Market Regimes Research Articles

Can welfare and labour market regimes explain cross‐country differences in the unemployment of young people?

AbstractNo single institution can reduce (long‐term) youth unemployment. Welfare and labour market institutions function as “bundles”, through multiple inter‐institutional synergies. Based on a focused literature review for theory and on cluster analysis for empirics, the author identifies five such regimes across the EU‐27 and estimates their effects on the youth unemployment ratio and on long‐term youth unemployment. The most helpful institutional arrangement for young people in the labour market would be a combination of strong dual apprenticeship embedded in a corporatist labour market regime with high levels of social security, active labour market policy, and spending on education and childcare.

Semiparametric Dynamic Max-Copula Model for Multivariate Time Series

SummaryThe paper presents a novel non-linear framework for the construction of flexible multivariate dependence structure (i.e. copulas) from existing copulas based on a straightforward ‘pairwise max-’rule. The newly constructed max-copula has a closed form and has strong interpretability. Compared with the classical ‘linear symmetric’ mixture copula, the max-copula can be viewed as a ‘non-linear asymmetric’ framework. It is capable of modelling asymmetric dependence and joint tail behaviour while also offering good performance in non-extremal behaviour modelling. Max-copulas that are based on single-factor and block factor models are developed to offer parsimonious modelling for structured dependence, especially in high dimensional applications. Combined with semiparametric time series models, the max-copula can be used to develop flexible and accurate models for multivariate time series. A new semiparametric composite maximum likelihood method is proposed for parameter estimation, where the consistency and asymptotic normality of estimators are established. The flexibility of the max-copula and the accuracy of the proposed estimation procedure are illustrated through extensive numerical experiments. Real data applications in value-at-risk estimation and portfolio optimization for financial risk management demonstrate the max-copula's promising ability to capture accurately joint movements of high dimensional multivariate stock returns under both normal and crisis regimes of the financial market.

Государственные закупки в условиях Евразийского экономического союза

The realization of the goals of the Eurasian economic Union is closely connected with the formation of common markets in various areas of economic cooperation. One of these areas are public procurement, which can have a significant impact on mutual trade between the member States in the framework of the functioning of the internal market of the Eurasian economic Union. To date, however, this effect is not significant. Prerequisites for this are the numerous “barriers”, “withdrawal” and “restrictions” that remain in the legislation of member States of the Eurasian economic Union, which requires its identify and resolve.
 The purpose of this study was to identify obstacles to the formation of a single public procurement market in the Eurasian economic Union. The objective of the study is the analysis of legal regulation of public procurement in member States of the Eurasian economic Union and the Eurasian economic Union with the aim of identifying the existing “barriers”, “withdrawal” and “limitations” in this field.
 To achieve the goals and objectives of the study are applied comparative legal, formal legal and formal logical methods, method of interpretation of law, as well as scientific methods.
 The results of the study identified obstacles to providing a high level of cross-border participation in public procurement. Revealed that the provision of unhindered access for potential suppliers and providers of member States to participate in public procurement is in direct proportion to ensure the regime of the single market for services in various service sectors. It is concluded that a necessary condition for the formation of a single market of public procurement is not only elimination of the existing “barriers”, “exceptions” and “limits” in the laws of the member States of the Eurasian economic Union, but also the completion of the process of building a single market for services, the further rapprochement of licensing systems, harmonization of mandatory rules and requirements in the member States of the Eurasian economic Union.

Deep finance: sovereign debt crises and the secondary market ‘fix’

Links between ballooning national debts and official aid conditionalities are well understood. Private sovereign debt markets, in contrast, have been largely overlooked outside mainstream economics. Yet, since the 1980s, a ‘secondary market regime’ in sovereign bonds has transformed financial geographies and legal practices, facilitating the build-up of riskier sovereign debts and strengthening specialized distressed debt investors. This secondary market ‘fix’ has enabled the international financial system to muddle through successive crises. Using the recently concluded Argentine debt saga as an example, I show how the secondary market regime’s effects on debtors are intertwined with, but distinct from, those of structural adjustment programmes; in cases of resistance to neoliberalism, ‘deep’ secondary market debt structures serve to push countries (back) into the neoliberal fold.

