Options-based forecasts of futures prices in the presence of limit moves

The reported analysis examines a simultaneous estimation option-based approach to forecast futures prices in the presence of daily price limit moves. The procedure explicitly allows for changing implied volatilities by estimating the implied futures price and the implied volatility simultaneously. Using futures and futures options data for three agricultural commodities, it is found that the simultaneous estimation approach accounts for the abrupt changes in implied volatility associated with limit moves and generates more accurate price forecasts than conventional methods that rely on only one implied variable.     

Equity market valuation,systematic risk and monetary policy

This study examines the relationship between equity market valuation and risk indicators that portend economic downswings. The indicators are implied options volatility, Treasury-Eurodollar (TED) spread and exchange rate. While implied volatility captures market risk in that it reflects the fear factor embedded in the price of an option, TED spread reflects the default risk premium that is priced into a key short-term credit instrument. Equity markets often show a tendency to reflect the incidence of these risk factors. And because they provide valuable information about the health of the economy, many have argued that equity market valuation be taken into account in the formulation of monetary policy. Results of this study not only show a statistically significant inverse relationship between the stock market and these risk factors, but also evidence of a cointegration. In a variance decomposition of the series, we find that equity valuation is a major contributor to the forecast error variances of each of the risk indicators, a finding that lends tacit support to the argument that risk indicators associated with the equity market be considered in monetary policy decisions.     

An enhanced implied tree model for option pricing: A study on Hong Kong property stock options

This paper empirically tests the practicability of the implied tree models on pricing the major HK real estate stock options and Hang Seng Index (HSI) Options, as an attempt to deal with the problem haunting the Black–Scholes Model in “volatility smiles”. Further, an iterative search procedure is originated to incorporate the idea of node-dependent interest rates to the implied binomial tree model. The results would then be compared with the original Cox, Ross, and Rubinstein (1979) [Cox, J., Ross, S. and Rubinstein, M. (1979), Option pricing: A simplified approach, Journal of Financial Economics, vol.7, no.3 (September), 229–264] tree models (CRR) in order to assess its performance, through an out-of-sample fitness test. The findings illustrate that the implied binomial trees, with node-dependent interest rates, provide a closer estimate of option prices than the original CRR tree models, when options are frequently traded in the market. Encouraging results are obtained from the in-sample fitness test on the implied trees to simulate the spot evolution of HSI options within a short period of time. However, the original CRR tree models outperform the implied tree models on either inactively traded property stock options, or options with distant time-to-maturity. Misrepresentation of future local volatilities, implied by the prices, and data constraints are likely the reasons hindering the development of the implied tree models.     

Do the central bank actions reduce interest rate volatility?

This paper investigates how Central Bank of Brazil (CBB) actions influence market uncertainty. We consider two kinds of actions: the monetary policy decision about the interest rate target and the pure communication event of this decision published one week later. Unlike related papers, we measure the market uncertainty by the implied volatility extracted from interest rate options. Implied volatility is more suitable than physical volatility to assess economic effects since it encompass market beliefs adjusted by risk. We use an event study approach to evaluate the impact of CBB actions. The results show that both the decisions about the target rate and the communication event reduce the interest rate volatility.     

Option-implied preferences adjustments, density forecasts, and the equity risk premium

The main objective of this paper is to analyse the value of information contained in prices of options on the IBEX 35 index at the Spanish Stock Exchange Market. The forward looking information is extracted using implied risk-neutral density functions estimated by a mixture of two-lognormals and several alternative risk adjustments. Our results show that, between October 1996 and March 2000, we can reject the hypothesis that the risk-neutral densities provide accurate predictions of the distributions of future realisations of the IBEX 35 index at 4- and 8-week horizons. When forecasting through risk-adjusted densities the performance of this period is statistically improved and we no longer reject that hypothesis. We show that risk adjustments based on a power specification for the stochastic discount factor—which is the approach used so far in the literature that derives the objective density function from option prices- generates an excessive volatility of risk premia. We use alternative risk adjustments and find that the forecasting performance of the distribution improves slightly in some cases when risk aversion is allowed to be time-varying. Finally, from October 1996 to December 2004, the ex-ante risk premium perceived by investors and that are embedded in option prices is between 12 and 18% higher than the premium required to compensate the same investors for the realised volatility in stock market returns.      

未定权益分析方法与中国宏观金融风险的测度分析

本文利用未定权益分析方法(CCA),在汇集、处理与整合编制多方数据的基础上,通过建立国民经济机构部门层面的风险财务报表,测度了2000—2008年我国的宏观金融风险,并直观展示和分析了该期间国民经济各机构部门风险敞口的动态演变情况。本文在我国特殊的数据背景下,基于我国金融市场发展的现状,探索了测度和监控我国系统性金融风险的具体理论与方法。     

Empirical of the Taiwan stock index option price forecasting model – applied artificial neural network

This work presents a novel neural network model for forecasting option prices using past volatilities and other options market factors. Out of different approaches to estimating volatility in the option pricing model, this study uses backpropagation neural network to forecast prices for Taiwanese stock index options. The ability to develop accurate forecasts of grey prediction volatility enables practitioners to establish an appropriate hedging strategy at in-the-money option.     

