TED Spread Research Articles

Generalized Autoregressive Conditional Betas: A New Multivariate Score-Driven Filter

Abstract In this paper, we extend the recent Gaussian autoregressive conditional beta (Gaussian-ACB) model from the literature on score-driven models. In the new asset pricing model, named the t generalized ACB (t-GACB) model, a multivariate score-driven filter for the t-distribution drives dynamic interaction effects among the beta coefficients. We present the econometric formulation and statistical inference for the t-GACB model, which we apply to 15 stocks from the United States (US) from 1999 to 2022. In our empirical application, we use the three Fama–French factors as asset pricing factors, and we also use the Volatility Index, TED Spread, and ICE BofA US High Yield Index Option-Adjusted Spread as exogenous explanatory variables that influence the beta coefficients. We compare the statistical and realized tracking error performances of the Gaussian-ACB, t-ACB, and t-GACB models, and we find that the t-GACB model improves the Gaussian-ACB model.

Evaluating the Impact of Financial Stability and Monetary Stability on Economic Growth: Evidence from an Emerging Economy

Financial stability and monetary stability both make an essential contribution to sustainable industrial growth and well-established industrial sectors contribute to sustainable economic development. The fundamental objective of this study is to create an FSI index to quantify financial strain in Pakistan. While utilizing monthly data starting from 2004-11 to 2017-7 the Financial Stress Index has four indicators which include TED spread, yield spread, stock price volatility, and exchange rate volatility through principal component analysis (PCA). An ARDL co-integration model is used to investigate the long-term and short-term relationships between time series data. The primary takeaways from this research are that financial stability and industrial production are positively correlated, while inflation and industrial production are negatively correlated. This study fills a knowledge gap by analyzing the impact of financial and monetary stability on economic growth in Pakistan using the Financial Stress Index. Lastly, this study sheds light on the financial and monetary concerns of Pakistan.

The impact of liquidity conditions on the time-varying link between U.S. municipal green bonds and major risky markets during the COVID-19 crisis: A machine learning approach

In this study, we aim to investigate the role of the liquidity risk channel in affecting the dynamic conditional correlations (DCCs) between the U.S. municipal green bonds and risky assets (energy commodities and stocks) by accounting for other macroeconomic risks and uncertainties during the COVID-19 crisis period. To explore the underlying mechanism behind the DCCs, we first derive the DCCs and then use novel machine learning techniques, such as CatBoost, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) models and select the most effective one based on its performance metrics. We also employ the Shapley Additive Explanations (SHAP) method to gain a greater understanding of machine learning predictions. The baseline findings suggest the critical role of the rising term spread in increasing the DCCs between the U.S. municipal green bonds and risky assets during the COVID-19 crisis. Equally important, we observe that this role is more pronounced at high levels of the term spread and that the term spread frequently interacts with funding liquidity conditions (TED spread). Our analysis holds valuable implications for the implementation of informed policy sets and the development of optimal portfolio diversification strategies in global markets.

국제자본조달유동성과 우리나라의 경기변동에 대한 연구

This study investigates the significance of the U.S. funding liquidity measure, TED spread, obtained by subtracting 3-month T-bill rate from 3-month Libor, in explaining the business cycle of South Korea and takes a look at recent changes pertaining to the transition to SOFR(Secured Overnignt Financing Rate) from Libor. This study contributes to the existing literature by empirically demonstrating the statistical significance of the global funding liquidity on the business cycle of South Korea, thereby enhancing the understanding of the business cycle in South Korea, and by examining SOFR which is gaining increasing attention. In applying the probit estimation model, a binary dependent variable is generated based on the business cycle stages and descriptive variables are constructed using term spread, short rate, and funding liquidity measures. The estimation results show that TED spread is significant in explaining the business cycle of South Korea, while the domestic funding liquidity measure proves to be insignificant, and considering U.S. term spread and TED spread along with domestic variables remarkably enhances the explanatory power. Under the circumstance that TED spread is no longer available due to the transition to SOFR, it is necessary to reassess the measurement of funding liquidity, considering recent studies which demonstrate that SOFR is less informative than Libor concerning credit and liquidity risks. Especially in case of the term SOFR, which covers vulnerabilities of overnignt rate and promotes practical use of the new benchmark rate, further research is required to figure out its informational contents on the funding conditions.

