A Study of the Performance of Option Strategy Benchmark Index in Global Option Markets

While most previous studies have analyzed the performance of the Option Strategy Benchmark Index (SBI) in a specific market such as S&P500 and KOSPI200, this study comprehensively investigates the performance of the option SBIs in nine global options markets in Europe, Asia, and Oceania. In the empirical analysis using the sample data from September 2008 to April 2019, the main results of this study are as follows. First, most of the option SBIs generally provide better performance than the simple buy-and-hold strategy, which is mainly due to a reduction in risk rather than improvement in returns. Second, the option SBIs based on straddle or protective put, one of the most popular option trading strategies, perform poorly in almost all markets, whereas the option SBIs based on covered call or (cash) covered put show relatively good performance. Finally, there is no significant difference in the performance of the option SBIs between markets in the same region or those with a similar level of development. However, we found significant differences in the performance of the option SBIs between Europe and Asia and developed and emerging markets.

Investor Taxes and Option Prices

We examine whether tax-sensitive investors play a significant role in options markets by examining whether option prices reflect investor taxes. Existing empirical option pricing literature ignores taxes. We exploit a unique setting where “index” options on the S&P 500 Index (SPX) and nearly identical “non-index” options on the exchange traded fund (ETF) tracking the S&P 500 Index (SPY) face different tax treatments. We find that higher investor taxes reduce option prices, indicating tax capitalization in options. We find consistent results when analyzing options around the investor tax changes enacted by the American Taxpayer Relief Act (ATRA) of 2012, and for options on stock indices other than the S&P 500 (e.g., Russell 2000). Altogether, our findings provide new evidence of an additional item – investor taxes – influencing option prices, suggesting that tax-sensitive investors play a non-trivial role in options markets and that taxes warrant consideration in broader options research.

Why Do Option Prices Predict Stock Returns? The Role of Price Pressure in the Stock Market

Stock and options markets can disagree about a stock’s value because of informed trading in options and/or price pressure in the stock. The predictability of stock returns based on this cross-market discrepancy in values is especially strong when accompanied by stock price pressure, and it does not depend on trading in options. We argue that option-implied prices provide an anchor for fundamental stock values that helps to distinguish stock price movements resulting from pressure versus news. Overall, our results are consistent with stock price pressure being the primary driver of the option price-based stock return predictability. This paper was accepted by Tyler Shumway, finance.

Neural networks and arbitrage in the VIX

The Chicago Board Options Exchange Volatility Index (VIX) is considered by many market participants as a common measure of market risk and investors’ sentiment, representing the market’s expectation of the 30-day-ahead looking implied volatility obtained from real-time prices of options on the S&P 500 index. While smaller deviations between implied and realized volatility are a well-known stylized fact of financial markets, large, time-varying differences are also frequently observed throughout the day. Furthermore, substantial deviations between the VIX and its futures might lead to arbitrage opportunities on the VIX market. Arbitrage is hard to exploit as the potential strategy to exploit it requires buying several hundred, mostly illiquid, out-of-the-money (put and call) options on the S&P 500 index. This paper discusses a novel approach to predicting the VIX on an intraday scale by using just a subset of the most liquid options. To the best of the authors’ knowledge, this the first paper, that describes a new methodology on how to predict the VIX (to potentially exploit arbitrage opportunities using VIX futures) using most recently developed machine learning models to intraday data of S&P 500 options and the VIX. The presented results are supposed to shed more light on the underlying dynamics in the options markets, help other investors to better understand the market and support regulators to investigate market inefficiencies.

Index Option Trading Activity and Market Returns

Do order flows in index derivatives play an informational role? Weekly index put order flow on the International Securities Exchange positively and robustly predicts weekly S&P 500 index returns. This result obtains mainly for net put buying and is stronger in high VIX periods and in periods following macroeconomic announcements. We explore rationales for our findings, which include investor sentiment, the notion that market makers trade on information in options markets, and option-based risk protection strategies used by retail investors. The last explanation accords best with our analysis. This paper was accepted by Tyler Shumway, finance.

Empirical Evidence of the Causative Association between Spot, Futures and Options Market: An ARDL Model Approach

Purpose: The purpose of this paper is to explore and provide evidence about the nature of short run causal relationship as well as the speed with which prices adjust towards achieving the long run equilibrium between cash and FAO markets in India as represented by National Stock Exchange. The study uses individual stocks for studying the underlying relationship.Design/Methodology: The paper makes use of the auto regressive distributed lag model to study the causal relationship between spot, futures and options markets. The study makes use of the 15-minute interval trades data for the purpose of analysis.Findings: The ARDL model shows a long run association between spot, futures & options (both call & put) prices but we do not have sufficient statistical evidence to conclude the short run causal association between the variable except for call and put options.Practical Implications: The results indicate that derivative markets are not leading the spot market but spot market contributes towards price discovery in the FAO markets. Potential investors can take their positions and design their portfolio in the cash and FAO segments using the insights provided by this piece of work.Originality/Value: This paper is an original piece of work towards evidencing the causative association between spot, futures and options markets using individual securities. Matters pertaining to price discovery process in Indian financial markets are issues of interest for financial thinkers, traders, investors and financial analysts.

Informed Trading Reactions to New Private Information: Evidence from Nonpublic Merger Negotiations

Theory provides competing predictions on whether informed investors immediately trade on newly generated private information. We address this question using Securities and Exchange Commission–mandated disclosures to identify the dates when new private information about target or acquiring firm value is created. We find that informed investors immediately trade on new private information in both the stock and options markets. Next, we investigate which factors drive the speed of these investors’ trading reactions to newly generated private information. We show that cross-sectional variation in the speed of their trading reactions can be explained by the number of privately informed investors, institutional ownership, the expected profits from informed trading and associated risk of attracting the attention of enforcement agencies, and the existence of public information about the acquisition deal. This paper was accepted by David Simchi-Levi, finance.