Earnings on options forecasts
Published by Emerald Publishing Limited. Anyone may reproduce, distribute, translate and create derivative works of this article for both commercial and non-commercial purposessubject to full attribution to the original publication and authors. Introduction Options securities have been traded using a variety of strategies with more or less success.
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Most of the strategies applied by traders are based on expectations regarding most commonly the trend of the underlying asset price and the level of the volatility of returns of the asset price. These expectations may either rely on: their intuition; their access to information.
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For example, Hsieh and He found that foreign institutional investors in the Taiwan market are the most informed traders, with their predictive ability being more apparent in a downward market. They tend to use out-of-the-money options to achieve high leverage, along with medium-term options to obtain large delta exposure and low theta risk, whilst also sacrificing liquidity by forgoing the use of short-term options; and these expectations may finally be obtained from fundamental, technical or econometric models.
This paper presents an original option trading strategy based on the well-known auto regressive integrated moving average ARIMA econometric model. Section 2 reviews the literature on option strategies.
Section 3 explains the methodology underlying the options trading strategy proposed in this paper. Section 4 presents and discusses the results.
Section 5 wraps up the main findings of the paper. Literature review Options are traded over-the-counter OTC through a dealer network or on centralized exchange markets. OTC markets are less transparent and operate with fewer rules than do exchanges.
OTC markets are mostly accessible to institutional investors and companies. Market participants of the options exchange market include professional traders working for proprietary trading firms and for institutional investors such as banks, investment companies, insurance companies or pension funds.
In the past two decades, easy access of retail investors to the options exchange market offered by brokerage firms on internet have added myriads of individuals to the number of options market participants. Bauer et al.
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The reasons of their poor performance are attributed to a lack of market timing due to overreaction to past stock market returns, high trading costs and the profile of gamblers that usually lack discipline and rational behavior.
This addition of unskilled investors is obviously a benefit for the options exchange market with an increased market depth because of higher trading volumes, higher open interests and tighter spreads. It is also beneficial to professional traders who see their revenues growing by placing opposite trades to the ones of individual investors.
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Options traders implement a variety of strategies, the most common strategies rely on the expectations of two parameters, the trend of the underlying asset price bull, bear or neutral market and the volatility of the returns of the underlying asset price increasing, earnings on options forecasts or neutral volatility.
In this two-dimension framework, traders will apply long call or long strap if they expect a bull market and an increasing volatility, long straddle, short butterfly or long strangle if they expect a neutral market and an increasing volatility, short straddle, long butterfly or short strangle if they expect a neutral market and a decreasing volatility, etc.
These strategies are extensively explained in manuals specialized in financial derivatives Hull,options trading books Bittman, ; Ansbacher, ; Trester, ; McMillan, or Kraus, In addition, Chaput and Ederington examined option spread and combination trading, identifying, which positions are commonly traded spreads, straddles, strangles and reviewing the reasons for trading combinations.
Yang et al. By analyzing intraday volatility information trading according to the demand for options, these authors determine the types of investors that are informed about future spot market volatility and conduct volatility information trading in a highly liquid options market.
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Among the studies assessing the performance of options strategies, Guo showed that after accounting for transaction costs, using the implied stochastic volatility regression method or the GARCH method to forecast the volatility of foreign exchange rates, both delta-neutral and straddle trading strategies involving currency options lead to observed profits not significantly different from zero.
Over a decade, Hemler and Miller analyzed options-based investment strategies vs a buy-and-hold strategy in the underlying stock for 10 stocks.
Identifying profitable options strategies in the earnings on options forecasts, Maris et al. Sheu and Wei introduced an effective option trading strategy based on superior volatility forecasts using earnings on options forecasts option price data from the Taiwan stock market. Simmons forecasted the ASX index with a differential evolutionary algorithm and applied an option trading strategy based on forecasts that shown to perform better than a buy and hold strategy.
Using a volatility forecasting model derived from three components of the financial statements, earnings yield volatility, change in market to book premium volatility and the covariance of the earnings yield with the change in market to book premium, Sridharan implemented a profitable option-based trading strategy.
Simon identified profitable VIX option trading strategies based on buying VIX options to exploit the tendency of VIX futures to rise and fall when the VIX futures curve is in backwardation and in contango, respectively and the tendency of VIX futures ex ante volatility premiums to spike and then revert to more typical levels.
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Hong et al. While significant profits are available on strategies that involve writing put options, their findings cast doubt on whether these profits can be genuinely attained in practice.
After bid-ask spreads are included, they find that the profitability is significantly reduced. This paper introduces a robust options strategy based on ARIMA forecasting and a predefined set of criteria.
Implied Volatility Caveat
The strategy is not left to the appreciation or intuition of the market participants but relies on a systematic methodology explained in the next chapter. Methodology The objective of the paper is to validate an original options trading strategy based on ARIMA forecasting. From the database, premiums quotations lower than 50 cents are removed, as the corresponding options are more subject to mispricing.