Fama–French–Carhart Factor-Based Premiums in the US REIT Market: A Risk Based Explanation, and the Impact of Financial Distress and Liquidity Crisis from 2001 to 2020

The study investigates the impact of financial distress (credit spread) and liquidity crises (TED spread) on size, value, profitability, investment and momentum premiums within the US Real Estate Investment Trust market. Using daily data from 2001 to 2020, we examine the presence, magnitude and significance of these premiums, along with assessing if these premiums are associated with higher risk. The study then employs Auto-regressive distributed lag and Error Correction Modeling to establish the long/short-run impact of financial distress and liquidity crisis on these premiums during recessionary and non-recessionary phases, including COVID-19. Premiums associated with all five factors are positive and significant. Secondly, in contradiction to the Efficient Market Hypothesis, we find that value and momentum portfolios provide superior returns without exposing investors to higher risk while portfolios based on size, profitability and investment, do tend to expose investors to a higher risk. Thirdly, in contradiction to the risk based explanation of Fama–French/Carhart (2015/1997), we find significant evidence of a fall in profitability and momentum premiums with an uptick in financial distress and liquidity crisis. On the other hand, size, value and investment premiums rise with financial distress/liquidity crisis, only during the recessionary phases. This impact is insignificant during non-recessionary phases.

In Search of Global Determinants of National Credit-to-GDP Gaps

This paper seeks to identify the most important global drivers of credit-to-GDP gaps for 35 countries. The analysis is performed on a country-by-country basis for the sub-periods 2000Q1:2007Q2, 2007Q3:2013Q4, and 2014Q1:2021Q1 and is based on two state-of-the-art methods for variable selection in the time series framework: the one covariate at a time multiple testing (OCMT) and adaptive least absolute shrinkage and selection operator (LASSO). We find that the number of salient global factors tends to increase over time, reaching its maximum during the post-crisis period. This period is also marked by a pronounced role of the global factors capturing the stance of the US monetary policy, while in the preceding sub-periods, the most significant factors are global credit conditions (the TED spread) and world industrial production, respectively. Regardless of the sub-periods, advanced economies’ credit-to-GDP gaps appear more dependent on the global factors than the gaps in emerging markets. In addition, we identify country-specific variables which shape the susceptibility of the national credit-to-GDP gaps to the global factors.

Volatility spillovers during normal and high volatility states and their driving factors: A cross‐country and cross‐asset analysis

AbstractUnderstanding the transmission of volatility across markets is essential for managing risk and financial stability, especially under crisis periods during which an extreme event occurring in one market is easily transmitted to another market. To gain such an understanding and enrich the related literature, we examine in this article the system of volatility spillovers across various equity markets and asset classes using a quantile‐based approach, allowing us to capture spillovers under normal and high volatility states. The sample period is 16 March 2011–10 November 2020 and the employed dataset comprises 12 implied volatility indices representing a forward‐looking measure of uncertainty of global equities, strategic commodities and the US Treasury bond market. The results show that the identity of transmitters and receivers of volatility shocks differ between normal and high volatility states. The US stock market is at the centre of volatility spillovers in the normal volatility state. European and Chinese stock markets and strategic commodities (e.g. crude oil and gold) become major volatility transmitters in the high volatility state, after acting as volatility receivers during normal periods. Furthermore, we study the drivers of implied volatility spillovers using regression models and find that US Default spread contributes to the total volatility spillover index in both volatility states, whereas TED spread plays a significant role in the normal volatility state. As for the role of short rate and risk aversion, it is significant in the high volatility state. These findings matter to the decision‐making process of risk managers and policymakers.

External capital market frictions, corporate governance, and tax avoidance: Evidence from the TED spread

This study investigates whether corporate tax avoidance can benefit shareholders when external capital market frictions are high. Using the TED spread as an exogenous shock to firm financial constraint, the study documents that firms tend to reduce their effective tax rates more aggressively when external financing is very costly. This negative relation is stronger in industries more sensitive to TED. Furthermore, we find that the positive effect of TED on tax avoidance is more pronounced within firms with good corporate governance. Our final analyses suggest that the tax-savings during the time of high external market frictions positively affect firm value and the positive effect on firm value is stronger within firms with good corporate governance.

