scholarly journals Fixed‐ k inference for volatility

2021 ◽  
Vol 12 (4) ◽  
pp. 1053-1084 ◽  
Author(s):  
Tim Bollerslev ◽  
Jia Li ◽  
Zhipeng Liao
Keyword(s):  
Asset Price ◽  
Block Size ◽  
Confidence Bands ◽  
Identification Schemes ◽  
High Dimensional Inference ◽  
News Announcement ◽  
Intraday Data ◽  
Calibrated Simulation ◽  
Equity Index ◽  
Spot Volatility

We present a new theory for the conduct of nonparametric inference about the latent spot volatility of a semimartingale asset price process. In contrast to existing theories based on the asymptotic notion of an increasing number of observations in local estimation blocks, our theory treats the estimation block size k as fixed. While the resulting spot volatility estimator is no longer consistent, the new theory permits the construction of asymptotically valid and easy‐to‐calculate pointwise confidence intervals for the volatility at any given point in time. Extending the theory to a high‐dimensional inference setting with a growing number of estimation blocks further permits the construction of uniform confidence bands for the volatility path. An empirically realistically calibrated simulation study underscores the practical reliability of the new inference procedures. An empirical application based on intraday data for the S&P 500 equity index reveals highly significant abrupt changes, or jumps, in the market volatility at FOMC news announcement times, validating recent uses of various high‐frequency‐based identification schemes in asset pricing finance and monetary economics.

Is the intrinsic value of a macroeconomic news announcement related to its asset price impact?

2017 ◽  
Vol 92 ◽  
pp. 78-95 ◽  
Author(s):  
Thomas Gilbert ◽  
Chiara Scotti ◽  
Georg Strasser ◽  
Clara Vega
Keyword(s):  
Intrinsic Value ◽  
Asset Price ◽  
Price Impact ◽  
Macroeconomic News ◽  
News Announcement

scholarly journals A PARSIMONIOUS CONTINUOUS TIME MODEL OF EQUITY INDEX RETURNS: INFERRED FROM HIGH FREQUENCY DATA

2004 ◽  
Vol 07 (08) ◽  
pp. 997-1030 ◽  
Author(s):  
MASCIA BEDENDO ◽  
STEWART D. HODGES
Keyword(s):  
Continuous Time ◽  
High Frequency ◽  
Monte Carlo Experiment ◽  
Continuous Time Model ◽  
Time Model ◽  
Data Set ◽  
Futures Contract ◽  
Volatility Model ◽  
Intraday Data ◽  
Equity Index

In this paper we propose a continuous time model capable of describing the dynamics of futures equity index returns at different time frequencies. Unlike several related works in the literature, we avoid specifying a model a priori and we attempt, instead, to infer it from the analysis of a data set of 5-minute returns on the S&P500 futures contract. We start with a very general specification. First we model the seasonal pattern in intraday volatility. Once we correct for this component, we aggregate intraday data into a daily volatility measure to reduce the amount of noise and its distorting impact on the results. We then employ this measure to infer the structure of the stochastic volatility model and of the leverage component, as well as to obtain insights on the shape of the distribution of conditional returns. Our model is then refined at a high frequency level by means of a simple nonlinear filtering technique, which provides an intraday update of volatility and return density estimates on the basis of observed 5-minute returns. The results from a Monte Carlo experiment indicate that a sample of returns simulated according to our model successfully replicates the main features observed in market returns.

Price efficiency and safe-haven property of Bitcoin in relation to stocks in the pandemic era

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Natalia Diniz-Maganini ◽  
Abdul A. Rasheed
Keyword(s):  
Fluctuation Analysis ◽  
Safe Haven ◽  
Price Efficiency ◽  
Market Prices ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Cross Correlation Analysis ◽  
Intraday Data ◽  
Country Index ◽  
Equity Index

