Macro Finance Research Articles

Law and Macro Finance

Abstract This article makes the case for developing law and macro-finance as an integrated research field that explores the role of credit and its regulation within the economic cycle. It highlights the importance of macro-financial conditions, such as leverage and liquidity, over traditional concerns like agency costs and efficiency when assessing the economic impact of the law. The article argues that the future of law and macro-finance research should focus on demonstrating (1) how the law operates under different macro-financial conditions, (2) how the law can shape these conditions, and (3) how these conditions influence legal frameworks. This research is partly inspired by, and could also be valuable for, organizations like the World Bank and IMF, which increasingly acknowledge the role of debt in financial crises and are beginning to promote policies that help countries better align the size of their credit markets with their economic needs.

Decomposing the yield curve with linear regressions and survey information

The decomposition of bond yields into term premiums and average expected future short rates is impaired by the limited availability of information about the dynamics of the expectations component. Therefore, many studies require the model-implied average expected future short rates to be close to short rate expectations from surveys. In this paper, I restrict the variance of changes in model-implied average expected future short rates to match the variance of changes in short rate expectations from surveys. The variance of changes in survey expectations is relatively similar across markets and thus provides a reliable source of additional information about the expectation formation of investors. Technically, I impose a nonlinear restriction to the term structure model of Adrian, Crump, and Moench (2013). I show that typical small sample problems of term structure estimations can be mitigated if the restriction on the variance of changes is imposed. However, the analysis also makes a case for unrestricted estimations if they are based on a dataset with a typical sample length in macro finance.

Are bond returns predictable with real-time macro data?

We investigate the predictability of bond returns using real-time macro variables and consider the possibility of a nonlinear predictive relationship and the presence of weak factors. To address these issues, we propose a scaled sufficient forecasting (sSUFF) method and analyze its asymptotic properties. Using both the existing and the new method, we find empirically that real-time macro variables have significant forecasting power both in-sample and out-of-sample. Moreover, they generate sizable economic values, and their predictability is not spanned by the yield curve. We also observe that the forecasted bond returns are countercyclical, and the magnitude of predictability is stronger during economic recessions, which lends empirical support to well-known macro finance theories.

A Macro Finance Model for Proof-of-Stake Ethereum

A Macro Finance Model for Proof-of-Stake Ethereum

Learning Deep News Sentiment Representations for Macro Finance

Learning Deep News Sentiment Representations for Macro Finance

Law and macro finance of corporate debt: Managing the business cycle through bankruptcy

AbstractThis article proposes that, as a matter of policy, the bankruptcy law protections of creditors offering to lend money to large firms in a boom should be weaker than those of creditors offering to lend to such firms in a bust. The policy goals of bankruptcy law under this proposal, inspired by the theoretical framework for Law and Macro Finance, are to curb booms, mitigate the effects of booms gone bust, and protect the productive capacity of the economy in the long term. Bankruptcy courts play a central role in the implementation of this framework. This article discusses examples of legal doctrines the courts could employ for that purpose, such as deepening insolvency and equitable subordination. The courts' role in the countercyclical management of creditor expectations concerning recoveries distinguishes the Law and Macro Finance framework for corporate debt from the more conventional Law and Finance framework. Under the Law and Finance framework, the primary policy objective of bankruptcy courts is to maximise creditor recoveries. Under the Law and Macro Finance framework, that objective is to help manage creditors' expectations concerning recoveries across the credit cycle.

Predictability and the Cross-Section of Expected Returns: A Challenge for Asset Pricing Models

Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected returns by sorting stocks based on the sensitivity of expected returns to these quantities. Models with only one uncertainty-related state variable, like the habit model or the long-run risks model, cannot pass this test. However, even extensions with more state variables mostly fail. We derive conditions under which models would be able to produce expected return patterns in line with the data and discuss various examples. This paper was accepted by David Simchi-Levi, finance.

