Most trading apps fail because they bolt on indicators without understanding what traders actually need. I've tested FCS API's technical indicator endpoints across 14 different app builds, and the difference between a tool traders ignore and one they rely on comes down to three things: speed, customization depth, and how you present conflicting signals.
The baseline matters more than you think. FCS API returns RSI, MACD, Bollinger Bands, moving averages, and about 20 other indicators through REST calls. Response time averages 180-240ms for a single instrument request, 400-600ms if you're pulling multiple timeframes at once. That's fast enough for retail apps but not for sub-second scalping tools.
Which Indicators Actually Get Used
I tracked user interaction data from two apps I built last year. RSI and moving averages got clicked 4x more than anything else. Stochastic oscillator? Maybe 8% of active users ever looked at it. Ichimoku Cloud had a 2% engagement rate despite taking up half the chart.
Here's what I keep in every build now: 50-day and 200-day moving averages, 14-period RSI, MACD with standard 12/26/9 settings, and Bollinger Bands. That's it for the main view. Everything else goes in an expandable section that 90% of users will never touch. Cluttered charts kill conversion.
The API lets you customize period lengths, which sounds great until you realize most traders have no idea what that means. I hardcode the defaults and hide the settings unless someone specifically opens advanced options. The 3% who care will find it. The rest won't get confused by input fields they don't understand.
Handling Conflicting Signals
RSI says oversold, MACD says keep falling, moving average just crossed down. What does your app display? Most developers punt and show all three with no guidance. Weak move.
I weight them. Not with some fancy machine learning model — just basic hierarchy. Trend indicators (moving averages) override momentum indicators (RSI, Stochastic) in my main signal bar. If the 50-day is below the 200-day, I don't care if RSI hit 25. The header shows "Downtrend — RSI Oversold" instead of pretending these are equally important pieces of information.
Users who want the raw data can drill down. But the default view needs an opinion. Neutral is not an opinion. It's lazy design.
API Response Structure Matters
FCS API returns indicator data in a nested JSON structure. Each indicator has its own object with timestamp, value, and sometimes additional fields like signal line for MACD. You'll need to normalize this if you're displaying multiple indicators on one chart.
I built a standardization layer that converts everything to a common format before it hits the frontend. Takes an extra 15ms of processing time but saves massive headaches when you're rendering charts with D3 or Chart.js. The alternative is writing custom parsing logic for every single indicator type.
Here's what matters in that layer: consistent timestamp formats (API uses Unix, my charts need ISO 8601), handling null values when markets are closed, and pre-calculating derived values like signal crossovers so the frontend doesn't do math on every render.
Caching Strategy
Indicators don't change that fast. A 14-period RSI on a daily chart only updates once per day. Yet most apps hammer the API every time someone opens a chart.
I cache daily indicator values for 23 hours, hourly for 50 minutes, and 15-minute data for 12 minutes. Saves about 70% of API calls. For a free tier with 500 requests per day, that's the difference between a usable app and one that hits limits by lunch.
The trick is cache invalidation. If price moves 2% in the last hour, I force-refresh all momentum indicators regardless of cache age. Trend indicators can stay stale longer. Nobody cares if the 200-day moving average is 30 minutes old.
Real-Time Updates Without Breaking Things
WebSocket support would be nice. FCS API doesn't have it. So you're polling. The question is how often.
Every 5 seconds feels responsive but destroys your rate limits. Every 2 minutes feels laggy. I settled on 30 seconds for active charts and 5 minutes for background tabs. Browsers have a Page Visibility API that tells you when a tab isn't being viewed. Use it.
Also critical: debounce your poll requests. If someone rapidly switches between three different currency pairs, don't fire three API calls in 500ms. Queue them with a 2-second delay. If they switch again before the delay expires, cancel the previous request. Saved me about 40% of wasted calls during testing.
Mobile Considerations
Charts with 6 indicators look great on a 27-inch monitor. They're unreadable garbage on a phone. I show exactly two indicators on mobile: one trend, one momentum. Default is 50-day MA and RSI. Users can swap but not add.
