Options Trading Strategies In Python: Intermediate

Yes, you will be awarded with a certification from QuantInsti after successfully completing the online learning units.

No, there are no live or classroom sessions in the course. You can ask your queries on community and get responses from fellow learners and faculty members.

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There is no admission criterion. You are recommended to go through the prerequisites section and be aware of skill sets gained and required to learn most from the course.

We respect your time, and hence, we offer concise but effective short-term courses created under professional guidance. We try to offer the most value within the shortest time. There are a few courses on Quantra which are free of cost. Please check the price of the course before enrolling in it. Once a purchase is made, we offer complete course content. For paid courses, we follow a 'no refund' policy.

Some of the course material is downloadable such as Python notebooks with strategy codes. We also guide you how to use these codes on your own system to practice further.

We focus on teaching these quantitative and machine learning techniques and how learners can use them for developing their own strategies. You may or may not be able to directly use them in your own system. Please do note that we are not advising or offering any trading/investment services. The strategies are used for learning & understanding purposes and we don't take any responsibility for the performance or any profit or losses that using these techniques results in.

Quantra environment is a zero-installation solution to get beginners to start off with coding in Python. While learning you won't have to download or install anything! However, if you wish to later implement the learning on your system, you can definitely do that. All the notebooks in the Quantra portal are available for download at the end of each course and they can be run in the local system just the same as they run in the portal. The user can modify/tweak/rework all such code files as per his need. We encourage you to implement different concepts learnt from different learning tracks into your trading strategy to make it more suited to the real-world scenario.

No. We provide you guidance on how to create strategy using different techniques and indicators, but no strategy is plug and play. A lot of effort is required to backtest any strategy, after which we fine-tune the strategy parameters and see the performance on paper trading before we finally implement the live execution of trades.

You can learn with or without coding knowledge. If you would like to do the analysis on excel, we would suggest you to start with course on Statistical Arbitrage in Trading. You can create and test your trading strategies using excel.

Alternatively, you can do the course on Python for Trading which will help you gain knowledge in all these fields: Python, Analysis and Financial markets.

Yes, you can deploy the backtested options trading strategies in the live market using IBridgePy API. A live trading strategy template will be provided in the course. The template uses IBridgePy to connect with Interactive Brokers. A subscription may be required for options data. You can tweak and optimise the strategy code, paper trade and finally deploy the strategies in the live market!

Lifetime access means that once you enroll in the course, you will have unlimited access to all course materials, including videos, resources, readings, and other learning materials for as long as the course remains available online. There are no time limits or expiration dates on your access, allowing you to learn at your own pace and revisit the content whenever you need it, even after you've completed the course. It's important to note that "lifetime" refers to the lifetime of the course itself—if the platform or course is discontinued for any reason, we will inform you in advance. This will allow you enough time to download or access any course materials you need for future use.

The Black Scholes or Black-Scholes-Merton (BSM) model is the most famous options pricing model that is used in options trading. The model is famous due to its accuracy in predicting prices which are very close to the market prices at option expiration. Before we discuss the BSM model, there are certain assumptions that the model factors into market volatility, no transaction costs, no dividend payout, and the options can only be exercised at expiry. A good number of parameters were considered while calculating the option price.

The variables involved in the model are :

S = Current underlying asset’s price
K = Strike Price
R = Rrisk - free interest rate
t = Time to maturity
N = Normal Distribution
c = Call Option Price
p = Put Option Price
σ = Volatility in the underlying asset’s price
ln = Log-Normal Prices ( Prices are log-normally distributed )

The Derman - Kani model was introduced by Iraj Kani and Emanuel Derman. The model is also known as local volatility. This model is usually used to model the volatility or price fluctuations involved with an option at different given periods and at different strike rates. Unlike the BSM model, this model does not assume volatility to be constant and provides near accurate prices based on volatility. The model states that local volatility can be calculated, given that the current asset price and time left in an option are mentioned. Thus , σt = σ ( St,t). Here, St = Stock or any underlying asset a given period of the option and t is the discrete-time point when such volatility is calculated. σ is the standard deviation.

The Heston model was introduced by Steve Heston and is a pure financial mathematical model used to model the “stochastic process involved in volatility”. Simply put, it means that the variance in such random volatility is normally distributed. Unlike the BSM model, it does not assume prices to be log-normally distributed and assumes volatility to be reverting back to its mean. It also assumes that there is a correlation between asset prices and their volatility.

Options greeks are factors that affect the price of an option. These factors are represented by greek symbols in the options industry and are thus known as “options greeks”. There are mainly four options greeks.

Delta - Delta is the change in the price of an option measured in relation to the change in the underlying asset. Delta can be both negative and positive and can range from +1 to -1.

Gamma - Gamma is the rate of change of delta.

Vega - Vega is the rate of change in premium based on the change in volatility or deviation in option prices.

Theta - It is the value of an option premium calculated based on the time left to expiry.

A calendar spread is a popular options strategy used frequently by traders in situations when they are not sure of the market direction. Here’s how the strategy works: A trader can buy a call option for a near month expiration date and sell a call for the month following the near month. Both, the calls have the same strike price and the same underlying asset. If a trader is bearish, an opposite directional position should be sufficient to implement the strategy. Conversely, this strategy can be used with a put option with a definitive perception of the trader. This strategy is popular in times of huge volatility or market uncertainty.

Forward volatility is future volatility that a trader expects in the options market. It is measured considering the implied volatility of an option. Using forward volatility, a trader takes positions for generating alpha. For example, if 90-day volatility(t2) is 8%(r2) and 180-day volatility(t1) is 10%( r1), we will first divide the days by 360 and so the forward volatility from 91 to 180 day is

= √t1/360 * r1^2 - t2/360 * r2^2 / t2/360 = √180/360 * 0.10^2 - 90/360 * 0.08 ^ 2/ 90/360 = √0.5 * 0.01 - 0.25 *0.0064 / 0.25 = √0.005 - 0.0016 / 0.25 = 0.1166 = 11.66%

So, in this case, the forward volatility from 91st to 180th day is 11.66 %.

Volatility smile and skew are very important parameters for understanding volatility intuitively in the options market. Let us first understand the “volatility smile”. It can be calculated with the help of two parameters;: the underlying asset’s price and implied volatility of the option. As the shape of its graphical representation is similar to a “smile”, it is thus known as the volatility smile. Implied volatility (IV) is high when the options strike price is either out of money (negative to the trader’s perception) or in the money ( trader making profit). In the case of theof at the money, IV is said to be the minimum. This is visible with options with the same expiration and the underlying asset, but different strike prices.

Volatility skew states that option prices with the same underlying asset and expiration date but with different strike prices will have different Implied volatility rates altogether. It can be termed as a phenomenon when the calls and puts with the same parameters have different IV due to an unusual event. Take for example, when a market crash takes place, a deep out of the money put option (with strike price far away from market price) becomes a highly valued in the money put option (with a market price close to the strike price ). In accordance with the market crash, the price of an underlying asset falls too, benefitting the out of the money option holder. Similarly, an in the money call option tends to have a lower IV due to its non-usefulness during a market crash. This leads to a ‘’skew’’.

Mibian library can help you price European options. You can use Quantsbin library to price American options. The concepts of Binomial Tree Pricing Model taught in the course can also be used for pricing American options.