Asset pricing with a financial sector

AbstractIn this paper, we study the quantitative asset pricing implications of a financial intermediary that faces a leverage constraint. We use a recursive method to construct the global solution that accounts for occasionally binding constraints. Quantitatively, our model generates a high and countercyclical equity premium, a low and smooth risk‐free interest rate, and a procyclical and persistent price–dividend ratio, despite an independently and identically distributed consumption growth process and a moderate risk aversion of 10. As a distinct prediction from our model, we find that when the intermediary is financially constrained, the interest rate spread between interbank and household loans spikes. This pattern is consistent with the empirical evidence that high TED spread coincides with low stock price and high stock market volatility.

Bitcoin futures risk premia

AbstractThis paper presents an empirical analysis of bitcoin futures risk premia. Based on the relevant theories and empirical findings of commodity futures risk premia, we study a battery of predictors, including position‐based measures, market microstructure factors, and macroeconomic variables. We find that trading activity and extreme sentiment of speculators and retailers present significant predicting power on the subsequent bitcoin futures price changes over different time horizons. We also find evidence that the lower transaction cost, the higher bitcoin futures risk premiums. Regarding macroeconomic variables, financial conditions index, TED spread, US M2 money stock, and funding cost of financial institutions could predict bitcoin futures returns. The return impact of net position changes of hedgers is likely to be affected by extremes in macroeconomic variables. Speculators behave like negative feedback traders, while retailers are positive feedback traders. This detailed analysis of the risk premia of this emerging derivatives market provides critical implications.

USD Exchange Rate Cycles Using Developed and Developing Currencies and Risk Factors

This paper predicts the exchange rates cyclical for US dollar [forecast two states for exchange rates; appreciation and depreciation] through using developing and developed currencies along with two risk factors (TED spreads and Inflation). Probity and logit models along with the principal component analysis and factor analysis are used to retain the most powerful components and factors. The empirical findings reveal that risk factors are not key factors in determining the exchange rates' cyclical behavior for the US dollar. Furthermore, the Sterling Pound is the only variable that has a consistent result that is more likely to cause appreciation for the US dollar exchange rate using all types of regressions. In addition, Renminbi shows inconsistent effects between different regressions; using OLS is less likely to cause appreciation for the US dollar exchange rate. By contrast, using Logit and Probit regressions is more likely to cause appreciation for the US dollar exchange rate. On the other hand, principal component analysis and factor analysis show that for all currencies we should retain two components and factors to be able to explain around 80% of the variation in exchange rate cyclical.

The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index

The purpose of this study is to find the influence of various macroeconomic factors on the volatility index, as macroeconomic factors affect stock market volatility, resulting in an impact on the VIX Index, representing the risk in the stock market. To estimate the significance and importance of the U.S. macroeconomic variables on stock market volatility and risk, classification problems from machine learning are constructed to predict the daily and weekly trends of the VIX Index. Data from May 2007 to December 2021 is considered for analysis. The selected models are trained with twenty-four daily features and twenty-four plus nine weekly features. The outcomes suggest that the decisions made by the Light GBM and XG Boost on ranking features can be significantly accepted over logistic regression. It is found from the results that economic policy uncertainty indices, gold price, the USD Index, and crude oil are signified as strong predictors. The Financial Stress Index, initial claims, M2, TED spread, Fed rate, and credit spread are also strong predictors, while various yields on fixed income securities make a little less impact on the VIX Index. The TED spread, Financial Stress Index, and Equity Market Volatility (Infectious Disease Tracker) are positively associated with the VIX.

