Examines US equity risk premiums amid COVID-19.
problem Analyzing equity risk premiums during the pandemic.
method Not specified in the abstract.
result Not specified in the abstract.
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48 results for “risk-premium”
The study reveals unspanned risks in equity option risk premiums, explaining negative premiums for certain options.
problem Explaining negative risk premiums for certain equity option types.
method Developed a decomposition of equity option risk premiums, operationalized the pricing kernel process, and incorporated unspanned risks.
result Empirical evidence supports the presence of unspanned risks, explaining negative risk premiums for certain options.
Unifying the theory of storage and the risk premium by an unobservable intrinsic electricity priceq-fin.MF
Introduces an unobservable intrinsic electricity price to link storage theory with risk premium.
problem Connecting storage theory with risk premium in electricity markets.
method Introduces an unobservable intrinsic electricity price and derives prices for various contracts.
result Finds an overall negative risk premium in empirical analysis.
A new method calculates risk loadings in classification ratemaking without subjective parameters.
problem Subjective risk loading parameters in classification ratemaking.
method Bootstrap method to calculate total risk premium, then determine risk loading parameters using quantile regression models.
result Risk premiums calculated by the new method reasonably differentiate different risk classes.
Paper finds significant impact of stock market swings on equity risk premium predictability.
problem Predicting equity risk premium based on stock market behavior changes.
method Introduced Bullish Index and used FDMAA for returns analysis; considered 28 indicators.
result Positive shocks in Bullish Index correlate with strong equity risk premium predictability for up to six months, while negative shocks correlate for up to nine months.
Equity risk premium is a central component of every risk and return model in finance and a key input to estimate costs of equity and capital in both corporate finance and valuation. An article by Damodaran examines three broad approaches for estimating the equity risk premium. The first is survey based, it consists in …
The risk premium is one of main concepts in mathematical finance. It is a measure of the trade-offs investors make between return and risk and is defined by the excess return relative to the risk-free interest rate that is earned from an asset per one unit of risk. The purpose of this article is to determine upper and …
The paper models exchange rate risk premium using mean-reverting dynamics.
problem Empirical failure of uncovered interest parity (UIP).
method Modeling risk premium using Ornstein-Uhlenbeck (OU) process embedded in stochastic differential equation for exchange rate.
result The model shows strong predictive performance at short and long horizons, but underperforms at intermediate horizons.
We construct the term structure of the (forward-looking, US market) equity risk premium from SPX option chains. The method is "model-light". Risk-neutral probability densities are estimated by fitting -component Gaussian mixture models to option quotes, where is a small integer (here 4 or 5). These densities are…
Study examines risk premium convergence rates in risk sharing contracts.
problem Analyzing risk premium convergence rates in risk sharing contracts.
method Examines the limiting behavior of risk premium associated with Pareto optimal risk sharing contracts under general law-invariant risk measures.
result Risk premium convergence rate is typically , not .
We study the risk premium impact in the Perturbative Black Scholes model. The Perturbative Black Scholes model, developed by Scotti, is a subjective volatility model based on the classical Black Scholes one, where the volatility used by the trader is an estimation of the market one and contains measurement errors. In t…
For a commodity spot price dynamics given by an Ornstein-Uhlenbeck process with Barndorff-Nielsen and Shephard stochastic volatility, we price forwards using a class of pricing measures that simultaneously allow for change of level and speed in the mean reversion of both the price and the volatility. The risk premium i…
New volatility model for option pricing with time-varying risk premium.
problem Volatility risk premium is time-varying and not well captured by existing models.
method Combines Markov switching with Realized GARCH framework to derive a state-dependent pricing kernel.
result The model reduces option pricing errors by 15% or more compared to competing models.
We present extensive evidence that ``risk premium'' is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit an approximately linear relation between the Sharpe ratio of various risk premium strategies (Equity, Fama-French, FX Carry,…
The study reveals traders' risk aversion and a new risk premium from market volumes.
problem Understanding traders' rationality and risk aversion from market volumes.
method Optimal Merton dynamics model to estimate average risk aversion and price of risk.
result Validation of the proposed trading strategy model on real data.
Realized GARCH model explains VIX and VRP dynamics.
problem Understanding VIX and VRP dynamics in financial markets.
method Developed Realized GARCH model with two shocks.
result Realized GARCH model outperforms conventional GARCH models.