Purpose When investors experience extreme uncertainty, they seek “safe havens” to reduce their risk, to limit their losses and to protect the value of their portfolios. The purpose of this paper is to examine the safe-haven properties of Bitcoin compared to the stock market. Design/methodology/approach Based on intraday data, this study compares the price efficiencies of Bitcoin and Morgan Stanley Capital Index (MSCI) using Multifractal Detrended Fluctuation Analysis for the second half of 2020. This study then evaluates Bitcoin’s safe-haven property using Detrended Partial-Cross-Correlation Analysis (DPCCA). Findings This study finds that the price efficiency of Bitcoin is lower than that of MSCI. Further, Bitcoin was not a safe haven at any time for the MSCI index. The net cross-correlations between Bitcoin and MSCI are weak and they vary at different time scales. Research limitations/implications The behavior of market prices varies over time. Therefore, it is important to replicate this study for other time periods. Social implications The paper sheds light on the price behavior of Bitcoin during a period of instability. The results suggest that the construction of portfolios should differ based on the time horizons of the investors. Originality/value The authors compare Bitcoin against a global equity index instead of a specific country index or commodity. They also demonstrate the applicability of DPCCA in finance research.

Testing risk proxies for financial collateral haircuts: adequacy of capturing tail risk

2020 ◽  
Vol 21 (3) ◽  
pp. 299-316
Author(s):  
Lukasz Prorokowski ◽  
Oleg Deev ◽  
Hubert Prorokowski
Keyword(s):  
Asset Price ◽  
Price Volatility ◽  
Statistical Tools ◽  
Tail Risk ◽  
Content Type ◽  
Kolmogorov Smirnov ◽  
Tail Events ◽  
Individual Asset ◽  
Equity Index ◽  
Smirnov Test

Purpose The use of risk proxies in internal models remains a popular modelling solution. However, there is some risk that a proxy may not constitute an adequate representation of the underlying asset in terms of capturing tail risk. Therefore, using empirical examples for the financial collateral haircut model, this paper aims to critically review available statistical tools for measuring the adequacy of capturing tail risk by proxies used in the internal risk models of banks. In doing so, this paper advises on the most appropriate solutions for validating risk proxies. Design/methodology/approach This paper reviews statistical tools used to validate if the equity index/fund benchmark are proxies that adequately represent tail risk in the returns on an individual asset (equity/fund). The following statistical tools for comparing return distributions of the proxies and the portfolio items are discussed: the two-sample Kolmogorov–Smirnov test, the spillover test and the Harrell’s C test. Findings Upon the empirical review of the available statistical tools, this paper suggests using the two-sample Kolmogorov–Smirnov test to validate the adequacy of capturing tail risk by the assigned proxy and the Harrell’s C test to capture the discriminatory power of the proxy-based collateral haircuts models. This paper also suggests a tool that compares the reactions of risk proxies to tail events to verify possible underestimation of risk in times of significant stress. Originality/value The current regulations require banks to prove that the modelled proxies are representative of the real price observations without underestimation of tail risk and asset price volatility. This paper shows how to validate proxy-based financial collateral haircuts models.

scholarly journals ESTIMATING THE VOLATILITY OCCUPATION TIME VIA REGULARIZED LAPLACE INVERSION

2015 ◽  
Vol 32 (5) ◽  
pp. 1253-1288 ◽  
Author(s):  
Jia Li ◽  
Viktor Todorov ◽  
George Tauchen
Keyword(s):  
Asset Price ◽  
Estimation Procedure ◽  
Small Sample ◽  
Occupation Time ◽  
Cumulative Distribution ◽  
Empirical Cumulative Distribution Function ◽  
Laplace Inversion ◽  
The Laplace Transform ◽  
Analysis Of Variation ◽  
Spot Volatility

We propose a consistent functional estimator for the occupation time of the spot variance of an asset price observed at discrete times on a finite interval with the mesh of the observation grid shrinking to zero. The asset price is modeled nonparametrically as a continuous-time Itô semimartingale with nonvanishing diffusion coefficient. The estimation procedure contains two steps. In the first step we estimate the Laplace transform of the volatility occupation time and, in the second step, we conduct a regularized Laplace inversion. Monte Carlo evidence suggests that the proposed estimator has good small-sample performance and in particular it is far better at estimating lower volatility quantiles and the volatility median than a direct estimator formed from the empirical cumulative distribution function of local spot volatility estimates. An empirical application shows the use of the developed techniques for nonparametric analysis of variation of volatility.

