Initial commit: 可转债轮动分析系统
- 实时行情：东财push2主源 + 腾讯批量报价备用源（自动切换） - 历史K线：东财push2his主源 + 腾讯web子域备用源（含熔断机制） - 增量同步：支持 -incr/-since 参数按存档日期增量入库 - 策略回测：净值曲线/10指标/基准对比，含基本面过滤 - 用户认证：用户名密码 + 邮箱验证码双登录方式 - 前端：三Tab SPA（实时行情/策略回测/数据管理）
This commit is contained in:
87
internal/strategy/doublelow.go
Normal file
87
internal/strategy/doublelow.go
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@@ -0,0 +1,87 @@
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// Package strategy 提供内置回测策略（MVC Service 层）。
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// 用户可在 backtest.Strategy 接口基础上扩展自定义轮动/网格等策略。
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package strategy
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import (
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"context"
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"fmt"
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"sort"
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"stock-analysis/internal/backtest"
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)
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// DoubleLowParams 双低轮动策略参数。
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type DoubleLowParams struct {
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TopN int // 持仓数量
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Rebalance int // 调仓周期（交易日）
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MinPrice float64 // 价格下限（过滤异常低价/退市风险债）
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MaxPrice float64 // 价格上限
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MaxPremium float64 // 溢价率上限（过滤高溢价债，0 表示不限制）
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}
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// DefaultDoubleLowParams 返回推荐默认参数。
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func DefaultDoubleLowParams() DoubleLowParams {
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return DoubleLowParams{TopN: 10, Rebalance: 21, MinPrice: 90, MaxPrice: 130, MaxPremium: 30}
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}
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// DoubleLow 双低轮动策略：每个调仓日选择"双低值 = 转债价 + 转股溢价率(%)"
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// 最低的 TopN 只转债等权持有。该策略兼顾"低价"的债性保护与"低溢价"的股性弹性，
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// 是经典的稳健型可转债轮动框架。
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type DoubleLow struct {
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params DoubleLowParams
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day int // 已执行的交易日计数
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}
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// NewDoubleLow 创建双低轮动策略。
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func NewDoubleLow(p DoubleLowParams) *DoubleLow {
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return &DoubleLow{params: p}
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}
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// Name 返回策略名称。
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func (s *DoubleLow) Name() string {
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return fmt.Sprintf("双低轮动(top%d,每%d交易日)", s.params.TopN, s.params.Rebalance)
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}
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// OnBar 实现 backtest.Strategy：交易日递增，到调仓日时按双低值选股返回目标持仓。
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func (s *DoubleLow) OnBar(ctx context.Context, date string, universe []backtest.Quote, hist *backtest.History) ([]backtest.Target, error) {
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s.day++
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if s.day > 1 && (s.day-1)%s.params.Rebalance != 0 {
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return nil, nil // 非调仓日
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}
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type cand struct {
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code string
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doubleLow float64
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}
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candidates := make([]cand, 0, len(universe))
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for _, q := range universe {
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if q.Price < s.params.MinPrice || q.Price > s.params.MaxPrice {
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continue
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}
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// 溢价率缺失（未入库）或非正时为 0/负值，不参与双低排序。
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if q.PremiumRate <= 0 {
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continue
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}
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if s.params.MaxPremium > 0 && q.PremiumRate > s.params.MaxPremium {
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continue
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}
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candidates = append(candidates, cand{
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code: q.Code,
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doubleLow: q.Price + q.PremiumRate,
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})
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}
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sort.Slice(candidates, func(i, j int) bool { return candidates[i].doubleLow < candidates[j].doubleLow })
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if len(candidates) > s.params.TopN {
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candidates = candidates[:s.params.TopN]
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}
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if len(candidates) == 0 {
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return nil, nil // 无合格标的，保持现状
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}
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weight := 1.0 / float64(len(candidates))
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targets := make([]backtest.Target, 0, len(candidates))
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for _, c := range candidates {
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targets = append(targets, backtest.Target{Code: c.code, Weight: weight})
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}
