Questions tagged [prediction]
The prediction tag has no usage guidance.
78
questions
1
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0answers
18 views
How to use multi-periods and mult-factors to predict stock price by linear regression?
Give data in $t_n$ denoted by $[x_1^n, x_2^n, ... x_d^n]$ and label $y_n$ to be predicted. We can just train a $d$-dimensional linear regression $y_n=\sum b_ix_i^n$ to make a prediction. However, I ...
0
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1answer
51 views
If a security has many options expiring on a day, can you predict its price direction?
r/wallstreetbets post alleges that because ~$1.9 Trillion USD of SPY call options expire on 3/20, the price of SPY will skyrocket on 3/20.
Is this correct? What can be deduced? I'm not expecting to ...
1
vote
1answer
50 views
Predicting time series based on another
This is more of a generic question, but I'm sure it has a best answer/methodology which is what I'm trying to reach. I'm trying to figure out a solid line of thought when looking at a time series X ...
0
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1answer
31 views
Relationship between Data Size and Arima Prediction Interval Width?
When we use Arima model to acquire Interval Predictions, will the width of prediction intervals decrease if we use more data (longer history) to fit the model?
0
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2answers
43 views
Updated Time Series Prediction Model When acquiring new data Points - Basic Question
Suppose I have a Time Series Model (assume ARIMA) and use it to make one-step ahead prediction.
If I acquire a new data point, (for example I was originally using the first 100 days to fit an Arima ...
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0answers
37 views
Replication of the paper: “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction”
I recently replicated the paper "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction" and found out that my estimation of the equity premium differs from the data provided ...
0
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1answer
46 views
Question is about the data in the paper: “A Comprehensive Look at The Empirical Performance of Equity Premium Prediction”
I would like to ask a question if you download the data from the Amit Goyal website:
http://www.hec.unil.ch/agoyal/
You will see that there are two columns "CRSP_SPvw" "CRSP_SPvwx", they are ...
1
vote
1answer
89 views
Proper Data Partitioning For Building a Forecasting Model
Goal: A team and I are looking to build a model that performs a predictive action for the state of the market on day T + n, using the data at hand on day ...
1
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0answers
82 views
How to weigh computational cost of updating an online predictive model for latency-constrained trading (e.g., market making, HFT)?
Say one has a predictive online model for market making or HFT (or just for anything strictly latency-constrained). In my specific example, I start with a Gaussian distribution over the "true value" ...
2
votes
1answer
104 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 ...
1
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0answers
27 views
Which technique determines if var x1 leads var y? Assuming var x1 may need to be transformed
Suppose I want to predict future changes in variable y (stock price over time). I notice that variable x1, inverted and delayed three months, tends to lead y. Which technique can I use to find other ...
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0answers
103 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.
...
0
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0answers
36 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.
...
2
votes
0answers
73 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 ...
1
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0answers
60 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 ...
3
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4answers
221 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 ...
0
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0answers
74 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 ...
2
votes
0answers
67 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 ...
3
votes
2answers
118 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 ...
1
vote
1answer
173 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 ...
6
votes
2answers
323 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 ...
5
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0answers
202 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 ...
0
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0answers
53 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 ...
8
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1answer
229 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 ...
1
vote
2answers
244 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, ...
5
votes
1answer
194 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 ...
2
votes
2answers
167 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 ...
4
votes
1answer
483 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 ...
0
votes
1answer
156 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 ...
1
vote
1answer
359 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
votes
1answer
356 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 ...
9
votes
3answers
3k 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 ...
1
vote
0answers
384 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
votes
0answers
289 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 ...
0
votes
1answer
430 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
votes
4answers
426 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
votes
1answer
301 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
votes
3answers
199 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 ...
0
votes
2answers
95 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?
2
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1answer
104 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). ...
1
vote
2answers
106 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 ...
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 ...
1
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1answer
356 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 ...
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 (...
1
vote
1answer
56 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
vote
1answer
212 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 ...
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 ...
0
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1answer
55 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 ...
1
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0answers
241 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 ...
