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We develop an N-regime Markov-switching model in which the latent state variable driving the regime switching is endogenously determined with the model disturbance term. The model’s structure captures a wide variety of patterns of endogeneity and yields a simple test of the null hypothesis of exogenous switching. We derive an iterative filter that generates objects of interest, including the model likelihood function and estimated regime probabilities. Using simulation experiments, we demonstrate that the maximum likelihood estimator performs well in finite samples and that a likelihood ratio test of exogenous switching has good size and power properties. We provide results from two applications of the endogenous switching model: a three-state model of US business cycle dynamics and a three-state volatility model of US equity returns. In both cases, we find statistically significant evidence in favor of endogenous switching.
We introduce variance-optimal semi-static hedging strategies for a given contingent claim. To obtain a tractable formula for the expected squared hedging error and the optimal hedging strategy we use a Fourier approach in a multidimensional factor model. We apply the theory to set up a variance-optimal semi-static hedging strategy for a variance swap in the Heston model, which is affine, in the 3/2 model, which is not, and in a market model including jumps.
We identify volatility breaks in all testable series in the FRED database over the 1957–2013 period. This yields 17,681 breaks, which we categorize using text analysis. We show that 70.5% of series categories experienced a decline in volatility over the 1985–1999 period, suggesting that the Great Moderation was far broader in scope than the literature has documented. We also show that this decline reversed in 2000, leading to a sharp increase in volatility for most time series categories; however, this did not fully materialize in GDP volatility until the Great Recession. Finally, we identify labor markets, demographics, finance, and government debt as potential drivers of low-frequency shifts in volatility over the 1957–2013 period.
This study examines the price level and volatility interaction between international staple food and cash crop futures price indices. Understanding the relationship between these commodities bears significant implications for low-income food deficit countries that depend on cash crops to finance food import bills. We use a wavelet analysis to decompose the price indices and then apply a BEKK-MGARCH (Baba, Engle, Kraft and Kroner–multivariate generalized autoregressive conditional heteroskedasticity) approach to analyze the relationship across timescales. Results indicate the level of correlation and volatility linkages are strongest at lower frequencies (longer run) than at higher timescales (short run), with information running from staple food to cash crop markets.
This research examined dicamba measurements following an application to soil inside a humidome. The dicamba formulations examined were the diglycolamine (DGA) and diglycolamine plus VaporGrip® (DGA+VG), both applied with glyphosate. Post-application dicamba measurements were related to ambient temperature, with more dicamba detected as the temperature increased. There also appeared to be a minimum temperature of ~15 C at which dicamba decreased to low levels. The addition of glyphosate to dicamba formulations decreased the spray mixture pH and increased the observed dicamba air concentrations. Adding glyphosate to DGA+VG increased detectable dicamba air concentrations by 2.9 to 9.3 times across the temperature ranges examined. Particle drift would not be expected to be a factor in the research, as applications were made remotely before treated soil was transported into the greenhouse. The most probable reason for the increased detection of dicamba at higher temperatures and with mixtures of glyphosate is via volatility.
We study the asymptotic behaviour of a class of small-noise diffusions driven by fractional Brownian motion, with random starting points. Different scalings allow for different asymptotic properties of the process (small-time and tail behaviours in particular). In order to do so, we extend some results on sample path large deviations for such diffusions. As an application, we show how these results characterise the small-time and tail estimates of the implied volatility for rough volatility models, recently proposed in mathematical finance.
Using a panel of 54 countries between 1980 and 2013, we find empirical support for the view that changes in the fiscal policy stance (year-on-year change in the cyclically adjusted primary balance) have a significant positive correlation with inflation volatility. An increase in the volatility of discretionary fiscal policies by one standard deviation raises inflation volatility by about 6%. Moreover, results using alternative inflation volatility proxies confirm that an expansionary fiscal stance increases price volatility. Another relevant outcome is that in a context of economic expansions (recessions) the harmful impact of fiscal activism on price volatility is soft (heightened), while the negative impact of fiscal activism on price stability is higher when fiscal policy is expansionary. Finally, fiscal activism fuels inflation volatility much more pronouncedly in emerging market economies vis-à-vis advanced economies.