Optimal carry trade portfolio choice under regime shifts

This paper studies optimal currency allocation of the carry trade in foreign exchange (FX). A number of empirical studies have documented a phenomenon referred to as the ‘forward premium puzzle’, which states that the carry trade is profitable on average. However, the carry reversal during the 2008 global crisis periods wiped out the profits earned by the trade. To account for the regime shifts in the joint distribution of returns on the carry trade with FX market portfolios, we adopt a Markov regime switching model. We find evidence of two economic regimes: one state captures periods of the forward premium puzzle and UIP being violated, whilst the other reports high FX volatility and negative return of carry trade portfolio. Furthermore, to quantify the economic significance of regimes in returns on currency portfolios, we consider their importance in investors’ optimal portfolio allocation problem. We find strong evidence that optimal currency portfolio holdings vary significantly across regimes and across short and long investment horizons, as investors anticipate a shift out of the current state. Our results also show that the regimes partially anticipate peso events as well as the changes of funding liquidity measured by the TED spreads. A strategy that accounts for regimes, thus, generates overall stronger performance than the single-state Gaussian IID model, a carry trade procedure as well as a buy-and-hold strategy.

A trend factor in commodity futures markets: Any economic gains from using information over investment horizons?

AbstractThis paper identifies a trend factor that exploits the short‐, intermediate‐, and long‐run moving averages of settlement prices in commodity futures markets. The trend factor generates statistically and economically large returns during the post‐financialization period 2004–2020. It outperforms the well‐known momentum factor by more than nine times the Sharpe ratio and has less downside risk. The trend factor cannot be explained by the existing factor models and is priced cross‐sectionally. Finally, we find that the trend factor is correlated with funding liquidity measured by the TED spread. Overall, the results indicate that there are significant economic gains from using the information on historical prices in commodity futures markets.

Does a Change in the TED Spread Impact Bank Stock Returns?

During the economic crisis of 2008, the global economic system came under tremendous stress due to unusually high activity in the risk spread and volatility in the financial asset valuation. The spread between the US T-bill rate and the London interbank offer rate (LIBOR), a proxy for perceived counterparty credit risk called the “TED spread,” also increased during the crisis period and impacted other economic variables. This study examines the impact of credit risk, as represented by the TED spread, on the daily returns of the ABAQ index, which represents community banks, and the KBW index, which represents the money center and other major banks. The findings, based on daily data from 2010–2020, are as follows: An increase in credit risk led to a decrease in returns for both community banks and money center banks; however, the significance of credit risk and its impact on the stock returns of community banks and money center banks diminished when controlled for other stock market movements. <b>Key Findings</b> ▪ The TED Spread is critical to investment valuation since it is an indicator of the price of money in the global banking system. ▪ As an indicator of the solvency of financial institutions, monetary liquidity, and perceived risk of the financial system, an increase in the TED spread impacts the daily returns of banks (community banks, money centers, and other major banks) negatively. ▪ An increase in the TED spread leads to the drying up of market liquidity that increases cost of funding and generates a negative reaction in the stock market. The study shows that stocks for both larger banks and community banks, while affected by the TED spread, are more impacted by general market movements.

The effect of financial, macroeconomic and sentimental factors on stock market volatility

The aim of this paper is to find economic factors that could be helpful in explaining the market’s shifts between periods of prosperity and crisis. The study took into account the main stock indices from developed markets of the USA, Germany and Great Britain, and from two emerging markets, i.e. Poland and Turkey. The analysis confirms the existence of two different states of volatility in these markets, namely the state with a positive returns’ mean and low volatility, and the state with a negative or insignificant mean and high volatility. The Markov-switching model with a dynamic probability matrix was applied in the study. The subject of the analysis was the impact of domestic and global factors, such as VIX and TED spread, oil prices, sentiment indices (ZEW), and macroeconomic indices (unemployment, longterm interest rate, CPI), on the probability of switching between the states. The authors concluded that in all the examined countries, changes in long-term interest rates have an influence on market returns. However, the direction of this impact is different for developed and emerging markets. As regards developed markets, high prices of oil, 10-year bonds, and the ZEW index can suggest a high probability of the countries remaining in the first state, whereas an increase in the VIX index and the TED spread significantly reduces the probability of staying in this state. The other studied factors proved to be rather local in nature.