We revisit the problem of pricing options with historical volatility estimators. We do this in the context of a generalized GARCH model with multiple time scales and asymmetry. It is argued that the reason for the observed volatility risk premium is tail risk aversion. We parametrize such risk aversion in terms of thre…
Study on price formation among investors with exponential utility and liabilities.
problem Equilibrium price formation among investors with heterogeneous risk-averseness and liabilities.
method Mean-field game theory and mean-field backward stochastic differential equations (BSDE).
result Existence of equilibrium risk-premium process and market clearing in the large population limit.
We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary independent increments process for the low-frequency dynamics, and model the la…
Proposes a new portfolio theory that optimizes returns and risk.
problem Inefficient market hypothesis and risk premium in finance markets.
method Introduces triplet (R, H, σ) model for portfolio optimization.
result Developed a global optimal strategy for different investor styles.
In the presence of ambiguity on the driving force of market randomness, we consider the dynamic portfolio choice without any predetermined investment horizon. The investment criteria is formulated as a robust forward performance process, reflecting an investor's dynamic preference. We show that the market risk premium …
The paper models asset pricing in a partially observed market using mean field game theory and exponential quadratic Gaussian framework.
problem Asset pricing in a market with partial observation and heterogeneous agents.
method Mean field game theory, exponential quadratic Gaussian framework, Kalman-Bucy filtering theory.
result Characterization of equilibrium risk premium through mean field BSDE and construction of unobservable risk premium process.
The study finds no evidence of stochastic arbitrage opportunities in S&P 500 index options.
problem Identifying arbitrage opportunities in S&P 500 index options.
method Developed linear and mixed-integer linear programs to compute the maximum option premium.
result No evidence of systematic stochastic arbitrage opportunities in S&P 500 index options.
On the Time-Varying Structure of the Arbitrage Pricing Theory using the Japanese Sector Indicesq-fin.ST
Study on time-varying APT validity in Japanese stock market.
problem Validity of Arbitrage Pricing Theory (APT) in Japanese stock market over time.
method Rolling window method applied to Fama and MacBeth's two-step regression and Kamstra and Shi's generalized GRS test.
result APT validity is unstable over time in Japanese stock market, influenced by monetary policy and business cycle.
Develops asset pricing models with mean field game theory for heterogeneous agents.
problem Tackles equilibrium asset pricing in incomplete markets with heterogeneous agents.
method Uses mean field game theory and mean field backward stochastic differential equations (BSDEs).
result Derives equilibrium risk premium and shows market clearing in the large population limit.
Machine learning helps estimate risk premiums of stocks without knowing their factors.
problem Estimate risk premiums of stocks without knowing their underlying factors.
method Used elastic-net machine learning to project stock returns onto peers and construct replicate portfolios.
result Unique stocks have higher SARP and excess returns than ubiquitous stocks.
Analyzes how rough volatility affects stock pricing and risk premium.
problem Impact of non-deterministic volatility risk on stock pricing.
method Rough volatility model under historical measure, analysis of stochastic volatility risk.
result Impact of non-deterministic volatility risk on pricing is significant.
Local risk-minimization for Barndorff-Nielsen and Shephard models with volatility risk premiumq-fin.MF
We derive representations of local risk-minimization of call and put options for Barndorff-Nielsen and Shephard models: jump type stochastic volatility models whose squared volatility process is given by a non-Gaussian rnstein-Uhlenbeck process. The general form of Barndorff-Nielsen and Shephard models includes two par…
In this paper analytic formulas for electricity derivatives are calculated. To this end, we assume that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition matrix. Since the classical derivatives pricing methodology cannot be used in case of …
Study on price formation in financial markets with a single default event.
problem Equilibrium price formation in financial markets with a single default risk.
method Characterized optimal strategies using quadratic-growth BSDEs, derived market-clearing condition, and established mean-field BSDE solvability.
result Characterized equilibrium risk premium and its dependence on default risk factors.
Proposes deep hedging for index options using implied volatility surface.
problem Managing risk in index option portfolios with complex dynamics.
method Integrates surface-informed decisions with multiple hedging instruments, accounting for transaction costs and variance risk premium.
result Consistently outperforms traditional hedging strategies across various market conditions.
(Early) AI Compute Asset Pricingq-fin.PR
The paper analyzes the pricing of a new compute futures asset.
problem Uncertainty in AI adoption and pricing of compute capital.
method An asset-pricing framework for compute futures, including synthetic futures pricing.
result Preliminary evidence suggests a positive compute risk premium.