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return targets, nil
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}
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152
internal/strategy/doublelow_test.go
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152
internal/strategy/doublelow_test.go
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@@ -0,0 +1,152 @@
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package strategy
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import (
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"context"
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"testing"
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"stock-analysis/internal/backtest"
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)
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func TestDoubleLow_Name(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 10, Rebalance: 21, MinPrice: 90, MaxPrice: 130, MaxPremium: 30})
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name := s.Name()
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if name == "" {
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t.Error("strategy name should not be empty")
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}
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}
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func TestDoubleLow_SelectByDoubleLowValue(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 3, Rebalance: 5, MinPrice: 90, MaxPrice: 130, MaxPremium: 30})
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universe := []backtest.Quote{
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{Code: "A", Price: 100, PremiumRate: 10}, // 双低 = 110
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{Code: "B", Price: 95, PremiumRate: 5}, // 双低 = 100 (最低)
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{Code: "C", Price: 110, PremiumRate: 20}, // 双低 = 130
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{Code: "D", Price: 105, PremiumRate: 8}, // 双低 = 113
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{Code: "E", Price: 120, PremiumRate: 15}, // 双低 = 135
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}
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targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if err != nil {
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t.Fatalf("unexpected error: %v", err)
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}
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if len(targets) != 3 {
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t.Fatalf("expected 3 targets, got %d", len(targets))
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}
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// 按双低值排序：B(100), A(110), D(113)
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codes := make(map[string]bool)
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for _, tg := range targets {
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codes[tg.Code] = true
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}
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if !codes["B"] || !codes["A"] || !codes["D"] {
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t.Errorf("expected codes B, A, D, got %v", codes)
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}
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}
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func TestDoubleLow_FilterByPriceRange(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 5, Rebalance: 5, MinPrice: 90, MaxPrice: 130, MaxPremium: 30})
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universe := []backtest.Quote{
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{Code: "A", Price: 85, PremiumRate: 5}, // 价格过低，过滤
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{Code: "B", Price: 100, PremiumRate: 10}, // 合格
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{Code: "C", Price: 135, PremiumRate: 5}, // 价格过高，过滤
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}
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targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if err != nil {
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t.Fatalf("unexpected error: %v", err)
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}
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if len(targets) != 1 {
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t.Fatalf("expected 1 target, got %d", len(targets))
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}
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if targets[0].Code != "B" {
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t.Errorf("expected code B, got %s", targets[0].Code)
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}
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}
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func TestDoubleLow_FilterByPremiumRate(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 5, Rebalance: 5, MinPrice: 90, MaxPrice: 130, MaxPremium: 20})
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universe := []backtest.Quote{
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{Code: "A", Price: 100, PremiumRate: 15}, // 合格
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{Code: "B", Price: 100, PremiumRate: 25}, // 溢价过高，过滤
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{Code: "C", Price: 100, PremiumRate: 0}, // 溢价为0，过滤
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{Code: "D", Price: 100, PremiumRate: -5}, // 负溢价，过滤
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}
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targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if err != nil {
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t.Fatalf("unexpected error: %v", err)
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}
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if len(targets) != 1 {
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t.Fatalf("expected 1 target, got %d", len(targets))
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}
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if targets[0].Code != "A" {
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t.Errorf("expected code A, got %s", targets[0].Code)
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}
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}
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func TestDoubleLow_NoQualifiedCandidates(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 3, Rebalance: 5, MinPrice: 90, MaxPrice: 130, MaxPremium: 30})
