Questions tagged [prediction]

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44 views

Beginner FFT (Fourier) transforms on closing prices for Apple

I don't know math very well, but I have been programming for many years. I would like to use FFT as a parameter to a ML model. The FFT is diving down sharply. I tried many stocks and its the same. ...
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23 views

Labeling Returns in 5 categories based on BL view approach

I have to label a time series of returns into 5 categories based on the Black Litterman view approach. The categories should look as follows: very bullish: + 2 std. dev. bullish: + 1 std. dev. ...
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0answers
26 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 ...
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4answers
156 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 ...
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0answers
49 views

Predicting stock returns using principal components of macroeconomic variables

I'm trying to detect return predictability by regressing stock returns on the first couple of principal components of a set of macroeconomic variables. I'm doing this for different stock styles such ...
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1answer
531 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 ...
4
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1answer
939 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 ...
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2answers
83 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 ...
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0answers
64 views

Can I make the simple moving average less lagging by this method?

I have (T+3) predicted prices for a stock. Let us assume that the predicted prices are going to be very close to the actual prices. can I alter the formula of simple moving average for 20 days like ...
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0answers
65 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 ...
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0answers
277 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 $P_{t}$, ...
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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 ...
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14answers
163k 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 ...
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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 (...
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2answers
271 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 ...
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1answer
164 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 ...
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0answers
163 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 ...
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50 views

Trading Signals with Different Lags

I have a momentum signal that gives best predictive power at 3 months and a valuation signal that gives best predictive power at one year. If I combine for a 3 month horizon by "interpolating" the ...
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1answer
191 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 ...
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2answers
185 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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2answers
438 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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1answer
167 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
136 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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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....
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1answer
278 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
771 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 ...
5
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1answer
298 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 ...
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1answer
138 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 ...
5
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2answers
984 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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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 ...
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1answer
298 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.....
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1answer
295 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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0answers
315 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 ...
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3answers
188 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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0answers
250 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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2answers
16k 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 ...
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1answer
385 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 $...
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4answers
397 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 ...
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2answers
85 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
97 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
104 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
287 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
54 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 ...
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1answer
199 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
995 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
53 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 ...
8
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1answer
562 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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3answers
232 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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0answers
232 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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2answers
862 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 ...