This paper extends the ongoing literature on the macroeconomic effects of money supply volatility. We use monthly data for the USA and a bivariate, Markov switching, structural vector error correction model that is modified to accommodate generalized autoregressive conditional heteroscedasticity-in-mean errors to isolate the effects of money growth volatility on output growth. The model allows us to study how monetary uncertainty affects economic growth across different macroeconomic regimes.
Introduced recently in mathematical finance by Bayer et al. (2016), the rough Bergomi model has proved particularly efficient to calibrate option markets. We investigate some of its probabilistic properties, in particular proving a pathwise large deviations principle for a small-noise version of the model. The exponential function (continuous but superlinear) as well as the drift appearing in the volatility process fall beyond the scope of existing results, and a dedicated analysis is needed.
We highlight a state variable misspecification with one accepted method to implement stochastic volatility (SV) in DSGE models when transforming the nonlinear state-innovation dynamics to its linear representation. Although the technique is more efficient numerically, we show that it is not exact but only serves as an approximation when the magnitude of SV is small. Not accounting for this approximation error may induce substantial spurious volatility in macroeconomic series, which could lead to incorrect inference about the performance of the model. We also show that, by simply lagging and expanding the state vector, one can obtain the correct state-space specification. Finally, we validate our augmented implementation approach against an established alternative through numerical simulation.
Herbicide active ingredients, formulation type, ambient temperature, and humidity can influence volatility. A method was developed using volatility chambers to compare relative volatility of different synthetic auxin herbicide formulations in controlled environments. 2,4-D or dicamba acid vapors emanating after application were captured in air-sampling tubes at 24, 48, 72, and 96 h after herbicide application. The 2,4-D or dicamba was extracted from sample tubes and quantified using liquid chromatography and tandem mass spectrometry. Volatility from 2,4-D dimethylamine (DMA) was determined to be greater than that of 2,4-D choline in chambers where temperatures were held at 30 or 40 C and relative humidity (RH) was 20% or 50%. Air concentration of 2,4-D DMA was 0.399 µg m−3 at 40 C and 20% RH compared with 0.005 µg m−3 for 2,4-D choline at the same temperature and humidity at 24 h after application. Volatility from 2,4-D DMA and 2,4-D choline increased as temperature increased from 30 to 40 C. However, volatility from 2,4-D choline was lower than observed from 2,4-D DMA. Volatility from 2,4-D choline at 40 C increased from 0.00458 to 0.0263 µg m−3 and from 0.00341 to 0.025 µg m−3 when humidity increased from 20% to 50% at 72 and 96 h after treatment, respectively, whereas, volatility from 2,4-D DMA tended to be higher at 20% RH compared with 50% RH. Air concentration of dicamba diglycolamine was similar at all time points when measured at 40 C and 20% RH. By 96 h after treatment, there was a trend for lower air concentration of dicamba compared with earlier timings. This method using volatility chambers provided good repeatability with low variability across replications, experiments, and herbicides.
Scholars of electoral behaviour regularly link political dissatisfaction to two types of behaviour: voting for populist parties and unstable voting behaviour. It is therefore not surprising that the electorates of populist parties are generally assumed to be rather volatile. In this article, we argue that this is not necessarily the case – in particular in a context of increasingly strong and viable populist parties. We make use of data from the Comparative Study of Electoral Systems project to show that voters for populist parties are neither more nor less volatile than voters for mainstream parties. Political dissatisfaction among voters for populist parties even increases the likelihood of stable voting for populist parties. The supply of populist parties further conditions the stability of the populist vote, as voters in systems with established populist parties are more likely to vote stably for populist parties. Finally, we find that in a context of strong and stable populist parties, the effect of political satisfaction on vote switching is somewhat reduced.
The literature on party system change and electoral volatility in post-communist Europe tends to make a clear-cut distinction between Central and Eastern European (CEE) party systems and Western European (WE) ones. The former are unstable and unpredictable and electoral volatility is driven by the continuous emergence of new political parties. Conversely, electoral stability is the rule in the latter, and volatility is associated with electoral shifts among established parties. This conventional wisdom suffers from three potential sources of bias: case selection, time coverage and method. By correcting these biases, this article investigates whether the traditional division between CEE and WE party systems has been levelled as regards volatility. To do so, it presents evidence based on an original data set of electoral volatility and its internal components covering 31 WE and CEE party systems since 1990. It finds that a process of asymmetric convergence in the levels of electoral volatility is taking place between the two regions, with Western Europe approaching Central and Eastern Europe with increasing electoral instability.