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universe := []backtest.Quote{
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{Code: "A", Price: 50, PremiumRate: 5},
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{Code: "B", Price: 200, PremiumRate: 10},
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}
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targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if err != nil {
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t.Fatalf("unexpected error: %v", err)
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}
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if targets != nil {
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t.Error("expected nil targets when no qualified candidates")
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}
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}
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func TestDoubleLow_RebalanceCycle(t *testing.T) {
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s := NewDoubleLow(DoubleLowParams{TopN: 3, Rebalance: 3, MinPrice: 90, MaxPrice: 130, MaxPremium: 30})
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universe := []backtest.Quote{
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{Code: "A", Price: 100, PremiumRate: 10},
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}
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// 第 1 天：调仓
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targets, _ := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets == nil {
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t.Error("day 1 should rebalance")
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}
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// 第 2-3 天：不调仓
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for i := 0; i < 2; i++ {
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targets, _ = s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets != nil {
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t.Errorf("day %d should not rebalance", i+2)
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}
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}
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// 第 4 天：调仓
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targets, _ = s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets == nil {
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t.Error("day 4 should rebalance")
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}
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}
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func TestDefaultDoubleLowParams(t *testing.T) {
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p := DefaultDoubleLowParams()
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if p.TopN != 10 {
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t.Errorf("TopN: expected 10, got %d", p.TopN)
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}
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if p.Rebalance != 21 {
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t.Errorf("Rebalance: expected 21, got %d", p.Rebalance)
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}
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if p.MinPrice != 90 {
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t.Errorf("MinPrice: expected 90, got %f", p.MinPrice)
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}
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if p.MaxPrice != 130 {
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t.Errorf("MaxPrice: expected 130, got %f", p.MaxPrice)
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}
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if p.MaxPremium != 30 {
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t.Errorf("MaxPremium: expected 30, got %f", p.MaxPremium)
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}
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}
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71
internal/strategy/lowprice.go
Normal file
71
internal/strategy/lowprice.go
Normal file
@@ -0,0 +1,71 @@
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// Package strategy 提供内置回测策略（MVC Service 层）。
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// 用户可在 backtest.Strategy 接口基础上扩展自定义轮动/网格等策略。
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package strategy
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import (
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"context"
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"fmt"
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"sort"
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"stock-analysis/internal/backtest"
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)
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// LowPriceParams 低价轮动策略参数。
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type LowPriceParams struct {
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TopN int // 持仓数量
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Rebalance int // 调仓周期（交易日）
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MinPrice float64 // 价格下限（过滤异常低价/退市风险债）
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MaxPrice float64 // 价格上限（低价策略通常低于 130）
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}
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// DefaultLowPriceParams 返回推荐默认参数。
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func DefaultLowPriceParams() LowPriceParams {
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return LowPriceParams{TopN: 10, Rebalance: 21, MinPrice: 80, MaxPrice: 130}
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}
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// LowPrice 低价轮动策略：每 Rebalance 个交易日，选择全市场价格最低的 TopN
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// 只转债等权持有。基于可转债"下有保底"特性，低价格通常意味着较低的下行风险，
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// 是经典的可转债轮动框架（演示用，可替换为双低/溢价等因子）。
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type LowPrice struct {
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params LowPriceParams
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day int // 已执行的交易日计数
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}
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// NewLowPrice 创建低价轮动策略。
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func NewLowPrice(p LowPriceParams) *LowPrice {
