Suchergebnisse

Financial markets serve numerous roles, amongst them of course is the uncoerced exchange of securities. In addition to that role, they serve a very useful function of conveying to market observers the information about the future, with the challenge being our ability to elicit and interpret that information. This paper addresses that latter function regarding the option markets which provide the value for the VIX 30-day implied volatility on the S&P 500 Market Index. It is demonstrated that the peak values of VIX during Persian Gulf I (1990–1991) and Persian Gulf II (2003) were nearly identical. The VIX measure is then computed during the crises of 2008–2009, 2020 and 2022. Critically, this paper demonstrates the valuable informational content provided by the "term structure of VIX", the set of cross-sectional implied volatilities observed with different times to expiration.

This paper applies long-memory techniques (both parametric and semi-parametric) to examine whether Brexit has led to any significant changes in the degree of persistence of the FTSE (Financial Times Stock Index) 100 Implied Volatility Index (IVI) and of the British pound's implied volatilities (IVs) vis-à-vis the main currencies traded in the FOREX (foreign exchange market), namely the euro, the US dollar and the Japanese yen. We split the sample to compare the stochastic properties of the series under investigation before and after the Brexit referendum, and find an increase in the degree of persistence in all cases except for the British pound-yen IV, whose persistence has declined after Brexit. These findings highlight the importance of completing swiftly the negotiations with the European Union (EU) to achieve an appropriate Brexit deal.

Purpose
While numerous empirical studies have tried to model and forecast the oil price volatility over the years, such attempts using the crude oil volatility index (OVX) rarely exist. In order to conceal this void, the purpose of this paper is to investigate whether including OVX in the realized volatility (RV) models improve the accuracy of predictions.


Design/methodology/approach
At the empirical stage, the authors employ several measures to frame the RV of crude oil futures returns. In particular, the authors use three different range-based RV estimators recommended by Parkinson (1980), Rogers and Satchell (1991) and Alizadeh et al. (2002), respectively.


Findings
The findings reveal that the information content of crude OVX helps to provide more accurate volatility predictions in comparison to the base-line RV model which contains only historical oil volatilities. Besides, the forecast encompassing test further suggests that the modified RV model (when OVX is introduced in the base-line RV model) forecast encompasses the conventional RV forecast in majority of the cases.


Practical implications
Since forecasting oil price volatility plays a vital role in portfolio optimization, derivatives pricing, optimum asset allocation decisions and risk management, the findings of this study thus carry important implications for energy economists, investors and policymakers.


Originality/value
This paper adds to the existing literature, since it is one of the initial studies to explore whether OVX is informative about the realized variance of the US oil market returns. The findings recommend that the information content of oil implied volatilities should be taken into account when modeling the US oil market volatility. In addition, range-based measures should be utilized while estimating the RV.

AbstractThis paper compares the ability of four valuation models — the Pure Diffusion model of Black‐Scholes‐Merton, the Absolute Diffusion and Pure Jump models of Cox‐Ross, and the mixed Jump‐Diffusion model of Merton — to explain the observed behavior of market prices of foreign currency options. The empirical tests are based on a comparison of the pattern of implied volatilities obtained from option market prices and the Black‐Scholes‐Merton model with those expected theoretically if exchange rates follow the four stochastic processes specified above. The results of the comparison show that the pattern of implied volatilities is most consistent with the mixed Jump‐Diffusion model.