How Smart Beta Strategies Work in the Hong Kong Market

Factor-based investing shares some common characteristics with passive investing such as rules-based construction, transparency, and cost-efficiency, and it also shares features of active investing in that it aims to enhance return and reduce risk compared to market-cap-weighted indices. In this paper, we examined the effectiveness of six well-known factors including size, value, low volatility, momentum, quality, and dividend in the Hong Kong equity market, their investability in practice, as well as the behavior of these factors under different market regimes from June 30, 2006, to June 30, 2017.

A Proposed Risk Modeling Shift from the Approach of Stochastic Differential Equation towards Machine Learning Clustering: Illustration with the Concepts of Anticipative & Responsible VaR

The aim of this technical document is threefold with the bigger picture being to contribute, within the challenging regulatory environment, to bring closer together traditional conflicting practices such as trading vs risk as well as risk responsiveness vs stability. In order to achieve this goal, we first expose some of the complexity associated to the risk factors and arbitrage constraints associated with the options and the high frequency markets by re-introducing the Implied Volatility Parametrization (IVP), and the High Frequency Trading Ecosystem (HFTE). The exposed complexity is then contrasted with the current obsolete Risk Methodologies which are based on simplistic SDEs which we extent using the Cointelation model in order to partially address some of the complexity introduced by the challenging regulatory environment such as scenario coherence. We then present a simple Machine Learning clustering methodology which is designed to address and mirror the enhancements of these SDEs in a simpler fashion. We illustrate our findings by introducing few new risk concepts such as the Anticipatible VaR which aims at being a leading as opposed to a lagging (Responsive) risk measure to a market regime change.

Anaerobic Digestion of Feedstock Grown on Marginal Land: Break-Even Electricity Prices

Marginal farm land is land characterised by low food, feed and fodder crop productivity due to soil and environmental limitations. Such land may however be utilised for bio-energy crop production. We investigate the economic viability of small scale combined heat and power anaerobic digestion (CHP AD) projects based on feedstock from farm waste and bio-energy crops grown on a representative temperate latitude marginal farm land in the UK. Using a realistic set of five project feedstock-mix scenarios, and considering standard technology and current market and policy regimes, we deploy a stochastic framework to assess prices of electricity required for these projects to break-even and conduct sensitivity analyses of key project parameters. Accounting for the current market prices and policy tariffs for heat, we find that critical electricity sale prices of about 17.46 p/kWh to 27.12 p/kWh are needed for the projects to break even. These prices are well above the current combined feed-in-tariff support and market prices for electricity over the past years in the UK. We conclude that the use of marginal land to generate power for export using small-scale CHP AD in the UK and the wider temperate latitude countries is unviable, if energy and farming policy regimes do not provide substantial support.

When Do Commodity Spot Price Regimes Matter for Inventory Managers?

An increasing number of firms buy commodities at spot markets characterized by price volatility. Due to different market regimes (e.g., bull and bear), spot price dynamics are non-stationary and only partially observable; neither the underlying stochastic price process, nor its parameters are known with certainty. To capture uncertainty in both price and price model, we exploit recent spot price observations to dynamically update (learning) probabilistic price regime information in the context of inventory control under stochastic demand and purchase price. By means of Bayesian dynamic programming, we prove that, if prices evolve according to doubly embedded stochastic processes described by hidden Markov regime switching (MRS) models, price(s)- and regime-belief-dependent (prior respectively posterior) base-stock policies, rather than price-dependent policies, are optimal. We distinguish between independent and Markovian price processes and demonstrate the difference concerning optimal base-stock functions and monotonicity properties. We numerically establish that ignoring regime shifts leads to suboptimal inventory decisions and we quantify the operational value of spot price models. We find that Bayesian regime belief updates (learning) can yield significant cost savings that are particularly high when demand volatility and inventory holding cost are low and regime persistence is high. However, in empirical environments, stochastic price models induce misleading speculation resulting in misspeculative inventory. Based on real spot market data, we show that price forecast accuracy and operational performance are not perfectly correlated and that it can be advantageous for inventory managers to ignore sophisticated price forecasting and instead follow a naive strategy.

Modeling regime‐dependent agricultural commodity price volatilities

AbstractIn stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.

