Questions tagged [forecasting]

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59
votes
9answers
34k views

How useful is the genetic algorithm for financial market forecasting?

There is a large body of literature on the "success" of the application of evolutionary algorithms in general, and the genetic algorithm in particular, to the financial markets. However, I feel ...
37
votes
4answers
9k views

What types of neural networks are most appropriate for trading?

What types of neural networks are most appropriate for forecasting returns? Can neural networks be the basis for a high-frequency trading strategy? Types of neural networks include: Radial Basis ...
35
votes
5answers
6k views

Why aren't econometric models used more in Quant Finance?

There is a big body of literature on econometric models like ARIMA, ARIMAX or VAR. Yet to the best of my knowledge practically nobody is making use of that in Quantitative Finance. Yes, there is a ...
34
votes
6answers
11k views

How to estimate real-world probabilities

In the world of finance, Risk-neutral pricing allow us to estimate the fair value of derivatives using the risk free rate as the expected return of the underlyings. However, the behavior of ...
31
votes
6answers
9k 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....
29
votes
8answers
15k views

How are cryptography and speech recognition technology applied to forecasting financial markets?

One of the answers to my previous question regarding the strategy of Renaissance Technologies, there was a reference to The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly ...
25
votes
3answers
4k views

How to forecast volatility using high-frequency data?

There is a large literature covering volatility forecasts with high-frequency tick data. Much of this has surrounded the concept of "realized volatility", such as: "Realized Volatility and ...
23
votes
5answers
25k views

Why are GARCH models used to forecast volatility if residuals are often correlated?

The answers to this question on forecast assessment suggest that if the sequence of residuals from the forecast are not properly independent, then the model is missing something and further changes ...
21
votes
4answers
8k views

How do you evaluate a covariance forecast?

Suppose you have two sources of covariance forecasts on a fixed set of $n$ assets, method A and method B (you can think of them as black box forecasts, from two vendors, say), which are known to be ...
20
votes
3answers
3k views

What type of analysis is appropriate for assessing the performance time-series forecasts?

When using time-series analysis to forecast some type of value, what types of error analysis are worth considering when trying to determine which models are appropriate. One of the big issues that ...
18
votes
2answers
2k views

How to forecast expected volatility from high-frequency equity panel data?

I'm wading through the vast sea of literature on realized volatility estimation and expected volatility forecasting (see, e.g. Realized Volatility by Andersen and Benzoni, which cites 120 other papers,...
17
votes
5answers
2k views

Why quants think that the risk-neutral measure should not be used for financial forecasting?

In posts regarding the $\mathbb{P}$ vs $\mathbb{Q}$ debate (see 1, 2, 3 or 4), most answers conclude that historical-based forecast are better suited than risk-neutral models for financial predictions....
15
votes
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 ...
14
votes
1answer
1k views

What is the Sugihara Trading System?

I recently heard the term Sugihara Trading System. I guess it might be some trading strategy or a special model to predict trends in market data, but I couldn't find out anything about it. Does anyone ...
13
votes
1answer
671 views

What methods do I need to learn in order forecast asset price movements?

What are the standard models used to forecast asset price movements? For example, if I were to trade an option, what model would I use in conjunction with option pricing models to forecast the stock ...
11
votes
4answers
2k views

Why are stock index futures not used to forecast how much the stock market will rise, given that interest rates futures are used for this purpose?

In news articles, the reader often read interest rates forecasts calculated based on interest rate futures. An example is here; How did traders calculate that the expected number of rate hikes is 4 ...
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
1answer
865 views

Is volatility for the next day forecastable? To any extent?

In a more general way: is there 1) a methodological approach to quantify the correctness of a model that produces a probability distribution for the, say, S&P 500 index return for the next ...
11
votes
2answers
3k views

How we can forecast stock prices using chaos theory?

I saw an article in which the writer had mentioned that he used chaos theory to predict stock prices and ended up with a profit over 30%. Chaos theory is basically about finding patterns called ...
11
votes
3answers
2k views

Why is volatility said to be persistent?

Persistence in volatility of stock returns is one of the common 'stylized facts' when it comes to analyzing time series. However, I am wondering for theoretical arguments why (estimated) volatility ...
11
votes
1answer
260 views

Trading strategy for a misspecified density

I am trying to implement a strategy that exploits potential misspecifications in density predictions (e.g.: long states with too-low probability; short states with too-high probability). In particular,...
10
votes
2answers
926 views

Can someone explain rigorously Taleb's criticism of Nate Silver's election forecasting?

Taleb makes the claim in this paper (and others) that there exists some sort of bound on the variance of a binary forecast such that if a forecaster's binary predictions exceed the bounds on variance ...
10
votes
2answers
3k views

How to forecast high-frequency data?

Introduction: I have seen a plenty of articles/books regarding volatility forecasting applied to high frequency data, but none of them were dedicated to forecasting the actual prices (for example bid/...
9
votes
4answers
670 views

Position management in presence of continuous forecast

Let's say we have an equity liquidity-providing model that was fitted on 1 minute bar periods. The model forecasts the 1-min next period return given the activity of the previous bars. Now, when we ...
9
votes
2answers
1k views

How do I replicate John Hussman's recession forecasting methodology?

John Hussman has a recession forecasting methodology he often posts about on his blog, and I am trying to replicate it using publicly available data. I would like to assess his accuracy in predicting ...
8
votes
2answers
515 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
2answers
862 views

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia?

Is there any research on applying state-space or dynamic linear models to forecasting equity risk premia on a security-by-security basis with a medium term horizon (say 3 month to 12 months horizon)? ...
8
votes
1answer
748 views

What are the ensemble techniques to forecast returns?

