Improved Dividend Estimation from Intraday Quotes

Liquid financial markets, such as the options market of the S&P 500 index, create vast amounts of data every day, i.e., so-called intraday data. However, this highly granular data is often reduced to single-time when used to estimate financial quantities. This under-utilization of the data may reduce the quality of the estimates. In this paper, we study the impacts on estimation quality when using intraday data to estimate dividends. The methodology is based on earlier linear regression (ordinary least squares) estimates, which have been adapted to intraday data. Further, the method is also generalized in two aspects. First, the dividends are expressed as present values of future dividends rather than dividend yields. Second, to account for heteroscedasticity, the estimation methodology was formulated as a weighted least squares, where the weights are determined from the market data. This method is compared with a traditional method on out-of-sample S&P 500 European options market data. The results show that estimations based on intraday data have, with statistical significance, a higher quality than the corresponding single-times estimates. Additionally, the two generalizations of the methodology are shown to improve the estimation quality further.

What is a Man, What Has He Got?

This issue Elie Ayache returns to complete his alternative reading of Bergomi which sheds new perspectives on Rough Volatility in relation to the meaning of the Options Market

The Skewness Risk in the Energy Market

In this paper, we study the skewness risk and its return predictability in the energy market. Skewness risk is often used to measure the possibility of market crash. We study both physical skewness (market skewness and cross-sectional average realized skewness) estimated from underlying stock returns and risk-neutral skewness evaluated from the options market. We find a significant positive relationship between one-month-ahead market return and average realized skewness in the energy market. This unique feature should be noted by investors and carefully considered by energy policymakers.

Why would you buy an electric car on Jetski Friday? Or, a critique of financial markets from an options trading room

This article presents a close, dialogue-based ethnographic account of a group of contemporary options market makers making a decision about pricing options in Tesla, Inc. Careful attention to their deliberations reveals how the rise of algorithms and automation on financial markets have rendered traders alienated and estranged from the markets they work on for their livelihood. This alienation arises, in part, due to novel cascade effects between futures and underlying equities, which algorithmic and automated trading seems to afford, and which also relate to news events as well as the actions of politicians and prominent business people. Emerging from this alienation, traders produce a critique of how highly automated financial markets allocate capital and how ripe they are for political manipulation.

The Profitability of Volatility Trading on Exchange-traded Dollar-rupee Options: Evidence of a Volatility Risk Premium?

This article examines the profitability of short volatility strategies in the exchange-traded USDINR options market. Returns from delta-hedged short positions in straddles, strangles and individual call and put options are examined across different trading horizons and volatility regimes. The study finds that short volatility strategies yield significant mean and median returns regardless of the trading horizon and option moneyness before considering transaction costs. This is suggestive of a volatility risk premium priced in USDINR options. However, the returns are found to be insignificant and even negative after accounting for trading costs such as bid-ask spreads and brokerage. The study concludes that although USDINR options appear to be overpriced because of the volatility risk premium, short option strategies can be profitably exploited only by market makers and institutional investors facing low spreads and funding costs. The findings are suggestive of an informationally efficient market.

A pre-predictive analysis of trading volume in the options market

Subject. This article examines the relationship between the three indicators of the derivatives market, namely price, trading volume, and open interest. Objectives. The article aims to characterize the dynamics of option trading volumes in terms of regularity and predictability of changes. Methods. For the study, we used general scientific methods. Results. The article substantiates the expediency of using fractal analysis methods to identify the stability of market trends, describes approaches to the classification of options, on the basis of which the range of options traded on the Moscow Exchange is characterized, and conducts a pre-predictive analysis of the time series of trading volume. Relevance. The results of the study can be useful to persons studying financial markets, market analysts and developers of option contracts.