private async void DisplayPricingData(string ticker)
{
List <double> priceslastyear = new List <double>();
List <string> dateslastyear = new List <string>();
// Creating the connection object
IAvapiConnection connection = AvapiConnection.Instance;
IAvapiResponse_TIME_SERIES_MONTHLY_ADJUSTED m_time_series_monthly_adjustedResponse;
// Set up the connection and pass the API_KEY provided by alphavantage.co
connection.Connect("7NIMRBR8G8UB7P8C");
// Get the TIME_SERIES_MONTHLY_ADJUSTED query object
Int_TIME_SERIES_MONTHLY_ADJUSTED time_series_monthly_adjusted =
connection.GetQueryObject_TIME_SERIES_MONTHLY_ADJUSTED();
// Perform the TIME_SERIES_MONTHLY_ADJUSTED request and get the result
m_time_series_monthly_adjustedResponse = await time_series_monthly_adjusted.QueryPrimitiveAsync(
ticker);
var data = m_time_series_monthly_adjustedResponse.Data;
if (data.Error)
{
Console.WriteLine(data.ErrorMessage);
}
else
{
int counter = 0;
foreach (var timeseries in data.TimeSeries)
{
//Grab 1 year worth of months data
if (counter < 12)
{
//add raw prices and dates to arrays
priceslastyear.Add(double.Parse(timeseries.adjustedclose, CultureInfo.InvariantCulture.NumberFormat));
Debug.WriteLine(float.Parse(timeseries.adjustedclose, CultureInfo.InvariantCulture.NumberFormat));
Debug.WriteLine(timeseries.DateTime);
Microcharts.Entry tempEntry = new Microcharts.Entry(float.Parse(timeseries.adjustedclose, CultureInfo.InvariantCulture.NumberFormat))
{
Label = timeseries.DateTime,
ValueLabel = timeseries.adjustedclose//Color = investmentList[i].color.ToSKColor()
};
entries.Add(tempEntry);
}
counter = counter + 1;
}
}
var chart = new LineChart()
{
Entries = entries, LineMode = LineMode.Straight, LineSize = 8, PointSize = 18, LabelTextSize = 25
};
this.chartView.Chart = chart;
}
private async void History5y(object sender, RoutedEventArgs e)
{
var values = new ChartValues <DateTimePoint>();
Int_TIME_SERIES_MONTHLY_ADJUSTED time_series_montly_adjusted = _connection.GetQueryObject_TIME_SERIES_MONTHLY_ADJUSTED();
try
{
IAvapiResponse_TIME_SERIES_MONTHLY_ADJUSTED time_series_weekly_adjustedResponse =
await time_series_montly_adjusted.QueryPrimitiveAsync(_args.Symbol);
var data = time_series_weekly_adjustedResponse.Data;
if (data.Error)
{
MessageBox.Show("Failed to fetch data", "Error");
SeriesCollection[0].Values = Read("\\5y.csv");
ResetZoomOnClick(sender, e);
return;
}
else
{
DateTime offset = new DateTime(DateTime.Today.Year - 5, DateTime.Today.Month, DateTime.Today.Day);
DateTime temp;
foreach (var timeseries in data.TimeSeries)
{
temp = DateTime.ParseExact(timeseries.DateTime, "yyyy-MM-dd", CultureInfo.InvariantCulture);
if (temp > offset)
{
values.Add(new DateTimePoint(temp, double.Parse(timeseries.adjustedclose) * _exchangeRate));
}
}
Write("\\5y.csv", values);
}
}
catch (Exception)
{
MessageBox.Show("Previse zahteva poslato u kratkom vremene server misli da si spamer! Oladi malo sa kliktanjem.");
SeriesCollection[0].Values = Read("\\5y.csv");
ResetZoomOnClick(sender, e);
return;
}
SeriesCollection[0].Values = Read("\\5y.csv");
//SeriesCollection[0].Values = values;
ResetZoomOnClick(sender, e);
}
static async Task <Tuple <double, double, List <double> > > SR_FetchPricingDataandExpectedReturn(string ticker)
{
//******************************************************************************************
//The purpose of this function is to do all calculations related to sharperatio that involve pricing data
// for a single company. This includes STDdev, and expected return. These will be stored in a dictionary
//******************************************************************************************
List <double> priceslastyear = new List <double>();
List <double> monthlyreturnpercentages = new List <double>();
// Creating the connection object
IAvapiConnection connection = AvapiConnection.Instance;
IAvapiResponse_TIME_SERIES_MONTHLY_ADJUSTED m_time_series_monthly_adjustedResponse;
// Set up the connection and pass the API_KEY provided by alphavantage.co
connection.Connect("7NIMRBR8G8UB7P8C");
// Get the TIME_SERIES_MONTHLY_ADJUSTED query object
Int_TIME_SERIES_MONTHLY_ADJUSTED time_series_monthly_adjusted =
connection.GetQueryObject_TIME_SERIES_MONTHLY_ADJUSTED();
// Perform the TIME_SERIES_MONTHLY_ADJUSTED request and get the result
m_time_series_monthly_adjustedResponse = await time_series_monthly_adjusted.QueryPrimitiveAsync(
ticker);
Console.WriteLine("******** STRUCTURED DATA TIME_SERIES_MONTHLY_ADJUSTED ********");
var data = m_time_series_monthly_adjustedResponse.Data;
if (data.Error)
{
Console.WriteLine(data.ErrorMessage);
return(null);
}
else
{
Console.WriteLine("PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP");
int counter = 0;
foreach (var timeseries in data.TimeSeries)
{
//Grab 5 years worth of months data
if (counter < 60)
{
//add raw prices to array
priceslastyear.Add(double.Parse(timeseries.adjustedclose, CultureInfo.InvariantCulture.NumberFormat));
if (counter > 0)
{
//take pricing data and calculate percent change between each pair of months
//Console.Write(((priceslastyear[counter] / priceslastyear[counter - 1]) - 1) * 100);
monthlyreturnpercentages.Add(((priceslastyear[counter] / priceslastyear[counter - 1]) - 1) * 100);
}
counter = counter + 1;
}
}
//Setup counter to average pricing data
double running_average = 0;
//Calculate STDDev of data
double std_dev = StdDev(monthlyreturnpercentages, true);
//Sum all the values in our list
for (var i = 0; i < monthlyreturnpercentages.Count(); i++)
{
running_average = monthlyreturnpercentages[i] + running_average;
}
//Finishing taking average by dividing by the number of entries
running_average = running_average / monthlyreturnpercentages.Count();
//Annualize the average (multiply by 12 since monthly)
running_average = running_average * 12;
//Add the values to the tuple and print!