Dynamic portfolio optimization across hidden market regimes

Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational advantages to using MPC when estimates of future returns are updated every time a new observation becomes available, since the optimal control actions are reconsidered anyway. MPC outperforms a static decision rule for changing the allocation and realizes both a higher return and a significantly lower risk than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces the number of trades is found to increase the robustness of the approach.

Strategic Delegation and International Permit Markets: Why Linking May Fail

We analyse a principal-agent relationship in the context of international climate policy. Principals in two countries first decide whether to merge domestic emission permit markets to an international market, then delegate the domestic permit supply to an agent. We find that principals select agents caring less for environmental damages than they do themselves in case of an international market regime, while they opt for self-representation in case of domestic markets. This strategic delegation incentive renders the linking of permit markets less attractive and constitutes a novel explanation for the reluctance to establish non-cooperative international permit markets.

Hedge ratio on Markov regime-switching diagonal Bekk–Garch model

China's stock market is known with quick change and violent fluctuation in recent years. This paper develops a Markov regime switching diagonal Bekk–Garch model, enabling parameters to be state dependent upon the regime of market. The empirical results show that different states exist. The high volatility regime has a lower state probability, while the low volatility regime has a higher state probability. The likelihood value show the regime-switching diagonal Bekk–Garch model fits the sample better. Both comparisons of hedge performance in and out-of-sample indicate that a regime-switching Bekk–Garch model is the optimal hedge strategy, followed by Bekk–Garch and OLS model.

Equity index variance: Evidence from flexible parametric jump–diffusion models

This paper analyzes a wide range of flexible drift and diffusion specifications of stochastic-volatility jump-diffusion models for daily S&P 500 index returns. We find that model performance is driven almost exclusively by the specification of the diffusion component whereas the drift specifications is of second-order importance. Further, the variance dynamics of non-affine models resemble popular non-parametric high-frequency estimates of variance, and their outperformance is mainly accumulated during turbulent market regimes. Finally, we show that jump diffusion models yield more reliable estimates for the expected return of variance swap contracts.

Fluid-Model-Based Car Routing for Modern Ridesharing Systems

We consider a closed queueing network model of ridesharing systems such as Didi Chuxing, Lyft, and Uber. We focus on empty-car routing, a mechanism by which we control car flow in the network to optimize system-wide utility functions, e.g. the availability of empty cars when a passenger arrives. We establish both process-level and steady-state convergence of the queueing network to a fluid limit in a large market regime where demand for rides and supply of cars tend to infinity, and use this limit to study a fluid-based optimization problem. We prove that the optimal network utility obtained from the fluid-based optimization is an upper bound on the utility in the finite car system for any routing policy, both static and dynamic, under which the closed queueing network has a stationary distribution. This upper bound is achieved asymptotically under the fluid-based optimal routing policy. Simulation results with real-word data released by Didi Chuxing demonstrate that the utility under the fluid-based optimal routing policy converges to the upper bound with a rate of 1/√N, where N is the number of cars in the network.

Investigating Dairy Farmers′ Resilience under a Transforming Policy and a Market Regime: The Case of North Karelia, Finland

Abstract The European dairy sector is currently facing unprecedented challenges under a transforming policy and a market regime. The expected changes will have relevant consequences for land use, the landscape, and the environment in rural areas dominated by dairy farming. Within this context, the aim of this paper is twofold. First, key characteristics of milk production in the region of North Karelia will be illustrated. Secondly, some light will be shed on dairy farmers′ challenges and adaptations to the dairy sector’s structural changes, and to what extent they contribute to the resilience of agricultural systems. In the light of an evident milk crisis, the findings suggest that farmers′ key challenge is the profitability of running a dairy enterprise. One of the consequences of the poor economic situation is the pressure to make investments in the conditions of a constantly changing policy. Flexibility and the ability to understand future trends are fundamental in adapting to socio-economic changes and unpredictability. Adaptation to unpredictability would not be possible without a key characteristic of farming activity: agriculture is not only a source of an income, but also a way of life, a sense of belonging to the land that significantly affects farmers′ decision-making.