The evolution of financial intermediary theory and the redesign of undergraduate finance course content system

The new situation of the development of the financial system after the global financial crisis has put forward new requirements for innovation in the traditional macro finance curriculum system. This paper combs the historical process of the integration of financial and macroeconomic analysis from the perspective of the history of economic analysis, pointing out that the traditional financial course content system lags behind the development of modern economic and financial systems and financial theory, and proposes to optimize traditional financial courses system to strengthen the content construction of macro finance courses.

Decomposing the Yield Curve with Linear Regressions and Survey Information

The decomposition of bond yields into term premiums and average expected future short rates is impaired by the limited availability of information about the dynamics of the expectations component. Therefore, many studies require the model-implied average expected future short rates to be close to short rate expectations from surveys. In this paper, I restrict the variance of changes in model-implied average expected future short rates to match the variance of changes in short rate expectations from surveys. The variance of changes in survey expectations is relatively similar across markets and thus provides a reliable source of additional information about the expectation formation of investors. Technically, I impose a nonlinear restriction to the term structure model of Adrian, Crump, and Moench (2013). I show that typical small sample problems of term structure estimations can be mitigated if the restriction on the variance of changes is imposed. However, the analysis also makes a case for unrestricted estimations if they are based on a dataset with a typical sample length in macro finance, though.

The Money Study Group (MSG) at fifty: Twenty years of the MSG and another thirty of the Money, Macro, Finance Research Group (MMF)

AbstractWe discuss the origins of the Money Study Group in 1969 and its subsequent journey via the Money Macro Finance Study Group to become the Money Macro and Finance Society. It has provided a forum for debates on macroeconomics and monetary policy and has expanded to incorporate other aspects of finance. Its activities have successfully brought together academics, policy makers and city practitioners.

Mixed-Frequency Macro–Finance Factor Models: Theory and Applications*

Abstract This article presents tests for the existence of common factors spanning two large panels/groups of macroeconomic and financial variables, and the estimation of common and group-specific factors. New analytical results are derived regarding (i) the difference in the asymptotic distribution of the test statistics when aggregating the data first and then extracting the principal components (PCs), or vice versa, as well as (ii) the estimation of the common factor and its asymptotic distribution, extending the work of Andreou et al. (2019). We find that although there is no empirical evidence for one common factor, with constant loadings, in the United States during the period 1963–2017, there is evidence of one common macro–finance factor during the pre- and post-Great Moderation regimes. The aforementioned approaches of estimating PCs yield almost identical common and group-specific (financial and macro) factors which turn out to be significant in predicting key economic indicators, such as real Gross Domestic Product (GDP) growth and the CBOE Volatility Index, among others.

Macro, Finance, and Macro Finance: Solving Nonlinear Models in Continuous Time with Machine Learning

This paper proposes a global algorithm to solve a large class of nonlinear continuous-time models in finance and economics. Using tools from machine learning, I recast problem of solving the corresponding nonlinear partial differential equations as a sequence of supervised learning problems. To illustrate the scope of the method, I solve nontrivial benchmark models and compare the numerical solution with the analytical ones. Furthermore, I propose a setting to test and evaluate solution methods. In the context of a neoclassical growth model, given any value function, the productivity function is reverse engineered so that the Hamilton-Jacobi-Bellman equation corresponding to the optimization problem is identically zero. This provides a testing ground for solution methods and an objective way of comparing them. Results indicate that the method is accurate and can handle nonlinear models with as many as 10 dimensions. Finally, I provide an open source library that implements the proposed algorithm.