Maturity and volatility effects on UK smiles

The smile effect is a result of an empirical observation of the options implied volatility with the same expiration date, across different exercise prices. However, its shape has been under discussion seeming to be dependent on the option underlying security. In this paper, and filling up a scarce empirical research on the topic, we used liquid equity options on 9 stocks traded on the London International Financial Futures and Options Exchange (LIFFE) between August 1990 and December 1991. We tested two different hypothesis for testing two different phenomena: (1) the increase of the smile as maturity approaches; (2) and the association between the smile and the volatility of the underlying stock. In order to estimate implied volatilities for unavailable exercise prices, we modelled the smile using cubic B-spline curves. We found empirical support for the smile intensification (the U-shape is more pronounced) as maturity approaches as well as when volatility rises. However, we found two major sources of disagreement with the literature on stochastic volatility models. First, as maturity approaches, out-of-the-money options implied volatility tends to be higher than the implied volatility of in-the-money options. Second, as the volatility of the underlying asset increases, the implied volatility of in-the-money options tends to be higher than implied volatility of out-of-the-money options.Received: September 2001, Accepted: September 2003, JEL Classification: G13Correspondence to: João L. C. DuqueWe thank Professor Dean A. Paxson (University of Manchester), António Sousa Câmara (University of Strathclyde), Ser-Huang Poon (University of Lancaster) and the attendees of the 26th EFA Annual Conference for helpful comments on previous versions of this paper. We also want to thank to two anonymous referees for their relevant comments and suggestions. Financial support granted by the Fundação para a Ciência e a Tecnologia (FCT) and the Programa Praxis XXI is gratefully acknowledged.     

Firm-specific risk and IPO market cycles

This article characterizes the role of risk in the initial public offering (IPO) cycle. While most of the previous literature uses the volatility of IPO initial returns to measure risk, we focus on different risk measures, namely firm-level systematic and idiosyncratic volatilities and the market-wide implied volatility index (VIX), to assess their role in the IPO cycle. Our results shed new light on (1) which risk measure is important in the determination of IPO cycles, (2) the temporal pattern of each risk component across issuing firms and (3) the relationship between market-wide uncertainty and IPO risk. Our findings reveal a lead-lag relationship between IPO waves, VIX and the IPO systematic risk measure. We also highlight the fact that market-level uncertainty predicts IPO activity and the level of idiosyncratic risk of the next-period-issuing firms. Issuing firms’ systematic risk can only be predicted by the systematic risk of firms now proceeding to their offering. The main implication resulting from our study is that one can better anticipate ‘hot-issue’ markets, as well as the specific risk components of future new issues. This will help improve upon the regulatory environment, IPO investment decisions and IPO timing given market receptivity.     

The information content of implied volatility in developed versus developing FX markets

This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies.     

The determinants of exchange settlement practices and the implication of volatility smile: Evidence from the Taiwan Futures Exchange

This paper proposes that the Taiwan Futures Exchange (TAIFEX) adopts a linear extrapolation method to set the settlement price for the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) options with less liquidity and thin trading. The empirical results indicate that the settlement-price-determined implied volatility is a smile function, consistent with the pattern of the market-price-determined implied volatility. Moreover, we examine the influence of economic factors on the TAIFEX's decision regarding the parameters of implied volatility function. Compared with the economic determinants of market-force-driven volatility parameters, the TAIFEX inappropriately values the impacts of the parameters of prior days, current stock returns, distribution of stock returns, long-term measurement of the stock market trend, market transaction cost, and time to maturity.     

Pricing bond options under a Markovian regime-switching Hull–White model

In this paper, we investigate the valuation of bond options under a Markovian regime-switching Hull–White model, where both the mean-reverting level and the volatility of the interest rate are modulated by a continuous-time, finite-state Markov chain. Using techniques of measure changes and the inverse Fourier transform, we obtain an integral representation for the pricing formula of a standard European option on a zero-coupon bond. Numerical results for the prices and implied volatilities of bond options arising in our model are given in a two-regime case.     

Effects of explicit FOMC policy-rate guidance on equities and risk measures

We quantify the impact of explicit Federal Open Market Committee (FOMC) policy-rate guidance used as an unconventional monetary-policy tool at the zero lower bound of the policy rate on US equity prices, as well as on the risk indicators of credit and CDS spreads, implied volatilities and US equity index risk reversals. We find that explicit FOMC policy-rate guidance announcements at the zero lower bound led to a significant increase in US equity prices, for an aggregate equity index as well as for US commercial bank and US nonfinancial equities. Moreover, we find that they led to a significant reduction in some credit spreads. They also led to a significant reduction in an implied volatility index for US government bonds, as well as in the absolute value of US equity risk reversals, implying a lower perceived risk attached to a large fall in the equity index.     

