Latest
Formula for sorting betting opportunities
The problem we will be tackling in this article is the following: Finding a way of quantifying the quality of a bet? The ultimate goal here is to be able to choose a bet among a set of potential candidates based on clear mathematical considerations. By the end of this reading, you will know a very simple yet powerful formula which will enable you to sort your betting opportunities based on their inherent quality.
Tags
AlgorithmicTrading
C
C++
Cryptocurrency
Elixir
Elm
Finance
Go
Java
JavaFX
Javascript
Kotlin
MachineLearning
Nim
NodeJS
Piston
Python
QuantitativeFinance
Rust
Scala
Torch
Trading
WebAssembly
Favourites
Powered by
More Articles
- Functional Programming exercises in Scala 3: Functions on Lists
- Kelly criterion for multiple mutually exclusive outcomes: A numerical approach
- Rust integration within the Elixir Phoenix framework
- Bet sizing using risk-of-ruin indicator
- Factory type pattern using Enums in Rust
- Sieve of Eratosthenes: Benchmarking Rust, Nim, Go against C
- Sudoku solver in idiomatic Rust
- Use statistical bootstrapping to validate an algorithmic trading strategy
- Numerically solve Kelly criterion for multiple simultaneous bets
- Export Rust functions to Java using JNI (WebAssembly comparison)
- Creating a JavaFX GUI for Rust WebAssembly using Asmble and Kotlin
- Mutability in Rust for functions and closures
- Interfacing Elm with Rust WebAssembly
- Fast development of 2D games and visualisation apps in Rust with Piston
- Reinforcement Learning with Torch in Rust: Solving Kuhn Poker
- How to use Torch in Rust with tch-rs
- Why are some downplaying the role of good fortune in Business and Speculation?
- Cryptocurrencies in the global economy
- Define your programming toolbox
- Passive investing is a game of chicken