Image Compression Using Vector Quantization with Variable Block Size Division

2010 ◽  
Vol 130 (8) ◽  
pp. 1431-1439 ◽  
Author(s):  
Hiroki Matsumoto ◽  
Fumito Kichikawa ◽  
Kazuya Sasazaki ◽  
Junji Maeda ◽  
Yukinori Suzuki
Keyword(s):  
Image Compression ◽  
Vector Quantization ◽  
Block Size ◽  
Variable Block

Intraday Price Formation in U.S. Equity Index Markets

CFA Digest ◽  
2004 ◽  
Vol 34 (3) ◽  
pp. 56-57
Author(s):  
Robert A. McLean
Keyword(s):  
Price Formation ◽  
Equity Index

Superionic Lithium Intercalation through 2 nm x 2 nm Columns in the Crystallographic Shear Phase Nb18W8O69

2019 ◽  
Author(s):  
Kent Griffith ◽  
Clare Grey
Keyword(s):  
High Performance ◽  
Rate Capability ◽  
Block Size ◽  
Lithium Intercalation ◽  
Resonance Spectroscopy ◽  
Complex Metal Oxides ◽  
Battery Electrode ◽  
Crystallographic Shear ◽  
Battery Material ◽  
First Time

Nb18W8O69 (9Nb2O5×8WO3) is the tungsten-rich end-member of the Wadsley–Roth crystallographic shear (cs) structures within the Nb2O5–WO3 series. It has the largest block size of any known, stable Wadsley–Roth phase, comprising 5 ´ 5 units of corner-shared MO6 octahedra between the shear planes, giving rise to 2 nm ´ 2 nm blocks. Rapid lithium intercalation is observed in this new candidate battery material and 7Li pulsed field gradient nuclear magnetic resonance spectroscopy – measured in a battery electrode for the first time at room temperature – reveals superionic lithium conductivity. In addition to its promising rate capability, Nb18W8O69 adds a piece to the larger picture of our understanding of high-performance Wadsley–Roth complex metal oxides.

A Study of the Average Flow in Open Channel with Baffle Blocks Distributed Uniformly

10.29007/zx1w ◽  
2018 ◽  
Author(s):  
Dung Tien Tran ◽  
Anh Tuan Le ◽  
Hong Nhung Le ◽  
Viet Hung Ho
Keyword(s):  
Water Level ◽  
Water Depth ◽  
Open Channel ◽  
Block Size ◽  
Average Flow ◽  
Modelling Studies ◽  
Baffle Block

A study of average flow in open channel with baffle blocks distributed uniformly has been considered by using channel with varied slopes. In this article, experimental and modelling studies were introduced when the correlation between the water depth and baffle block size is significant. The objective of the work is to give the rudimentary relations between discharge and water level in the channels. When the water depth is large, the effect of bottom channel friction on the flow is relatively small. This paper also gives applications of the software ‘Telemac-2D’ to simulate the flow under different conditions.

The Micro and Macro of Managerial Beliefs

2020 ◽  
Author(s):  
Jose Maria Barrero
Keyword(s):  
Rational Expectations ◽  
Asset Price ◽  
Heterogeneous Firms ◽  
Adjustment Costs ◽  
Consumer Welfare ◽  
Sales Growth ◽  
Firm Level ◽  
Managerial Decisions ◽  
Managerial Beliefs ◽  
Growth Volatility

This paper studies how biases in managerial beliefs affect managerial decisions, firm performance, and the macroeconomy. Using a new survey of US managers I establish three facts. (1) Managers are not over-optimistic: sales growth forecasts on average do not exceed realizations. (2) Managers are overprecise (overconfident): they underestimate future sales growth volatility. (3) Managers overextrapolate: their forecasts are too optimistic after positive shocks and too pessimistic after negative shocks. To quantify the implications of these facts, I estimate a dynamic general equilibrium model in which managers of heterogeneous firms use a subjective beliefs process to make forward-looking hiring decisions. Overprecision and overextrapolation lead managers to overreact to firm-level shocks and overspend on adjustment costs, destroying 2.1 percent of the typical firm’s value. Pervasive overreaction leads to excess volatility and reallocation, lowering consumer welfare by 0.5 to 2.3 percent relative to the rational expectations equilibrium. These findings suggest overreaction may amplify asset-price and business cycle fluctuations.

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