Can we capture the explosive nature of volatility skew observed in the market, without resorting to non-Markovian models? We show that, in terms of skew, the Heston model cannot match the market at both long and short maturities simultaneously. We introduce Abi Jaber (2019)'s Lifted Heston model and explain how to price options with it using both the cosine method and standard Monte-Carlo techniques. This allows us to back out implied volatilities and compute skew for both models, confirming that the Lifted Heston nests the standard Heston model. We then produce and analyze the skew for Lifted Heston models with a varying number N of mean reverting terms, and give an empirical study into the time complexity of increasing N. We observe a weak increase in convergence speed in the cosine method for increased N, and comment on the number of factors to implement for practical use.

In this thesis, we propose a new and simple approach of extending the single-factor Heston stochastic volatility model to a more flexible one in solving option pricing problems.  In this approach, the volatility process for the underlying asset dynamics depends on the time to maturity of the option. As this idea is inspired by the Heath-Jarrow-Morton framework which models the evolution of the full dynamics of forward rate curves for various maturities, we name this approach as the HJM-type stochastic volatility (HJM-SV)  model. We conduct an empirical analysis by calibrating this model to real-market option data for underlying assets including an equity  (ABB stock) and a market index (EURO STOXX 50), for two separated time spans from Jan 2017 to Dec 2017 (before the COVID-19 pandemic) and from Nov 2019 to Nov 2020 (after the start of COVID-19 pandemic). We investigate the optimal way of dividing the set of option maturities into three classes, namely, the short-maturity, middle-maturity, and long-maturity classes. We calibrate our HJM-SV model to the data in the following way, for each class a single-factor Heston stochastic volatility model is calibrated to the corresponding market data. We address the question that how well the new HJM-SV model captures the feature of implied volatility surface given by the market data.

The purpose of our thesis is to examine the relationship between option implied volatility and analyst consensus recommendation revisions. We offer a Swedish perspective on the growing popularity of equity options and its relationship with different stock market participants and returns. We chose the Swedish options market since it is substantially smaller in relation to the stock market than in countries such as the US, it is also not as studied. First, we conduct an event study using a fixed effects OLS model to determine the effect of analysts’ consensus recommendation revision. Second, we use a probit regression model to determine the probability of a revision given the option implied volatility. We find that there is generally a statistically significant relationship between option implied volatility and analyst consensus recommendation revisions as well as with abnormal returns, providing further discussion on the information sharing between the two markets and its participants.

This thesis studies realized volatility (RV), implied volatility (IV) and their applications in stochastic volatility models. The first essay uses both daytime and overnight high-frequency price data for equity index futures to estimate the RV of the S\&P500 and NASDAQ 100 indexes. Empirical results reveal strong inter-correlation between the regular-trading-time and after-hour RVs, as well as a significant predictive power of overnight RV on daytime RV and vice versa. We propose a new day-night realized stochastic volatility (DN-SV-RV) model, where the daytime and overnight returns are jointly modeled with their RVs, and their latent volatilities are correlated. The newly proposed DN-SV-RV model has the best out-of-sample return distribution forecasts among the models considered. The second essay extends the realized stochastic volatility model by jointly estimating return, RV and IV. We examine how RV and IV enhance the estimation of the latent volatility process for both the S\&P500 index and individual stocks. The third essay re-examines asymmetric stochastic volatility (ASV) models with different return-volatility correlation structures given RV and IV. We show by simulation that estimating the ASV models with return series alone may infer erroneous estimations of the correlation coefficients. The incorporation of volatility measures helps identify the true return-volatility correlation within the ASV framework. Empirical evidence on global equity market indices verifies that ASV models with additional volatility measures not only obtain significantly different estimations of the correlations compared to the benchmark ASV models, but also improve out-of-sample return forecasts. / Thesis / Doctor of Philosophy (PhD)

Models of the term structure of interest rates play a central role in the modern theory of pricing bonds and other interest rate claims. Term structure models based on the principle of no-arbitrage, especially those of the Heath-Jarrow-Morton (1992) class, have become very popular recently, both with academics and practitioners. Surprisingly however, although the implied volatility function plays a crucial role in these no-arbitrage term structure models, there is little systematic evidence to guide optimal model specification within this broad class. We study the implied volatility in the Heath-Jarrow-Morton framework using Eurodollar futures options data. We estimate a daily time series of forward rates within the HJM framework such that, by construction, the predicted futures prices from our model exactly match the observed futures prices. Next, we estimate a daily time series of volatility parameters such that the sum of squared errors between futures options prices predicted by the model and observed futures options prices is minimized. We use the six different volatility specifications suggested by Amin and Morton (1994) within the HJM class of models to price interest rate claims. Since the volatilities are the only unobservables, we use these models to infer the volatilities from the market prices of Eurodollar futures options over the 1987-1998 periods. The minimized sum of squared errors in the option prices is used as the measure of accuracy of each specific model. Each model differs from the others in its ability to match the market option prices and the time required for the computation. We compare the performances of the six volatility specifications in the accuracy-versus-computation time tradeoff. We document the systematic biases between the model and market prices as a function of option type, maturity, and moneyness. We also examine alternative numerical implementations of HJM models using the six volatility specifications. In particular, we analyze the impact on accuracy and computation time of using different numbers of time-steps. We also examine the effect of using time-steps of varying lengths within the same estimation procedure, and of ordering the time-steps in different ways. / Ph. D.