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return &LowPrice{params: p}
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}
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// Name 返回策略名称。
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func (s *LowPrice) Name() string {
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return fmt.Sprintf("低价轮动(top%d,每%d交易日)", s.params.TopN, s.params.Rebalance)
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}
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// OnBar 实现 backtest.Strategy：交易日递增，到调仓日时选股返回目标持仓。
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func (s *LowPrice) OnBar(ctx context.Context, date string, universe []backtest.Quote, hist *backtest.History) ([]backtest.Target, error) {
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s.day++
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if s.day > 1 && (s.day-1)%s.params.Rebalance != 0 {
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return nil, nil // 非调仓日
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}
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candidates := make([]backtest.Quote, 0, len(universe))
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for _, q := range universe {
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if q.Price >= s.params.MinPrice && q.Price <= s.params.MaxPrice {
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candidates = append(candidates, q)
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}
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}
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sort.Slice(candidates, func(i, j int) bool { return candidates[i].Price < candidates[j].Price })
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if len(candidates) > s.params.TopN {
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candidates = candidates[:s.params.TopN]
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}
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if len(candidates) == 0 {
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return nil, nil // 无合格标的，保持现状
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}
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weight := 1.0 / float64(len(candidates))
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targets := make([]backtest.Target, 0, len(candidates))
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for _, q := range candidates {
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targets = append(targets, backtest.Target{Code: q.Code, Weight: weight})
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}
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return targets, nil
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}
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139
internal/strategy/lowprice_test.go
Normal file
139
internal/strategy/lowprice_test.go
Normal file
@@ -0,0 +1,139 @@
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package strategy
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import (
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"context"
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"testing"
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"stock-analysis/internal/backtest"
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)
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func TestLowPrice_Name(t *testing.T) {
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s := NewLowPrice(LowPriceParams{TopN: 10, Rebalance: 21, MinPrice: 80, MaxPrice: 130})
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name := s.Name()
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if name == "" {
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t.Error("strategy name should not be empty")
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}
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}
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func TestLowPrice_FirstDaySelectsTopN(t *testing.T) {
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s := NewLowPrice(LowPriceParams{TopN: 3, Rebalance: 5, MinPrice: 80, MaxPrice: 130})
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universe := []backtest.Quote{
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{Code: "A", Price: 100},
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{Code: "B", Price: 90},
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{Code: "C", Price: 110},
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{Code: "D", Price: 85},
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{Code: "E", Price: 120},
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{Code: "F", Price: 75}, // 低于 MinPrice，应被过滤
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{Code: "G", Price: 135}, // 高于 MaxPrice，应被过滤
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}
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targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if err != nil {
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t.Fatalf("unexpected error: %v", err)
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}
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if len(targets) != 3 {
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t.Fatalf("expected 3 targets, got %d", len(targets))
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}
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// 按价格升序，应选 D(85), B(90), A(100)
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codes := make(map[string]bool)
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for _, tg := range targets {
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codes[tg.Code] = true
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}
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if !codes["D"] || !codes["B"] || !codes["A"] {
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t.Errorf("expected codes D, B, A, got %v", codes)
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}
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// 权重应为等权 1/3
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for _, tg := range targets {
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if tg.Weight != 1.0/3.0 {
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t.Errorf("weight for %s: expected %f, got %f", tg.Code, 1.0/3.0, tg.Weight)
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}
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}
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}
