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0answers
473 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? ...
4
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0answers
164 views

Rolling window Kendall's tau against APARCH(1,1) correlation

Assume you want to forecast the correlation matrix of a stocks' basket (say 15 ~ 20 stocks from different sectors); assume you need to forecast at $T$ days because you will use the forecast ouput with ...
1
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0answers
218 views

Modeling asset performance to Bitcoin revenue

I'm attempting to model asset performance to Bitcoin revenue, which is a driving force in the Bitcoin community. Question Is there any model, or research being done that tracks "hashes per second" ...
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2answers
577 views

Evaluating forecasting algorithm

I am trying to evaluate a forecasting algorithm for stock price prediction. However, the performance of the algorithm may be very much tied to the trading strategy. Is there a systematic way for ...
8
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4answers
496 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 ...
7
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2answers
199 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 ...
6
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1answer
1k 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 ...
2
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1answer
383 views

Econometric vs ANN models for forecast?

I hope this is an appropriate question for this forum... for me it is an obvious query since it intrigues me for a long time. Ok, assume there are 2 distinct classes of models: econometric (AR, MA, ...
13
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2answers
967 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 ...
6
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4answers
239 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 ...
9
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1answer
931 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 ...
7
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2answers
626 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)? ...
2
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1answer
389 views

Techniques for forecasting short-frame data?

I'm having a problem in which a time series of 24 data points is given to forecast the next 12 data points. This 24 data points might be sparse (many are missing). Do you have any suggestion on what ...
7
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2answers
413 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 ...
3
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1answer
667 views

Rolling GARCH and higher moments

I m recently doing my dissertation and faced with problem in estimation basic rolling GARCh (1,1) process. I have 2500 observation and need to forecast 1 day ahead volatility in rolling form. I will ...
9
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2answers
913 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
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1answer
541 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 ...
8
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2answers
2k 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 ...
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5answers
5k 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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8answers
8k 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 ...
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3answers
6k 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: Support Vector ...
8
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4answers
1k 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?
18
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3answers
3k 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 ...
14
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4answers
13k 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 ...
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9answers
17k 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 ...
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4answers
4k 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 ...
6
votes
1answer
588 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 ...
12
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4answers
2k 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 ...
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2answers
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 ...