It was pointed in an other question that ensemble methods can help to reduce curve fitting. What are your experience with these and which one seems the most appropriate? If I had two forecasters that ...
8
votes
1answer
3k views

What is the best way to forecast prepayment rate in an emerging market mortgage loan portfolio?

I constructed a model to forecast the prepayment rates for a mortgage loan portfolio (of mortgages in an emerging market) using probit regression on factors such as loan-to-value, PTI, time from ...
8
votes
1answer
1k views

Density forecast of a GARCH model

I am currently working on developing a series of density forecasts and I am encountering some problems. I am working on weekly S&P 500 returns and the returns process is described as $r_{t} = \...
8
votes
1answer
2k views

Estimate rolling stochastic volatility forecast using stochvol in R

I want to use the R package stochvol to fit a SV model to a DAX training set and use the output to estimate a rolling one-step-ahead forecast: ...
8
votes
2answers
251 views

Is there an optimal covariance one would want forecasts to have?

Often in a quant process, one will generate a time series of return forecasts and use them in some sort of optimization to generate a portfolio. Generally, there will be a covariance matrix of market ...
7
votes
3answers
2k views

The Basis of Using Technical Indicators as Inputs

In the process of my research I very often come across academic papers regarding modelling and trading strategies that in one way or another incorporate some technical indicators. For example in some ...
7
votes
4answers
261 views

What is a sound way to project Company X's earnings over the next Y years?

I need to estimate cumulative earnings over the next Y years and I'd like to find a solution that is theoretically sound and relatively simple. Can anyone recommend an approach? Given: I have 30 ...
7
votes
1answer
937 views

How to use physics models in Time Series Analysis and Forecasting.

I have been studying methods of Technical Analysis for several years and I am disappointed. I actually do not consider it useful. I have not met anyone who can constantly win in the market using these ...
7
votes
2answers
1k views

How do you synthesize a probability density function (pdf) from equally weighted price data?

What I'm working with: I have a collection of prices that has very few to no repeating values (depending on the look back period) ie each price value is unique, some prices are clustered and some can ...
6
votes
3answers
1k views

Modelling and forecasting mixed frequency financial data

I was wondering if someone could provide some guidance to me. I would like to Combine various financial data of mixed frequencies (some daily, weekly, some quarterly) to a composite index. I have ...
6
votes
1answer
2k views

Why are multiple custom curves (swap) built for one desk?

Currently in a journey of learning and getting my hands a bit dirty with Interest Rate Swaps. Why there are multiple customized curves built by many even within one desk? For e.g. Short Rates desk ...
6
votes
4answers
3k views

Is there any way to easily estimate and forecast seasonal ARIMA-GARCH model in any software?

I use R to estimate a seasonal ARIMA(8,0,0)(5,0,1)[7] model for the seasonal differences of logs of daily electricity prices: ...
6
votes
2answers
354 views

Forecasting volatility farther ahead with autoregressive machine learning

ARIMA and GARCH are old news for predicting volatility time series of asset returns. I am aware of papers that replace ARIMA and GARCH with machine learning algorithms to predict financial volatility ...
5
votes
2answers
622 views

Predicting the Future FX Spot Rates

Say I need to predict what the spot rate between USD and CAD will be in 3 months. What will be the most accurate measure or model that I could possibly use? Does the 3 month forward rate necessarily ...
5
votes
1answer
751 views

Coin Toss System

Coin Toss Runs Calculator The expected number of runs for two consecutive heads or tails is 3. Is there an edge if we place a progressive constant size bet(limited to 3 times)for consecutive ...
5
votes
2answers
153 views

Is there a relation between these two forecasting/estimation approaches?

When learning econometrics I have usually seen stuff from the following perspective: Assume $Y_t = f(X_t) + e_t$, where f is some function of $X_t$ (typically linear). For example, assume $Y_t = X_t *...
4
votes
3answers
1k views

What is the purpose of short rate models?

Just venturing into quantitative finance and studying short rate models (Vasicek, CIR, Hull-White etc.). Wanted to ask a very simple intuitive question. How would a practitioner use these models? I ...
4
votes
2answers
189 views

How would you forecast volatility without using any programming languages or machine learning or anything of that sort?

I am trying to forecast volatility. I am on the tactical asset allocation team. No one on our team knows machine learning or any programming languages. We are fundamental equity research analysts ...
4
votes
1answer
2k views

Simulating returns from ARMA(1,0)-GARCH(1,1) model

I want to obtain a simulation of one-step ahead forecasts of stock returns process governed by ARMA(1,0)-GARCH(1,1) process. The returns are of form: $x_t = \mu + \delta x_{t-1} + \sigma_t z_t$ From ...
4
votes
3answers
346 views

How is a GARCH model readily complementary to a forecasting model?

Hi Quantitative Finance Stack Exchange, It's my first go at GARCH models so give me a chance with my phrasing. I'm looking for an answer to a general question. First, I understand that you can have ...
4
votes
1answer
2k views

ARIMA model, cannot get rid of low order ACF spike

I've gone through all the steps to fit a good ARIMA model - I plotted the data, I looked at the ADF tests, I looked at the ACF plot with no AR and MA terms just a constants. I came up with an ARMA(0,1,...
4
votes
1answer
65 views

How to prove that the expected squared error associated with the optimal combination weight is smaller than the minimum of 2 forecast variances?

I am looking at linear combination of two forecasts (Bates and Granger, 1969). I would like to understand how to prove that the expected squared error associated with the optimal combination weight is ...
4
votes
0answers
127 views

Comparison of normalization methods on market returns

I am looking to use a multi-factor model to make target-return predictions. Since the factor-returns come from different scales I need to normalize first. There are different ways to normalize ...