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func TestLowPrice_NonRebalanceDay(t *testing.T) {
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s := NewLowPrice(LowPriceParams{TopN: 3, Rebalance: 5, MinPrice: 80, MaxPrice: 130})
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universe := []backtest.Quote{
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{Code: "A", Price: 100},
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}
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// 第 1 天：调仓
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targets, _ := s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets == nil {
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t.Error("day 1 should rebalance")
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}
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// 第 2-5 天：不调仓
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for i := 0; i < 4; i++ {
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targets, _ = s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets != nil {
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t.Errorf("day %d should not rebalance", i+2)
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}
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}
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// 第 6 天：调仓
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targets, _ = s.OnBar(context.Background(), "2020-01-02", universe, nil)
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if targets == nil {
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t.Error("day 6 should rebalance")
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}
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}
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func TestLowPrice_NoQualifiedCandidates(t *testing.T) {
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s := NewLowPrice(LowPriceParams{TopN: 3, Rebalance: 5, MinPrice: 80, MaxPrice: 130})
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// 所有标的价格都不在范围内
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universe := []backtest.Quote{
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{Code: "A", Price: 50},
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{Code: "B", Price: 200},
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}
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||||
|
||||
targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
|
||||
if err != nil {
|
||||
t.Fatalf("unexpected error: %v", err)
|
||||
}
|
||||
if targets != nil {
|
||||
t.Error("expected nil targets when no qualified candidates")
|
||||
}
|
||||
}
|
||||
|
||||
func TestLowPrice_FewerThanTopN(t *testing.T) {
|
||||
s := NewLowPrice(LowPriceParams{TopN: 10, Rebalance: 5, MinPrice: 80, MaxPrice: 130})
|
||||
|
||||
universe := []backtest.Quote{
|
||||
{Code: "A", Price: 100},
|
||||
{Code: "B", Price: 110},
|
||||
}
|
||||
|
||||
targets, err := s.OnBar(context.Background(), "2020-01-02", universe, nil)
|
||||
if err != nil {
|
||||
t.Fatalf("unexpected error: %v", err)
|
||||
}
|
||||
if len(targets) != 2 {
|
||||
t.Fatalf("expected 2 targets, got %d", len(targets))
|
||||
}
|
||||
// 权重应为等权 1/2
|
||||
for _, tg := range targets {
|
||||
if tg.Weight != 0.5 {
|
||||
t.Errorf("weight for %s: expected 0.5, got %f", tg.Code, tg.Weight)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
func TestDefaultLowPriceParams(t *testing.T) {
|
||||
p := DefaultLowPriceParams()
|
||||
if p.TopN != 10 {
|
||||
t.Errorf("TopN: expected 10, got %d", p.TopN)
|
||||
}
|
||||
if p.Rebalance != 21 {
|
||||
t.Errorf("Rebalance: expected 21, got %d", p.Rebalance)
|
||||
}
|
||||
if p.MinPrice != 80 {
|
||||
t.Errorf("MinPrice: expected 80, got %f", p.MinPrice)
|
||||
}
|
||||
if p.MaxPrice != 130 {
|
||||
t.Errorf("MaxPrice: expected 130, got %f", p.MaxPrice)
|
||||
}
|
||||
}
|
||||
79
internal/strategy/premium.go
Normal file
79
internal/strategy/premium.go
Normal file
@@ -0,0 +1,79 @@
|
||||
package strategy
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"sort"
|
||||
|
||||
"stock-analysis/internal/backtest"
|
||||
)
|
||||
|
||||
// PremiumParams 溢价率轮动策略参数。
|
||||
type PremiumParams struct {
|
||||
TopN int // 持仓数量
|
||||
Rebalance int // 调仓周期（交易日）
|
||||
MinPrice float64 // 价格下限
|
||||
MaxPrice float64 // 价格上限
|
||||
}
|
||||
|
||||
// DefaultPremiumParams 返回推荐默认参数（价格放宽到 90-150）。
|
||||
func DefaultPremiumParams() PremiumParams {
|
||||
return PremiumParams{TopN: 10, Rebalance: 21, MinPrice: 90, MaxPrice: 150}
|
||||
}
|
||||
|
||||
// Premium 溢价率轮动策略：每 Rebalance 个交易日，选择转股溢价率最低的 TopN
|
||||
// 只转债等权持有。溢价率低意味着转债价格与正股联动紧密，正股涨则转债跟涨，
|
||||
// 适合正股上涨行情，避免"正股涨转债不涨"的尴尬。
|
||||
type Premium struct {
|
||||
params PremiumParams
|
||||
day int
|
||||
}
|
||||
|
||||
// NewPremium 创建溢价率轮动策略。
|
||||
func NewPremium(p PremiumParams) *Premium {
|
||||
return &Premium{params: p}
|
||||
}
|
||||
|
||||
// Name 返回策略名称。
|
||||
func (s *Premium) Name() string {
|
||||
return fmt.Sprintf("溢价率轮动(top%d,每%d交易日)", s.params.TopN, s.params.Rebalance)
|
||||
}
|
||||
|
||||
// OnBar 实现 backtest.Strategy：到调仓日时按溢价率升序选股。
|
||||
// 注意：东财历史K线API不返回转股溢价率，当前数据库中的 PremiumRate 均为 0。
|
||||
// 因此策略暂以"价格"作为溢价率的代理排序指标（低价债通常溢价率更低），
|
||||
// 待后续接入正股K线数据后将改为按实际溢价率排序。
|
||||
func (s *Premium) OnBar(ctx context.Context, date string, universe []backtest.Quote, hist *backtest.History) ([]backtest.Target, error) {
|
||||
s.day++
|
||||
if s.day > 1 && (s.day-1)%s.params.Rebalance != 0 {
|
||||
return nil, nil
|
||||
}
|
||||
|
||||
candidates := make([]backtest.Quote, 0, len(universe))
|
||||
for _, q := range universe {
|
||||
if q.Price >= s.params.MinPrice && q.Price <= s.params.MaxPrice {
|
||||
candidates = append(candidates, q)
|
||||
}
|
||||
}
|
||||
// 按溢价率排序：有实际溢价率数据时优先使用，否则回退到价格排序。
|
||||
sort.Slice(candidates, func(i, j int) bool {
|
||||
pi, pj := candidates[i].PremiumRate, candidates[j].PremiumRate
|
||||
if pi > 0 && pj > 0 {
|
||||
return pi < pj
|
||||
}
|
||||
return candidates[i].Price < candidates[j].Price
|
||||
})
|
||||
if len(candidates) > s.params.TopN {
|
||||
candidates = candidates[:s.params.TopN]
|
||||
}
|
||||
if len(candidates) == 0 {
|
||||
return nil, nil
|
||||
}
|
||||
|
||||
weight := 1.0 / float64(len(candidates))
|
||||
targets := make([]backtest.Target, 0, len(candidates))
|
||||
for _, q := range candidates {
|
||||
targets = append(targets, backtest.Target{Code: q.Code, Weight: weight})
|
||||
}
|
||||
return targets, nil
|
||||
}
|
||||
Reference in New Issue
Block a user