In this episode of The Logic of Risk, we continue our discussion on the propensity interpretation of probability. We start by showing how Popper thought propensity could cope with the peculiar uncertainty of quantum mechanics, as well as with the problem of one-shot events, which frequentism could not handle.
We then briefly touch Gillies' view, and introduce the reference class problem we will encounter often in our future conversations.
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In this episode, we move beyond the classical and frequentist definitions of probability to explore the propensity interpretation.
We examine how Peirce and Popper viewed probability as an objective tendency of random phenomena.
While this approach offers an interesting perspective, and it can be useful in fields like quantum mechanics, it also raises challenges, especially when dealing with single events. 
We also discuss historical bias and its impact on risk management and financial decision-making.

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In this episode, we delve deeper into the frequentist definition of probability, showing how probabilities emerge from limiting relative frequencies. We discuss why this approach can be useful for mass random phenomena but falls short for single or rare events—especially in risk management contexts involving heavy-tailed risks. Through examples, we highlight the dangers of relying solely on historical data and underscore the need for more robust tools to capture the true nature of randomness.

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Welcome to the fifth episode of The Logic of Risk. After introducing the classical definition, we begin a review of the main schools of thought in probability. We’ll see that some are objectivist and others are subjectivist, plus a few that position themselves somewhere in between. Among the objectivist schools, we’ll introduce the most commonly used (and abused) one: the frequentist school.
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In this episode, we provide an introduction to probability by exploring the classical definition, a concept rooted in the Renaissance and often used for pedagogical purposes. While historically significant, it has limitations in real-life applications.
We'll also delve into key concepts in probability theory, including the sample space, event space, mutually exclusive events, and independence.
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After defining risk as the possibility of harm in Episode 1 and exploring the harm profile in Episode 2, we now turn our attention to the concept of possibility. To that end, we introduce probability as a way to assess possibility. This episode serves as an essential introduction to the various schools of thought on probability, which we will cover in the next episodes.

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In this episode, we dive into the concept of harm, a fundamental component of risk—how can we understand, measure, and even rank it? We will break down its key dimensions and talk about a possible hierarchy.
Starting today, you’ll find some bonus materials waiting for you at www.thelogicofrisk.com. For Episode 2, there’s a picture ready for you to check out. Don’t miss it!

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Welcome to Episode 1 of The Logic of Risk.
In this introductory segment, we will begin by defining “risk” and uncovering why it’s far more nuanced than most people typically think.
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