How Vulnerable Are Financial Markets to COVID-19? A Comparative Study of the US and South Korea

In this study, we carry out a comparative analysis between the US and South Korea, with a special attention to three key areas, including the stock market, the currency market, and the bond market. By employing a composite model, VAR-GARCH-BEKK, we will attempt to capture both mean and volatility spillovers between the pandemic and financial markets, so as to explore the extent and ways in which the COVID-19 pandemic influences the financial sector. The empirical results provide substantial evidence in the following areas: (i) South Korea seems more vulnerable since all of its financial markets are seen to be statistically associated with the growth in infections. (ii) For the US, only the stock market is negatively impacted by the confirmed cases in terms of a conditional mean spillover model. (iii) According to the impulse response functions (IRFs), apart from the US dollar index, both the TED spread and stock returns respond significantly to innovations from the pandemic. (iv) There is little evidence to support the presence of volatility transmission from the pandemic to the financial markets in the two countries.

Leveraged Funds and the Shadow Cost of Leverage Constraints

ABSTRACTUsing the most comprehensive data set of leveraged funds known to the literature, we measure the market‐wide shadow cost of leverage constraints and examine its pricing implications. The shadow cost averages 0.53% per annum from 2006 to 2016, spikes upon quarter‐ends when banks face tighter capital requirements, positively predicts future betting‐against‐beta (BAB) returns, and negatively correlates with contemporaneous BAB returns. Stocks that experience lower returns when the shadow cost increases earn 0.85% more per month. Overall, our shadow cost measure fits the predictions of leverage‐constraint‐based theories better than the widely used TED spread.

Investigating the Impact of COVID-19 Outbreak On U.S. Stock Market

SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia a clear cause. The world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partial or totally lockdown. The objective of this study is to investigate the impact of COVID-19 on U.S stock market. The objective of this study is to investigate the impact of COVID-19 on U.S stock market. The author uses extreme bound analysis for market interpretation and sourced data from the Federal Reserve Economic Database (FRED) and Our World in Data COVID-19, from January 2 to November 16 2020.The results of the study show that, Foreign Exchange and Stringency Index are the only determinants of Stock Prices from Leamer EBA approach. Again, the normal model show that, Interest Rate, TED spread (i.e. the difference between the 3 months Treasury bill and the 3-month LIBOR based in U.S. dollars), Foreign Exchange, and Stringency Index are robust determinants of Stock Prices while the generic model highlights the importance of TED spread, Foreign Exchange, Stringency Index, Interest Rate. In addition, the correlation matrix show that, Bitcoin, Interest Rate, Foreign exchange and Gold Price have a Positive Impact on Stock Price while Stringency Index and the TED Spread has a negative significant relationship with stock prices.

Investigating the Impact of COVID-19 Outbreak On U.S. Bond and Commercial Paper Market

SARS-Cov-2 was first reported in Wuhan, a town in Hubei Province of China with a population of 11 million in December 2019, following an outbreak of non-pneumonia a clear cause. The virus has now spread across the globe to more than 200 countries and territories, and the world health organization (WHO) described it as a pandemic on 11 March 2020. On the economic front, COVID-19 has led more than 200 countries partial or totally lockdown, disrupted global supply chain, and induced a significant fall in both economic activity and financial asset prices. United States, being one of the highest country affected by the Virus with 80.9M Cases, 45.8M Infected, and 1.77M Deaths as at the 28th of December 2020. Recently vaccines have been developed but the contamination wave keeps on increasing every day. On the socioeconomic front, COVID-19 has led more than 200 countries into partial or total lockdown, disrupted global supply chains, and induced a fall in both economic activity and financial asset prices. The objective of this research is to investigate the impact of COVID-19 on U.S Bond and Commercial Paper Markets.The result show that, intercept, interest rate, TED spread and Total cases are the only determinants of Bond price because of the robust relationship between them. Meanwhile, normal model show that, Intercept, TED spread (i.e. the difference between the 3 months Treasury bill and the 3-month LIBOR based in U.S. dollars), Total Cases, Interest Rate, and Total Death are robust determinants of the prices of Treasury bill while the generic model highlights the importance of Interest Rate, Total Cases, Total COVID-19 Deaths cases.