In real life, the closest thing to the concept of an option is insurance. An insurance contract is a contract whereby, for a period of time (like the term of an option), if the insured asset (like the underlying of an option) suffers damage in excess of a specified amount (like the price of the underlying falling below the strike price of a put option), then the insurance company is required to pay the insured the excess of the specified amount (like the seller of an option paying the difference between the spot price and the strike price of the option). The covenant. The above comparison shows that insurance contracts are very similar to options contracts. Naturally we can understand the price of an option by reference to the premium.
The premium is set by considering the probability of the occurrence of an insured event and the loss in the event of the event. Similarly, we can think in the same way when understanding the price of an option. As a seller/buyer of options, the first thing you want to do is estimate a payout/return probability density equation, then calculate the average payout/return for the contract, and add the expected risk-reward to arrive at a reasonable premium for the option. Considering the price of an option in this way involves the difficult question of how to estimate the payout/return probability density equation at expiry. In simple terms, when we sell a call option with a strike price of 120, we know that at expiry we will need to pay 10 when the underlying price rises to 130 and 20 when the price rises to 140, but how do we know the probability of the underlying at different price levels at expiry?
Using historical data alone to estimate the payout/return density probability equation can be problematic because the historical price characteristics of a financial security do not necessarily reflect its future characteristics. For example, while everyone is reveling in the appreciation of wealth in the stock market, a financial storm may have crept in. Moreover, due to the complexity of the financial securities market, even the most advanced theoretical models cannot accurately characterize the prices of financial securities. Moreover, as option prices are generated by market bids, it is difficult for option sellers to protect themselves against losses caused by their mis-estimated payout density probability equations by levying additional model risk premiums. For example, we can construct our own model to estimate future market volatility, and as volatility increases, the option seller's average payout will increase, and therefore the option premium should increase accordingly. We can even revise our option pricing model to get what we think is a reasonable option price. In addition, sometimes it is not necessary to consider the payout/return probability density equation of the contract to determine whether the option price is reasonable, but simply to see whether the option price is within the risk-free arbitrage boundary, and if it is significantly outside, then the price is unreasonable. In addition, we can also capture the price of an option by assessing the cost to the market of fully hedging the option risk and the cost of fully replicating the same option.
In summary, the price of an option is similar to a premium and we can assess whether the price of an option is reasonable by estimating the corresponding cost and, in some cases, by using the risk-free arbitrage boundary to quickly identify unreasonable option prices, so to be a good options trader, you should focus on developing and training in this area.
