Kelly Criterion, State Price Density Equilibrium and Bayesian Statistics

2020 ◽  
Author(s):  
Jan Vecer
Keyword(s):  
Bayesian Statistics ◽  
Kelly Criterion ◽  
State Price ◽  
State Price Density

The State Price Density Implied by Crude Oil Futures and Option Prices

2021 ◽  
Author(s):  
Peter Christoffersen ◽  
Kris Jacobs ◽  
Xuhui (Nick) Pan
Keyword(s):  
The State ◽  
Stock Index ◽  
Economic Conditions ◽  
Option Prices ◽  
Oil Futures ◽  
State Price ◽  
Price Increases ◽  
Crude Oil Futures ◽  
State Price Density ◽  
Positive Return

Abstract Both large oil price increases and decreases are associated with deteriorating economic conditions. The projection of the state price density (SPD) onto oil returns estimated from oil futures and option prices displays a U-shaped pattern. Because investors assign high state prices to large negative and large positive oil returns, the U-shaped SPD may steepen in either tail when economic conditions deteriorate. The positive return region of the SPD is more closely related to economic conditions. The oil SPD contains information about economic conditions and future security returns that is distinct from the information in the stock index SPD.

scholarly journals Nonparametric Estimation of Fractional Option Pricing Model

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qing Li ◽  
Songlin Liu ◽  
Misi Zhou
Keyword(s):  
Option Pricing ◽  
Stock Exchange ◽  
Option Price ◽  
Integral Function ◽  
The State ◽  
Pricing Model ◽  
State Price ◽  
Black Scholes ◽  
Option Pricing Model ◽  
State Price Density

The establishment of the fractional Black–Scholes option pricing model is under a major condition with the normal distribution for the state price density (SPD) function. However, the fractional Brownian motion is deemed to not be martingale with a long memory effect of the underlying asset, so that the estimation of the state price density (SPD) function is far from simple. This paper proposes a convenient approach to get the fractional option pricing model by changing variables. Further, the option price is transformed as the integral function of the cumulative density function (CDF), so it is not necessary to estimate the distribution function individually by complex approaches. Finally, it encourages to estimate the fractional option pricing model by the way of nonparametric regression and makes empirical analysis with the traded 50 ETF option data in Shanghai Stock Exchange (SSE).

Two Trees with Heterogeneous Beliefs: Spillover Effect of Disagreement

2018 ◽  
Vol 54 (4) ◽  
pp. 1791-1819 ◽  
Author(s):  
Bing Han ◽  
Lei Lu ◽  
Yi Zhou
Keyword(s):  
Model Prediction ◽  
Large Firm ◽  
Spillover Effect ◽  
The State ◽  
Heterogeneous Beliefs ◽  
The Novel ◽  
State Price ◽  
State Price Density ◽  
Novel Model

In a model where investors disagree about the fundamentals of two stocks, the state-price density depends on investor disagreements for both stocks, especially the larger stock. This implies that disagreement among investors in a large firm has a spillover effect on the pricing of other stocks owned by these investors. The pricing effects of investor disagreements crucially depend on the average belief biases. Empirical findings support the novel model prediction of a disagreement spillover effect and help reconcile some mixed evidence in the literature.

Macroeconomic information and implied volatility: evidence from Australian index options

2014 ◽  
Vol 6 (1) ◽  
pp. 46-62 ◽  
Author(s):  
Hassan Tanha ◽  
Michael Dempsey ◽  
Terrence Hallahan
Keyword(s):  
Implied Volatility ◽  
Return Distribution ◽  
Index Options ◽  
Content Type ◽  
Market Participants ◽  
Macroeconomic Information ◽  
State Price ◽  
Macroeconomic Announcements ◽  
State Price Density ◽  
The Impact

Purpose – The purpose of this paper is to understand that option pricing is the response of option implied volatility (IV) to macroeconomic announcements. Design/methodology/approach – The authors use high-frequency data on ASX SPI 200 index options to examine the response of option IV, as well as higher moments of the underlying return distribution, to macroeconomic announcements. Additionally, the authors identify the response of the moments as a function of moneyness of the options. Findings – The findings suggest that in-the-money and out-of-the money options have difference characteristics in their responses, leading to the conclusion that heterogeneity in investor beliefs and preferences affect option IV through the state price density (SPD) function. Originality/value – The research contributes to the literature that examines whether IV captures the beliefs of market participants about the likelihood of future states together with the preferences of market participants towards these states. In particular, the authors relate changes in option IV to changes in macroeconomic announcements, through the impact of these announcements on the moments of the SPD function.

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