Questions tagged [prediction]

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2answers
414 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, ...
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1answer
257 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 ...
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2answers
228 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 ...
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1answer
915 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?
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2answers
2k 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 ...
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1answer
192 views

Momentum Analysis on Indices

I'm interested in analysis of day-on-day momentum of certain large indices. In particular, I'm interested in the predictive power of the sign of the price change of the first hour of trading with ...
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1answer
479 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.....
5
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1answer
470 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 ...
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3answers
5k 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 ...
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0answers
535 views

R squared statistic in predictions of returns

My question is related to an article which use predictive linear regression for the stock returns. There is told that R squared statistic of 1.6% is high. How can we measure which R squared is high? I ...
2
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0answers
351 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 ...
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1answer
559 views

Trouble understanding lookahead bias

I understand lookahead bias is pretty common industry knowledge. But I cannot wrap my head around how I am introducing it and could use a nice and easy explanation. Here's my thought process. I have $...
2
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4answers
525 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 ...
5
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1answer
330 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 ...
2
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3answers
283 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 ...
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2answers
100 views

What kind of indicators would you look in the market preceding a recession/crisis?

What kind of indicators may have predicted the upcoming financial crisis in the 2000 or 2008?
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1answer
113 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). ...
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2answers
118 views

How to assign n day target variables in machine learning

I am trying to forecast future price using supervised machine learning. My logic is to take open and close price from t, t-1, t-2 and t-3 period to predict future close price in the period t+1,t+3 ...
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1answer
3k 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 ...
1
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1answer
498 views

Design models using adjusted or unadjusted stock prices (time series prediction)?

I'm creating a predictive model for closing price of stocks (using neural network and support vector machines.). Is it appropriate to use adjusted prices or unadjusted prices for this prediction ...
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1answer
3k 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 (...
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1answer
59 views

Methods or models to predict activity of clients of a bank

I'm a Physicist but I'd like to know if there are some methods or models to predict the activity of the clients of a bank. I heard that banks are interested in this sort of analysis so I got curious ...
1
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1answer
229 views

Building predictive model for closing price using only previous days data

I am trying to determine which quantitative model to try and build a predictive model for the next day's closing price for all the S&P stocks based on their bar for that particular day. However, I ...
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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 ...
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1answer
56 views

Modeling EOD ETFs price returns together or individually?

Let's say you want to model the next day price returns for a set of US equities large cap ETFs (a relatively homogenous group). Would you model all the ETFs as a single, 15 years data set, or each ETF ...
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0answers
250 views

Estimating the next tick movement in Chinese markets

I'm working on high frequency trading in the Chinese Futures market and I've been having a bit of trouble with getting orders to go through due to the lack of liquidity and large fluctuations. To ...
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5answers
398 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 ...
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1answer
706 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 ...
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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. ...
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2answers
1k views

Explanatory variables for regression predicting weekly stock returns

In an empirical analysis I'm trying to predict log() weekly stock returns. I'm trying to model stock returns in a panel data model framework. As explanatory variables I have 1) a measure of investor ...
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2answers
1k views

Calculation of price momentum using weekly price observations

In an empirical analysis I'm trying to predict stock returns using different firm characteristics. I would like to use price momentum as an explanatory variable, but I'm not quite sure how to ...
2
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4answers
2k 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/...
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2answers
465 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 ...
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2answers
21k 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 ...
2
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1answer
192 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 ...
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0answers
91 views

How to choose a window for curve fitting and prediction?

I am using Pareto distribution to fit a serie of survival rates (with least square). My ultimate goal is to use this fitting curve for prediction. Thus I would mainly focus on the tail of the ...
3
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0answers
285 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 $P_{t}$, ...
12
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2answers
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 ...
6
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2answers
574 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?
8
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1answer
629 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 ...
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1answer
1k 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
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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. (...
3
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0answers
555 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?...
1
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2answers
968 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, ...
15
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1answer
7k 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 ...
4
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0answers
584 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 ...
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2answers
512 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 ...
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5answers
13k 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 ...
15
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5answers
11k 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 ...
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3answers
4k 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 ...