Asset prices and economic fluctuations: The implications of stochastic volatility

This paper investigates whether the multi-factor stochastic volatility of stock returns is related to economic fluctuations and affects asset prices. We address these issues in a dynamic Fama-French three-factor volatility model framework. Consistent with the ICAPM with stochastic volatility (Campbell et al., 2017), we find that the conditional volatility of the size and value factors is significantly related to economic uncertainty. These volatilities are also significant pricing factors. The out-of-sample forecasting analysis further reveals that the conditional volatility can predict stock returns and deliver economic gain in asset allocation. Our analysis sharpens the understanding on the link between the stock market and economic fundamentals.     

A common factor of stochastic volatilities between oil and commodity prices

This article analyses the multivariate stochastic volatilities (SVs) with a common factor influencing volatilities in the prices of crude oil and agricultural commodities, used for both biofuel and nonbiofuel purposes. Modelling the volatility is crucial because the volatility is an important variable for asset allocation, risk management and derivative pricing. We develop a SV model comprising a latent common volatility factor with two asymptotic regimes with a smooth transition between them. In contrast to conventional volatility models, SVs are generated by the logistic transformation of latent factors, which comprise two components: the common volatility factor and an idiosyncratic component. We present a SV model with a common factor for oil, corn and wheat from 8 August 2005 to 10 October 2014, using a Markov chain Monte Carlo method to estimate the SVs and extract the common volatility factor. We find that the volatilities of oil and grain markets are persistent. According to the estimated common volatility factor, high volatility periods match the 2007–2009 recession and the 2007–2008 financial crisis quite well. Finally, the extracted common volatility factor exhibits a distinct pattern.     

Forecasting European economic policy uncertainty

Forecasting the economic policy uncertainty in Europe is of paramount importance given the ongoing sovereign debt crisis. This paper evaluates monthly economic policy uncertainty index forecasts and examines whether ultra‐high frequency information from asset market volatilities and global economic uncertainty can improve the forecasts relatively to the no‐change forecast. The results show that the global economic policy uncertainty provides the highest predictive gains, followed by the European and US stock market realized volatilities. In addition, the European stock market implied volatility index is shown to be an important predictor of the economic policy uncertainty.     

Intraday return and volatility relationships between the Ibex 35 spot and futures markets

This paper analyses the intraday lead-lag relationships between returns and volatilities in the Ibex 35 spot and futures markets. Using hourly data, we jointly analyze the interactions between markets, estimating a bivariate error correction model with GARCH perturbations which captures stochastically the presence of an intraday U-shaped curve for both spot and futures market volatility. Our findings show a bidirectional causal relationship between market volatilities, with a positive feedback. This two-way transmission of volatility is consistent with market prices evolving according to a long-run equilibrium relationship, and shocks affecting both markets in the same direction. Our empirical results also support a unidirectional cross interaction from futures to spot market returns. This pattern suggests that the futures market leads the spot market in order to incorporate the arrival of new information.     

Fuzzy Value-at-risk: Accounting for Market Liquidity

In this paper we present a value-at-risk measure which accounts for market liquidity. We show that taking into account market liquidity implies a decoupling of valuation of long and short positions. We present a pricing model, named fuzzy measure model, that yields different values for positions of different sign and that can be usefully exploited to account for liquidity risk. This methodology is well-suited to price options when the distribution of the underlying asset is not known precisely, as in the case of implied options in corporate claims or real options. As an example, we apply our pricing technique to an option based model of value-at-risk, in line with the Merton and Perold approach, and we recover different value-at-risk figures for long and short positions.
(J.E.L.: C00, D81, G12).     

Exploiting volatility movements in the Sydney futures exchange's bank bill contract

An appropriate stochastic model was fitted to one year of data on the implied volatility of options on 90 day bank accepted bill futures contracts traded in the Sydney Futures Exchange. The model used was ARIMA augmented with day of the week variables, an option time to maturity variable, and recent values of historic volatility. The high ex-post predictive accuracy of the model was then employed as the central element of a strategy of buy low/sell high volatility.We employed two trading schemes with suitably constructed Delta neutral portfolios comprising bill futures and call and put options on those futures over a period of six months, to test whether speculative trading profit could be earned. The existence of trading profits before transaction costs validated the potential of the buy low/sell high volatility strategies to generate speculative profits. The absence of any such trading profits after transaction costs however, showed that the market pricing of these securities is such that the dependencies within implied volatility cannot be profitably exploited.This result may be interpreted as evidence supporting an hypothesis of a semi-strong form of market efficiency.