#randomWalk

2026-01-20

#randomwalk through some suburban wetlands. The air is 40°C my feet maybe 24°C. Water isn't warm enough for crocs yet #australia #irwinaward

Zhachzhach
2025-08-20

Burton Malkiel's "A Random Walk Down Wall Street" is a classic for a reason. He argues that the short-term stock market is largely unpredictable, and new information is priced in so quickly that you can't get an edge. A recent experiment pitting a fish against an AI algorithm for stock picking backs this up in the most hilarious way.

Let's talk about what this means for your portfolio: zhach.news/random-walk-down-wa

katch wreckkatchwreck
2025-08-01
Steven P. Sanderson II, MPHspsanderson.com@bsky.brid.gy
2025-07-10

Want to visualize a 2D Random Walk of the Wilcox distribution in #R then the RandomWalker package developed by myself and Antti Rask can do that. #R #RStats #RandomWalker #RandomWalk #Visualization #ggplot2 #TidyData

library(RandomWalker)
library(ggplot2)

random_wilcox_walk(.m = 1, .k = 2, .dimensions = 2) |> 
  ggplot(aes(x = x, y = y)) + 
  geom_path(aes(color = step_number)) + 
  scale_color_viridis_c(option = "plasma") + 
  labs(
    title = "2D Random Wilcox Walk", 
    x = "X Position", 
    y = "Y Position"
  ) + 
  theme_minimal() + 
  theme(legend.position = "none") + 
  theme(
    axis.text.x = element_blank(), 
    axis.ticks.y = element_blank(), 
    axis.text.y = element_blank(), 
    axis.ticks.x = element_blank()
  )library(RandomWalker)
library(ggplot2)

random_wilcox_walk(.m = 1, .k = 2, .dimensions = 2) |> 
  ggplot(aes(x = x, y = y)) + 
  geom_path(aes(color = step_number)) + 
  scale_color_viridis_c(option = "plasma") + 
  labs(
    title = "2D Random Wilcox Walk", 
    x = "X Position", 
    y = "Y Position"
  ) + 
  theme_minimal() + 
  theme(legend.position = "none") + 
  theme(
    axis.text.x = element_blank(), 
    axis.ticks.y = element_blank(), 
    axis.text.y = element_blank(), 
    axis.ticks.x = element_blank()
  )
Jörg Kantelkantel
2025-06-18
2025-04-12

Geometric Brownian Motion is the stochastic differential equation used to model stock prices: dS = μSdt + σSdW. This forms the mathematical foundation for options pricing, Monte Carlo market simulations, and much of modern finance theory. Fascinating intersection of math and markets! #StochasticCalculus #FinancialModeling #RandomWalk

Just me, the dirt road, and the whispers of the forest. 🌲✨ Who else loves getting lost in nature?
#randomwalk #nature #naturephotograhy #forest
2025-01-17

#genuary17 - Pi is 4? When contemplating how to approach this one, I recalled the fascinating Monte Carlo methods for calculating pi, like counting how many random dots fall inside a circle, or Buffon's needle experiment. A method unfamiliar to me until now method is based on random walk. I had to code it up and try it, and then thought about what would have to change to make pi come out to be 4. Instead of a random walk where each step is randomly either -1 or 1, the steps would need to be approximately -0.885 or +0.885. This image visualizes the difference, with the cream color walks for the regular pi, and the turquoise paths the "pi=4". #pi #randomwalk #genuary #genuary2025

Thousands of wavy light blue and cream lines form a funnel leading to the bottom of the image. Looks like a comet with tail pointing upward.
2024-09-18

Light, or photons, created in the sun undergo a series of random, scattered movements called a ‘random walk’ which delays light leaving the sun by tens to even hundreds of thousands of years.

Thanks for sharing, Space According to Skylar !

#science #sciencefacts #randomwalk #sunlight #photon #sun #light

Valentin LechevalVLecheval@ecoevo.social
2024-07-31

Hot from the press, with Richard Mann
and @elva: 🐜 Random walks with spatial and temporal resets can explain individual and colony-level searching patterns in ants

royalsocietypublishing.org/doi

#physics #ants #animalmovement #animabehaviour #randomwalk #behaviouralecology

2024-04-16

A drunk man will find his way home, but a drunk bird may get lost forever.” What is this sentence about?

In 2D, the random walk is “recurrent”, i.e. you are guaranteed to go back to where you started; but in 3D, the random walk is “transient”, the opposite of “recurrent”. In fact, for the 2D case, that also means that you are guaranteed to go to ALL places in the world (the only constraint is, of course, time). [Think about why.]

Markov chains are also an important tool in modelling the real world, and so I feel like this is a good excuse for bringing it up.

At the end, I also compare this phenomenon to Stein’s paradox – in both cases, there is a cutoff between 2 and 3 dimensions, and they have similar intuitive explanation – is that a coincidence?

Random walks in 2D and 3D are fundamentally different

#MarkovChain #MarkovChains #Math #Mathematics #nowWatching #randomWalk #randomness #StochasticProcess #YouTube

Jörg Kantelkantel
2024-01-05
Dr. Juande Santander-Velajuandesant@astrodon.social
2023-04-19

Then you can plot it with:

```import matplotlib.pyplot as plt
ax = plt.figure().add_subplot(projection='3d')
ax.plot(*w.T, lw=0.25, alpha=0.5)
plt.show()
```

#TIL #TodayILearned #Python #NumPy #RandomWalk

Dr. Juande Santander-Velajuandesant@astrodon.social
2023-04-19

TIL that NumPy has `np.cumsum` and `np.cumprod` that you can use to accumulate sums and products, and you can use them in one axis of a multidimensional array.

For instance, you can have a 3xn matrix of 3D vectors centered around (0,0,0)…

```python
import numpy as py
v = np.random.rand(1000,3)*0.1-0.05```

You can calculate a random walk with

`w = np.cumsum(v, axis=0)`

#TIL #TodayILearned #Python #NumPy #RandomWalk

Client Info

Server: https://mastodon.social
Version: 2025.07
Repository: https://github.com/cyevgeniy/lmst