Cover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1: The Basics of Algorithmic Trading -- Historical Market Data -- Live Market Data -- Backtesting and Trading Platforms -- Brokers -- Performance Metrics -- Portfolio Optimization -- Summary -- Exercises -- Chapter 2: Factor Models -- Time-series Factors -- Cross-sectional Factors -- A Two-Factor Model -- Using Option Prices to Predict Stock Returns -- 1) Implied Moments -- 2) Monthly Change in Implied Volatilities -- 3) Put-call Implied Volatilities -- 4) OTM Put-ATM Call Implied Volatilities -- 5) Daily Change in Implied Market Volatility -- Short Interest -- Liquidity -- Statistical Factors -- Putting Them All Together -- Summary -- Exercises -- Chapter 3: Time-Series Analysis -- AR(p) -- ARMA(p, q) -- VAR(p) -- State Space Models -- Summary -- Exercises -- Chapter 4: Artificial Intelligence Techniques -- Stepwise Regression -- Regression Tree -- Cross Validation -- Bagging -- Random Subspace and Random Forest -- Boosting -- Classification Tree -- Support Vector Machine -- Hidden Markov Model -- Neural Network -- Data Aggregation and Normalization -- Application to Stocks Selection -- Summary -- Exercises -- Chapter 5: Options Strategies -- Trading Volatility without Options -- Predicting Volatility -- Event-Driven Strategies -- Gamma Scalping -- Dispersion Trading -- Cross-Sectional Mean Reversion of Implied Volatility -- Summary -- Exercises -- Chapter 6: Intraday Trading and Market Microstructure -- Latency Reduction -- Order Type and Routing Optimization -- Adding Liquidity -- Taking Liquidity -- Routing to Dark Pools -- Adverse Selection Reduction -- Backtesting Intraday Strategies -- Order Flow -- Order Book Imbalance -- Summary -- Exercises -- Chapter 7: Bitcoins -- Bitcoin Facts -- Time-Series Techniques -- Mean Reversion Strategy -- Artificial Intelligence Techniques.

This Dissertation builds a routine to extract inflation expectations from options through the risk-neutral distribution methodology, based on the Black-Scholes pricing model. The data includes cap and floor options, equivalents of call and put options with inflation as the underlying, with some technical differences. The methodology includes extracting implied volatilities from observed prices of caps and floors, then use a cubic interpolation on implied volatilities, to be able to fit to the volatility smile. Further, taking advantage of Breeden and Litzenberger (1976), the initial density functions are calculated as the second derivative of the option price in the Black-Scholes model. For a more encapsulating approach, the cap and floor density functions were aggregated, thereby being able to compare net effects with objectives of the monetary policy. A robustness test was also performed to analyze price variations along the two days prior, and after, the announcements of each policy, using floor options and inflation-linked swaps. The results show that, the ABSPP & CBPP3 and the TLTRO I announcements registered decreases, although the variations in prices and densities are small, therefore suggesting the importance of anticipation of measures and of other transmission channels to assess the effects of these policies. This is in line with the September 2015 report by the Vice-President of the ECB, Vítor Constâncio, that acclaims the effectiveness of the non-conventional monetary policies in controlling low inflation expectations, although affirming that the below, but close to, 2% goal of inflation has not been met. ; Esta Dissertação elabora uma rotina para extrair expetativas de inflação através de uma metodologia de distribuição neutra de risco, baseada no modelo de preços de Black-Scholes. A data utilizada inclui opções cap e floor, equivalentes às calls e puts mas com inflação subjacente, com certas diferenças tecnicas. A metodologia engloba extrair volatilidades implicitas dos preços das opções observadas, procedendo uma interpolação cúbica nas volatilidades implicitas, para ser possível aplicar um fit ao grafico da volatilidade. Tomando partido do trabalho realisado por Breenden e Litzenberger (1978), as funções de densidade iniciais são calculadas apartir da segunda derivada da função do preço de opções do modelo Black-Scholes. Para uma perspectiva completa, procedeu-se ao agregamento das funções de densidade dos caps e floors numa única garantindo também as comparações com objectivos da politica monetária. Um teste de rebustez foi também conduzido através das variações dos preços de floors e swaps, dois dias antes e depois dos anuncios das politicas. Os resultados indicam que para quantificar com sucesso os efeitos destas politicas, um periodo de tempo maior deve ser considerado, sugerindo ainda a importância da antecipação das medidas e outros canais de transmissão para averiguar os efeitos da mesma. Isto está em linha com o documento apresentado em Setembro de 2015 por Vítor Constâncio, VP do ECB, que enalteceu a efetividade das medidas de politica monetária não convencionais no combate às expectativas de baixa inflação, acrescentado ainda que o objectivo do banco central de inflação inferior, mas perto de, 2% ainda não foi atingido.