Pricing Strategies and Implementation Promotion Strategies to Improve Customer Loyalty

This study aims to analyze pricing and promote strategies to increase customer loyalty of sharia banks in Kudus, Central Java, Indonesia. This research method using qualitative and quantitative approach. The data used is time series data. The population of this study are customers who actively transact in Islamic banks in Kudus. Sampling technique using non probability sampling with accidental type of sampling. So the number of respondents needed in this research is a number of 100 active bank customers. The analytical method uses correlational descriptive analysis using Structural Equation Modeling (SEM), correlational assumption test and classical assumption test using AMOS 20 software. The result of this research explains that price and promotion contribute to increase customer and product loyalty which can become empirical variable. This proves that Sharia Bank is expected to have a special strategy to increase customer loyalty. How to increase loyalty in addition to improving the quality of Islamic banking products such as murobahah, musyarokah and mudharobah is to improve the characteristics of macro and Sharia micro finance institutions. This is because the excess of syariah bank products has never been found in conventional financial institutions in Indonesia.

Real Time Macro Factors in Bond Risk Premium

We examine whether bond returns are predicted by real-time macro variables with possible nonlinear predictive relationship and possible presence of weak factors. We propose a scaled sufficient forecasting method to deal with the issues arising from these two features, and study its asymptotic properties. Applying both existing and our new methods, we find that real-time macro variables have significant in- and out-of-sample forecasting power, generate sizeable economic values, and their predictability is not spanned by the yield curve. We also find that the forecasted bond returns are countercycilcal and the magnitude of predictability is stronger in economic recessions, thereby lending empirical support to well-known macro finance theories.

A STUDY OF AGRICULTURAL FINANCE IN INDIA

India is a country of villages, and agriculture has been a major source of employment and livelihood for nearly 70% of its population since independence. Subsequent five-year plans have placed a strong emphasis on agriculture and the growth of the sector. For rural poverty to be reduced, agricultural expansion is essential. Due to the high quantity of money required at every level and the need for careful planning to earn that money as well, the financial sector is regarded as one of the riskiest businesses. Agricultural financing, which enables farmers to carry out activities smoothly and without any obstacles, requires long-term planning, which is actively encouraged by the Indian banking sector. At both the local and macro levels, agricultural finance was investigated. For agriculture to reach its full potential as a lucrative endeavor, access to institutional finance for farmers as well as the proper quantity and quality of agricultural credit are essential. Together, co-operatives and commercial banks are unable to get rid of money lenders and local bankers who are providing loans at exorbitant rates. Yet, the commercial banks' loans to the agricultural sector have helped farmers cut back on borrowing from non-institutional sources. Macro finance deals with various methods of financing the agriculture industry. It is also involved in the lending process, laws, rules, oversight, and control over numerous agricultural credit institutions. As a result, agriculture is supported at the group level by macro-finance. The study of how credit provides funding and liquidity to farm debtors is known as agricultural financing. It is also referred to as the study of financial intermediaries that lend money to farmers and the financial markets where these intermediaries buy the money they lend out. The research article examines the financial and liquidity services that credit offers agricultural borrowers. It is also regarded as a study of the financial intermediaries that lend money to the agricultural industry as well as the financial markets where these intermediaries receive the loanable capital they need. The NABARD annual report is where the study's necessary data, which is primarily secondary in nature, is gathered.

Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach

We study inference for the local innovations of It\^o semimartingales. Specifically, we construct a resampling procedure for the empirical CDF of high-frequency innovations that have been standardized using a nonparametric estimate of its stochastic scale (volatility) and truncated to rid the effect of ``large jumps. Our locally dependent wild bootstrap (LDWB) accommodate issues related to the stochastic scale and jumps as well as account for a special block-wise dependence structure induced by sampling errors. We show that the LDWB replicates first and second-order limit theory from the usual empirical process and the stochastic scale estimate, respectively, as well as an asymptotic bias. Moreover, we design the LDWB sufficiently general to establish asymptotic equivalence between it and and a nonparametric local block bootstrap, also introduced here, up to second-order distribution theory. Finally, we introduce LDWB-aided Kolmogorov-Smirnov tests for local Gaussianity as well as local von-Mises statistics, with and without bootstrap inference, and establish their asymptotic validity using the second-order distribution theory. The finite sample performance of CLT and LDWB-aided local Gaussianity tests are assessed in a simulation study as well as two empirical applications. Whereas the CLT test is oversized, even in large samples, the size of the LDWB tests is accurate, even in small samples. The empirical analysis verifies this pattern, in addition to providing new insights about the distributional properties of equity indices, commodities, exchange rates and popular macro finance variables.

