State price density analysis of equity market volatility: Tools for fund managers

2014 ◽  
Author(s):  
Michael O'Neill
Author(s):  
Peter Christoffersen ◽  
Kris Jacobs ◽  
Xuhui (Nick) Pan

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.


2018 ◽  
Vol 35 (2) ◽  
pp. 222-243
Author(s):  
Scott J. Niblock ◽  
Elisabeth Sinnewe

Purpose The purpose of this paper is to examine whether superior risk-adjusted returns can be generated using monthly covered call option strategies in large capitalized Australian equity portfolios and across varying market volatility conditions. Design/methodology/approach The authors construct monthly in-the-money (ITM) and out-of-the-money (OTM) S&P/ASX 20 covered call portfolios from 2010 to 2015 and use standard and alternative performance measures. An assessment of variable levels of market volatility on risk-adjusted return performance is also carried out using the spread between implied and realized volatility indexes. Findings The results of this paper show that covered call writing produces similar nominal returns at lower risk when compared against the standalone buy-and-hold portfolio. Both standard and alternative performance measures (with the exception of the upside potential ratio) demonstrate that covered call portfolios produce superior risk-adjusted returns, particularly when written deeper OTM. The 36-month rolling regressions also reveal that deeper OTM portfolios deliver greater risk-adjusted returns in the majority of the sub-periods investigated. This paper also establishes that volatility spread variation may be a driver of performance for covered call writing in Australia. Originality/value The authors suggest that deeper OTM covered call strategies based on large capitalized portfolios create value for investors/fund managers in the Australian stock market and can be executed in volatile market conditions. Such strategies are particularly useful for those seeking market neutral asset allocation and less risk exposure in volatile market environments.


10.3386/w5307 ◽  
1995 ◽  
Author(s):  
Geert Bekaert ◽  
Campbell Harvey

Author(s):  
John Gilligan ◽  
Mike Wright

This chapter defines private equity, describes the origins of the private equity market, and examines the data on the size and growth of the private equity industry. Private equity is risk capital provided outside the public markets. The businesses invested in by private equity range from early stage ventures, usually termed venture capital investments, through businesses requiring growth or development capital to the purchase of an established business in a management buyout or buy-in. Much, but not all, of the investing done in the private equity market is by private equity funds. The objective of a private equity fund is to invest equity or risk capital in a portfolio of private companies which are identified and researched by the private equity fund managers. The chapter then considers what private equity fund managers do. It also provides a brief history of private equity before assessing how big the private equity market is.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qing Li ◽  
Songlin Liu ◽  
Misi Zhou

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).


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