Fundamental and Market Inputs for Predicting Foreign Exchange
Summary
The discussion considers what additional time series might help a neural network forecast daily foreign exchange rates. Suggested inputs include currency crosses, interest rate differentials, yield curve slopes, and changes in rates, along with country-level macroeconomic releases such as GDP, inflation, and employment. The latter may inform long-term trends, but their release frequency may not match daily or intraday trading, and later revisions can complicate their use.
Other proposals include precious and industrial metals, energy prices, commodity futures, and broad equity indices. These markets may provide context for currency valuation; for example, a rising gold price in dollar terms can reflect dollar weakness against hard assets. Technical indicators are also suggested, though the discussion does not establish a fundamental rationale for them. The recommendations are exploratory rather than a tested feature set: historical relationships alone may be spurious, and no comparative predictive results, timing protocol, or out-of-sample evidence is provided.
Key ideas
- Interest rate differentials and yield curve measures are proposed as fundamental currency predictors.
- Macroeconomic releases may suit longer-term signals, but their timing and subsequent revisions limit daily use.
- Commodity and hard-asset prices can provide a reference for interpreting a currency’s relative value.
- Equity indices and technical indicators are suggested as additional model inputs, without evidence of predictive benefit.
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# Intermarket analysis - related time series? # Intermarket analysis - related time series? I'm about to embark on training a neural network on daily forex data, with a view to obtaining a predictive network. I'm also interested in using data other than the forex currency pair data itself, in a manner similar to intermarket analysis. What other time series data does the panel think will provide meaningful input? Obviously, various other forex cross rates are important, along with perhaps interest rate time series. But what about perhaps less intuitively obvious time series? I'm more interested in time series that have a justifiably fundamental reason for inclusion rather than those that might simply exhibit historical correlation. Links to online references/papers, e.g. SSRN etc. would be very welcome. ## Answer by TonyMorland (score 2) https://quant.stackexchange.com/a/14138 In addition to FX currency cross rates and interest rates, several other potentially useful inputs are: 1) Economic data (GDP, inflation rates, employment figures) for the specific countries whose currencies you are interested in. While these data may be useful indicators, there are however two problems: Firstly the granularity of the data. If you are using EOD or intra-day FX data then ideally you would like the other inputs to your NN to be on a similar timescale and these are not. The second problem is that government statistics are often subject to "adjustment" some time after issue. Notwithstanding these caveats, such economic data may be useful with regard to long-term trends. 2) FX rates are relative values of one fiat currency against another without any absolute scale of "true" value. It is useful to also include as input "hard" asset price series such as precious and base metals and energy. These help to provide at least some form of absolute reference. For example a rising price of gold (denominated in USD) can alternatively be viewed as a decline in the value of the USD vs. hard assets. ## Answer by Kevin Pei (score 1) https://quant.stackexchange.com/a/14493 It's also necessary to look into technical indicators and filters. Technically analysis are often widely employed by finance practitioners and can apply to any sort of timeframe whether that's intra-day or EODs. Since ANNs are able to fit complex non-linear inputs, it would not hurt to add many of those indicators into the mix ## Answer by Roshan (score 1) https://quant.stackexchange.com/a/17082 Actually you can find a papers talking about some relationship between almost any two types of indicators. But based on my work this what I suggest you add: - Commodities futures (continues) (Many paper on the relationship between oil prices and USD, gold/silver and USD) - Market indices (DJI, S&P500, DAX, SET, NZ40, ...) I would also suggest that you inverse the patterns of these indices and futures and add both original and inversed pattern. ## Answer by KML (score 0) https://quant.stackexchange.com/a/17079 Interest rate differentials is the most justifiable fundamental input, also the most explanatory second order input you should use. Another is the slope of the yield curve and the difference in slope between pairs. You can also look at the relative difference in speed of interest rate changes. Another fundamental input is the real IR spread. Good luck.
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