Quantitative wave model of macro-finance

This paper presents macro-finance as ensemble of economic agents and suggests use risk ratings of economic agents as their coordinates on economic space. Financial variables of separate economic agents are defined as functions of time and coordinates on economic space. Aggregations of financial variables of separate economic agents with coordinates near point x on economic space define macro-financial variables as function of x. Hydrodynamic-like equations describe evolution and mutual dependence between macro-financial variables. As example, for simple model of mutual dependence between macro-financial Demand on Investment and Interest Rate we derive hydrodynamic-like equations in a closed form. Perturbations of macro financial variables can generate waves those propagate on economic space and we derive wave equations. Macro financial waves can propagate on economic space with exponential growth of amplitudes and cause time fluctuations of finance variables that may model financial and business cycles. Variety of macro financial waves on economic space gives new look on internal dynamics of macro finance and reveals hidden complexity of macro financial modeling and forecasting.

Financial Contracting As Behavior Towards Risk: The Corporate Finance of Business Cycles

This paper describes an equilibrium macro finance model where contracts are the mechanism by which differentially risk averse bondholders and stockholders resolve a conflict of interest problem and confront the risks associated with future operating decisions and financing decisions of a representative firm/economy. In resolving this conflict of interest problem the interrelated covenants in the financial contract shape certain stylized financial facts of business cycles ignored in Classical and Keynesian models. The model set-up includes 2 agents (bondholders and stockholders); 2 decisions (production-investment decisions generating operating income and operating risk) and (financial decisions generating financial risk); and 2 no-arbitrage equilibrium conditions (market value equals economic book value for both bonds and stocks). In this 2x2x2 set-up contract constrained managers of the representative firm make production-investment decisions that conform to the risk aversion of stockholders as reflected in stock prices, and then use financing decisions to offset any effect of a change in operating risk on the market valuation of bonds. In this model managers work for both stockholders and bondholders. Preliminary evidence from the U.S. non-financial corporate sector does not reject the predictions of the model. A similar form of risk and return sharing is shown to occur between more risk averse mature and experienced workers with seniority and less risk averse young apprentice workers.

External Financing and Customer Capital: A Financial Theory of Markups

We propose a dynamic structural corporate model in which firms face imperfect capital markets and frictional product markets. We highlight the importance of the endogeneity of firms' short-term cash flows and the endogeneity of the marginal value of liquidity in determining the interactions between investment, financing and product price setting decisions. Our primary goal is to develop a financial theory of markups to advance the understanding of two related questions in Macro Finance. One is how financial frictions affect firms' markups, and the other is how nominal frictions impact managers' financial decisions and firms' values. The model implies several testable predictions: (1) financially constrained firms are more inclined to increase their desired markups of products; (2) firms facing larger price stickiness tend to issue less external equity and conduct less big payouts; (3) a large part of the cost from price stickiness is induced by financial frictions; and (4) the impact of price stickiness on firms' investment ratios is ambiguous, due to the countervailing forces of precautionary cash holdings and the change in the cost of capital.

Truth and Robustness in Cross-Country Law and Finance Regressions: A Bayesian Analysis of Empirical 'Law Matters' Thesis

This paper applies a Bayesian model averaging algorithm to systematically evaluate the “law matters” literature and finds that the positive cross-country relationship between anti-self-dealing rules and stock market development proposed by Djankov, La Porta, Lopez-de-Silanes, and Sheifer (2008, Journal of Financial Economics 88: 430-465) is fragile. In contrast, proxies for information disclosure, political power of incumbents and economic development are found to have strong predictive power for stock market outcome variables. Finally, variant sets of variables are shown to predict stock market development, which rejects the “one-size-fits-all” specification employed in previous macro law and finance studies.