In electricity markets, it is sensible to use a two-factor model with mean reversion for spot prices. One of the factors is an Ornstein-Uhlenbeck (OU) process driven by a Brownian motion and accounts for the small variations. The other factor is an OU process driven by a pure jump Lévy process and models the characteri…
Study finds stocks with common firm fears earn lower returns.
problem Identifying and quantifying firm-level investor fears.
method Analysis of equity options to identify common firm-level fears and their impact on stock returns.
result Stocks with exposure to common bad fears earn lower returns and require higher compensation.
Noise, risk premium, and bubbleq-fin.GN
The existence of the pricing kernel is shown to imply the existence of an ambient information process that generates market filtration. This information process consists of a signal component concerning the value of the random variable X that can be interpreted as the timing of future cash demand, and an independent no…
Proposes a new model to price options considering market forces beyond Black-Scholes.
problem Tackles the limitations of the Black-Scholes model in capturing unexpected market behaviors.
method Uses the analogy between quantum harmonic oscillator and financial market dynamics to propose a new market force-driven model.
result Shows how various market forces can be incorporated to modify option pricing, providing practical applications.
We show that different rates should be used for borrowing and discount rates, and that the risk-free rate should be used for discounting when assessing and comparing the cost of energy accross diffferent producers and technologies, on the example of photovoltaics. Recent quantitative models using the same rate for borr…
This paper investigates the time-varying risk-premium relation of the Chinese stock markets within the framework of cross-sectional momentum and contrarian effects by adopting the Capital Asset Pricing Model and the French-Fama three factor model. The evolving arbitrage opportunities are also studied by quantifying the…
The Financialization of Proof-of-Stake: Asymptotic Centralization under Exogenous Risk Premiumsq-fin.GN
Model shows PoS networks can be captured by external finance, leading to centralization.
problem Long-term centralization of PoS networks under external finance pressures.
method Heterogeneous macroeconomic model with two actor classes: investors and consumers.
result External finance forces PoS networks to centralize, leading to zero internal staking yield.
Investors benefit from long horizons in a market with mean-reverting equity returns.
problem Optimal portfolio choice in a market with mean-reverting risk-free rate and equity risk-premium.
method Mean-variance optimization, Euler-Lagrange equation, Calculus of Variations, spectral problem.
result Optimal policies are characterized by eigenvalues of the lambda-matrix, leading to better risk-return trade-offs for long-term investors.
We build a general model for pricing defaultable claims. In addition to the usual absence of arbitrage assumption, we assume that one defaultable asset (at least) looses value when the default occurs. We prove that under this assumption, in some standard market filtrations, default times are totally inaccessible stoppi…
A new stock index model simplifies high-dimensional stock data.
problem Reflecting the overall stock market activity in high-dimensional data.
method Manifold learning and feature detection on discrete Laplace-Beltrami operator.
result The MF index series approximates the stock market better and has lower risk.
We decompose the squared price-of-risk premium into three components: intervention-stable premium, confounding wedge, and information loss.
problem Decomposing the squared price-of-risk premium into its components
method Identifying an order-three obstruction to aggregation across portfolios
result The decomposition is estimable and detectable with a permutation-calibrated screen
Asset Pricing and Deep Learningq-fin.ST
Deep learning improves asset pricing and risk premium measurement.
problem Improving asset pricing and risk premium measurement using deep learning.
method Investigates various deep learning methods for asset pricing, especially for risk premia measurement.
result RNNs with memory mechanism and attention have the best performance in terms of predictivity.
This paper examines momentum spillover across multiple asset classes using only pricing data.
problem Challenges in studying momentum spillover across diverse asset classes due to lack of common characteristics.
method Utilised a linear and interpretable graph learning model to reveal momentum spillover network.
result Network momentum strategy yields a Sharpe ratio of 1.5 and an annual return of 22%.
Testing procedures for predictive regressions with lagged autoregressive variables imply a suboptimal inference in presence of small violations of ideal assumptions. We propose a novel testing framework resistant to such violations, which is consistent with nearly integrated regressors and applicable to multi-predictor…
We show that the martingale component in the long-term factorization of the stochastic discount factor due to Alvarez and Jermann (2005) and Hansen and Scheinkman (2009) is highly volatile, produces a downward-sloping term structure of bond Sharpe ratios, and implies that the long bond is far from growth optimality. In…
Quantum crypto-economics: Blockchain prediction markets for the evolution of quantum technologyq-fin.PR
Quantum crypto-economics models price risks in blockchain technology.
problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.