We decompose, within an ARCH framework, the daily volatility of stocks into overnight and intra-day contributions. We find, as perhaps expected, that the overnight and intra-day returns behave completely differently. For example, while past intra-day returns affect equally the future intra-day and overnight volatilitie…
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48 results for “overnight volatility”
We point out a stunning time asymmetry in the short time cross correlations between intra-day and overnight volatilities (absolute values of log-returns of stock prices). While overnight volatility is significantly (and positively) correlated with the intra-day volatility during the \textit{following} day (allowing thu…
Tail risk forecasting with semi-parametric regression models by incorporating overnight informationq-fin.RM
This study improves tail risk forecasting by integrating overnight information into semi-parametric models.
problem Improving tail risk forecasting in financial markets.
method Proposes RES-CAViaR-oc models combining overnight return and realized volatility, using Bayesian estimation.
result Realized volatility and overnight return significantly improve tail risk forecasting.
Proposes overnight volatility model for better market dynamics.
problem Lack of high-frequency data during close-to-open period.
method Itô diffusion model with weighted least squares estimation.
result Developed and validated overnight volatility model.
We investigate the two components of the total daily return (close-to-close), the overnight return (close-to-open) and the daytime return (open-to-close), as well as the corresponding volatilities of the 2215 NYSE stocks from 1988 to 2007. The tail distribution of the volatility, the long-term memory in the sequence, a…
We propose a 4-factor model for overnight returns and give explicit definitions of our 4 factors. Long horizon fundamental factors such as value and growth lack predictive power for overnight (or similar short horizon) returns and are not included. All 4 factors are constructed based on intraday price and volume data a…
News explains most overnight stock market gains.
problem Understanding why overnight stock market gains are common.
method Supervised topic analysis of 2.4 million news articles.
result Time variation in news topics and their responses explain overnight returns.
This work models overnight rates with jumps and discontinuities, extending classical short-rate models.
problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.
Stock markets show unusual overnight and intraday returns.
problem Unusual patterns of overnight and intraday returns in stock markets.
method Analyzed features of the returns to deduce the cause.
result The only plausible explanation for these returns is that they are due to market manipulation.
We propose a new model of the liquidity driven banking system focusing on overnight interbank loans. This significant branch of the interbank market is commonly neglected in the banking system modeling and systemic risk analysis. We construct a model where banks are allowed to use both the interbank and the securities …
Split-Session Cluster GARCH for Overnight and Intraday Returns: The Role of Tail Heterogeneityecon.EM
The Split-Session Cluster GARCH model captures tail heterogeneity in overnight and intraday returns.
problem Capturing tail behavior and dependence in multivariate asset returns.
method Convolution- distributions, session and sector clustering, block-structured correlation matrices.
result Session-specific and sector-level tail parameters improve model fit and out-of-sample performance.
Study finds option volume imbalance predicts equity market returns.
problem Predicting equity market returns using option volume imbalance.
method Nonlinear analysis of option volumes decomposed into five market participant classes.
result Strong signals of predictability of excess market returns from Market-Maker volumes.
Robinhood users react strongly to overnight price changes and big losers, trading quickly after extreme losses.
problem Understanding trading behavior of Robinhood users, especially in high-frequency trading scenarios.
method Analyzed intraday and overnight price changes, focusing on big losers and gainers.
result Robinhood users react more to overnight price changes and big losers, trading quickly after extreme losses.
They Still Haven't Told Youq-fin.GN
Quant firms manipulate stock markets overnight and intraday.
problem Unexplained consistent overnight and intraday returns in stock markets.
method Analysis of trading patterns and market movements.
result Large quant firms expand and contract portfolios to create mark-to-market gains.
We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday return are described by a discrete time homogeneous semi-Markov process and the overnight returns are modeled by a Markov chain. Based on this assumptions we derived…
The paper validates a classifier for identifying intraday regime shifts in MNQ futures.
problem Developing reliable trading signals from intraday regime shifts in MNQ futures.
method Constructed a composite day-classification system using three observable conditions.
result Classifier-positive days exhibit distinct intraday behavior but fail to generate profitable trading signals.
The paper models SOFR and EFFR dynamics, reconciling diffusive and piecewise paths.
problem Updating interest rate models for SOFR, which is becoming a key benchmark.
method Calibrates a model to SOFR and EFFR futures prices, reconciling diffusive and piecewise paths.
result The model reflects key empirical features of SOFR dynamics and reconciles diffusive and piecewise paths.
