions Index in Iran: TVP-FAVAR Approach

The dynamic impact mechanism of China's financial conditions on real economy and international crude oil market

As financial conditions become more complex and variable, capturing economic patterns becomes harder. The Financial Conditions Index (FCI) has gained traction as a tool to assess the performance of financial markets in nations or regions. This paragraph has created the China FCI using various financial indicators from 2002 to 2022. And with the use of statistical models like DMA-TVP-FAVAR, mixed-frequency Granger causality test, TVP-SV-VAR, and MS-VAR to analyze the relationship between China's financial condition, real economy, and the crude oil market. Different impacts were observed over time and in response to economic shocks, Results show that the fluctuation of international oil price has a negative impact on our financial condition. Therefore, the government should consider the impact of external shock factors such as international crude oil price when formulating financial policies to prevent financial risks.

Reassessing growth vulnerability

SummaryThis paper replicates the results of Adrian et al. (American Economic Review, 2019) that GDP growth volatility is mainly driven by the lower quantiles of the distribution which is predicted by the financial condition. It extends their study by estimating the model with the IVX‐QR estimator of Lee (Journal of Econometrics, 2016) and double weighted estimator of Cai et al. (Journal of Econometrics, 2022) considering that the financial condition index is highly serially correlated. Both models are estimated with the smoothed estimating equation approach of Kaplan and Sun (Econometric Theory, 2017). The results show that the findings of Adrian et al. (American Economic Review, 2019) are robust to possible bias due to the existence of persistent predictors. The out‐of‐sample forecasting exercises suggest that methods that are robust to the existence of persistent predictors can improve forecasting performance at the lower quantiles of the GDP growth distribution.

Nghiên cứu tác động của chỉ số điều kiện tài chính tới lạm phát ở Việt Nam

This paper investigates the impact of the financial condition index on inflation in Vietnam by using the Autoregressive- Distributed Lag Model (ARDL) combined with a time series dataset from January 2013 to December 2022. Research results show that loosening financial conditions will put pressure on inflation in the short term but not in the long term. In addition, the oil price and M2 money supply also have a positive impact on Vietnam’s inflation. On that basis, this paper also proposes policy recommendations to improve the effectiveness of monetary policy in Vietnam

Analisa Fiskal di Provinsi Jawa Barat Periode 2019-2021

ABSTRACT
 The requirement to implement regional autonomy and fiscal decentralization is a good regional fiscal health condition. This study took a sample of districts / cities in West Java Province in the period 2019 - 2021 to be analyzed using the Fiscal Health Index. The research method uses a quantitative descriptive study and as the unit of analysis sets all districts / cities. The fiscal health condition of each Regency / City in the West Java Province region before and during the Covid-19 pandemic can be described through the results of the analysis. From the measurement of each indicator, it can be seen that the regions with good financial health conditions are Pangandaran Regency, Majalengka Regency, Cirebon City, and Banjar City. The financial condition of Pangandaran Regency is relatively stable, even though the two years of the Covid-19 pandemic have not experienced significant shocks. Likewise with Majalengka Regency, although the index fell at the beginning of the pandemic (2019, and 2020), in 2021 the index increased significantly. On the other hand, the financial health conditions that are classified as poor are Cianjur, Karawang, and West Bandung. These three regions have a financial condition index far from other regions. In 2019, West Bandung Regency and in 2021 Cianjur Regency are the regions with the lowest index while in 2020 the lowest is Karawang Regency. 
 Keywords: Regional Fiscal Health, Fiscal Decentralization, Financial Independence, Financial Flexibility, Service Solvency

The effects of central bank extraordinary measures on financial conditions: Evidence from Mexico

ABSTRACT This paper analyses the effects of the extraordinary measures implemented by the Central Bank of Mexico during the COVID-19 pandemic on financial conditions. For this purpose, we estimate a factor-augmented vector autoregressive model for the period 2001–2021. Based on this model, we construct a Financial Conditions Index, estimate the response of this indicator and its components from a shock to the outstanding amount of these measures, and conduct a counterfactual exercise to further analyse the effect of the aforementioned measures. The main results indicate that these extraordinary measures seem to have contributed to improve financial conditions. In particular, we find that if these measures had not been implemented, the sovereign risk premium, the 10-year government bond yield, the slope of the yield curve, and the long- and short-term yield spreads between Mexico and the US would have been higher by around 56, 31, 27, 37, and 49 basis points in December 2020, respectively. At the same time, the Mexican peso/US dollar exchange rate and its volatility would have been higher by 5 and 2 percentage points, respectively. In turn, the Mexican stock market index would have been lower by 10 percentage points.

Across‐the‐Curve Credit Spread Indices

AbstractWe design a novel across‐the‐curve credit spread index, AXI, a measure of the recent cost of wholesale unsecured debt funding for publicly listed US bank holding companies and commercial banks. AXI, a benchmark for bank lending and risk management, is the weighted average of credit spreads for unsecured debt instruments with maturities ranging from overnight to five years, with weights that reflect both transaction and issuance volumes. We provide illustrative output of the bond‐based component of AXI. By widening coverage to include all corporate debt issuers, we also build a financial conditions index (FXI).

