The Central Bank Shift to Market Maker of Last Resort: The Unintended Consequences of Unconventional Monetary Policies

We analyze the transition of central banks from lenders to market makers of last resort. The adoption of unconventional monetary policies characterizes this transition. In their new role as market makers, central banks engage in the latter by extending and reinforcing interventions in other markets than the traditional bank reserves market. We then explain that the difference between the two roles is one of degree rather than kind. In both cases, the prevention of liquidity shortages is a primary concern. As conventional policies become inadequate, central banks resort to unconventional policies to escape a general liquidity shortage at the zero lower bound. However, these unconventional policies do not solve the structural problems in financial and real markets. Both conventional and unconventional monetary policies cause price distortions, in particular on asset markets. The policies of the market maker of last resort prevent necessary readjustments of cyclical divergences between real and financial markets.

On the Safe-Haven Ability of Bitcoin, Gold, and Commodities for International Stock Markets: Evidence from Spillover Index Analysis

Stock market is susceptible to various external shocks for its tight dependence on economic fundamentals, financial speculation, and fragile emotions in massive traders, making it a very risky market for investors. In this paper, we aim to identify whether commonly recognized safe-haven assets, that is, bitcoin, gold, and commodities, can provide investors with effective hedging utility in international stock markets, especially during periods of extreme market turbulence. By using the spillover index method based on the TVP-VAR model, we find that firstly, bitcoin, gold, and commodities can only offer weak hedging effects on stock markets. Furthermore, their abilities to act as a safe haven are ranked as: commodities > gold > bitcoin. Secondly, in general, we have observed the increasing hedging ability of these safe-haven assets in times of extreme market turmoil. Thirdly, among international stock and safe-haven asset markets, the world and the developed stock markets act as the net spillover transmitters, while bitcoin, gold, and commodities are the net recipients. Lastly, the total spillover effects are time-varying and increase significantly after the outbreak of extreme events.

Does Momentum Trading Generate Extra Downside Risk?

Momentum strategies tend to provide low returns during market crashes, and they crash themselves when the market rebounds after significant crashes. This is reflected by positive downside market betas and negative upside market betas of zero-cost momentum portfolios. Such asymmetry in upside and downside risks is unfavorable for investors and requires a risk premium. It arises mechanically because of momentum portfolio rebalancing based on trailing asset performance. The asymmetry in upside and downside risks is a robust unifying feature of momentum portfolios in various geographical and asset markets. The momentum premium can be rationalized within a standard asset-pricing framework, where upside and downside risks are priced differently.

Leaning against the Bubble: Central Bank Intervention in Walrasian Asset Markets

The paper presents a two-period Walrasian financial market model composed of informed and uninformed rational investors, and noise traders. The rational investors maximize second period consumption utility from the payoffs of trading risk-free holdings to risky assets in the first period. The central bank reacts directly to asset price movements by selling or buying assets to stabilize the market price. It is found that the intervention makes the risky asset’s market price per share less sensitive to information shocks, which presses the market price towards its average price thus reducing price variance. The informed investors’ prediction coefficient remains unaffected, but that of the uninformed investors is magnified, which cancels out the negative effect on shock sensitivity thus keeping the expected value of the risky asset’s dividend constant. Finally, the introduction of the policy rule does not affect rational investors’ risk per share. A general conclusion is that the central bank’s policy can be regarded as an effective automatic stabilizer of financial markets.

Trade and Resource Sustainability with Asset Markets

Trade changes incentives to protect an open-access natural resource independently of its effect on the resource price. General equilibrium linkages cause resource policy to affect the price of privately owned assets regardless of whether they are used in the resource sector. In the closed economy, the asset market in our overlapping generations setting creates incentives for currently living agents to protect the natural resource. The interplay of the asset market and general equilibrium effects causes trade to reverse these incentives. Trade liberalization and the establishment of formal property rights are policy complements: the former makes the latter more important.

