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17
votes
7answers
6k 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 ...
32
votes
8answers
12k 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 ...
18
votes
3answers
5k 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 ...
16
votes
3answers
2k 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 ...
11
votes
2answers
779 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 ...
14
votes
2answers
2k 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 ...
1
vote
0answers
460 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? ...