This study examines the relationship between company management guidance, and ex-ante crash risk over the duration of 2008(Jan 2006-Dec 2009) financial crisis using the implied volatility skew, which is based upon ex-ante volatility implied by the pricing model developed by Black-Scholes (1973). The study finds that over the duration of this crisis period, management guidance decreases with a rise in ex-ante crash risk. Further, the study provides evidence on the relationship of management guidance and earnings volatility, and how that is affected by a firm's industry product concentration based on the Herfindahl-Hirschman Index (HHI) score.

No description available.

Master of Science / Department of Agricultural Economics / Ted C. Schroeder / Glynn T. Tonsor / Cattle feeders face significant profit risk when placing cattle on feed. Risks arise from both financial and biological sources. To date, few standardized measures exist to measure current risks against historic levels, or to obtain forward looking risk estimates. Those that do exist could benefit from updates and inclusion of additional risk elements. This study measures the risk of expected profits when cattle are placed on feed. This study creates a forward-looking estimate of expected feedlot profits using futures and options market data as price forecasts. Joint probability distributions are created for prices and cattle performance variables affecting feedlot profit margins. Monte Carlo simulation techniques are then employed to generate probability distributions of expected feedlot profits. Results show cattle feeding is a risky business and cattle feeders have been placing cattle on feed facing significantly negative expected returns since June, 2010. This assessment of negative expected profits is consistent with other findings. Over the study’s 2002 to 2013 time frame, the relative risk to cattle feeding profits accounted for by feed costs has been increasing, while the relative risk levels from feeder cattle and fed cattle prices remain steady. Additionally, the probability of realized per-head profits greater than $100 has been decreasing since 2009 and the probability of realized per-head profits less than $-100 has been increasingly rapidly.

本文主要探討股票選擇權的隱含波動率是否能夠有效反應公司的財務風險與違約風險，並使用Merton (1974)與Black and Scholes (1973)的選擇權評價模型推導出每日的負債權益比率，作為公司財務風險的代理變數；違約風險的代理變數則是使用Bandyopadhyay (2007)的風險中立違約機率與真實世界違約機率。首先，本文觀察到隱含波動率和股票報酬率之間的確存在負向關係，除此之外，也發現非系統隱含波動率與股票報酬率之間也有負向關係。進一步研究非系統隱含波動率是否能夠反應公司風險，結果顯示當公司的財務風險與違約風險增加時，非系統隱含波動率會上升。最後，本文比較非系統隱含波動率與GARCH模型的波動率對公司財務風險與違約風險的資訊內涵，並執行包圍檢定、工具變數兩階段迴歸分析與非包覆模型的檢定，發現非系統隱含波動率的資訊內涵無法包圍GARCH模型的波動率，但兩者的資訊內涵互相交集。

Equity Risk Premium (ERP) is the cornerstone in Financial Economics. It is a basic requirement in stock valuation, evaluation of portfolio performance and asset allocation. For the last decades, several studies have attempted to investigate the relationship between macroeconomic drivers of ERP. In this work, I empirically investigate the macroeconomic determinants of UK ERP. For this I parsimoniously cover a large body of literature stemming from ERP puzzle. I motivate the empirical investigation based on three mutually exclusive theoretical lenses. The thesis is organised in the journal paper format. In the first paper I review the literature on ERP over the past twenty-eight years. In particular, the aim of the paper is three fold. First, to review the methods and techniques, proposed by the literature to estimate ERP. Second, to review the literature that attempts to resolve the ERP puzzle, first coined by Mehra and Prescott (1985), by exploring five different types of modifications to the standard utility framework. And third, to review the literature that investigates and develops relationship between ERP and various macroeconomic and market factors in domestic and international context. I find that ERP puzzle is still a puzzle, within the universe of standard power utility framework and Consumption Capital Asset Pricing Model, a conclusion which is in line with Kocherlakota (1996) and Mehra (2003). In the second paper, I investigate the impact of structural monetary policy shocks on ex-post ERP. More specifically, the aim of this paper is to investigate the whether the response of UK ERP is different to the structural monetary policy shocks, before and after the implementation of Quantitative Easing in the UK. I find that monetary policy shocks negatively affect the ERP at aggregate level. However, at the sectoral level, the magnitude of the response is heterogeneous. Further, monetary policy shocks have a significant negative (positive) impact on the ERP before (after) the implementation of Quantitative Easing (QE). The empirical evidence provided in the paper sheds light on the equity market’s asymmetric response to the Bank of England’s monetary policy before and after the monetary stimulus. In the third paper I examine the impact of aggregate and disaggregate consumption shocks on the ex-post ERP of various FTSE indices and the 25 Fama-French style value-weighted portfolios, constructed on the basis of size and book-to-market characteristics. I extract consumption shocks using Structural Vector Autoregression (SVAR) and investigate its time-series and cross-sectional implications for ERP in the UK. These structural consumption shocks represent deviation of agent’s actual consumption path from its theoretically expected path. Aggregate consumption shocks seem to explain significant time variation in the ERP. At disaggregated level, when the actual consumption is less than expected, the ERP rises. Durable and Semi-durable consumption shocks have a greater impact on the ERP than non-durable consumption shocks. In the fourth and final paper I investigate the impact of short and long term market implied volatility on the UK ERP. I also examine the pricing implications of innovations to short and long term implied market volatility in the cross-section of stocks returns. I find that both the short and the long term implied volatility have significant negative impact on the aggregate ERP, while at sectoral level the impact is heterogeneous. I find both short and long term volatility is priced negatively indicating that (i) investors care both short and long term market implied volatility (ii) investors are ready to pay for insurance against these risks.