In housing affordability levels and volatility, there could hardly be a greater contrast than between the UK and Germany. Differences in history, institutions and policies are explored in this paper. Residential housing supply has been far more expansionary in Germany and mortgage credit more tightly regulated. A sensibly regulated rental market and stable German house prices have combined to leave the rental sector with over half of tenures. Policy failures in the UK have resulted in widening intergenerational inequality, increased social exclusion, adversely affected productivity and growth and raised the risk of financial instability. Policy lessons are drawn for the UK, which go far beyond the remit of the immediately responsible Ministry of Housing, Communities and Local Government.
Volatility is a central theme of the scholarship on party competition. At the extreme, entire systems collapse. Bolivia, Ecuador, and Venezuela each went through a protracted period of change with the crash of old parties and the rise of new ones, including one representing the “new left.” Average electoral volatility grew by more than 50 percent and remained high for a decade or more. Can this churning surface of party death, birth, and change obscure undercurrents of stabilization in individual voting behavior? This project decomposes electoral volatility into two subtypes: system-level volatility—long-term spatial and temporal trends of change in support (e.g., realignment)—and individual volatility—fluid and cycle-specific fluctuations in support (e. g., electoral swing). It shows that the high volatility through the transformation has been at the system level, not the individual level. The cause is the stronger partisan and ethnic bonds mobilized by the new left.
This study contributes to the literature by using a spillover index method to examine the changing interrelations in volatility among corn and energy future prices. This methodology allows us to account for endogenously determined economic fundamentals and market speculation. After controlling for market trends and seasonality, we find relative large increases in volatility spillovers between corn, crude oil, and ethanol futures prices. Our results suggest that the cross-commodity spillovers provide useful incremental information in determining future price volatility; however, a commodity's own dynamics explain the largest portion of volatility spillovers.
We investigate the demand for money and the degree of substitutability among monetary assets in the United States using the generalized Leontief and the Minflex Laurent (ML) models as suggested by Serletis and Shahmoradi (2007). In doing so, we merge the demand systems literature with the recent financial econometrics literature, relaxing the homoskedasticity assumption and instead assuming that the covariance matrix of the errors of flexible demand systems is time-varying. We also pay explicit attention to theoretical regularity, treating the curvature property as a maintained hypothesis. Our findings indicate that only the curvature constrained ML model with a Baba, Engle, Kraft, and Kroner (BEKK) specification for the conditional covariance matrix is able to generate inference consistent with theoretical regularity.
In this paper we relate the set of structure-preserving equivalent martingale measures ℳsp for financial models driven by semimartingales with conditionally independent increments to a set of measurable and integrable functions 𝒴. More precisely, we prove that ℳsp ≠ ∅ if and only if 𝒴 ≠ ∅, and connect the sets ℳsp and 𝒴 to the semimartingale characteristics of the driving process. As examples we consider integrated Lévy models with independent stochastic factors and time-changed Lévy models and derive mild conditions for ℳsp ≠ ∅.
In this paper, we extend the framework of Klein  [Journal of Banking & Finance 20: 1211–1229] to a general model under the double exponential jump model with stochastic volatility on the underlying asset and the assets of the counterparty. Firstly, we derive the closed-form characteristic functions for this dynamic. Using the Fourier-cosine expansion technique, we get numerical solutions for vulnerable European put options based on the characteristic functions. The inverse fast Fourier transform method provides a fast numerical algorithm for the twice-exercisable vulnerable Bermuda put options. By virtue of the modified Geske and Johnson method, we obtain an approximate pricing formula of vulnerable American put options. Numerical simulations are made for investigating the impact of stochastic volatility on vulnerable options.
Over the last decades, Western European party systems have experienced growing levels of electoral volatility and the recurring emergence of successful new parties. This evidence calls into question the issue of party system institutionalization (PSI), a topic taken for granted so far in Western Europe, following the conventional wisdom that party systems are highly institutionalized in this region. This article tackles this issue and provides some contributions: it offers a theoretical clarification of PSI and develops an index allowing for cross-country and cross-time comparability; it looks for an explanation, by testing the impact of various potential determinants and their changes over time. Covering 324 elections in 19 countries since 1945, the analysis shows that, since the 1970s, a process of de-institutionalization is going on and that PSI is mainly a function of the cleavage structure and the number of parties, with economic performance becoming relevant only in the last period.