Questions tagged [prediction]

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130
votes
15answers
164k views

How can I go about applying machine learning algorithms to stock markets?

I am not very sure, if this question fits in here. I have recently begun, reading and learning about machine learning. Can someone throw some light onto how to go about it or rather can anyone share ...
31
votes
5answers
8k views

Any research on how natural language processing can be used to forecast stocks?

Is there any published research of decent quality linking news or unstructured information to asset returns? I know that Thomson Reuters offers its Machine Readable news (MRN), so somebody must use it....
19
votes
3answers
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 ...
14
votes
1answer
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 ...
14
votes
5answers
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 ...
12
votes
1answer
2k views

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 ...
11
votes
4answers
2k views

Can the futures market's open interest predict commodity, treasury, and equity returns?

I came across this article and became curious. Can the futures market's open interest really predict market action?
11
votes
2answers
17k views

GARCH model and prediction

I have a question about the prediction of volatility and returns of a time series. Basically it is a question about predict in the ...
10
votes
1answer
2k views

ARMA+GARCH prediction with package rugarch (R)

I am analyzing FTSE 100 series, from 2007-01-01 to 2010-12-31 (university exam homework). I have to use the data 'til 2010-11-30 as sample, and the remaining (23) observations as in-sample forecast (...
9
votes
3answers
2k views

Determine trends of data (direction detection or turning point detection)

I'm working on a model to determine trends (direction detection or turning point detection). Suppose that we have a stock trend which is illustrated below. Blue line is real trend of stock close ...
8
votes
2answers
495 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 ...
8
votes
1answer
207 views

Are returns predictable, Campbell and Shiller (1988)

Following from the thread, Drivers of equity returns: dividend yield, change in P/E and dividend (or earnings) growth 1) Why are returns predictable from this, is there a reason? 2) Can we expect ...
8
votes
1answer
573 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 ...
7
votes
10answers
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? ...
7
votes
2answers
444 views

Quant teams predicting the World Cup

It is a good tradition of the quant teams of the major banks to predict the World Cup. As an example see this new paper from Goldman Sachs: The World Cup and Economics 2014 (Brazil will win by the ...
6
votes
5answers
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 ...
6
votes
2answers
546 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?
6
votes
2answers
313 views

Does predictability in a VAR process imply mean reversion or momentum?

There seems to be some disagreement in the literature about this. Define predicability of a stationary series to be $\sigma^2_{t-1} / \sigma^2_t$ Finding mean reverting portfolios using canonical ...
6
votes
1answer
555 views

What machine learning method is more suitable for prediction of financial time series?

I have time series data for various assets and which I transform to create various features. I have framed the problem as a classification task where I attempt to predict either a positive or negative ...
5
votes
1answer
182 views

how are financial data with sparse and asynchronous features imputed in predictive modeling?

I watched a presentation from a large quantitative finance firm that spends a lot of effort around predictive modeling. One of the points the presenter emphasized was that they deal with a lot of ...
5
votes
1answer
336 views

Predict probability of returns: How does changing volatility affect the return pdf?

I am trying to predict the future probability of stock returns based on the return distribution. Therefore I calculate the returns as $\frac{P(t)}{P(t-1)}$ for the whole daily data and fit a ...
5
votes
1answer
300 views

Interpret predictions weekly and monthly stock price returns [closed]

I have built a model in R that predicts weekly and monthly returns of stock prices using regression trees, roughly based on https://www.r-bloggers.com/using-cart-for-stock-market-forecasting/. In my ...
5
votes
2answers
1k views

Predict Futures Prices based on weather + agricultural data

I’m working in the area of Data Mining and have come up with the following idea for my Masters project.The text may not be the best structured but it’s a working draft to give you a quick idea. ...
5
votes
0answers
190 views

Implementing Hanson`s LMSR with Limit Orderbooks

I am trying to integrate Hanson's LMSR (see (see logarithmic market scoring rule)into an order-book with traditional bid/ask-limit orders (in KDB+/Q). The following functions define the basic LMSR ...
4
votes
1answer
387 views

What is the stambaugh bias? Why is it important for predictability regressions?

