# Questions tagged [prediction]

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### Tools/R code for predicting Dragon-Kings

The theory of the so called Dragon-Kings, esp. by Didier Sornette (ETH Zürich), basically states that financial crises and crashes are predictable (contrary to the theory of black swans). The ...
536 views

### Predict Market Direction, What is forecastable/unforecastable?

Let's decompose the return process $R_t$ as follows : $$R_{t} = sign(R_{t}) * |R_{t}|$$ What's part of the equation is forecastable?
561 views

### Do futures have predictive value?

Futures closely mirror their underlying, as can be seen in the charts below. Eventually, at expiration, they reach the value of the underlying. However, they seem to show no extra information about ...
965 views

### Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether S&...
1k views

### Which prediction market model is efficient and simple to use?

For a college project I'm tasked with implementing prediction market. Which model of it I'd better choose? I want something useful and simple enough for other people to quickly understand and use. (...
540 views

### Oscillatory time-series forecasting

I was wondering if this mean(160)-reverting/oscillatory time series "SUM" can be considered chaotic & forecastable to some extend short-term? http://sg.myfreepost.com/sgTOTO_analysispower.php?...
850 views

### Howto Calculate An Error's Partial Derivative in ANN

This is a follow-on question from this post I made, "Multilayer Perceptron (Neural Network) for Time Series Prediction", a few months back. I'm constructing a feed-forward artificial neural network, ...
6k views

### Multilayer Perceptron (Neural Network) for Time Series Prediction

I have it in mind to build a Multilayer Perceptron for predicting financial time series. I understand the algorithm concepts (linear combiner, activation function, etc). But while trying to build the ...
568 views

### Algorithms for predicting a couple points in the future

I'm familiar with supervised learning algorithms like regression and neural networks which look at a bunch of input points and learn a function which outputs a value (the value varying depending on ...
489 views

### The T+H Problem in Factor model forecasts

Suppose we train on M individuals consisting of T observations (i.e. TxM design matrix). The dependent variable is one-year return for each security (H = horizon of one year). In a factor model ...
10k views

### How many explanatory variables is too many?

When researching any sort of predictive model, whether using ordinary linear regression or more sophisticated methods such as neural networks or classification and regression trees, there seems to ...
9k views

### Using linear regression on (lagged) returns of one stock to predict returns of another

Suppose I want to build a linear regression to see if returns of one stock can predict returns of another. For example, let's say I want to see if the VIX return on day X is predictive of the S&P ...
3k views

### How to incorporate technical indicators into neural networks?

I plan to develop a neural network to trade commodities futures, but while messing around with some code, a question came up. If I understand correctly, people use various technical indicators with ...
3k views

### Using Black-Scholes equations to “buy” stocks

From what I understand, Black-Scholes equation in finance is used to price options which are a contract between a potential buyer and a seller. Can I use this mathematical framework to "buy" a stock? ...