Console.Write(ticker + ", ");
Console.Write(std_dev + ", ");
Console.Write(running_average + ", ");
var pricingdata = Tuple.Create(std_dev, running_average, monthlyreturnpercentages);
//Return this value
return(pricingdata);
}
}
static async Task <double> CalculateSharpeRatioForCompany(string ticker)
{
List <double> priceslastyear = new List <double>();
List <double> monthlyreturnpercentages = new List <double>();
// Creating the connection object
IAvapiConnection connection = AvapiConnection.Instance;
IAvapiResponse_TIME_SERIES_MONTHLY_ADJUSTED m_time_series_monthly_adjustedResponse;
// Set up the connection and pass the API_KEY provided by alphavantage.co
connection.Connect("7NIMRBR8G8UB7P8C");
// Get the TIME_SERIES_MONTHLY_ADJUSTED query object
Int_TIME_SERIES_MONTHLY_ADJUSTED time_series_monthly_adjusted =
connection.GetQueryObject_TIME_SERIES_MONTHLY_ADJUSTED();
// Perform the TIME_SERIES_MONTHLY_ADJUSTED request and get the result
m_time_series_monthly_adjustedResponse = await time_series_monthly_adjusted.QueryPrimitiveAsync(
ticker);
Console.WriteLine("******** STRUCTURED DATA TIME_SERIES_MONTHLY_ADJUSTED ********");
var data = m_time_series_monthly_adjustedResponse.Data;
if (data.Error)
{
Console.WriteLine(data.ErrorMessage);
return(0);
}
else
{
int counter = 0;
foreach (var timeseries in data.TimeSeries)
{
//Grab 5 years worth of months data
if (counter < 60)
{
//add raw prices to array
priceslastyear.Add(double.Parse(timeseries.adjustedclose, CultureInfo.InvariantCulture.NumberFormat));
if (counter > 0)
{
//take pricing data and calculate percent change between each pair of months
//Console.Write(((priceslastyear[counter] / priceslastyear[counter - 1]) - 1) * 100);
monthlyreturnpercentages.Add(((priceslastyear[counter] / priceslastyear[counter - 1]) - 1) * 100);
}
counter = counter + 1;
}
}
double HistAvgMonthlyReturn = 0;
for (var i = 0; i < monthlyreturnpercentages.Count; i++)
{
//Console.WriteLine(monthprice);
HistAvgMonthlyReturn = HistAvgMonthlyReturn + monthlyreturnpercentages[i];
}
//Calculate the average monthly return
HistAvgMonthlyReturn = HistAvgMonthlyReturn / monthlyreturnpercentages.Count;
//Console.WriteLine(HistAvgMonthlyReturn);
//Here we need to calculate the Historical Monthly standard deviation based on the Std dev
// of the monthlyreturnpercentages
double Summation = 0;
for (var i = 0; i < monthlyreturnpercentages.Count; i++)
{
Summation = Summation + Math.Pow(monthlyreturnpercentages[i] - HistAvgMonthlyReturn, 2);
}
Summation = Summation / monthlyreturnpercentages.Count;
double HistAvgMonthlyStdDev = Math.Sqrt(Summation);
//Annualize our standard deviation
double AnnualStdDev = HistAvgMonthlyStdDev * Math.Sqrt(12);
double AnnualReturn = ((Math.Pow((100 + HistAvgMonthlyReturn), 12)) - 100);
double Riskfreerate = 3;
//Console.WriteLine(HistAvgMonthlyReturn);
Console.WriteLine(ticker);
Console.WriteLine(AnnualReturn);
//Console.WriteLine(Riskfreerate);
//Console.WriteLine(AnnualStdDev);
//Calculate the SharpeRatio for the Company
double SharpeRatioforCompany = (AnnualReturn - Riskfreerate) / AnnualStdDev;
//Console.WriteLine(SharpeRatioforCompany);
return(AnnualReturn);
}
}