This paper examines how the U.S.--China trade war affects stock markets, finding evidence of financial contagion and changes in risk channels.
problem The impact of the U.S.--China trade war on stock markets and financial contagion.
method Developed a novel jump-diffusion process to account for risk contagion, using high-frequency financial data and quasi-maximum likelihood estimator.
result Evidence of financial contagion from the U.S. to China, with changes in risk contagion channels.
Systemic risks characterizing the Russian overnight interbank market from the network point of view are analyzed.
Extended CIR process with jumps at fixed dates for modeling overnight rates.
problem Modeling overnight rates with jumps at predetermined dates.
method Formal definition and existence proof of a CIR process with stochastic discontinuities.
result Extended CIR process inherits affine property and non-negativity.
A symmetry-guided definition of time may enhance and simplify the analysis of historical series with recurrent patterns and seasonalities. By enforcing simple-scaling and stationarity of the distributions of returns, we identify a successful protocol of time definition in Finance. The essential structure of the stochas…
It is well known that traded foreign exchange forwards and cross currency swaps (CCS) cannot be priced applying overnight cash and carry arguments as they imply absence of funding advantage of one currency to the other. This paper proposes a heuristic present value concept for multi-currency pricing and hedging which a…
Correlations in the Bond-Future Marketcond-mat.stat-mech
We analyze the time series of overnight returns for the bund and btp futures exchanged at LIFFE (London). The overnight returns of both assets are mapped onto a one-dimensional symbolic-dynamics random walk: The `bond walk'. During the considered period (October 1991 - January 1994) the bund-future market opened earlie…
This note justifies approximations of arithmetic forwards using weighted averages of overnight forwards.
problem Theoretical justification for approximations of arithmetic forwards.
method Presentation of a central equation and computationally cheaper methods to approximate .
result Theoretical bounds and closed-form expressions for arithmetic factors in Gaussian HJM models.
Examines SOFR derivatives pricing and hedging post-LIBOR discontinuation.
problem Pricing and hedging of SOFR derivatives post-LIBOR discontinuation.
method One-factor model based on Vasicek's equation for overnight interest rates dynamics.
result Arbitrage-free pricing and hedging of SOFR derivatives instruments.
American Depositary Receipts (ADRs) are exchange-traded certificates that rep- resent shares of non-U.S. company securities. They are major financial instruments for investing in foreign companies. Focusing on Asian ADRs in the context of asyn- chronous markets, we present methodologies and results of empirical analysi…
The CTRW in finance: Direct and inverse problems with some generalizations and extensionscond-mat.stat-mech
We study financial distributions within the framework of the continuous time random walk (CTRW). We review earlier approaches and present new results related to overnight effects as well as the generalization of the formalism which embodies a non-Markovian formulation of the CTRW aimed to account for correlated increme…
We present a quantitative study of the markets and models evolution across the credit crunch crisis. In particular, we focus on the fixed income market and we analyze the most relevant empirical evidences regarding the divergences between Libor and OIS rates, the explosion of Basis Swaps spreads, and the diffusion of c…
We point out a simple equities trading strategy that allows a sufficiently large, market-neutral, quantitative hedge fund to achieve outsized returns while simultaneously contributing significantly to increasing global wealth inequality. Overnight and intraday return distributions in major equity indices in the United …
We develop a maximum penalized quasi-likelihood estimator for estimating in a nonparametric way the diffusion function of a diffusion process, as an alternative to more traditional kernel-based estimators. After developing a numerical scheme for computing the maximizer of the penalized maximum quasi-likelihood function…
Using Premia and Nsp for Constructing a Risk Management Benchmark for Testing Parallel Architecturecs.CE
Financial institutions have massive computations to carry out overnight which are very demanding in terms of the consumed CPU. The challenge is to price many different products on a cluster-like architecture. We have used the Premia software to valuate the financial derivatives. In this work, we explain how Premia can …
High-value transactions between Australian banks are settled in the Reserve Bank Information and Transfer System (RITS) administered by the Reserve Bank of Australia. RITS operates on a real-time gross settlement (RTGS) basis and settles payments sourced from the SWIFT, the Austraclear, and the interbank transactions e…
We introduce here for the first time the long-term swap rate, characterised as the fair rate of an overnight indexed swap with infinitely many exchanges. Furthermore we analyse the relationship between the long-term swap rate, the long-term yield, see Biagini et al. [2018], Biagini and Härtel [2014], and El Karoui et a…
We study a class of backtests for forecast distributions in which the test statistic depends on a spectral transformation that weights exceedance events by a function of the modeled probability level. The weighting scheme is specified by a kernel measure which makes explicit the user's priorities for model performance.…
Heterotic Risk Modelsq-fin.PM
We give a complete algorithm and source code for constructing what we refer to as heterotic risk models (for equities), which combine: i) granularity of an industry classification; ii) diagonality of the principal component factor covariance matrix for any sub-cluster of stocks; and iii) dramatic reduction of the facto…
Obstructive sleep apnea is a serious condition causing a litany of health problems especially in the pediatric population. However, this chronic condition can be treated if diagnosis is possible. The gold standard for diagnosis is an overnight sleep study, which is often unobtainable by many potentially suffering from …
Alternative perspective on mean-field LIBOR market model, maintaining practicality and applicability.