Interdependence dynamics of corporate equity and public real estate markets

PurposeWith growing interdependence between financial markets, the goal of this paper is to examine the dynamic interdependence between corporate equity and public real estate markets for the USA and a select group of seven European developed economies under a cross-country framework in crisis and boom market conditions. Dynamic interdependence is related to four measures of market linkages of “correlation, spillover, connectedness and causality”.Design/methodology/approachThis study adopts a four-step investigation. The authors first estimate “time-varying variance–covariance spillovers and implied correlations” modeled with the bivariate BEKK-MGARCH methods. Second, the methods of Diebold and Yilmaz (2012, 2014) measure the conditional volatility spillover-connectedness effects across the corporate equity and public real estate markets based on a decomposition of the forecast error variance. Third, the authors implement nonlinear bivariate and multivariate causality tests to understand the lead-lag dynamics of the two asset markets' returns, volatilities and net directional volatility connectedness across different sample periods. Finally, the authors conclude the study by providing a portfolio hedging analysis.FindingsThe authors find that corporate equity and public real estate are moderately interdependent to the extent that their diversification benefits increases in the longer term. Moreover, the authors find increased corporate equity-public real estate causal dependence of the market groups of the European and international portfolios during the GFC and INTERCRISIS periods. The nonlinear causality test findings indicate that the joint information of asset markets can be a useful source of prediction for future innovation of market risks. Additionally, policy makers may also be able to employ conditional volatility and volatility connectedness as two other measures to manage market stability in the cross-asset market dependence during highly volatile periods.Research limitations/implicationsOne major take away from this academic research is since international portfolio investors are not only concerned the long-term price relationship but also the correlation structure and volatility spillover-connectedness, the conditional BEKK modeling, generalized risk connectedness analysis and nonlinear causal dependence explorations from this multi-country study can shed fresh light on the nature of market interdependence and magnitude of volatility connectedness effects in a multi-portfolio framework.Practical implicationsThe hedging performance analysis for portfolio diversification and risk management indicates that industrial stocks (“pure” equities) are valuable assets that can improve the hedging performance of a well-diversified corporate equity-public real estate portfolio during crisis periods. For policymakers, the findings provide important information about the nature of causal links and predictability during the crisis and asset-market boom periods. They can then equip with this information to manage and coordinate market stability in cross corporate equity-real estate relationships effectively.Originality/valueAlthough traditional research has in general reported at least a moderate degree of relationship between the two asset markets, investors' knowledge of stock-public real estate market linkage is somewhat inadequate and confine mostly to broad stocks (i.e. stocks that are exposed to public real estate influence) in a single-country context. In this paper, the authors examine the interdependence dynamics in a multi-country (multi-portfolio) context. A clear understanding their changing market relationships in a multi-country context is of crucial importance for portfolio investors, financial institutions and policy makers. Moreover, since the authors use an orthogonal stock market index, the authors allow global investors to understand the potential diversification benefits from stock markets that are beyond the public real estate market under different market conditions.

Long-Term Finance and Investment with Frictional Asset Markets

Trading frictions in financial markets affect more long-term than short-term bonds, generating an upward-sloping yield curve. Long-term financing is more expensive in economies with higher trading frictions so firms choose to borrow and invest in shorter horizons and lower productivity projects. The theory guides a new identification of the slope of liquidity spread in the data. We measure and calibrate the model for the United States, and counterfactual exercises suggest that variations in trading frictions can have significant effects on maturity choices and investment. A policy intervention improves liquidity, reduces long-term financial costs, and promotes investment in longer-term projects. (JEL E43, E44, E52, G12, G21, G32, O16)

Common risk factors in the returns on digital assets: evidence from cryptocurrency market

Introduction. Digital financial assets are a relatively new phenomenon. More and more, they include virtual currencies, and in particular cryptocurrencies. Both regulators and financial market players are becoming increasingly interested in such assets. Cryptocurrencies have no intrinsic value, and this encourages scientific studies on the problem of price formation and risk management associated with cryptocurrency operations. Most papers on the problem lack a systematic ap-proach and do not provide solutions to a large number of fundamental issues. Purpose. The purpose of our study was to develop a method for the risk analysis of operations with digital financial assets, namely cryptocurrencies. Methodology. In our study, we used parametric methods of data analysis and ma-chine learning methods, description, analysis, synthesis, induction, deduction, comparison, and grouping method. The sample was accumulated between April 2013 and April 2021 and included cryptocurrencies with the market capitalization of over 1 million USD. Results. The study determined the common risk factors for the cryptocurrency market. The risk factors are presented as linear combinations of returns of subsets of cryptocurrencies with dynamically changing weight coefficients. The risk factors were formed based on the market information, which included the price of the cryptocurrency, the trading volume, and its market capitalization. Conclusions. The study demonstrated that the cryptocurrency market is suscepti-ble to market anomalies common to traditional financial asset markets. In addition to the risk factors based on the market capitalization of cryptocurrencies (the size) and their aggregate profitability (the momentum), the article presents statistically relevant risk factors which reflect the growth rate of the market capitalization and the level of illiquidity of cryptocurrencies. In order to explain the market anomalies and the arbitrary strategies based on them, the article presents several factor models of cryptocurrency price formation. These models can be used to develop an in-tegrated approach to the risks associated with operations with digital financial as-sets.