Framework for evolving spectrum management regimes: Lessons from India

India has seen a marked change in spectrum policy over the past decade from a legacy administrative regime to a more market oriented one wherein it has adopted auctions in the primary market, trading in the secondary market and has liberalised spectrum to make it technology and service neutral. It has faced numerous challenges, constraints, and legacy issues in its transition, thus providing a rich context for analysis. Using the case study of India, we developed a framework that highlights the various dimensions to be considered while migrating from an administrative to a market regime for spectrum management. The framework also helps to assess the current orientation of a spectrum policy regime and provides a direction for adopting a higher market orientation. We used the framework in the Indian context to show that while India had adopted market mechanisms, it had a low level of market orientation.

Keeping Up Appearances: The British Public Policy Response to the Trafficking of Domestic Workers in a Changing Regime of Social Protection

ABSTRACTThe UK domestic work industry is expanding. Private arrangements with domestic workers are growing in a setting where the cost of social care is progressively passed on from the state to the family. Yet domestic workers are increasingly unprotected despite the legislative and policy apparatus that British governments developed over the last decade to tackle human trafficking. Drawing on case law and empirical data, this article indicates how the welfare, migration, and labor market regime regulating social protection in the UK structures an environment of labor exploitation, which prevents authorities from tackling phenomena of exploitation and trafficking.

The perforated borders of labour migration and the formal state

PurposeThe purpose of this paper is to explore the variation in migrant labour market regimes and what these reveal about variant patterns of state and extra state regulation in two contemporary political economies.Design/methodology/approachResearch based upon a participatory action research agenda in Mexico and the north of Ireland. Migrant workers and their families where involved in the project and its development. This included participation in the research design, its focus and purpose.FindingsMigrant workers experiences of labour market subordination are part of wider processes of subordination and exclusion involving both the state, but also wider, often meta- and para-state, agents. In different locations, states and contexts, the precarity experienced by migrant workers and their families highlights the porosity of the formal rational legal state and moreover, in the current economic context, the compatibility of illegality and state sponsored neoliberal economic policies.Research limitations/implicationsIt is important to extend this study to other geographic and political economy spaces.Practical implicationsThe study challenges the limits of state agency suggesting the need for extra state, i.e. civil society, participation to support and defend migrant workers.Originality/valueNotwithstanding the two very different socio-economic contexts, the paper reveals that the interaction, dependence and restructuring of migrant labour markets can be understood within the context of meta- and para-state activities that link neoliberal employment insecurities. Migrants’ experiences illustrate the extent to which even formal legal employment relations can also be sustained by para- and meta- (illegal and alegal) actions and institutions.

Pricing and capacity provision in electricity markets: an experimental study

The creation of adequate investment incentives has been of great concern in the restructuring of the electricity sector. However, to achieve this, regulators have applied different market designs across countries and regions. In this paper we employ laboratory methods to explore the relationship between market design, capacity provision and pricing in electricity markets. Subjects act as firms, choosing their generation capacity and competing in uniform price auction markets. We compare three regulatory designs: (1) a baseline price cap system that restricts scarcity rents, (2) a price spike regime that effectively lifts these restrictions, and (3) a capacity market that directly rewards the provision of capacity. Restricting price spikes leads to underinvestment. In line with the regulatory intention both alternative designs lead to sufficient investment albeit at the cost of higher energy prices during peak periods and substantial capacity payments in the capacity market regime. To some extent these results confirm theoretical expectations. However, we also find lower than predicted spot market prices as sellers compete relatively intensely in capacities and prices, and the capacity markets are less competitive than predicted.

Can volume predict Bitcoin returns and volatility? A quantiles-based approach

Prior studies on the price formation in the Bitcoin market consider the role of Bitcoin transactions at the conditional mean of the returns distribution. This study employs in contrast a non-parametric causality-in-quantiles test to analyse the causal relation between trading volume and Bitcoin returns and volatility, over the whole of their respective conditional distributions. The nonparametric characteristics of our test control for misspecification due to nonlinearity and structural breaks, two features of our data that cover 19th December 2011 to 25th April 2016. The causality-in-quantiles test reveals that volume can predict returns – except in Bitcoin bear and bull market regimes. This result highlights the importance of modelling nonlinearity and accounting for the tail behaviour when analysing causal relationships between Bitcoin returns and trading volume. We show, however, that volume cannot help predict the volatility of Bitcoin returns at any point of the conditional distribution.