problem Maintaining practicality and applicability of mean-field LIBOR market model.
method Embedding mean-field model in a classical setup, controlling term rate variances over large time horizons.
result Framework can be directly applied to model term rates from SOFR, ESTR, or other nearly risk-free overnight rates.
They Chose to Not Tell Youq-fin.GN
Silence on suspicious stock market patterns persists despite lack of plausible explanations.
problem Suspicious patterns in stock market returns not explained or warned about.
method Analysis of correspondence and market data over five years.
result People aware of suspicious patterns chose not to alert the public.
Exact relationships found between ATM slope, volatility swap, and zero vanna.
problem Understanding relationships between implied volatilities and swaps.
method Analyzes exact relationships between ATM slope, volatility swap, and zero vanna.
result Exact relationships between ATM slope, volatility swap, and zero vanna.
Study local volatility from rough volatility models, finding new skew rule.
problem Understanding local volatility from rough volatility models.
method Analyzing asymptotic behavior of local volatility surface generated by rough stochastic volatility models.
result New skew rule: ratio of implied and local vol skews tends to 1/(H + 3/2).
This paper models short rates with jumps using PDEs.
problem Capturing jumps and spikes in interest rates.
method PDE approach for pricing interest rate derivatives.
result Established Feynman-Kač representation and derived solutions.
On options-driven realized volatility forecasting: Information gains via rough volatility modelq-fin.RM
Enhanced volatility forecasting using options data and rough volatility model.
problem Improving realized volatility forecasting accuracy.
method Infer spot volatility from options data using rough stochastic volatility model, accelerate estimation with deep learning, benchmark against traditional models.
result Augmented HAR-RV-RHeston model outperforms traditional models in daily and long-term forecasting.
We consider an asset whose risk-neutral dynamics are described by a general class of local-stochastic volatility models and derive a family of asymptotic expansions for European-style option prices and implied volatilities. Our implied volatility expansions are explicit; they do not require any special functions nor do…
Study on estimating volatility of volatility using Fourier methods and provides insights into volatility dynamics.
problem Estimating the volatility of volatility (vol-of-vol) accurately and efficiently.
method Used Fourier methodology to estimate integrated volatility of volatility, bias-corrected and without bias-correction, comparing their asymptotic properties and accuracy.
result The bias-corrected estimator reaches the optimal rate , while the uncorrected estimator has a slower rate and smaller asymptotic variance.
Extends Heston model with local volatility for better fit to market volatilities.
problem Fitting stochastic volatility models to market volatilities.
method Adds local volatility term to rough-Heston model, preserving stylized results.
result Provides a proper extrapolation scheme for calibration.
Derives equations for life insurance reserves with interest rate uncertainty.
problem Life insurance reserves with stochastic interest rates.
method Partial differential equations for reserves under stochastic interest rates.
result Explicit solutions for reserves under specific models.
The paper values perpetual callable American volatility options using a mean-reverting volatility model.
problem Valuation of callable American volatility put options.
method Modeling volatility dynamics as a mean-reverting 3/2 process and proposing a pricing formula.
result The value of perpetual callable American volatility put options is discussed under given conditions.
The stochastic volatility model is one of volatility models which infer latent volatility of asset returns. The Bayesian inference of the stochastic volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm which is superior to other Markov Chain Monte Carlo methods in sampling volatility variables. …