What is the Stambaugh bias? Why is it important for predictability regressions? Can anyone explain it in simple terms?
4
votes
2answers
1k views

What is time-varying risk premium? Forecasting stock returns

I am trying to understand the concept 'Time-varying aggregate risk premium'. Here is an extract from a Forecasting book, written by Rapach and Zhou, "However, rational asset pricing theory posits ...
4
votes
1answer
1k views

How quants use ML models for stock market prediction

I am learning machine learning to use it for stock market price forecasting. While doing that I got this question. If we take any country with stock exchange they have more than one investment assests ...
4
votes
0answers
571 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 ...
3
votes
4answers
193 views

Predicting portfolio returns

I suppose there are roughly two approaches to predict portfolio returns. Either predict the returns of all underlying stocks and aggregate all individual stock predictions, or predict the portfolio ...
3
votes
2answers
100 views

Any research on label/target variable design for ML training?

is there any discussion or paper about how to define/design the labels for the ML training? Intuitively I can think of: Net return of the next future day Net return using the max candle-high value of ...
3
votes
0answers
280 views

Good criteria to sort state-space $\beta_{t}$ according to Kalman filter output

Let's assume the usual state-space linear model without constant term for simplicity: $y_{t}=\beta_{t} X_{t}+\epsilon_{t}$ If we apply Gaussian Kalman filter to estimate $\beta_{t}$ we get $P_{t}$, ...
3
votes
0answers
546 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?...
2
votes
4answers
411 views

What is currently predictable in the stock and bond markets and what is not

Disclaimer: I have some knowledge of statistics, machine learning and probability theory, but next to zero knowledge of finance (I had to look up Wikipedia to refresh my knowledge of the difference ...
2
votes
3answers
241 views

Technical Indicators reference

I have been looking for a good reference where I can find how technical indicators of stock market analysis are calculated. I have a dataset (time series) which I want to extract these indicators to ...
2
votes
2answers
154 views

Fractal market hypothesis testing

I would like to do an analysis on the AEX stock exchange index for the last 20 years, but I ran into some issues. It would be really appreciated if you can answer my questions: In order to apply ...
2
votes
1answer
92 views

time series data modeling for deep learning

what is the best format to feed the input data, which are time series with varying density over time, to a deep learning network, while at any iteration we want to feed a batch of data including a ...
2
votes
1answer
102 views

Window length for predictive regressions

I am building a trading strategy that predicts the current period returns using historical returns (think e.g. using an estimated OLS model to predict next weeks return based on this weeks return). ...
2
votes
1answer
1k views

predict next day's close price using hmm

I am reading this paper(Stock market forecasting using hidden Markov model: a new approach) and get confused about how they predict the next day's close price. Below is what the authors say about how ...
2
votes
3answers
195 views

What is the better representative of a P-B ratio for a sector?

What is a better representative of a P-B ratio for a sector, for using it as a factor to predict future returns on that sector? The market weighted average of P-B for all names in that index, or ...
2
votes
1answer
183 views

Economic indicators leading the yield curve

There is a lot of research on how the government yield curve can be used to predict the economy. The government yield curve is often seen as a leading indicator. But for which variables is the curve a ...
2
votes
0answers
44 views

Mean directional accuracy and zero

I'm trying to use mean directional accuracy to evaluate my directional predictions in back-test, but it can't deal with realised directions which are 0, due to the comparison of the signs of ...
2
votes
0answers
66 views

Why can the t-bill rate forecast stock returns?

The tbill rate is used as a predictor of the equity premium in a number of papers. Whilst there is not a general consensus about whether it is a significant predictor, it is still widely used. I ...
2
votes
0answers
271 views

Good books on predictive modeling (for alpha signal research)

In terms of books on predictive models, I find ESL (elements of statistical learning) trying to cover too much and serves more like a reference, instead of explaining and developing the theories for ...
2
votes
4answers
1k views

Implementing A 50/50 Prediction Model Strategy

Reworded the question for clarity (see edits for original post): How can one knowingly foresee where a 50/50 prediction model will be profitable? For previous posts: I understand that if I have a 50/...
1
vote
1answer
336 views

Predict the behavior of a time series (P&L trading desk)

I work at the trading desk P&L department at a large bank. The trading desk has positions in almost all sorts of derivatives (options, futures) over a long list of stocks, currencies, commodities.....
1
vote
1answer
171 views

Should there be a relation between stocks when used as input data for integrating Technical Analysis with Machine Learning?

I'm integrating Technical Analysis with Deep Learning for the first phase of my research. I wanted to know how should I pick (or group) stocks as input data and whether there should be relation ...
1
vote
1answer
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. (...
1
vote
2answers
230 views

Working with time series with different resolutions

I’m looking at making predictions of close prices (stocks/commodities), and have access to various data sources to help predict. However, most of these sources are in a different time frame, ...
1
vote
1answer
986 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&...
1
vote
2answers
869 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, ...