New tourism financial condition index: extended with terrorist attacks

Purpose- In this study, a composite indicator that can be followed in the financial markets has been developed. The tourism financial conditions index has been developed in the literature for tourism based on MCI (Monetary Conditions Index) and FCI (Financial Conditions Index). The index is called the Tourism Financial Conditions Index in their studies. This study ensures that the calculation of the tourism index by adding the terror variable to the index can better reflect the expectations. Methodology- While constructing the composite indicator Z-score is used for standardization. With this standardization terrorist attacks variable is added to the composite indicator. The relationship between New Tourism Financial Composite Indicator and Tourism Stock Market Index Return is analyzed with the Threshold VAR method. This method is used because of the nonlinearity of variables. Findings: Monthly data for the period 2009:07 – 2017:12 were used in the study. The countries examined are Australia, Denmark, France, Italy, Spain, Türkiye and the UK. It is aimed to examine the relationship between the calculated NTFCI and the Tourism Stock Exchange data of each country. T-VAR results show the relationship between these variables. Conclusion - In this study, the new version of the TFCI index with terrorist incidents is presented. Chang (2015) developed the TFCI index for the tourism sector. We think that the countries should also consider the effect of terrorism in their economic and financial research in tourism area. Based on this idea, the index was expanded by adding the terror variable to the previously developed TFCI composite indicator and its relationship with the tourism stock market index as a financial indicator was examined. The TVAR model is applied which shows the short-term dynamic relationship. Models for different countries were estimated and similar results were obtained for different countries. Keywords: Tourism financial conditions index, tourism sector, monetary conditions index, financial conditions index JEL Codes: E44, E47, G32

The Financial Conditions Index as an additional tool for policy-makers in developing countries: the Mexican case

PurposeThe idea of this study is to provide a solid Financial Condition Index (FCI) that allows the monetary transmission policy to be monitored in a country which in recent decades has suffered from major financial and monetary crises.Design/methodology/approachThe authors construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime. Using monthly data from 1995 to 2017, the authors estimate FCIs with two different methodologies and build the index by taking into account the mechanism of transmission of monetary policy and incorporating the most relevant financial variables.FindingsThis study’s results show that, likewise for developing countries as Mexico, an FCI could be a useful tool for managing monetary policy in reducing macroeconomic fluctuations.Originality/valueApart from building a predictor of possible financial stress, the authors construct an FCI for a central bank that pursues inflation targeting and to analyse the role of financial asset prices in formulating monetary policy.HighlightsWe construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime.The FCIs are based on (1) a vector autoregression model (VAR); (2) an autoregressive distributed lag model (ARDL) and (3) a factor-augmented vector autoregression model (FAVAR).FCI could become a new target for monetary policy within a hybrid inflation-targeting framework.FCI could be a good tool for managing monetary policy in developing countries with a low-inflation environment.

The macro-financial effects of international bank lending on emerging markets

We provide novel empirical evidence on the effects of cross-border bank lending on emerging market economies' (EMEs) macro-financial conditions. We identify causal effects by leveraging the heterogeneity in the size distribution of bilateral cross-border bank lending to construct granular instrumental variables for aggregate cross-border bank lending to 22 EMEs. Cross-border bank credit causes higher domestic activity in EMEs and looser financial conditions. Financial condition indices ease, nominal and real effective exchange rates appreciate, sovereign and corporate spreads narrow, domestic interest rates fall, and housing prices increase. Similarly, real domestic credit grows, real GDP expands, and imports rise. Using a simple model, we motivate our instrument and show how commonly used instruments that correlate with global financial conditions (e.g. the global financial cycle) can yield biased estimates. We find empirical evidence of an amplification bias, which is consistent with the prominent role of global risk perceptions and international risk spillovers.

FINANCIAL CONDITION OF LOCAL GOVERNMENT AFTERMATH OF COVID 19 PANDEMIC-ARCHIVAL ANALYSIS

This research aims to examine two aspects: (1) the provincial government of Indonesia's financial condition index; and (2) the influence of the financial condition on cases of COVID 19 handling. This study uses a descriptive quantitative approach with archival data analysis for 2015-2021. The provinces of Aceh, DKI Jakarta, Kalimantan Timur, NTT, and Papua Barat have the best financial condition index in Indonesia, according to an assessment of provincial government financial health. Financial condition has an simultaneous effect on COVID-19 pandemic handling. The results showed that H1 was approved with sig. 0.001 of simultaneous influence of provincial government's financial condition on COVID-19 cases. H3 is recognized with sig <0.001 that financial independent index partial effect on COVID-19 cases. With a sig. 0.187, H3 is rejected, indicating that budget solvency has no partial impact on the 19 cases. With a sig. 0.885, H4 is refused, indicating that service level solvency has no influence on situations of COVID-19. Budget solvency, financial independence, and service level solvency are independent variables that can account for 38,1% of the 19 covid cases that occurred in the province.