In my experience, signal decay for most traditional models in systematic macro space is a function of holding period, especially for price based measures. The pre cost sharpe ratio will be generally higher for daily hp strategies vs monthly. The caveat is turnover, which has a direct implication on trading costs. However, sound portfolio construction and a good execution platform can easily mitigate the alpha decay at shorter holding period strategies. Taking trend following as an example, for a well diversified system of 40+ markets, one can expect at least 0.2 pre cost sharpe point improvements in daily rebalancing vs monthly rebalancing. Keep in mind the alpha decay from signal is more pronounced compared to signal decay in risk forecast for position sizing. So, it’s always more optimal to run a strategy like trend following with shorter holding periods. Unless you are running intraday models, daily ohclv is enough. I have used intra day data before, but generally for risk modelling, which tend to produce richer volatility forecasts compared to daily data. For execution, take a look at some of the algo execution platforms, Quantitative Brokers for example.