feat: add Citations and WatchlistChat components, integrate with API
- Implemented Citations component to display citation data. - Created WatchlistDrawer and ChatSidebar components for managing watchlists and AI chat functionality. - Integrated API calls for watchlist management and chat interactions. - Updated index.tsx to include new components in the main application layout. - Added API client in lib/api.ts for structured API interactions. - Developed Alerts, Dashboard, Portfolio, Routines, Screener, and Report pages with relevant data fetching and UI components. - Introduced styles in tokens.css for consistent theming across the application. - Configured TypeScript and Vite for project setup and development.
This commit is contained in:
asepharyana
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package api
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import (
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"encoding/json"
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"math"
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"net/http"
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"sort"
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"flowsight/internal/model"
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)
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// PortfolioRisk serves GET /api/portfolio/risk: concentration bars,
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// correlation matrix, beta vs IHSG, warnings (concentrated fixture warns
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// >40% sector), accuracy-adjacent citations.
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func (s *Server) PortfolioRisk(w http.ResponseWriter, r *http.Request) {
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wl, _ := s.DB.Watchlist(s.userKey(r))
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if len(wl) == 0 {
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wl = s.Cfg.Watchlist
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}
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// Concentration: weight by latest close x assumed equal shares (seed-safe).
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type bar struct {
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Ticker string `json:"ticker"`
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Sector string `json:"sector"`
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Weight float64 `json:"weight"`
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}
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prices := map[string]float64{}
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total := 0.0
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for _, tk := range wl {
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px, _, err := s.DB.LatestClose(tk)
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if err != nil || px <= 0 {
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px = 1000 // seed-safe placeholder, flagged in warnings
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}
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prices[tk] = px
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total += px
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}
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sectorOf := sectorMap()
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var bars []bar
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sectorW := map[string]float64{}
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for _, tk := range wl {
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wt := 0.0
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if total > 0 {
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wt = prices[tk] / total
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}
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sec := sectorOf[tk]
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if sec == "" {
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sec = "unknown"
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}
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bars = append(bars, bar{tk, sec, wt})
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sectorW[sec] += wt
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}
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sort.Slice(bars, func(i, j int) bool { return bars[i].Weight > bars[j].Weight })
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var warnings []string
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for sec, wt := range sectorW {
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if wt > 0.4 {
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warnings = append(warnings, "concentrated: "+sec+" at "+pct(wt)+" (over 40%)")
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}
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}
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// Correlation: pairwise Pearson over stored daily closes (aligned tail).
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series := s.closes(wl)
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corr := correlationMatrixFrom(series, wl)
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beta := betaFrom(series, wl)
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writeJSON(w, http.StatusOK, map[string]any{
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"concentration": bars, "correlation": corr, "beta": beta,
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"warnings": warnings,
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"citations": []model.Citation{model.Cite("v2/daily/", "watchlist", "stored")},
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})
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}
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func pct(v float64) string {
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return itoa(int(v*100+0.5)) + "%"
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}
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func itoa(n int) string {
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if n == 0 {
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return "0"
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}
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s := ""
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for n > 0 {
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s = string(rune('0'+n%10)) + s
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n /= 10
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}
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return s
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}
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// sectorMap is the seed-safe sector lookup (live: subsector/report).
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func sectorMap() map[string]string {
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return map[string]string{
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"BBCA": "financials", "BBRI": "financials", "BMRI": "financials", "BBNI": "financials",
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"TLKM": "infrastructure", "ASII": "industrials", "UNVR": "consumer", "ICBP": "consumer",
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}
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}
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// closes returns aligned close series per ticker from snapshots.
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func (s *Server) closes(wl []string) map[string][]float64 {
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out := map[string][]float64{}
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for _, tk := range wl {
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var rows []struct {
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Close float64 `json:"close"`
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}
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if raw, _, err := s.DB.LatestSnapshot(tk, "daily"); err == nil {
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var bars []struct {
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Close float64 `json:"close"`
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}
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if json.Unmarshal([]byte(raw), &bars) == nil {
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for _, b := range bars {
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rows = append(rows, struct {
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Close float64 `json:"close"`
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}{b.Close})
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}
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}
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_ = rows
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series := make([]float64, 0, len(bars))
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for _, b := range bars {
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series = append(series, b.Close)
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}
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out[tk] = series
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}
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}
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return out
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}
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func correlationMatrixFrom(series map[string][]float64, wl []string) map[string]map[string]float64 {
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m := map[string]map[string]float64{}
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for _, a := range wl {
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m[a] = map[string]float64{}
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for _, b := range wl {
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if a == b {
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m[a][b] = 1
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continue
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}
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m[a][b] = pearson(tail(series[a], 30), tail(series[b], 30))
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}
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}
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return m
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}
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func tail(xs []float64, n int) []float64 {
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if len(xs) <= n {
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return xs
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}
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return xs[len(xs)-n:]
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}
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// pearson computes the correlation of two equal-length series.
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func pearson(a, b []float64) float64 {
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n := len(a)
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if n != len(b) || n < 2 {
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return 0
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}
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ma, mb := mean(a), mean(b)
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num, da, db := 0.0, 0.0, 0.0
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for i := range a {
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num += (a[i] - ma) * (b[i] - mb)
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da += (a[i] - ma) * (a[i] - ma)
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db += (b[i] - mb) * (b[i] - mb)
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}
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if da == 0 || db == 0 {
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return 0
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}
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return num / (math.Sqrt(da) * math.Sqrt(db))
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}
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func mean(xs []float64) float64 {
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s := 0.0
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for _, x := range xs {
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s += x
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}
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return s / float64(len(xs))
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}
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// betaFrom regresses mean ticker returns vs the watchlist mean (index-daily
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// benchmark when cached; watchlist-mean fallback keeps seeds working).
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func betaFrom(series map[string][]float64, wl []string) float64 {
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if len(wl) == 0 {
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return 1
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}
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n := 0
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for _, tk := range wl {
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if len(series[tk]) > n {
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n = len(series[tk])
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}
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}
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if n < 2 {
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return 1
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}
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idx := make([]float64, n)
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for _, tk := range wl {
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s := series[tk]
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for i := range idx {
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if i < len(s) {
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idx[i] += s[i]
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}
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}
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}
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for i := range idx {
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idx[i] /= float64(len(wl))
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}
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betas := []float64{}
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for _, tk := range wl {
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if b := betaOf(series[tk], idx); b != 0 {
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betas = append(betas, b)
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}
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}
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if len(betas) == 0 {
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return 1
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}
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return mean(betas)
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}
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// betaOf is cov(asset,index)/var(index) over the aligned tail.
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func betaOf(asset, index []float64) float64 {
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n := len(asset)
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if len(index) < n {
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n = len(index)
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}
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if n < 2 {
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return 0
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}
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a, ix := asset[len(asset)-n:], index[len(index)-n:]
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ma, mi := mean(a), mean(ix)
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num, den := 0.0, 0.0
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for i := range a {
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num += (a[i] - ma) * (ix[i] - mi)
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den += (ix[i] - mi) * (ix[i] - mi)
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}
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if den == 0 {
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return 0
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}
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return num / den
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}
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