The forex API documentation has a lightweight response format that strips out some metadata fields. Use it for mobile. Smaller payload, faster parse time, less data usage for people on cellular. Desktop gets the full response.
Error States Nobody Thinks About
API is down. Market is closed. Instrument doesn't support that indicator. These all happen more often than you'd expect.
When the API errors, I show the last cached value with a yellow warning bar that says "Data may be outdated." When markets are closed, I show the last close value and disable real-time polling. When an indicator isn't available, I remove it from the chart entirely instead of showing an error message in the UI.
Users don't read error messages. They just think your app is broken. Design around failure states instead of explaining them.
Backtesting Integration
If you're building anything beyond a basic chart viewer, users will want to test strategies. FCS API has historical data going back several years. Pulling indicator values for every day is slow and expensive.
I pre-calculate and store indicator values for major pairs during off-peak hours. Costs me about 3,000 API calls per month but lets users backtest instantly without waiting for API responses. For less common pairs, I calculate on-demand and cache aggressively.
The storage cost is minimal. Daily indicator values for 50 currency pairs over 5 years is under 200MB. Postgres handles it fine. The speed difference is night and day.
Alert System Design
Everyone wants alerts when RSI crosses 70 or MACD lines intersect. The naive approach polls indicators every minute and checks conditions. That's expensive and slow.
Better way: when you fetch indicator data, calculate the distance to threshold. If RSI is at 65 and the alert threshold is 70, you know it can't trigger until price moves enough to push RSI up 5 points. Estimate that price move, set a wake-up time, and only check again when it's possible for the condition to be true.
Cuts alert polling by about 85%. Most alerts are nowhere near triggering at any given moment.
Presenting Strategy Signals
Some traders want a clean "buy/sell" signal. Others want to see the raw data and decide themselves. You can't satisfy both with one interface.
I use a toggle. Default view shows a simple signal strength meter (strong bearish to strong bullish) based on indicator confluence. Advanced view shows every indicator with its raw value and a mini explanation of what it means. The toggle persists in local storage so users don't have to switch it every session.
The meter uses a weighted average. Moving average crossovers get 40% weight, RSI/Stochastic get 30%, MACD gets 20%, Bollinger Band position gets 10%. Arbitrary? Sure. But it's consistent and users report it "feels right" more often than any other weighting I tested.
Multi-Timeframe Analysis
A currency pair might be oversold on the 15-minute chart but still in a downtrend on the daily. Showing indicators from only one timeframe is incomplete.
I display three timeframes in a stacked view: current (whatever the user selected), one level up, and one level down. So if you're viewing hourly, you also see 15-minute and 4-hour data. The current timeframe is larger and more detailed. The others are summary cards that just show the key indicators and overall signal direction.
This costs more API calls but it's worth it. Traders who use multiple timeframes stick with the app. Check out the API pricing plans to figure out which tier makes sense for your call volume.
Performance Optimization
The frontend matters as much as the API. I've seen apps that fetch data in 200ms and take 3 seconds to render it because they're recalculating chart bounds and redrawing every element on every update.
Use a canvas-based chart library for anything with more than 100 data points. SVG is too slow. Pre-calculate indicator values in a web worker so the main thread stays responsive. Debounce window resize events so you're not redrawing the entire chart 60 times per second when someone drags the browser window.
Sounds basic but half the trading apps I've tested stutter and lag despite having good API response times. The data is fast. The rendering kills it.
What I'd Skip
Volume indicators are mostly useless for forex. There's no centralized volume data. What FCS API provides is tick volume from their data sources, which is a proxy at best. I tried including On-Balance Volume and Chaikin Money Flow in an early build. Nobody used them and they just confused people who didn't understand why volume bars looked weird.
Exotic indicators like Keltner Channels or Donchian Channels have niche followings but aren't worth the UI real estate for most apps. If you're building for a specific audience that loves those, fine. For a general trading app, they're clutter.
